From 27bb5b8734383699ce93d80783a2e886001821d0 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Tue, 4 Jun 2024 16:22:47 -0400 Subject: [PATCH 01/86] testing --- score_definition.py | 101 ++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 101 insertions(+) create mode 100644 score_definition.py diff --git a/score_definition.py b/score_definition.py new file mode 100644 index 00000000..4a579fa2 --- /dev/null +++ b/score_definition.py @@ -0,0 +1,101 @@ +import requests + +from pathlib import Path +import json +from typing import Union + +from sasctl import Session +from sasctl._services.cas_management import CASManagement as cas + +username = "edmdev" # brmdev for a non-administrator session +password = "Go4thsas" + +host = "edmlatest.ingress-nginx.edmtest-m1.edm.sashq-d.openstack.sas.com" +#do we need to change host when putting it into the Git repository + +sess = Session(host, username, password, protocol="http") + +DEFAULT_SERVER = "cas-shared-default" +DEFAULT_CASUSER = "Public" +DEFAULT_TABLE = "" + +def score_definition(score_def_name: str, model_id: str, table_name: str, description:str = "", server_name: str = DEFAULT_SERVER, library_name: str = DEFAULT_CASUSER, model_version: str = "latest"): + """Creates the score definition service. + + Parameters + -------- + score_def_name: str + Name of score definition + model_id: str + A user-inputted model that exists in a project. + table_name: str + A user-inputted table name in CAS Management. + description: str + Description of score definition. Defaults to an empty string. + server_name: str, optional + The server within CAS that the table is in. Defaults to "cas-shared-default" + library_name: str, optional + The library within the CAS server the table exists in. Defaults to "Public" + model_version: str, optional + Defaults to "latest". + + Returns + ------- + RestObj + + """ + + try: + model = sess.get(f"modelRepository/models/{model_id}") + model_project_id = model.json()["projectId"] + except: + print("This model may not exist in a project.") #tested -> should also catch if model just doesn't exist + + + #mapping + inputMapping = [] + for i, input_item in enumerate(model_id["inputVariables"]): + var = {"mappingValue":input_item["name"],"mappingType":"datasource","variableName":input_item["name"]} + #mapping value and variable name are the same because the table values and model values are the same (remember MM quick start where automatically names matched up?) + #will above always be the case? How do we handle exceptions + + inputMapping.append(var) + + try: + table = sess.get(f"casManagement/servers/{server_name}/caslibs/{library_name}/tables/{table_name}") + table_contents = table.json() + except: + table_data = input("The inputted table does not exist. Enter the file path for the data in your table (CSV, XLS, XLSX, SAS7BDT or SASHDAT file).") + cas.upload_file(str(table_data), table_name) + table = sess.get(f"casManagement/servers/{server_name}/caslibs/{library_name}/tables/{table_name}") + + save_score_def = {"name": score_def_name, + "description": description, + "objectDescriptor":{"uri":"/modelManagement/models/"+model_id, + "name":model_id["name"] +"("+model_version+")", + "type":"sas.models.model"}, + "inputData":{"type":"CASTable", + "serverName":DEFAULT_SERVER, + "libraryName":DEFAULT_CASUSER, + "tableName":table_name}, + "properties":{"tableBaseName":"", + "outputLibraryName":DEFAULT_CASUSER, + "outputTableName":score_def_name, + "modelOrigUri":"/modelRepository/models/"+ model_id["id"], + "projectUri":"/modelRepository/projects/"+ model_project_id, + "projectVersionUri": "/modelRepository/projects/"+ model_project_id+"/projectVersions/" + model_id["projectVersionId"], + "publishDestination":"", + "versionedModel": model_id["name"] +"("+ model_version+")"}, + "mappings": inputMapping} # Getting the input variables from the model that eventually have to be mapped to the input table created/retrieved from CAS Management + #Array of mappings between Score Object variables and Input Data columns. + + headers_score_def = { + 'Content-Type': "application/json" + } + + new_score_def = sess.post("scoreDefinitions/definitions", data=json.dumps(save_score_def), headers=headers_score_def) + + return new_score_def + + + From 44dc0fb19015bec687c476fb1a60230466b29ce7 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Tue, 4 Jun 2024 16:42:14 -0400 Subject: [PATCH 02/86] "Testing." --- score_definition.py | 64 +++------------------------------------------ score_execution.py | 40 ++++++++++++++++++++++++++++ 2 files changed, 44 insertions(+), 60 deletions(-) create mode 100644 score_execution.py diff --git a/score_definition.py b/score_definition.py index 4a579fa2..5e624dd4 100644 --- a/score_definition.py +++ b/score_definition.py @@ -7,19 +7,11 @@ from sasctl import Session from sasctl._services.cas_management import CASManagement as cas -username = "edmdev" # brmdev for a non-administrator session -password = "Go4thsas" - -host = "edmlatest.ingress-nginx.edmtest-m1.edm.sashq-d.openstack.sas.com" -#do we need to change host when putting it into the Git repository - -sess = Session(host, username, password, protocol="http") - DEFAULT_SERVER = "cas-shared-default" DEFAULT_CASUSER = "Public" DEFAULT_TABLE = "" -def score_definition(score_def_name: str, model_id: str, table_name: str, description:str = "", server_name: str = DEFAULT_SERVER, library_name: str = DEFAULT_CASUSER, model_version: str = "latest"): +def score_definition(score_def_name: str, model_id: str, table_name: str = "", description:str = "", server_name: str = "cas-shared-default", library_name: str = "Public", model_version: str = "latest"): """Creates the score definition service. Parameters @@ -29,7 +21,7 @@ def score_definition(score_def_name: str, model_id: str, table_name: str, descr model_id: str A user-inputted model that exists in a project. table_name: str - A user-inputted table name in CAS Management. + A user-inputted table name in CAS Management. Defaults to an empty string. description: str Description of score definition. Defaults to an empty string. server_name: str, optional @@ -48,54 +40,6 @@ def score_definition(score_def_name: str, model_id: str, table_name: str, descr try: model = sess.get(f"modelRepository/models/{model_id}") model_project_id = model.json()["projectId"] + except: - print("This model may not exist in a project.") #tested -> should also catch if model just doesn't exist - - - #mapping - inputMapping = [] - for i, input_item in enumerate(model_id["inputVariables"]): - var = {"mappingValue":input_item["name"],"mappingType":"datasource","variableName":input_item["name"]} - #mapping value and variable name are the same because the table values and model values are the same (remember MM quick start where automatically names matched up?) - #will above always be the case? How do we handle exceptions - - inputMapping.append(var) - - try: - table = sess.get(f"casManagement/servers/{server_name}/caslibs/{library_name}/tables/{table_name}") - table_contents = table.json() - except: - table_data = input("The inputted table does not exist. Enter the file path for the data in your table (CSV, XLS, XLSX, SAS7BDT or SASHDAT file).") - cas.upload_file(str(table_data), table_name) - table = sess.get(f"casManagement/servers/{server_name}/caslibs/{library_name}/tables/{table_name}") - - save_score_def = {"name": score_def_name, - "description": description, - "objectDescriptor":{"uri":"/modelManagement/models/"+model_id, - "name":model_id["name"] +"("+model_version+")", - "type":"sas.models.model"}, - "inputData":{"type":"CASTable", - "serverName":DEFAULT_SERVER, - "libraryName":DEFAULT_CASUSER, - "tableName":table_name}, - "properties":{"tableBaseName":"", - "outputLibraryName":DEFAULT_CASUSER, - "outputTableName":score_def_name, - "modelOrigUri":"/modelRepository/models/"+ model_id["id"], - "projectUri":"/modelRepository/projects/"+ model_project_id, - "projectVersionUri": "/modelRepository/projects/"+ model_project_id+"/projectVersions/" + model_id["projectVersionId"], - "publishDestination":"", - "versionedModel": model_id["name"] +"("+ model_version+")"}, - "mappings": inputMapping} # Getting the input variables from the model that eventually have to be mapped to the input table created/retrieved from CAS Management - #Array of mappings between Score Object variables and Input Data columns. - - headers_score_def = { - 'Content-Type': "application/json" - } - - new_score_def = sess.post("scoreDefinitions/definitions", data=json.dumps(save_score_def), headers=headers_score_def) - - return new_score_def - - - + print("This model may not exist in a project.") #tested -> should also catch if model just doesn't exist \ No newline at end of file diff --git a/score_execution.py b/score_execution.py new file mode 100644 index 00000000..acfada17 --- /dev/null +++ b/score_execution.py @@ -0,0 +1,40 @@ +import requests + +from pathlib import Path +import json +from typing import Union + +from sasctl import Session +from sasctl._services.cas_management import CASManagement as cas + +DEFAULT_SERVER = "cas-shared-default" +DEFAULT_CASUSER = "Public" +DEFAULT_TABLE = "" + +def score_execution(score_def_name: str, model_id: str, table_name: str, description:str = "", server_name: str = DEFAULT_SERVER, library_name: str = DEFAULT_CASUSER, model_version: str = "latest"): + """Creates the score definition service. + + Parameters + -------- + score_def_name: str + Name of score definition + model_id: str + A user-inputted model that exists in a project. + table_name: str + A user-inputted table name in CAS Management. + description: str + Description of score definition. Defaults to an empty string. + server_name: str, optional + The server within CAS that the table is in. Defaults to "cas-shared-default" + library_name: str, optional + The library within the CAS server the table exists in. Defaults to "Public" + model_version: str, optional + Defaults to "latest". + + Returns + ------- + RestObj + + """ + + all_score_executions = sess.get("scoreExecution/executions") From 3df1df9462f85cc8ab205ec72f4321e516db9332 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Wed, 19 Jun 2024 10:33:02 -0400 Subject: [PATCH 03/86] Fixing comments --- score_definition.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/score_definition.py b/score_definition.py index 5e624dd4..1667fb5c 100644 --- a/score_definition.py +++ b/score_definition.py @@ -42,4 +42,4 @@ def score_definition(score_def_name: str, model_id: str, table_name: str = "", model_project_id = model.json()["projectId"] except: - print("This model may not exist in a project.") #tested -> should also catch if model just doesn't exist \ No newline at end of file + print("This model may not exist in a project.") \ No newline at end of file From 407427b3f2add8a9b4f63ff9599c303bdb801c64 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Wed, 19 Jun 2024 10:50:22 -0400 Subject: [PATCH 04/86] Getting a model and input mapping --- score_definition.py | 31 +++++++++++++++++++++++++------ 1 file changed, 25 insertions(+), 6 deletions(-) diff --git a/score_definition.py b/score_definition.py index 1667fb5c..3e5c3e4f 100644 --- a/score_definition.py +++ b/score_definition.py @@ -11,18 +11,18 @@ DEFAULT_CASUSER = "Public" DEFAULT_TABLE = "" -def score_definition(score_def_name: str, model_id: str, table_name: str = "", description:str = "", server_name: str = "cas-shared-default", library_name: str = "Public", model_version: str = "latest"): +def score_definition(score_def_name: str, model_id: str, table_name: str, description:str = "", server_name: str = "cas-shared-default", library_name: str = "Public", model_version: str = "latest"): """Creates the score definition service. Parameters -------- score_def_name: str - Name of score definition + Name of score definition. model_id: str - A user-inputted model that exists in a project. + A user-inputted model id where the model exists in a project. table_name: str - A user-inputted table name in CAS Management. Defaults to an empty string. - description: str + A user-inputted table name in CAS Management. + description: str, optional Description of score definition. Defaults to an empty string. server_name: str, optional The server within CAS that the table is in. Defaults to "cas-shared-default" @@ -40,6 +40,25 @@ def score_definition(score_def_name: str, model_id: str, table_name: str = "", try: model = sess.get(f"modelRepository/models/{model_id}") model_project_id = model.json()["projectId"] + model_project_version_id = model.json()["projectVersionId"] + model_name = model.json()["name"] except: - print("This model may not exist in a project.") \ No newline at end of file + print("This model may not exist in a project.") + + #mapping + inputMapping = [] + for input_item in model.json()["inputVariables"]: + var = {"mappingValue":input_item["name"],"mappingType":"datasource","variableName":input_item["name"]} + inputMapping.append(var) + + table = sess.get(f"casManagement/servers/{server_name}/caslibs/{library_name}/tables/{table_name}") + try: + print(table.json()) #because table_name is an empty string/none, it's ignore the last part of the uri and just printing all the tables, that's why error code 400 is not being recognized + table_status_code = table.json()['httpStatusCode'] + if table_status_code == 404 or table_status_code == 400: + table_file = input("The inputted table does not exist. Enter the file path for the data in your table (CSV, XLS, XLSX, SAS7BDT or SASHDAT file).") + cas.upload_file(str(table_file), table_name) + table = sess.get(f"casManagement/servers/{server_name}/caslibs/{library_name}/tables/{table_name}") + except: + print("Table GET API call successful due to no 'httpStatusCode' key.") \ No newline at end of file From 8af52b4ae4ff54ed838a043deb820fcf31492d95 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Wed, 19 Jun 2024 11:56:31 -0400 Subject: [PATCH 05/86] Creating score definition JSON information --- score_definition.py | 28 +++++++++++++++++++++++++++- 1 file changed, 27 insertions(+), 1 deletion(-) diff --git a/score_definition.py b/score_definition.py index 3e5c3e4f..0aac08d6 100644 --- a/score_definition.py +++ b/score_definition.py @@ -61,4 +61,30 @@ def score_definition(score_def_name: str, model_id: str, table_name: str, descr cas.upload_file(str(table_file), table_name) table = sess.get(f"casManagement/servers/{server_name}/caslibs/{library_name}/tables/{table_name}") except: - print("Table GET API call successful due to no 'httpStatusCode' key.") \ No newline at end of file + print("Table GET API call successful due to no 'httpStatusCode' key.") + + save_score_def = {"name": score_def_name, + "description": description, + "objectDescriptor":{"uri":f"/modelManagement/models/{model_id}", + "name":f"{model_name}({model_version})", + "type":"sas.models.model"}, + "inputData":{"type":"CASTable", + "serverName":server_name, + "libraryName":library_name, + "tableName":table_name}, + "properties":{"tableBaseName":"", + "modelOrigUri":f"/modelRepository/models/{model_id}", + "projectUri":f"/modelRepository/projects/{model_project_id}", + "projectVersionUri": f"/modelRepository/projects/{model_project_id}/projectVersions/{model_project_version_id}", + "publishDestination":"", + "versionedModel": f"{model_name}({model_version})"}, + "mappings": inputMapping} # Getting the input variables from the model that eventually have to be mapped to the input table created/retrieved from CAS Management + #Array of mappings between Score Object variables and Input Data columns. + + headers_score_def = { + 'Content-Type': "application/json" + } + + new_score_def = sess.post("scoreDefinitions/definitions", data=json.dumps(save_score_def), headers=headers_score_def) + + return new_score_def \ No newline at end of file From 1461ded78ad32d54c45f2c552b601f5faa1e5574 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Wed, 19 Jun 2024 16:55:11 -0400 Subject: [PATCH 06/86] Adding comments and adjusting for various API call and responses --- score_definition.py | 45 ++++++++++++++++++++++----------------- score_execution.py | 51 +++++++++++++++++++++++++++++---------------- 2 files changed, 59 insertions(+), 37 deletions(-) diff --git a/score_definition.py b/score_definition.py index 0aac08d6..282b568a 100644 --- a/score_definition.py +++ b/score_definition.py @@ -19,17 +19,17 @@ def score_definition(score_def_name: str, model_id: str, table_name: str, descr score_def_name: str Name of score definition. model_id: str - A user-inputted model id where the model exists in a project. + A user-inputted model if where the model exists in a project. table_name: str - A user-inputted table name in CAS Management. + A user-inputted table name in CAS Management. description: str, optional Description of score definition. Defaults to an empty string. server_name: str, optional - The server within CAS that the table is in. Defaults to "cas-shared-default" + The server within CAS that the table is in. Defaults to "cas-shared-default". library_name: str, optional - The library within the CAS server the table exists in. Defaults to "Public" + The library within the CAS server the table exists in. Defaults to "Public". model_version: str, optional - Defaults to "latest". + The user-chosen version of the model with the specified model_id. Defaults to "latest". Returns ------- @@ -44,25 +44,31 @@ def score_definition(score_def_name: str, model_id: str, table_name: str, descr model_name = model.json()["name"] except: - print("This model may not exist in a project.") - - #mapping - inputMapping = [] - for input_item in model.json()["inputVariables"]: - var = {"mappingValue":input_item["name"],"mappingType":"datasource","variableName":input_item["name"]} - inputMapping.append(var) + print("This model may not exist in a project or the model may not exist at all.") + # Checking if the model exists and if it's in a project + + try: + inputMapping = [] + for input_item in model.json()["inputVariables"]: + var = {"mappingValue":input_item["name"],"mappingType":"datasource","variableName":input_item["name"]} + inputMapping.append(var) + except: + print("This model does not have the optional 'inputVariables' parameter.") + # Optional mapping - Maps the variables in the data to the variables of the score object. It's not necessary to create a score definition. + table = sess.get(f"casManagement/servers/{server_name}/caslibs/{library_name}/tables/{table_name}") try: - print(table.json()) #because table_name is an empty string/none, it's ignore the last part of the uri and just printing all the tables, that's why error code 400 is not being recognized table_status_code = table.json()['httpStatusCode'] if table_status_code == 404 or table_status_code == 400: table_file = input("The inputted table does not exist. Enter the file path for the data in your table (CSV, XLS, XLSX, SAS7BDT or SASHDAT file).") - cas.upload_file(str(table_file), table_name) + cas.upload_file(str(table_file), table_name) #do I need to add a check if the file doesn't exist or does upload_file take care of that? table = sess.get(f"casManagement/servers/{server_name}/caslibs/{library_name}/tables/{table_name}") + # Checks if the inputted table exists, and if not, uploads a file to create a new table except: - print("Table GET API call successful due to no 'httpStatusCode' key.") - + pass + #The API call to get the table was successful, and therefore will not have an 'httpStatusCode' value. This 'pass' statement will allow the successful get API calls to proceed. + save_score_def = {"name": score_def_name, "description": description, "objectDescriptor":{"uri":f"/modelManagement/models/{model_id}", @@ -78,8 +84,8 @@ def score_definition(score_def_name: str, model_id: str, table_name: str, descr "projectVersionUri": f"/modelRepository/projects/{model_project_id}/projectVersions/{model_project_version_id}", "publishDestination":"", "versionedModel": f"{model_name}({model_version})"}, - "mappings": inputMapping} # Getting the input variables from the model that eventually have to be mapped to the input table created/retrieved from CAS Management - #Array of mappings between Score Object variables and Input Data columns. + "mappings": inputMapping} + # Consolidating all of the model and table information to create the score definition information headers_score_def = { 'Content-Type': "application/json" @@ -87,4 +93,5 @@ def score_definition(score_def_name: str, model_id: str, table_name: str, descr new_score_def = sess.post("scoreDefinitions/definitions", data=json.dumps(save_score_def), headers=headers_score_def) - return new_score_def \ No newline at end of file + return new_score_def + # The response information of the score definition can be seen as a JSON as well as the RestOBJ \ No newline at end of file diff --git a/score_execution.py b/score_execution.py index acfada17..462eb60d 100644 --- a/score_execution.py +++ b/score_execution.py @@ -7,34 +7,49 @@ from sasctl import Session from sasctl._services.cas_management import CASManagement as cas -DEFAULT_SERVER = "cas-shared-default" -DEFAULT_CASUSER = "Public" -DEFAULT_TABLE = "" - -def score_execution(score_def_name: str, model_id: str, table_name: str, description:str = "", server_name: str = DEFAULT_SERVER, library_name: str = DEFAULT_CASUSER, model_version: str = "latest"): +def score_execution(score_definition, description: str = "", output_server_name: str = "cas-shared-default", output_library_name: str = "Public", output_table_name: str = ""): """Creates the score definition service. Parameters -------- - score_def_name: str - Name of score definition - model_id: str - A user-inputted model that exists in a project. - table_name: str - A user-inputted table name in CAS Management. + score_definition + Score Definition RestObj. description: str Description of score definition. Defaults to an empty string. - server_name: str, optional - The server within CAS that the table is in. Defaults to "cas-shared-default" - library_name: str, optional - The library within the CAS server the table exists in. Defaults to "Public" - model_version: str, optional - Defaults to "latest". + output_server_name: str, optional + The server within CAS that the output table is in. Defaults to "cas-shared-default". + output_library_name: str, optional + The library within the CAS server the output table exists in. Defaults to "Public". + output_table_name: str, optional + The name of the output table. Defaults to an empty string. + Returns ------- RestObj """ + try: + score_definition_id = score_definition.json()["id"] + score_definition_name = score_definition.json()["name"] + score_definition_model_id = score_definition.json["modelId"] + score_definition_model_name = score_definition.json["modelName"] + except: + print("The input score definition object may not exist. Please check it was passed in correctly") + + if output_table_name == "": + output_table_name = f"{score_definition_model_name}_{score_definition_id}" + + try: + filtered_score_executions = sess.get(f"scoreExecution/executions?filter=eq(scoreExecutionRequest.scoreDefinitionId,%27{score_definition_id}%27)") + deleted_score_execution = sess.delete(f"scoreExecution/executions/{filtered_score_executions["items"][0]["id"]}") + #can there be more than one score execution for a score definition running (execCount >= 1) + except: + pass + - all_score_executions = sess.get("scoreExecution/executions") + + + + + From 07d6c9338dc57139719ed1c0333bbb134453d40f Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Thu, 20 Jun 2024 12:22:18 -0400 Subject: [PATCH 07/86] Exits program after an error --- .../sasctl/_services/score_definitions.py | 6 ++---- .../sasctl/_services/score_execution.py | 0 2 files changed, 2 insertions(+), 4 deletions(-) rename score_definition.py => src/sasctl/_services/score_definitions.py (96%) rename score_execution.py => src/sasctl/_services/score_execution.py (100%) diff --git a/score_definition.py b/src/sasctl/_services/score_definitions.py similarity index 96% rename from score_definition.py rename to src/sasctl/_services/score_definitions.py index 282b568a..2a29fd01 100644 --- a/score_definition.py +++ b/src/sasctl/_services/score_definitions.py @@ -1,4 +1,5 @@ import requests +import sys from pathlib import Path import json @@ -7,9 +8,6 @@ from sasctl import Session from sasctl._services.cas_management import CASManagement as cas -DEFAULT_SERVER = "cas-shared-default" -DEFAULT_CASUSER = "Public" -DEFAULT_TABLE = "" def score_definition(score_def_name: str, model_id: str, table_name: str, description:str = "", server_name: str = "cas-shared-default", library_name: str = "Public", model_version: str = "latest"): """Creates the score definition service. @@ -44,7 +42,7 @@ def score_definition(score_def_name: str, model_id: str, table_name: str, descr model_name = model.json()["name"] except: - print("This model may not exist in a project or the model may not exist at all.") + sys.exit("This model may not exist in a project or the model may not exist at all.") # Checking if the model exists and if it's in a project try: diff --git a/score_execution.py b/src/sasctl/_services/score_execution.py similarity index 100% rename from score_execution.py rename to src/sasctl/_services/score_execution.py From 2110d66cee574d7bcc52030c5cf6488f5a079e9d Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Thu, 20 Jun 2024 16:56:03 -0400 Subject: [PATCH 08/86] Added original score_execution implementation --- src/sasctl/_services/score_execution.py | 80 ++++++++++++++++++++++++- 1 file changed, 79 insertions(+), 1 deletion(-) diff --git a/src/sasctl/_services/score_execution.py b/src/sasctl/_services/score_execution.py index 462eb60d..38625bcb 100644 --- a/src/sasctl/_services/score_execution.py +++ b/src/sasctl/_services/score_execution.py @@ -7,6 +7,7 @@ from sasctl import Session from sasctl._services.cas_management import CASManagement as cas + def score_execution(score_definition, description: str = "", output_server_name: str = "cas-shared-default", output_library_name: str = "Public", output_table_name: str = ""): """Creates the score definition service. @@ -47,8 +48,85 @@ def score_execution(score_definition, description: str = "", output_server_name: except: pass + import requests + +from pathlib import Path +import json +from typing import Union + +from sasctl import Session +from sasctl._services.cas_management import CASManagement as cas + + + + +def score_execution(score_definition, description: str = "", output_server_name: str = "cas-shared-default", output_library_name: str = "Public", output_table_name: str = ""): + """Creates the score definition service. + + Parameters + -------- + score_definition: RestObj + A score definition existing on the server. + description: str + Description of score execution. Defaults to an empty string. + output_server_name: str + The name of the output server the output table and output library is stored in. Defaults to "cas-shared-default". + output_library_name: str + The name of the output library the output table is stored in. Defaults to "Public". + output_table_name: str + The name of the output table the score execution or analysis output will be stored in. Defaults to an empty string. + + Returns + ------- + RestObj + + """ + + headers_score_exec = { + "Content-Type": "application/json" + } + + try: + + score_def_id = score_definition.json()["id"] + score_exec_name = score_definition.json()["name"] + model_uri = score_definition.json()["objectDescriptor"]["uri"] + model_name = score_definition.json()["objectDescriptor"]["name"] + model_input_library = score_definition.json()["inputData"]["libraryName"] + model_input_server = score_definition.json()["inputData"]["serverName"] + model_table_name = score_definition.json()["inputData"]["tableName"] + + model_table = sess.get(f"casManagement/servers/{model_input_server}/caslibs/{model_input_library}/tables/{model_table_name}") + model_table_name = model_table.json()["name"] + model_table_id = model_table.json()["id"] + except: + print("The score definition may not exist or the fields are incomplete.") + + if output_table_name == "": + output_table_name = f"{model_name}_{score_def_id}" #is output table the same as I specified in score_definition/do I need to create one or does it automatically create one? + try: + score_execution = sess.get(f"/scoreExecution/executions?filter=eq(scoreExecutionRequest.scoreDefinitionId,%27{score_def_id}%27)") #getting all of them because + execCount = score_execution.json()['count'] + if execCount == 1: + execTaskId = score_execution.json()["items"][0]["id"] + deleted_score_execution = sess.delete(f"scoreExecution/executions/{execTaskId}") + print(deleted_score_execution) + except: + print("There may not be a score execution already running.") + + create_score_exec = {"name": score_exec_name, + "description": description, + "hints": {"objectURI":model_uri, #because I'm scoring a model, is that why this is required? + "modelTable":model_table_id, + "inputTableName":model_table_name, + "inputLibraryName": model_input_library}, + "scoreDefinitionId": score_def_id, + "outputTable": {"tableName": output_table_name, + "libraryName": output_library_name, + "serverName": output_server_name}} - + new_score_execution = sess.post("scoreExecution/executions", data=json.dumps(create_score_exec), header=headers_score_exec) + return new_score_execution From 3e46e784a309adcb69c44a7d6e6fe0fe1c46af14 Mon Sep 17 00:00:00 2001 From: Scott-Lindauer_sasinst Date: Fri, 21 Jun 2024 12:07:30 -0400 Subject: [PATCH 09/86] refactor: swap in Service class for ScoreDefinitions class --- src/sasctl/_services/score_definitions.py | 170 ++++++++++++---------- 1 file changed, 95 insertions(+), 75 deletions(-) diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index 2a29fd01..5faf82d8 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -6,90 +6,110 @@ from typing import Union from sasctl import Session -from sasctl._services.cas_management import CASManagement as cas +from .cas_management import CASManagement +from .model_repository import ModelRepository as mr +from .service import Service -def score_definition(score_def_name: str, model_id: str, table_name: str, description:str = "", server_name: str = "cas-shared-default", library_name: str = "Public", model_version: str = "latest"): - """Creates the score definition service. +class ScoreDefinitions(Service): + """ + Used for creating and maintaining score definitions. + + The Score Definitions API is used for creating and maintaining score definitions. - Parameters + See Also -------- - score_def_name: str - Name of score definition. - model_id: str - A user-inputted model if where the model exists in a project. - table_name: str - A user-inputted table name in CAS Management. - description: str, optional - Description of score definition. Defaults to an empty string. - server_name: str, optional - The server within CAS that the table is in. Defaults to "cas-shared-default". - library_name: str, optional - The library within the CAS server the table exists in. Defaults to "Public". - model_version: str, optional - The user-chosen version of the model with the specified model_id. Defaults to "latest". + `` + """ - Returns - ------- - RestObj + _SERVICE_ROOT = "/scoreDefinitions" + _cas_management = CASManagement() + + list_definitions, get_definition, update_definition, delete_definition = Service._crud_funcs( + "/definitions", "definition") + + # def create_score_definition() + def score_definition(cls, score_def_name: str, model_id: str, table_name: str, description:str = "", server_name: str = "cas-shared-default", library_name: str = "Public", model_version: str = "latest"): + """Creates the score definition service. + + Parameters + -------- + score_def_name: str + Name of score definition. + model_id: str + A user-inputted model if where the model exists in a project. + table_name: str + A user-inputted table name in CAS Management. + description: str, optional + Description of score definition. Defaults to an empty string. + server_name: str, optional + The server within CAS that the table is in. Defaults to "cas-shared-default". + library_name: str, optional + The library within the CAS server the table exists in. Defaults to "Public". + model_version: str, optional + The user-chosen version of the model with the specified model_id. Defaults to "latest". + + Returns + ------- + RestObj - """ + """ - try: - model = sess.get(f"modelRepository/models/{model_id}") - model_project_id = model.json()["projectId"] - model_project_version_id = model.json()["projectVersionId"] - model_name = model.json()["name"] + try: + model = mr.get_model(model_id) + model_project_id = model.json()["projectId"] + model_project_version_id = model.json()["projectVersionId"] + model_name = model.json()["name"] + + except: + sys.exit("This model may not exist in a project or the model may not exist at all.") + # Checking if the model exists and if it's in a project - except: - sys.exit("This model may not exist in a project or the model may not exist at all.") - # Checking if the model exists and if it's in a project - - try: - inputMapping = [] - for input_item in model.json()["inputVariables"]: - var = {"mappingValue":input_item["name"],"mappingType":"datasource","variableName":input_item["name"]} - inputMapping.append(var) - except: - print("This model does not have the optional 'inputVariables' parameter.") + try: + inputMapping = [] + for input_item in model.json()["inputVariables"]: + var = {"mappingValue":input_item["name"],"mappingType":"datasource","variableName":input_item["name"]} + inputMapping.append(var) + except: + print("This model does not have the optional 'inputVariables' parameter.") + + # Optional mapping - Maps the variables in the data to the variables of the score object. It's not necessary to create a score definition. - # Optional mapping - Maps the variables in the data to the variables of the score object. It's not necessary to create a score definition. - - table = sess.get(f"casManagement/servers/{server_name}/caslibs/{library_name}/tables/{table_name}") - try: - table_status_code = table.json()['httpStatusCode'] - if table_status_code == 404 or table_status_code == 400: - table_file = input("The inputted table does not exist. Enter the file path for the data in your table (CSV, XLS, XLSX, SAS7BDT or SASHDAT file).") - cas.upload_file(str(table_file), table_name) #do I need to add a check if the file doesn't exist or does upload_file take care of that? - table = sess.get(f"casManagement/servers/{server_name}/caslibs/{library_name}/tables/{table_name}") - # Checks if the inputted table exists, and if not, uploads a file to create a new table - except: - pass - #The API call to get the table was successful, and therefore will not have an 'httpStatusCode' value. This 'pass' statement will allow the successful get API calls to proceed. + table = cls._cas_management.get_table(server_name, library_name, table_name) + try: + table_status_code = table.json()['httpStatusCode'] + if table_status_code == 404 or table_status_code == 400: + table_file = input("The inputted table does not exist. Enter the file path for the data in your table (CSV, XLS, XLSX, SAS7BDT or SASHDAT file).") + cls._cas_management.upload_file(str(table_file), table_name) #do I need to add a check if the file doesn't exist or does upload_file take care of that? + table = cls._cas_management.get_table(server_name, library_name, table_name) + # Checks if the inputted table exists, and if not, uploads a file to create a new table + except: + pass + #The API call to get the table was successful, and therefore will not have an 'httpStatusCode' value. This 'pass' statement will allow the successful get API calls to proceed. - save_score_def = {"name": score_def_name, - "description": description, - "objectDescriptor":{"uri":f"/modelManagement/models/{model_id}", - "name":f"{model_name}({model_version})", - "type":"sas.models.model"}, - "inputData":{"type":"CASTable", - "serverName":server_name, - "libraryName":library_name, - "tableName":table_name}, - "properties":{"tableBaseName":"", - "modelOrigUri":f"/modelRepository/models/{model_id}", - "projectUri":f"/modelRepository/projects/{model_project_id}", - "projectVersionUri": f"/modelRepository/projects/{model_project_id}/projectVersions/{model_project_version_id}", - "publishDestination":"", - "versionedModel": f"{model_name}({model_version})"}, - "mappings": inputMapping} - # Consolidating all of the model and table information to create the score definition information - - headers_score_def = { - 'Content-Type': "application/json" - } + save_score_def = {"name": score_def_name, + "description": description, + "objectDescriptor":{"uri":f"/modelManagement/models/{model_id}", + "name":f"{model_name}({model_version})", + "type":"sas.models.model"}, + "inputData":{"type":"CASTable", + "serverName":server_name, + "libraryName":library_name, + "tableName":table_name}, + "properties":{"tableBaseName":"", + "modelOrigUri":f"/modelRepository/models/{model_id}", + "projectUri":f"/modelRepository/projects/{model_project_id}", + "projectVersionUri": f"/modelRepository/projects/{model_project_id}/projectVersions/{model_project_version_id}", + "publishDestination":"", + "versionedModel": f"{model_name}({model_version})"}, + "mappings": inputMapping} + # Consolidating all of the model and table information to create the score definition information + + headers_score_def = { + 'Content-Type': "application/json" + } - new_score_def = sess.post("scoreDefinitions/definitions", data=json.dumps(save_score_def), headers=headers_score_def) + new_score_def = cls.post("/definitions", data=json.dumps(save_score_def), headers=headers_score_def) - return new_score_def - # The response information of the score definition can be seen as a JSON as well as the RestOBJ \ No newline at end of file + return new_score_def + # The response information of the score definition can be seen as a JSON as well as the RestOBJ \ No newline at end of file From 210bf6c6aa57f5173be4a9375532118305b8239a Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Tue, 25 Jun 2024 17:31:40 -0400 Subject: [PATCH 10/86] Refactoring and adjusting for invalid HTTP status codes --- score_definition.py | 113 ++++++++++++++++++++++++++++++++++++++++++++ score_execution.py | 94 ++++++++++++++++++++++++++++++++++++ 2 files changed, 207 insertions(+) create mode 100644 score_definition.py create mode 100644 score_execution.py diff --git a/score_definition.py b/score_definition.py new file mode 100644 index 00000000..a2fcafec --- /dev/null +++ b/score_definition.py @@ -0,0 +1,113 @@ +import requests +import sys + +from pathlib import Path +import json +from typing import Union + +from sasctl import Session +from .cas_management import CASManagement +from .model_repository import ModelRepository as mr +from .service import Service + + +class ScoreDefinitions(Service): + """ + Used for creating and maintaining score definitions. + + The Score Definitions API is used for creating and maintaining score definitions. + + See Also + -------- + `REST Documentation ` + """ + + _SERVICE_ROOT = "/scoreDefinitions" + _cas_management = CASManagement() + + list_definitions, get_definition, update_definition, delete_definition = Service._crud_funcs( + "/definitions", "definition") + + @classmethod + def create_score_definition(cls, score_def_name: str, model_id: str, table_name: str, description:str = "", server_name: str = "cas-shared-default", library_name: str = "Public", model_version: str = "latest"): + """Creates the score definition service. + + Parameters + -------- + score_def_name: str + Name of score definition. + model_id: str + A user-inputted model if where the model exists in a project. + table_name: str + A user-inputted table name in CAS Management. + description: str, optional + Description of score definition. Defaults to an empty string. + server_name: str, optional + The server within CAS that the table is in. Defaults to "cas-shared-default". + library_name: str, optional + The library within the CAS server the table exists in. Defaults to "Public". + model_version: str, optional + The user-chosen version of the model with the specified model_id. Defaults to "latest". + + Returns + ------- + RestObj + + """ + + try: + model = mr.get_model(model_id) + model_project_id = model.json()["projectId"] + model_project_version_id = model.json()["projectVersionId"] + model_name = model.json()["name"] + + except: + raise Exception("This model may not exist in a project or the model may not exist at all.") + # Checking if the model exists and if it's in a project + + try: + inputMapping = [] + for input_item in model.json()["inputVariables"]: + var = {"mappingValue":input_item["name"],"mappingType":"datasource","variableName":input_item["name"]} + inputMapping.append(var) + except: + print("This model does not have the optional 'inputVariables' parameter.") + + # Optional mapping - Maps the variables in the data to the variables of the score object. It's not necessary to create a score definition. + + table = cls._cas_management.get_table(server_name, library_name, table_name) + try: + table.raise_for_status() + except requests.exceptions.HTTPError as error: + print(f"HTTP Error: {error}") + table_file = input("The inputted table does not exist. Enter the file path for the data in your table (CSV, XLS, XLSX, SAS7BDT or SASHDAT file).") + cls._cas_management.upload_file(str(table_file), table_name) #do I need to add a check if the file doesn't exist or does upload_file take care of that? + table = cls._cas_management.get_table(server_name, library_name, table_name) + # Checks if the inputted table exists, and if not, uploads a file to create a new table + + save_score_def = {"name": score_def_name, + "description": description, + "objectDescriptor":{"uri":f"/modelManagement/models/{model_id}", + "name":f"{model_name}({model_version})", + "type":"sas.models.model"}, + "inputData":{"type":"CASTable", + "serverName":server_name, + "libraryName":library_name, + "tableName":table_name}, + "properties":{"tableBaseName":"", + "modelOrigUri":f"/modelRepository/models/{model_id}", + "projectUri":f"/modelRepository/projects/{model_project_id}", + "projectVersionUri": f"/modelRepository/projects/{model_project_id}/projectVersions/{model_project_version_id}", + "publishDestination":"", + "versionedModel": f"{model_name}({model_version})"}, + "mappings": inputMapping} + # Consolidating all of the model and table information to create the score definition information + + headers_score_def = { + 'Content-Type': "application/json" + } + + new_score_def = cls.post("/definitions", data=json.dumps(save_score_def), headers=headers_score_def) + + return new_score_def + # The response information of the score definition can be seen as a JSON as well as the RestOBJ \ No newline at end of file diff --git a/score_execution.py b/score_execution.py new file mode 100644 index 00000000..56eba931 --- /dev/null +++ b/score_execution.py @@ -0,0 +1,94 @@ +import requests + +from pathlib import Path +import json +from typing import Union + +from sasctl import Session +#from sasctl._services.cas_management import CASManagement as cas +from .score_definition import ScoreDefinitions as sd +from .service import Service + +class ScoreExecutions(Service): + """ + The Score Execution API is used to produce a score by + executing the mapped code generated by score objects using the score definition. + + See Also + -------- + `REST Documentation ` + """ + + _SERVICE_ROOT = "/scoreExecution" + + list_executions, get_execution, update_execution, delete_execution = Service._crud_funcs( + "/executions", "execution") + +@classmethod +def score_execution(cls, score_definition_id: str, description: str = "", output_server_name: str = "cas-shared-default", output_library_name: str = "Public", output_table_name: str = ""): + """Creates the score definition service. + + Parameters + -------- + score_definition_id: str + A score definition id representing score definition existing on the server that needs to be executed. + description: str, optional + Description of score execution. Defaults to an empty string. + output_server_name: str, optional + The name of the output server the output table and output library is stored in. Defaults to "cas-shared-default". + output_library_name: str, optional + The name of the output library the output table is stored in. Defaults to "Public". + output_table_name: str, optional + The name of the output table the score execution or analysis output will be stored in. Defaults to an empty string. + + Returns + ------- + RestObj + + """ + + try: + score_definition = sd.get_definition(score_definition_id) + score_exec_name = score_definition.json()["name"] + model_uri = score_definition.json()["objectDescriptor"]["uri"] + model_name = score_definition.json()["objectDescriptor"]["name"] + model_input_library = score_definition.json()["inputData"]["libraryName"] + model_input_server = score_definition.json()["inputData"]["serverName"] + model_table_name = score_definition.json()["inputData"]["tableName"] + except: + raise Exception('The score definition may not exist.') + # Gets information about the scoring object from the score definition and raises an exception if the score definition does not exist + + if output_table_name == "": + output_table_name = f"{model_name}_{score_definition_id}" + # Defining a default output table name + try: + score_execution = sess.get(f"/scoreExecution/executions?filter=eq(scoreExecutionRequest.scoreDefinitionId,%27{score_definition_id}%27)") # how to use crud functions on something with such a specifc filter + execution_count = score_execution.json()['count'] + if execution_count == 1: + execution_id = score_execution.json()["items"][0]["id"] + deleted_score_execution = cls.delete_execution(execution_id) + print(deleted_score_execution) + except: + print("There may not be a score execution already running.") + + # Deleting any score executions that are already executing the same score definition + + headers_score_exec = { + "Content-Type": "application/json" + } + + create_score_exec = {"name": score_exec_name, + "description": description, + "hints": {"objectURI":model_uri, + "inputTableName":model_table_name, + "inputLibraryName": model_input_library}, + "scoreDefinitionId": score_definition_id, + "outputTable": {"tableName": output_table_name, + "libraryName": output_library_name, + "serverName": output_server_name}} + + # Creating the score execution + + new_score_execution = cls.post("scoreExecution/executions", data=json.dumps(create_score_exec), headers=headers_score_exec) + return new_score_execution \ No newline at end of file From dddc11603c364e8748d69429f613f6a9899b9159 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Wed, 26 Jun 2024 16:13:44 -0400 Subject: [PATCH 11/86] Raising exception if input file for table does not exist --- score_definition.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/score_definition.py b/score_definition.py index a2fcafec..3bfe2c0e 100644 --- a/score_definition.py +++ b/score_definition.py @@ -84,6 +84,11 @@ def create_score_definition(cls, score_def_name: str, model_id: str, table_name cls._cas_management.upload_file(str(table_file), table_name) #do I need to add a check if the file doesn't exist or does upload_file take care of that? table = cls._cas_management.get_table(server_name, library_name, table_name) # Checks if the inputted table exists, and if not, uploads a file to create a new table + try: + table.raise_for_status() + except requests.exceptions.HTTPError as error: + print(f"HTTP Error: {error}") + raise Exception("Something went wrong when creating a table. Check to see if the file path inputted exists.") save_score_def = {"name": score_def_name, "description": description, From e697c25fca018e729710cb9760156fd3edd41d3c Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Wed, 26 Jun 2024 16:35:45 -0400 Subject: [PATCH 12/86] Added import statements --- score_definition.py | 3 ++- score_execution.py | 5 +++-- 2 files changed, 5 insertions(+), 3 deletions(-) diff --git a/score_definition.py b/score_definition.py index 3bfe2c0e..a39b3552 100644 --- a/score_definition.py +++ b/score_definition.py @@ -5,7 +5,7 @@ import json from typing import Union -from sasctl import Session +from ..core import current_session, delete, get, sasctl_command from .cas_management import CASManagement from .model_repository import ModelRepository as mr from .service import Service @@ -20,6 +20,7 @@ class ScoreDefinitions(Service): See Also -------- `REST Documentation ` + """ _SERVICE_ROOT = "/scoreDefinitions" diff --git a/score_execution.py b/score_execution.py index 56eba931..4b6eb127 100644 --- a/score_execution.py +++ b/score_execution.py @@ -4,8 +4,8 @@ import json from typing import Union -from sasctl import Session -#from sasctl._services.cas_management import CASManagement as cas +#from sasctl import Session +from ..core import current_session, delete, get, sasctl_command from .score_definition import ScoreDefinitions as sd from .service import Service @@ -17,6 +17,7 @@ class ScoreExecutions(Service): See Also -------- `REST Documentation ` + """ _SERVICE_ROOT = "/scoreExecution" From ba59858906a9901e22dcc19d89330d82d8955ebe Mon Sep 17 00:00:00 2001 From: Samya Potlapalli Date: Wed, 26 Jun 2024 17:00:18 -0400 Subject: [PATCH 13/86] Rename score_execution.py to src/_services/score_execution.py --- score_execution.py => src/_services/score_execution.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) rename score_execution.py => src/_services/score_execution.py (98%) diff --git a/score_execution.py b/src/_services/score_execution.py similarity index 98% rename from score_execution.py rename to src/_services/score_execution.py index 4b6eb127..0debd0cf 100644 --- a/score_execution.py +++ b/src/_services/score_execution.py @@ -92,4 +92,4 @@ def score_execution(cls, score_definition_id: str, description: str = "", outpu # Creating the score execution new_score_execution = cls.post("scoreExecution/executions", data=json.dumps(create_score_exec), headers=headers_score_exec) - return new_score_execution \ No newline at end of file + return new_score_execution From ba11e118b7960fe78c2a70c79c25027f2f5528f8 Mon Sep 17 00:00:00 2001 From: Samya Potlapalli Date: Fri, 28 Jun 2024 12:49:25 -0400 Subject: [PATCH 14/86] Rename score_definition.py to src/sasctl/_services/score_definition.py --- score_definition.py => src/sasctl/_services/score_definition.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) rename score_definition.py => src/sasctl/_services/score_definition.py (99%) diff --git a/score_definition.py b/src/sasctl/_services/score_definition.py similarity index 99% rename from score_definition.py rename to src/sasctl/_services/score_definition.py index a39b3552..a5c17b9c 100644 --- a/score_definition.py +++ b/src/sasctl/_services/score_definition.py @@ -116,4 +116,4 @@ def create_score_definition(cls, score_def_name: str, model_id: str, table_name new_score_def = cls.post("/definitions", data=json.dumps(save_score_def), headers=headers_score_def) return new_score_def - # The response information of the score definition can be seen as a JSON as well as the RestOBJ \ No newline at end of file + # The response information of the score definition can be seen as a JSON as well as the RestOBJ From 409167c56476782558173ac23d8468b6f1d3a43a Mon Sep 17 00:00:00 2001 From: Scott-Lindauer_sasinst Date: Mon, 1 Jul 2024 14:03:08 -0400 Subject: [PATCH 15/86] refactor: move score_execution to appropriate directory --- src/_services/score_execution.py | 95 ---------------- src/sasctl/_services/score_execution.py | 140 +++++++++--------------- 2 files changed, 50 insertions(+), 185 deletions(-) delete mode 100644 src/_services/score_execution.py diff --git a/src/_services/score_execution.py b/src/_services/score_execution.py deleted file mode 100644 index 0debd0cf..00000000 --- a/src/_services/score_execution.py +++ /dev/null @@ -1,95 +0,0 @@ -import requests - -from pathlib import Path -import json -from typing import Union - -#from sasctl import Session -from ..core import current_session, delete, get, sasctl_command -from .score_definition import ScoreDefinitions as sd -from .service import Service - -class ScoreExecutions(Service): - """ - The Score Execution API is used to produce a score by - executing the mapped code generated by score objects using the score definition. - - See Also - -------- - `REST Documentation ` - - """ - - _SERVICE_ROOT = "/scoreExecution" - - list_executions, get_execution, update_execution, delete_execution = Service._crud_funcs( - "/executions", "execution") - -@classmethod -def score_execution(cls, score_definition_id: str, description: str = "", output_server_name: str = "cas-shared-default", output_library_name: str = "Public", output_table_name: str = ""): - """Creates the score definition service. - - Parameters - -------- - score_definition_id: str - A score definition id representing score definition existing on the server that needs to be executed. - description: str, optional - Description of score execution. Defaults to an empty string. - output_server_name: str, optional - The name of the output server the output table and output library is stored in. Defaults to "cas-shared-default". - output_library_name: str, optional - The name of the output library the output table is stored in. Defaults to "Public". - output_table_name: str, optional - The name of the output table the score execution or analysis output will be stored in. Defaults to an empty string. - - Returns - ------- - RestObj - - """ - - try: - score_definition = sd.get_definition(score_definition_id) - score_exec_name = score_definition.json()["name"] - model_uri = score_definition.json()["objectDescriptor"]["uri"] - model_name = score_definition.json()["objectDescriptor"]["name"] - model_input_library = score_definition.json()["inputData"]["libraryName"] - model_input_server = score_definition.json()["inputData"]["serverName"] - model_table_name = score_definition.json()["inputData"]["tableName"] - except: - raise Exception('The score definition may not exist.') - # Gets information about the scoring object from the score definition and raises an exception if the score definition does not exist - - if output_table_name == "": - output_table_name = f"{model_name}_{score_definition_id}" - # Defining a default output table name - try: - score_execution = sess.get(f"/scoreExecution/executions?filter=eq(scoreExecutionRequest.scoreDefinitionId,%27{score_definition_id}%27)") # how to use crud functions on something with such a specifc filter - execution_count = score_execution.json()['count'] - if execution_count == 1: - execution_id = score_execution.json()["items"][0]["id"] - deleted_score_execution = cls.delete_execution(execution_id) - print(deleted_score_execution) - except: - print("There may not be a score execution already running.") - - # Deleting any score executions that are already executing the same score definition - - headers_score_exec = { - "Content-Type": "application/json" - } - - create_score_exec = {"name": score_exec_name, - "description": description, - "hints": {"objectURI":model_uri, - "inputTableName":model_table_name, - "inputLibraryName": model_input_library}, - "scoreDefinitionId": score_definition_id, - "outputTable": {"tableName": output_table_name, - "libraryName": output_library_name, - "serverName": output_server_name}} - - # Creating the score execution - - new_score_execution = cls.post("scoreExecution/executions", data=json.dumps(create_score_exec), headers=headers_score_exec) - return new_score_execution diff --git a/src/sasctl/_services/score_execution.py b/src/sasctl/_services/score_execution.py index 38625bcb..0b0c8b1d 100644 --- a/src/sasctl/_services/score_execution.py +++ b/src/sasctl/_services/score_execution.py @@ -4,76 +4,40 @@ import json from typing import Union -from sasctl import Session -from sasctl._services.cas_management import CASManagement as cas +from .score_definition import ScoreDefinitions as sd +from .service import Service - -def score_execution(score_definition, description: str = "", output_server_name: str = "cas-shared-default", output_library_name: str = "Public", output_table_name: str = ""): - """Creates the score definition service. +class ScoreExecution(Service): + """ + The Score Execution API is used to produce a score by + executing the mapped code generated by score objects using the score definition. - Parameters + See Also -------- - score_definition - Score Definition RestObj. - description: str - Description of score definition. Defaults to an empty string. - output_server_name: str, optional - The server within CAS that the output table is in. Defaults to "cas-shared-default". - output_library_name: str, optional - The library within the CAS server the output table exists in. Defaults to "Public". - output_table_name: str, optional - The name of the output table. Defaults to an empty string. - + `REST Documentation ` - Returns - ------- - RestObj - """ - try: - score_definition_id = score_definition.json()["id"] - score_definition_name = score_definition.json()["name"] - score_definition_model_id = score_definition.json["modelId"] - score_definition_model_name = score_definition.json["modelName"] - except: - print("The input score definition object may not exist. Please check it was passed in correctly") - - if output_table_name == "": - output_table_name = f"{score_definition_model_name}_{score_definition_id}" - - try: - filtered_score_executions = sess.get(f"scoreExecution/executions?filter=eq(scoreExecutionRequest.scoreDefinitionId,%27{score_definition_id}%27)") - deleted_score_execution = sess.delete(f"scoreExecution/executions/{filtered_score_executions["items"][0]["id"]}") - #can there be more than one score execution for a score definition running (execCount >= 1) - except: - pass - - import requests - -from pathlib import Path -import json -from typing import Union - -from sasctl import Session -from sasctl._services.cas_management import CASManagement as cas - - - + + _SERVICE_ROOT = "/scoreExecution" + + list_executions, get_execution, update_execution, delete_execution = Service._crud_funcs( + "/executions", "execution") -def score_execution(score_definition, description: str = "", output_server_name: str = "cas-shared-default", output_library_name: str = "Public", output_table_name: str = ""): +@classmethod +def score_execution(cls, score_definition_id: str, description: str = "", output_server_name: str = "cas-shared-default", output_library_name: str = "Public", output_table_name: str = ""): """Creates the score definition service. Parameters -------- - score_definition: RestObj - A score definition existing on the server. - description: str + score_definition_id: str + A score definition id representing score definition existing on the server that needs to be executed. + description: str, optional Description of score execution. Defaults to an empty string. - output_server_name: str + output_server_name: str, optional The name of the output server the output table and output library is stored in. Defaults to "cas-shared-default". - output_library_name: str + output_library_name: str, optional The name of the output library the output table is stored in. Defaults to "Public". - output_table_name: str + output_table_name: str, optional The name of the output table the score execution or analysis output will be stored in. Defaults to an empty string. Returns @@ -82,52 +46,48 @@ def score_execution(score_definition, description: str = "", output_server_name """ - headers_score_exec = { - "Content-Type": "application/json" - } - try: - - score_def_id = score_definition.json()["id"] + score_definition = sd.get_definition(score_definition_id) score_exec_name = score_definition.json()["name"] model_uri = score_definition.json()["objectDescriptor"]["uri"] model_name = score_definition.json()["objectDescriptor"]["name"] model_input_library = score_definition.json()["inputData"]["libraryName"] model_input_server = score_definition.json()["inputData"]["serverName"] model_table_name = score_definition.json()["inputData"]["tableName"] - - model_table = sess.get(f"casManagement/servers/{model_input_server}/caslibs/{model_input_library}/tables/{model_table_name}") - model_table_name = model_table.json()["name"] - model_table_id = model_table.json()["id"] except: - print("The score definition may not exist or the fields are incomplete.") - + raise Exception('The score definition may not exist.') + # Gets information about the scoring object from the score definition and raises an exception if the score definition does not exist + if output_table_name == "": - output_table_name = f"{model_name}_{score_def_id}" #is output table the same as I specified in score_definition/do I need to create one or does it automatically create one? + output_table_name = f"{model_name}_{score_definition_id}" + # Defining a default output table name try: - score_execution = sess.get(f"/scoreExecution/executions?filter=eq(scoreExecutionRequest.scoreDefinitionId,%27{score_def_id}%27)") #getting all of them because - execCount = score_execution.json()['count'] - if execCount == 1: - execTaskId = score_execution.json()["items"][0]["id"] - deleted_score_execution = sess.delete(f"scoreExecution/executions/{execTaskId}") + score_execution = sd.get(f"/scoreExecution/executions?filter=eq(scoreExecutionRequest.scoreDefinitionId,%27{score_definition_id}%27)") # how to use crud functions on something with such a specifc filter + execution_count = score_execution.json()['count'] + if execution_count == 1: + execution_id = score_execution.json()["items"][0]["id"] + deleted_score_execution = cls.delete_execution(execution_id) print(deleted_score_execution) except: print("There may not be a score execution already running.") - - create_score_exec = {"name": score_exec_name, - "description": description, - "hints": {"objectURI":model_uri, #because I'm scoring a model, is that why this is required? - "modelTable":model_table_id, - "inputTableName":model_table_name, - "inputLibraryName": model_input_library}, - "scoreDefinitionId": score_def_id, - "outputTable": {"tableName": output_table_name, - "libraryName": output_library_name, - "serverName": output_server_name}} - new_score_execution = sess.post("scoreExecution/executions", data=json.dumps(create_score_exec), header=headers_score_exec) - return new_score_execution - - + # Deleting any score executions that are already executing the same score definition + headers_score_exec = { + "Content-Type": "application/json" + } + create_score_exec = {"name": score_exec_name, + "description": description, + "hints": {"objectURI":model_uri, + "inputTableName":model_table_name, + "inputLibraryName": model_input_library}, + "scoreDefinitionId": score_definition_id, + "outputTable": {"tableName": output_table_name, + "libraryName": output_library_name, + "serverName": output_server_name}} + + # Creating the score execution + + new_score_execution = cls.post("scoreExecution/executions", data=json.dumps(create_score_exec), headers=headers_score_exec) + return new_score_execution From a7e6288fd4bb53f71a72de361641f14df9a9940e Mon Sep 17 00:00:00 2001 From: Scott-Lindauer_sasinst Date: Mon, 1 Jul 2024 14:04:48 -0400 Subject: [PATCH 16/86] refactor: remove redundant score_definition.py; leave plural form to match API --- src/sasctl/_services/score_definition.py | 119 ---------------------- src/sasctl/_services/score_definitions.py | 34 ++++--- 2 files changed, 19 insertions(+), 134 deletions(-) delete mode 100644 src/sasctl/_services/score_definition.py diff --git a/src/sasctl/_services/score_definition.py b/src/sasctl/_services/score_definition.py deleted file mode 100644 index a5c17b9c..00000000 --- a/src/sasctl/_services/score_definition.py +++ /dev/null @@ -1,119 +0,0 @@ -import requests -import sys - -from pathlib import Path -import json -from typing import Union - -from ..core import current_session, delete, get, sasctl_command -from .cas_management import CASManagement -from .model_repository import ModelRepository as mr -from .service import Service - - -class ScoreDefinitions(Service): - """ - Used for creating and maintaining score definitions. - - The Score Definitions API is used for creating and maintaining score definitions. - - See Also - -------- - `REST Documentation ` - - """ - - _SERVICE_ROOT = "/scoreDefinitions" - _cas_management = CASManagement() - - list_definitions, get_definition, update_definition, delete_definition = Service._crud_funcs( - "/definitions", "definition") - - @classmethod - def create_score_definition(cls, score_def_name: str, model_id: str, table_name: str, description:str = "", server_name: str = "cas-shared-default", library_name: str = "Public", model_version: str = "latest"): - """Creates the score definition service. - - Parameters - -------- - score_def_name: str - Name of score definition. - model_id: str - A user-inputted model if where the model exists in a project. - table_name: str - A user-inputted table name in CAS Management. - description: str, optional - Description of score definition. Defaults to an empty string. - server_name: str, optional - The server within CAS that the table is in. Defaults to "cas-shared-default". - library_name: str, optional - The library within the CAS server the table exists in. Defaults to "Public". - model_version: str, optional - The user-chosen version of the model with the specified model_id. Defaults to "latest". - - Returns - ------- - RestObj - - """ - - try: - model = mr.get_model(model_id) - model_project_id = model.json()["projectId"] - model_project_version_id = model.json()["projectVersionId"] - model_name = model.json()["name"] - - except: - raise Exception("This model may not exist in a project or the model may not exist at all.") - # Checking if the model exists and if it's in a project - - try: - inputMapping = [] - for input_item in model.json()["inputVariables"]: - var = {"mappingValue":input_item["name"],"mappingType":"datasource","variableName":input_item["name"]} - inputMapping.append(var) - except: - print("This model does not have the optional 'inputVariables' parameter.") - - # Optional mapping - Maps the variables in the data to the variables of the score object. It's not necessary to create a score definition. - - table = cls._cas_management.get_table(server_name, library_name, table_name) - try: - table.raise_for_status() - except requests.exceptions.HTTPError as error: - print(f"HTTP Error: {error}") - table_file = input("The inputted table does not exist. Enter the file path for the data in your table (CSV, XLS, XLSX, SAS7BDT or SASHDAT file).") - cls._cas_management.upload_file(str(table_file), table_name) #do I need to add a check if the file doesn't exist or does upload_file take care of that? - table = cls._cas_management.get_table(server_name, library_name, table_name) - # Checks if the inputted table exists, and if not, uploads a file to create a new table - try: - table.raise_for_status() - except requests.exceptions.HTTPError as error: - print(f"HTTP Error: {error}") - raise Exception("Something went wrong when creating a table. Check to see if the file path inputted exists.") - - save_score_def = {"name": score_def_name, - "description": description, - "objectDescriptor":{"uri":f"/modelManagement/models/{model_id}", - "name":f"{model_name}({model_version})", - "type":"sas.models.model"}, - "inputData":{"type":"CASTable", - "serverName":server_name, - "libraryName":library_name, - "tableName":table_name}, - "properties":{"tableBaseName":"", - "modelOrigUri":f"/modelRepository/models/{model_id}", - "projectUri":f"/modelRepository/projects/{model_project_id}", - "projectVersionUri": f"/modelRepository/projects/{model_project_id}/projectVersions/{model_project_version_id}", - "publishDestination":"", - "versionedModel": f"{model_name}({model_version})"}, - "mappings": inputMapping} - # Consolidating all of the model and table information to create the score definition information - - headers_score_def = { - 'Content-Type': "application/json" - } - - new_score_def = cls.post("/definitions", data=json.dumps(save_score_def), headers=headers_score_def) - - return new_score_def - # The response information of the score definition can be seen as a JSON as well as the RestOBJ diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index 5faf82d8..a5c17b9c 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -5,7 +5,7 @@ import json from typing import Union -from sasctl import Session +from ..core import current_session, delete, get, sasctl_command from .cas_management import CASManagement from .model_repository import ModelRepository as mr from .service import Service @@ -19,7 +19,8 @@ class ScoreDefinitions(Service): See Also -------- - `` + `REST Documentation ` + """ _SERVICE_ROOT = "/scoreDefinitions" @@ -28,8 +29,8 @@ class ScoreDefinitions(Service): list_definitions, get_definition, update_definition, delete_definition = Service._crud_funcs( "/definitions", "definition") - # def create_score_definition() - def score_definition(cls, score_def_name: str, model_id: str, table_name: str, description:str = "", server_name: str = "cas-shared-default", library_name: str = "Public", model_version: str = "latest"): + @classmethod + def create_score_definition(cls, score_def_name: str, model_id: str, table_name: str, description:str = "", server_name: str = "cas-shared-default", library_name: str = "Public", model_version: str = "latest"): """Creates the score definition service. Parameters @@ -62,7 +63,7 @@ def score_definition(cls, score_def_name: str, model_id: str, table_name: str, model_name = model.json()["name"] except: - sys.exit("This model may not exist in a project or the model may not exist at all.") + raise Exception("This model may not exist in a project or the model may not exist at all.") # Checking if the model exists and if it's in a project try: @@ -77,15 +78,18 @@ def score_definition(cls, score_def_name: str, model_id: str, table_name: str, table = cls._cas_management.get_table(server_name, library_name, table_name) try: - table_status_code = table.json()['httpStatusCode'] - if table_status_code == 404 or table_status_code == 400: - table_file = input("The inputted table does not exist. Enter the file path for the data in your table (CSV, XLS, XLSX, SAS7BDT or SASHDAT file).") - cls._cas_management.upload_file(str(table_file), table_name) #do I need to add a check if the file doesn't exist or does upload_file take care of that? - table = cls._cas_management.get_table(server_name, library_name, table_name) - # Checks if the inputted table exists, and if not, uploads a file to create a new table - except: - pass - #The API call to get the table was successful, and therefore will not have an 'httpStatusCode' value. This 'pass' statement will allow the successful get API calls to proceed. + table.raise_for_status() + except requests.exceptions.HTTPError as error: + print(f"HTTP Error: {error}") + table_file = input("The inputted table does not exist. Enter the file path for the data in your table (CSV, XLS, XLSX, SAS7BDT or SASHDAT file).") + cls._cas_management.upload_file(str(table_file), table_name) #do I need to add a check if the file doesn't exist or does upload_file take care of that? + table = cls._cas_management.get_table(server_name, library_name, table_name) + # Checks if the inputted table exists, and if not, uploads a file to create a new table + try: + table.raise_for_status() + except requests.exceptions.HTTPError as error: + print(f"HTTP Error: {error}") + raise Exception("Something went wrong when creating a table. Check to see if the file path inputted exists.") save_score_def = {"name": score_def_name, "description": description, @@ -112,4 +116,4 @@ def score_definition(cls, score_def_name: str, model_id: str, table_name: str, new_score_def = cls.post("/definitions", data=json.dumps(save_score_def), headers=headers_score_def) return new_score_def - # The response information of the score definition can be seen as a JSON as well as the RestOBJ \ No newline at end of file + # The response information of the score definition can be seen as a JSON as well as the RestOBJ From 8d55624676c2aeeff327993407909fa384c73f95 Mon Sep 17 00:00:00 2001 From: Scott-Lindauer_sasinst Date: Mon, 1 Jul 2024 14:07:50 -0400 Subject: [PATCH 17/86] chore: apply black linter --- src/sasctl/_services/score_definitions.py | 120 ++++++++++++++-------- src/sasctl/_services/score_execution.py | 82 +++++++++------ 2 files changed, 126 insertions(+), 76 deletions(-) diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index a5c17b9c..d9836820 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -14,25 +14,35 @@ class ScoreDefinitions(Service): """ Used for creating and maintaining score definitions. - + The Score Definitions API is used for creating and maintaining score definitions. - + See Also -------- `REST Documentation ` - + """ - + _SERVICE_ROOT = "/scoreDefinitions" _cas_management = CASManagement() - - list_definitions, get_definition, update_definition, delete_definition = Service._crud_funcs( - "/definitions", "definition") - + + list_definitions, get_definition, update_definition, delete_definition = ( + Service._crud_funcs("/definitions", "definition") + ) + @classmethod - def create_score_definition(cls, score_def_name: str, model_id: str, table_name: str, description:str = "", server_name: str = "cas-shared-default", library_name: str = "Public", model_version: str = "latest"): + def create_score_definition( + cls, + score_def_name: str, + model_id: str, + table_name: str, + description: str = "", + server_name: str = "cas-shared-default", + library_name: str = "Public", + model_version: str = "latest", + ): """Creates the score definition service. - + Parameters -------- score_def_name: str @@ -40,7 +50,7 @@ def create_score_definition(cls, score_def_name: str, model_id: str, table_name model_id: str A user-inputted model if where the model exists in a project. table_name: str - A user-inputted table name in CAS Management. + A user-inputted table name in CAS Management. description: str, optional Description of score definition. Defaults to an empty string. server_name: str, optional @@ -48,8 +58,8 @@ def create_score_definition(cls, score_def_name: str, model_id: str, table_name library_name: str, optional The library within the CAS server the table exists in. Defaults to "Public". model_version: str, optional - The user-chosen version of the model with the specified model_id. Defaults to "latest". - + The user-chosen version of the model with the specified model_id. Defaults to "latest". + Returns ------- RestObj @@ -61,59 +71,79 @@ def create_score_definition(cls, score_def_name: str, model_id: str, table_name model_project_id = model.json()["projectId"] model_project_version_id = model.json()["projectVersionId"] model_name = model.json()["name"] - + except: - raise Exception("This model may not exist in a project or the model may not exist at all.") + raise Exception( + "This model may not exist in a project or the model may not exist at all." + ) # Checking if the model exists and if it's in a project - + try: inputMapping = [] for input_item in model.json()["inputVariables"]: - var = {"mappingValue":input_item["name"],"mappingType":"datasource","variableName":input_item["name"]} + var = { + "mappingValue": input_item["name"], + "mappingType": "datasource", + "variableName": input_item["name"], + } inputMapping.append(var) except: print("This model does not have the optional 'inputVariables' parameter.") - + # Optional mapping - Maps the variables in the data to the variables of the score object. It's not necessary to create a score definition. - + table = cls._cas_management.get_table(server_name, library_name, table_name) try: table.raise_for_status() except requests.exceptions.HTTPError as error: print(f"HTTP Error: {error}") - table_file = input("The inputted table does not exist. Enter the file path for the data in your table (CSV, XLS, XLSX, SAS7BDT or SASHDAT file).") - cls._cas_management.upload_file(str(table_file), table_name) #do I need to add a check if the file doesn't exist or does upload_file take care of that? + table_file = input( + "The inputted table does not exist. Enter the file path for the data in your table (CSV, XLS, XLSX, SAS7BDT or SASHDAT file)." + ) + cls._cas_management.upload_file( + str(table_file), table_name + ) # do I need to add a check if the file doesn't exist or does upload_file take care of that? table = cls._cas_management.get_table(server_name, library_name, table_name) # Checks if the inputted table exists, and if not, uploads a file to create a new table try: table.raise_for_status() except requests.exceptions.HTTPError as error: - print(f"HTTP Error: {error}") - raise Exception("Something went wrong when creating a table. Check to see if the file path inputted exists.") - - save_score_def = {"name": score_def_name, - "description": description, - "objectDescriptor":{"uri":f"/modelManagement/models/{model_id}", - "name":f"{model_name}({model_version})", - "type":"sas.models.model"}, - "inputData":{"type":"CASTable", - "serverName":server_name, - "libraryName":library_name, - "tableName":table_name}, - "properties":{"tableBaseName":"", - "modelOrigUri":f"/modelRepository/models/{model_id}", - "projectUri":f"/modelRepository/projects/{model_project_id}", - "projectVersionUri": f"/modelRepository/projects/{model_project_id}/projectVersions/{model_project_version_id}", - "publishDestination":"", - "versionedModel": f"{model_name}({model_version})"}, - "mappings": inputMapping} - # Consolidating all of the model and table information to create the score definition information - - headers_score_def = { - 'Content-Type': "application/json" + print(f"HTTP Error: {error}") + raise Exception( + "Something went wrong when creating a table. Check to see if the file path inputted exists." + ) + + save_score_def = { + "name": score_def_name, + "description": description, + "objectDescriptor": { + "uri": f"/modelManagement/models/{model_id}", + "name": f"{model_name}({model_version})", + "type": "sas.models.model", + }, + "inputData": { + "type": "CASTable", + "serverName": server_name, + "libraryName": library_name, + "tableName": table_name, + }, + "properties": { + "tableBaseName": "", + "modelOrigUri": f"/modelRepository/models/{model_id}", + "projectUri": f"/modelRepository/projects/{model_project_id}", + "projectVersionUri": f"/modelRepository/projects/{model_project_id}/projectVersions/{model_project_version_id}", + "publishDestination": "", + "versionedModel": f"{model_name}({model_version})", + }, + "mappings": inputMapping, } + # Consolidating all of the model and table information to create the score definition information + + headers_score_def = {"Content-Type": "application/json"} - new_score_def = cls.post("/definitions", data=json.dumps(save_score_def), headers=headers_score_def) + new_score_def = cls.post( + "/definitions", data=json.dumps(save_score_def), headers=headers_score_def + ) return new_score_def # The response information of the score definition can be seen as a JSON as well as the RestOBJ diff --git a/src/sasctl/_services/score_execution.py b/src/sasctl/_services/score_execution.py index 0b0c8b1d..bc2ab728 100644 --- a/src/sasctl/_services/score_execution.py +++ b/src/sasctl/_services/score_execution.py @@ -4,29 +4,39 @@ import json from typing import Union -from .score_definition import ScoreDefinitions as sd +from .score_definitions import ScoreDefinitions as sd from .service import Service + class ScoreExecution(Service): """ - The Score Execution API is used to produce a score by + The Score Execution API is used to produce a score by executing the mapped code generated by score objects using the score definition. - + See Also -------- `REST Documentation ` - + """ - + _SERVICE_ROOT = "/scoreExecution" - - list_executions, get_execution, update_execution, delete_execution = Service._crud_funcs( - "/executions", "execution") + + list_executions, get_execution, update_execution, delete_execution = ( + Service._crud_funcs("/executions", "execution") + ) + @classmethod -def score_execution(cls, score_definition_id: str, description: str = "", output_server_name: str = "cas-shared-default", output_library_name: str = "Public", output_table_name: str = ""): +def score_execution( + cls, + score_definition_id: str, + description: str = "", + output_server_name: str = "cas-shared-default", + output_library_name: str = "Public", + output_table_name: str = "", +): """Creates the score definition service. - + Parameters -------- score_definition_id: str @@ -39,7 +49,7 @@ def score_execution(cls, score_definition_id: str, description: str = "", outpu The name of the output library the output table is stored in. Defaults to "Public". output_table_name: str, optional The name of the output table the score execution or analysis output will be stored in. Defaults to an empty string. - + Returns ------- RestObj @@ -55,39 +65,49 @@ def score_execution(cls, score_definition_id: str, description: str = "", outpu model_input_server = score_definition.json()["inputData"]["serverName"] model_table_name = score_definition.json()["inputData"]["tableName"] except: - raise Exception('The score definition may not exist.') + raise Exception("The score definition may not exist.") # Gets information about the scoring object from the score definition and raises an exception if the score definition does not exist - + if output_table_name == "": output_table_name = f"{model_name}_{score_definition_id}" # Defining a default output table name try: - score_execution = sd.get(f"/scoreExecution/executions?filter=eq(scoreExecutionRequest.scoreDefinitionId,%27{score_definition_id}%27)") # how to use crud functions on something with such a specifc filter - execution_count = score_execution.json()['count'] + score_execution = sd.get( + f"/scoreExecution/executions?filter=eq(scoreExecutionRequest.scoreDefinitionId,%27{score_definition_id}%27)" + ) # how to use crud functions on something with such a specifc filter + execution_count = score_execution.json()["count"] if execution_count == 1: execution_id = score_execution.json()["items"][0]["id"] deleted_score_execution = cls.delete_execution(execution_id) print(deleted_score_execution) except: print("There may not be a score execution already running.") - + # Deleting any score executions that are already executing the same score definition - headers_score_exec = { - "Content-Type": "application/json" + headers_score_exec = {"Content-Type": "application/json"} + + create_score_exec = { + "name": score_exec_name, + "description": description, + "hints": { + "objectURI": model_uri, + "inputTableName": model_table_name, + "inputLibraryName": model_input_library, + }, + "scoreDefinitionId": score_definition_id, + "outputTable": { + "tableName": output_table_name, + "libraryName": output_library_name, + "serverName": output_server_name, + }, } - create_score_exec = {"name": score_exec_name, - "description": description, - "hints": {"objectURI":model_uri, - "inputTableName":model_table_name, - "inputLibraryName": model_input_library}, - "scoreDefinitionId": score_definition_id, - "outputTable": {"tableName": output_table_name, - "libraryName": output_library_name, - "serverName": output_server_name}} - # Creating the score execution - - new_score_execution = cls.post("scoreExecution/executions", data=json.dumps(create_score_exec), headers=headers_score_exec) - return new_score_execution + + new_score_execution = cls.post( + "scoreExecution/executions", + data=json.dumps(create_score_exec), + headers=headers_score_exec, + ) + return new_score_execution From 6e6390d5a1e960f80a95108e474011ac0f337329 Mon Sep 17 00:00:00 2001 From: Scott-Lindauer_sasinst Date: Mon, 1 Jul 2024 15:11:57 -0400 Subject: [PATCH 18/86] refactor: add comments and proper indenting for classmethod --- src/sasctl/_services/score_execution.py | 161 ++++++++++++------------ 1 file changed, 79 insertions(+), 82 deletions(-) diff --git a/src/sasctl/_services/score_execution.py b/src/sasctl/_services/score_execution.py index bc2ab728..f2032ba1 100644 --- a/src/sasctl/_services/score_execution.py +++ b/src/sasctl/_services/score_execution.py @@ -1,9 +1,9 @@ -import requests - from pathlib import Path import json from typing import Union +from requests import HTTPError + from .score_definitions import ScoreDefinitions as sd from .service import Service @@ -25,89 +25,86 @@ class ScoreExecution(Service): Service._crud_funcs("/executions", "execution") ) - -@classmethod -def score_execution( - cls, - score_definition_id: str, - description: str = "", - output_server_name: str = "cas-shared-default", - output_library_name: str = "Public", - output_table_name: str = "", -): - """Creates the score definition service. - - Parameters - -------- - score_definition_id: str - A score definition id representing score definition existing on the server that needs to be executed. - description: str, optional - Description of score execution. Defaults to an empty string. - output_server_name: str, optional - The name of the output server the output table and output library is stored in. Defaults to "cas-shared-default". - output_library_name: str, optional - The name of the output library the output table is stored in. Defaults to "Public". - output_table_name: str, optional - The name of the output table the score execution or analysis output will be stored in. Defaults to an empty string. - - Returns - ------- - RestObj - - """ - - try: + @classmethod + def score_execution( + cls, + score_definition_id: str, + description: str = "", + output_server_name: str = "cas-shared-default", + output_library_name: str = "Public", + output_table_name: str = "", + ): + """Creates the score definition service. + + Parameters + -------- + score_definition_id: str + A score definition id representing score definition existing on the server that needs to be executed. + description: str, optional + Description of score execution. Defaults to an empty string. + output_server_name: str, optional + The name of the output server the output table and output library is stored in. Defaults to "cas-shared-default". + output_library_name: str, optional + The name of the output library the output table is stored in. Defaults to "Public". + output_table_name: str, optional + The name of the output table the score execution or analysis output will be stored in. Defaults to an empty string. + + Returns + ------- + RestObj + + """ + + # Gets information about the scoring object from the score definition and raises an exception if the score definition does not exist score_definition = sd.get_definition(score_definition_id) + if score_definition.status_code >= 400: + raise HTTPError(score_definition.json()) score_exec_name = score_definition.json()["name"] model_uri = score_definition.json()["objectDescriptor"]["uri"] model_name = score_definition.json()["objectDescriptor"]["name"] model_input_library = score_definition.json()["inputData"]["libraryName"] - model_input_server = score_definition.json()["inputData"]["serverName"] + model_input_server = score_definition.json()["inputData"]["serverName"] # Will this value be used in the future? If not, remove? -- Scott model_table_name = score_definition.json()["inputData"]["tableName"] - except: - raise Exception("The score definition may not exist.") - # Gets information about the scoring object from the score definition and raises an exception if the score definition does not exist - - if output_table_name == "": - output_table_name = f"{model_name}_{score_definition_id}" - # Defining a default output table name - try: - score_execution = sd.get( - f"/scoreExecution/executions?filter=eq(scoreExecutionRequest.scoreDefinitionId,%27{score_definition_id}%27)" - ) # how to use crud functions on something with such a specifc filter - execution_count = score_execution.json()["count"] - if execution_count == 1: - execution_id = score_execution.json()["items"][0]["id"] - deleted_score_execution = cls.delete_execution(execution_id) - print(deleted_score_execution) - except: - print("There may not be a score execution already running.") - - # Deleting any score executions that are already executing the same score definition - - headers_score_exec = {"Content-Type": "application/json"} - - create_score_exec = { - "name": score_exec_name, - "description": description, - "hints": { - "objectURI": model_uri, - "inputTableName": model_table_name, - "inputLibraryName": model_input_library, - }, - "scoreDefinitionId": score_definition_id, - "outputTable": { - "tableName": output_table_name, - "libraryName": output_library_name, - "serverName": output_server_name, - }, - } - - # Creating the score execution - - new_score_execution = cls.post( - "scoreExecution/executions", - data=json.dumps(create_score_exec), - headers=headers_score_exec, - ) - return new_score_execution + + # Defining a default output table name if none is provided + if not output_table_name: + output_table_name = f"{model_name}_{score_definition_id}" + + # Deleting any score executions that are already executing the same score definition + try: + score_execution = sd.get( + f"/scoreExecution/executions?filter=eq(scoreExecutionRequest.scoreDefinitionId,%27{score_definition_id}%27)" + ) # how to use crud functions on something with such a specifc filter -- You can't; this is as good as it gets -- Scott + execution_count = score_execution.json()["count"] # Exception catch location + if execution_count == 1: + execution_id = score_execution.json()["items"][0]["id"] + deleted_score_execution = cls.delete_execution(execution_id) + print(deleted_score_execution) + except KeyError: + print("There may not be a score execution already running.") + + headers_score_exec = {"Content-Type": "application/json"} + + create_score_exec = { + "name": score_exec_name, + "description": description, + "hints": { + "objectURI": model_uri, + "inputTableName": model_table_name, + "inputLibraryName": model_input_library, + }, + "scoreDefinitionId": score_definition_id, + "outputTable": { + "tableName": output_table_name, + "libraryName": output_library_name, + "serverName": output_server_name, + }, + } + + # Creating the score execution + new_score_execution = cls.post( + "scoreExecution/executions", + data=json.dumps(create_score_exec), + headers=headers_score_exec, + ) + return new_score_execution From fcb19abab9b3ca012a64528a4c971a536c3e9263 Mon Sep 17 00:00:00 2001 From: Scott-Lindauer_sasinst Date: Wed, 3 Jul 2024 11:31:07 -0400 Subject: [PATCH 19/86] fix: proper call to model_repository in score_definitions.py --- src/sasctl/_services/score_definitions.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index d9836820..3294a99b 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -7,7 +7,7 @@ from ..core import current_session, delete, get, sasctl_command from .cas_management import CASManagement -from .model_repository import ModelRepository as mr +from .model_repository import ModelRepository from .service import Service @@ -25,6 +25,7 @@ class ScoreDefinitions(Service): _SERVICE_ROOT = "/scoreDefinitions" _cas_management = CASManagement() + _model_respository = ModelRepository() list_definitions, get_definition, update_definition, delete_definition = ( Service._crud_funcs("/definitions", "definition") @@ -67,7 +68,7 @@ def create_score_definition( """ try: - model = mr.get_model(model_id) + model = cls._model_respository.get_model(model_id) model_project_id = model.json()["projectId"] model_project_version_id = model.json()["projectVersionId"] model_name = model.json()["name"] From a38f4a71a25da1bca46fa9a2101645b9fdc8c11a Mon Sep 17 00:00:00 2001 From: Scott-Lindauer_sasinst Date: Wed, 3 Jul 2024 11:31:46 -0400 Subject: [PATCH 20/86] fix: proper call to cls for score execution and black formatting --- src/sasctl/_services/score_execution.py | 19 +++++++++---------- 1 file changed, 9 insertions(+), 10 deletions(-) diff --git a/src/sasctl/_services/score_execution.py b/src/sasctl/_services/score_execution.py index f2032ba1..b37eb822 100644 --- a/src/sasctl/_services/score_execution.py +++ b/src/sasctl/_services/score_execution.py @@ -1,6 +1,4 @@ -from pathlib import Path import json -from typing import Union from requests import HTTPError @@ -54,7 +52,7 @@ def score_execution( RestObj """ - + # Gets information about the scoring object from the score definition and raises an exception if the score definition does not exist score_definition = sd.get_definition(score_definition_id) if score_definition.status_code >= 400: @@ -63,25 +61,26 @@ def score_execution( model_uri = score_definition.json()["objectDescriptor"]["uri"] model_name = score_definition.json()["objectDescriptor"]["name"] model_input_library = score_definition.json()["inputData"]["libraryName"] - model_input_server = score_definition.json()["inputData"]["serverName"] # Will this value be used in the future? If not, remove? -- Scott model_table_name = score_definition.json()["inputData"]["tableName"] - + # Defining a default output table name if none is provided if not output_table_name: output_table_name = f"{model_name}_{score_definition_id}" - + # Deleting any score executions that are already executing the same score definition try: - score_execution = sd.get( - f"/scoreExecution/executions?filter=eq(scoreExecutionRequest.scoreDefinitionId,%27{score_definition_id}%27)" + score_execution = cls.get( + f"/executions?filter=eq(scoreExecutionRequest.scoreDefinitionId,%27{score_definition_id}%27)" ) # how to use crud functions on something with such a specifc filter -- You can't; this is as good as it gets -- Scott - execution_count = score_execution.json()["count"] # Exception catch location + execution_count = score_execution.json()[ + "count" + ] # Exception catch location if execution_count == 1: execution_id = score_execution.json()["items"][0]["id"] deleted_score_execution = cls.delete_execution(execution_id) print(deleted_score_execution) except KeyError: - print("There may not be a score execution already running.") + print("There may not be a score execution already running.") headers_score_exec = {"Content-Type": "application/json"} From 4087b596a191b99044f5a60e3e0cdc62db414b82 Mon Sep 17 00:00:00 2001 From: Scott-Lindauer_sasinst Date: Wed, 3 Jul 2024 15:17:24 -0400 Subject: [PATCH 21/86] First draft of unit testing for score definitions and score execution --- src/sasctl/_services/score_definitions.py | 7 ++- src/sasctl/_services/score_execution.py | 2 +- tests/unit/test_score_definitions.py | 74 +++++++++++++++++++++++ 3 files changed, 79 insertions(+), 4 deletions(-) create mode 100644 tests/unit/test_score_definitions.py diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index 3294a99b..30bde428 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -1,4 +1,5 @@ import requests +from requests import HTTPError import sys from pathlib import Path @@ -73,9 +74,9 @@ def create_score_definition( model_project_version_id = model.json()["projectVersionId"] model_name = model.json()["name"] - except: - raise Exception( - "This model may not exist in a project or the model may not exist at all." + except KeyError: + raise HTTPError( + "This model may not exist in a project or the model may not exist at all. See error: " + model.json() ) # Checking if the model exists and if it's in a project diff --git a/src/sasctl/_services/score_execution.py b/src/sasctl/_services/score_execution.py index b37eb822..dae3605f 100644 --- a/src/sasctl/_services/score_execution.py +++ b/src/sasctl/_services/score_execution.py @@ -71,7 +71,7 @@ def score_execution( try: score_execution = cls.get( f"/executions?filter=eq(scoreExecutionRequest.scoreDefinitionId,%27{score_definition_id}%27)" - ) # how to use crud functions on something with such a specifc filter -- You can't; this is as good as it gets -- Scott + ) execution_count = score_execution.json()[ "count" ] # Exception catch location diff --git a/tests/unit/test_score_definitions.py b/tests/unit/test_score_definitions.py new file mode 100644 index 00000000..dfb1929b --- /dev/null +++ b/tests/unit/test_score_definitions.py @@ -0,0 +1,74 @@ +#!/usr/bin/env python +# encoding: utf-8 +# +# Copyright © 2024, SAS Institute Inc., Cary, NC, USA. All Rights Reserved. +# SPDX-License-Identifier: Apache-2.0 + +import json +import os +import pickle +import random +import tempfile +import unittest +from pathlib import Path +from unittest import mock + +import numpy as np +import pandas as pd +import pytest +from requests import HTTPError + +import sasctl.pzmm as pzmm +from sasctl import current_session +from sasctl.core import RestObj, VersionInfo +from sasctl._services.score_definitions import ScoreDefinitions as sd + +def test_create_score_definition(): + """ + Test Cases: + - Valid model id? + - yes + - no + - Valid input mapping? + - yes + - no + """ + + with mock.patch( + "sasctl._services.model_repository.ModelRepository.get_model" + ) as get_model: + with mock.patch( + "sasctl._services.cas_management.CASManagement.get_table" + ) as get_table: + with mock.patch( + "sasctl._services.cas_management.CASManagement.upload_file" + ) as upload_file: + # # Test for valid model id, no input mapping, get_table succeeded, and post succeeds + # get_model.return_value = RestObj( + # projectId = "54321", + # projectVersionId = "67890", + # name = "test_model", + # ) + # get_table.return_value = RestObj() + # raise_for_status.return_value = None + + # response = sd.create_score_definition( + # score_def_name = "test_create_sd", + # model_id = "12345", + # table_name = "test_table", + # ) + + # assert response + + # Test for invalid model id + get_model.return_value = RestObj() + with pytest.raises( + HTTPError + ): + sd.create_score_definition( + score_def_name = "test_create_sd", + model_id = "12345", + table_name = "test_table", + ) + + \ No newline at end of file From 43f2ab104f3903ddbf62cd062c1d1765279ac9b0 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Fri, 5 Jul 2024 17:22:22 -0400 Subject: [PATCH 22/86] Added comments for test cases in test.score_definitions.py and started building out functions/calls to test for score_execution --- src/sasctl/_services/score_execution.py | 2 +- tests/unit/test_score_definitions.py | 22 ++++++++++-- tests/unit/test_score_execution.py | 48 +++++++++++++++++++++++++ 3 files changed, 69 insertions(+), 3 deletions(-) create mode 100644 tests/unit/test_score_execution.py diff --git a/src/sasctl/_services/score_execution.py b/src/sasctl/_services/score_execution.py index dae3605f..8561fe45 100644 --- a/src/sasctl/_services/score_execution.py +++ b/src/sasctl/_services/score_execution.py @@ -24,7 +24,7 @@ class ScoreExecution(Service): ) @classmethod - def score_execution( + def create_score_execution( cls, score_definition_id: str, description: str = "", diff --git a/tests/unit/test_score_definitions.py b/tests/unit/test_score_definitions.py index dfb1929b..536c14a3 100644 --- a/tests/unit/test_score_definitions.py +++ b/tests/unit/test_score_definitions.py @@ -32,6 +32,12 @@ def test_create_score_definition(): - Valid input mapping? - yes - no + -Valid table name? + -yes + -no + -Valid file? + -yes + -no """ with mock.patch( @@ -64,11 +70,23 @@ def test_create_score_definition(): get_model.return_value = RestObj() with pytest.raises( HTTPError - ): + ): #test tget_Table since we don't know what the return value is restobj sd.create_score_definition( score_def_name = "test_create_sd", model_id = "12345", table_name = "test_table", ) - + #Test for invalid tableName + + #Test for invalid score_definition json/post doesn't succeed + + #Test for valid model id, with input mapping, get_table succeeded, and post succeeds + + #Test for valid model id, with input mapping, get_table didn't succeed, post succeeds + + #Test for valid model id, with input mapping, get_Table succeeds, post doesn't succeed + + #Testing for valid model id, no input, no get_Table, post doesn't succee + + #do we need to test every possibility of valids and invalids against all the api calls? \ No newline at end of file diff --git a/tests/unit/test_score_execution.py b/tests/unit/test_score_execution.py new file mode 100644 index 00000000..93abfde7 --- /dev/null +++ b/tests/unit/test_score_execution.py @@ -0,0 +1,48 @@ +#!/usr/bin/env python +# encoding: utf-8 +# +# Copyright © 2024, SAS Institute Inc., Cary, NC, USA. All Rights Reserved. +# SPDX-License-Identifier: Apache-2.0 + +import json +import os +import pickle +import random +import tempfile +import unittest +from pathlib import Path +from unittest import mock + +import numpy as np +import pandas as pd +import pytest +from requests import HTTPError + +import sasctl.pzmm as pzmm +from sasctl import current_session +from sasctl.core import RestObj, VersionInfo +from sasctl._services.score_definitions import ScoreDefinitions as sd + +def test_create_score_execution(): + """ + Test Cases: + - Valid score definition id? + -yes + -no + - Valid execution id? + + -Valid count key? + + """ + + with mock.patch( + "sasctl._services.score_definitions.ScoreDefinitions.get_definition" + ) as get_definition: + with mock.patch( + "sasctl._services.score_execution.ScoreExecution.get_execution" + ) as get_execution: + with mock.patch( + "sasctl._services.score_execution.ScoreExecution.delete_execution" + ) as delete_execution: + exit() + #raise HTTP error? \ No newline at end of file From 9e439606f97a281b953d21cdc2e42afca43ad658 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Thu, 11 Jul 2024 15:50:58 -0400 Subject: [PATCH 23/86] Testing requests approach to pass get_model test --- tests/unit/test_score_definitions.py | 65 +++++++++++++--------------- 1 file changed, 31 insertions(+), 34 deletions(-) diff --git a/tests/unit/test_score_definitions.py b/tests/unit/test_score_definitions.py index 536c14a3..f67cded9 100644 --- a/tests/unit/test_score_definitions.py +++ b/tests/unit/test_score_definitions.py @@ -20,7 +20,7 @@ import sasctl.pzmm as pzmm from sasctl import current_session -from sasctl.core import RestObj, VersionInfo +from sasctl.core import RestObj, VersionInfo, request from sasctl._services.score_definitions import ScoreDefinitions as sd def test_create_score_definition(): @@ -43,50 +43,47 @@ def test_create_score_definition(): with mock.patch( "sasctl._services.model_repository.ModelRepository.get_model" ) as get_model: - with mock.patch( + with mock.patch( "sasctl._services.cas_management.CASManagement.get_table" ) as get_table: with mock.patch( "sasctl._services.cas_management.CASManagement.upload_file" ) as upload_file: + get_model.request.return_value.json.return_value = { + "projectId": "54321", + "projectVersionId": "67890", + "name": "test_model" + } + #get_table.return_value = None + #upload_file.return_value = RestObj + + response = sd.create_score_definition( + score_def_name = "test_create_sd", + model_id = "12345", + table_name = "test_table" + ) + assert response + # # Test for valid model id, no input mapping, get_table succeeded, and post succeeds - # get_model.return_value = RestObj( - # projectId = "54321", - # projectVersionId = "67890", - # name = "test_model", - # ) + # get_table.return_value = RestObj() # raise_for_status.return_value = None - # response = sd.create_score_definition( - # score_def_name = "test_create_sd", - # model_id = "12345", - # table_name = "test_table", - # ) + # assert response # Test for invalid model id - get_model.return_value = RestObj() - with pytest.raises( - HTTPError - ): #test tget_Table since we don't know what the return value is restobj - sd.create_score_definition( - score_def_name = "test_create_sd", - model_id = "12345", - table_name = "test_table", - ) - #Test for invalid tableName - - #Test for invalid score_definition json/post doesn't succeed - - #Test for valid model id, with input mapping, get_table succeeded, and post succeeds - - #Test for valid model id, with input mapping, get_table didn't succeed, post succeeds - - #Test for valid model id, with input mapping, get_Table succeeds, post doesn't succeed - - #Testing for valid model id, no input, no get_Table, post doesn't succee - - #do we need to test every possibility of valids and invalids against all the api calls? + #get_model.return_value = RestObj() + #with pytest.raises( + #HTTPError + #): #test tget_Table since we don't know what the return value is restobj + #sd.create_score_definition( + #score_def_name = "test_create_sd", + #model_id = "12345", + #table_name = "test_table", + #) + #Test for valid and invalid for each + #Start with testing invalid and realize you can work from the last call to the first because the last call working means the first call must have worked + \ No newline at end of file From b4692a0eca4cc9d390d3252c4345ec2d3ad597d8 Mon Sep 17 00:00:00 2001 From: Scott-Lindauer_sasinst Date: Thu, 11 Jul 2024 16:47:46 -0400 Subject: [PATCH 24/86] refactor: adjust score_definitions.py for easier unit testing --- src/sasctl/_services/score_definitions.py | 37 +++++++++-------------- 1 file changed, 15 insertions(+), 22 deletions(-) diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index 30bde428..6e492177 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -38,6 +38,7 @@ def create_score_definition( score_def_name: str, model_id: str, table_name: str, + table_file: Union[str, Path] = None, description: str = "", server_name: str = "cas-shared-default", library_name: str = "Public", @@ -53,6 +54,8 @@ def create_score_definition( A user-inputted model if where the model exists in a project. table_name: str A user-inputted table name in CAS Management. + table_file: str or Path, optional + A user-provided path to an uploadable file. Defaults to None. description: str, optional Description of score definition. Defaults to an empty string. server_name: str, optional @@ -68,16 +71,15 @@ def create_score_definition( """ - try: - model = cls._model_respository.get_model(model_id) - model_project_id = model.json()["projectId"] - model_project_version_id = model.json()["projectVersionId"] - model_name = model.json()["name"] - - except KeyError: + model = cls._model_respository.get_model(model_id) + + if model.status_code >= 400: raise HTTPError( "This model may not exist in a project or the model may not exist at all. See error: " + model.json() ) + model_project_id = model.json()["projectId"] + model_project_version_id = model.json()["projectVersionId"] + model_name = model.json()["name"] # Checking if the model exists and if it's in a project try: @@ -95,25 +97,16 @@ def create_score_definition( # Optional mapping - Maps the variables in the data to the variables of the score object. It's not necessary to create a score definition. table = cls._cas_management.get_table(server_name, library_name, table_name) - try: - table.raise_for_status() - except requests.exceptions.HTTPError as error: - print(f"HTTP Error: {error}") - table_file = input( - "The inputted table does not exist. Enter the file path for the data in your table (CSV, XLS, XLSX, SAS7BDT or SASHDAT file)." - ) + if table.status_code >= 400 and not table_file: + raise HTTPError("This table may not exist in CAS. Please include the `table_file` argument in the function call if it doesn't exist. See error" + table.json()) + elif table.status_code >= 400 and table_file: cls._cas_management.upload_file( str(table_file), table_name ) # do I need to add a check if the file doesn't exist or does upload_file take care of that? - table = cls._cas_management.get_table(server_name, library_name, table_name) + uploaded_table = cls._cas_management.get_table(server_name, library_name, table_name) + if uploaded_table.status_code >= 400: + raise HTTPError("The file failed to upload properly or another error occurred. See the error: " + uploaded_table.json()) # Checks if the inputted table exists, and if not, uploads a file to create a new table - try: - table.raise_for_status() - except requests.exceptions.HTTPError as error: - print(f"HTTP Error: {error}") - raise Exception( - "Something went wrong when creating a table. Check to see if the file path inputted exists." - ) save_score_def = { "name": score_def_name, From c68cb8b900ea6ddc92b7d1dc354fe5ab9b13aee7 Mon Sep 17 00:00:00 2001 From: Scott-Lindauer_sasinst Date: Thu, 11 Jul 2024 16:48:30 -0400 Subject: [PATCH 25/86] test: update unit tests and put in draft score_definitions test --- tests/unit/test_score_definitions.py | 28 ++++++++++++++++++---------- 1 file changed, 18 insertions(+), 10 deletions(-) diff --git a/tests/unit/test_score_definitions.py b/tests/unit/test_score_definitions.py index f67cded9..2a5ea1fd 100644 --- a/tests/unit/test_score_definitions.py +++ b/tests/unit/test_score_definitions.py @@ -49,20 +49,28 @@ def test_create_score_definition(): with mock.patch( "sasctl._services.cas_management.CASManagement.upload_file" ) as upload_file: - get_model.request.return_value.json.return_value = { - "projectId": "54321", - "projectVersionId": "67890", - "name": "test_model" - } - #get_table.return_value = None - #upload_file.return_value = RestObj - - response = sd.create_score_definition( + get_model.return_value.status_code = 404 + with pytest.raises(HTTPError): + sd.create_score_definition( score_def_name = "test_create_sd", model_id = "12345", table_name = "test_table" ) - assert response + + get_model.return_value.status_code = 200 + get_model.return_value.json.return_value = { + "id": "12345", + "projectId": "54321", + "projectVersionId": "67890", + "name": "test_model", + } + get_table.return_value.status_code = 404 + with pytest.raises(HTTPError): + sd.create_score_definition( + score_def_name = "test_create_sd", + model_id = "12345", + table_name = "test_table" + ) # # Test for valid model id, no input mapping, get_table succeeded, and post succeeds From a73a08c7b9882c63cdb0c2de37fbc3cf9a4ea87d Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Mon, 15 Jul 2024 10:39:51 -0400 Subject: [PATCH 26/86] Formatting score definitions and running binary classification to test scoring services on an example notebook --- .../DecisionTreeClassifier.pickle | Bin 8180 -> 9036 bytes .../DecisionTreeClassifier.zip | Bin 439383 -> 451495 bytes .../ModelProperties.json | 13 +- .../DecisionTreeClassifier/dmcas_fitstat.json | 16 +- .../DecisionTreeClassifier/dmcas_lift.json | 364 +- .../DecisionTreeClassifier/dmcas_misc.json | 267 + .../dmcas_relativeimportance.json | 169 + .../DecisionTreeClassifier/dmcas_roc.json | 3586 ++++----- .../score_DecisionTreeClassifier.py | 95 +- .../GradientBoosting/GradientBoosting.pickle | Bin 1214738 -> 1350424 bytes .../GradientBoosting/GradientBoosting.zip | Bin 1644992 -> 1792885 bytes .../GradientBoosting/ModelProperties.json | 13 +- .../GradientBoosting/dmcas_fitstat.json | 22 +- .../GradientBoosting/dmcas_lift.json | 314 +- .../GradientBoosting/dmcas_misc.json | 267 + .../dmcas_relativeimportance.json | 169 + .../GradientBoosting/dmcas_roc.json | 3190 ++++---- .../score_GradientBoosting.py | 95 +- .../RandomForest/ModelProperties.json | 13 +- .../RandomForest/RandomForest.pickle | Bin 1609252 -> 1805903 bytes .../hmeqModels/RandomForest/RandomForest.zip | Bin 2039934 -> 2248588 bytes .../RandomForest/dmcas_fitstat.json | 30 +- .../hmeqModels/RandomForest/dmcas_lift.json | 700 +- .../hmeqModels/RandomForest/dmcas_misc.json | 267 + .../dmcas_relativeimportance.json | 169 + .../hmeqModels/RandomForest/dmcas_roc.json | 6776 ++++++++--------- .../RandomForest/score_RandomForest.py | 95 +- ...m_binary_classification_model_import.ipynb | 318 +- examples/pzmm_regression_model_import.ipynb | 9 +- src/sasctl/_services/score_definitions.py | 12 +- tests/unit/test_score_executions.py | 48 + 31 files changed, 9170 insertions(+), 7847 deletions(-) create mode 100644 examples/data/hmeqModels/DecisionTreeClassifier/dmcas_misc.json create mode 100644 examples/data/hmeqModels/DecisionTreeClassifier/dmcas_relativeimportance.json create mode 100644 examples/data/hmeqModels/GradientBoosting/dmcas_misc.json create mode 100644 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b/examples/data/hmeqModels/DecisionTreeClassifier/ModelProperties.json @@ -2,16 +2,19 @@ "name": "DecisionTreeClassifier", "description": "Description for the DecisionTreeClassifier model.", "scoreCodeType": "python", - "trainTable": "", + "trainTable": "cas-shared-default/Public/DecisionTreeClassifier_train_data", "trainCodeType": "Python", - "algorithm": "", + "algorithm": "DecisionTreeClassifier", "function": "Classification", "targetVariable": "BAD", "targetEvent": "1", - "targetLevel": "BINARY", + "targetLevel": "Binary", "eventProbVar": "P_1", "modeler": "sasdemo", "tool": "Python 3", - "toolVersion": "3.8.16", - "properties": [] + "toolVersion": "3.11.7", + "properties": [], + "eventPercentage": "0.20182166826462", + "selectionStatistic": "_RASE_", + "selectionStatisticValue": "0.33514616799162" } \ No newline at end of file diff --git a/examples/data/hmeqModels/DecisionTreeClassifier/dmcas_fitstat.json b/examples/data/hmeqModels/DecisionTreeClassifier/dmcas_fitstat.json index 163db488..3b0f0cdb 100644 --- a/examples/data/hmeqModels/DecisionTreeClassifier/dmcas_fitstat.json +++ b/examples/data/hmeqModels/DecisionTreeClassifier/dmcas_fitstat.json @@ -222,13 +222,14 @@ "_MCE_": 0.88710450623202, "_ASE_": 0.11232295391947, "_MCLL_": 0.99896429012045, - "_KS_": null, + "_KS_": 1.0, "_KSPostCutoff_": null, "_DIV_": 4172.0, "_TAU_": null, "_KSCut_": null, - "_C_": null, - "_PartInd_": null + "_C_": 0.85770092470509, + "_PartInd_": null, + "_KS2_": 0.71540184941018 }, "rowNumber": 2, "header": null @@ -243,14 +244,15 @@ "_DataRole_": "TEST", "_MCE_": 0.99328859060402, "_ASE_": 0.10439243746467, - "_MCLL_": 0.18029189766592, - "_KS_": null, + "_MCLL_": 0.1674139049754, + "_KS_": 1.0, "_KSPostCutoff_": null, "_DIV_": 1788.0, "_TAU_": null, "_KSCut_": null, - "_C_": null, - "_PartInd_": null + "_C_": 0.83803076656035, + "_PartInd_": null, + "_KS2_": 0.6760615331207 }, "rowNumber": 3, "header": null diff --git a/examples/data/hmeqModels/DecisionTreeClassifier/dmcas_lift.json b/examples/data/hmeqModels/DecisionTreeClassifier/dmcas_lift.json index 1ba21ee6..47531d9d 100644 --- a/examples/data/hmeqModels/DecisionTreeClassifier/dmcas_lift.json +++ b/examples/data/hmeqModels/DecisionTreeClassifier/dmcas_lift.json @@ -1569,24 +1569,24 @@ "_column_": "predict", "_RespBest_": 100.0, "_DataRole_": "TEST", - "_CumResp_": 21.8566849075543, - "_PctRespBest_": 98.8888888888889, - "_Gain_": 3.37133698151086, - "_CumLift_": 4.37133698151086, + "_CumResp_": 21.7739353186039, + "_PctRespBest_": 90.0, + "_Gain_": 3.35478706372078, + "_CumLift_": 4.35478706372078, "_Event_": "1", "_TargetName_": null, - "_PctResp_": 21.6138328530259, + "_PctResp_": 19.5965417867435, "_GainBest_": 19.0, "_CumLiftBest_": 20.0, - "_Lift_": 4.37133698151086, - "_CumPctResp_": 21.6138328530259, - "_NEventsBest_": 89.0, - "_CumPctRespBest_": 98.8888888888889, + "_Lift_": 4.35478706372078, + "_CumPctResp_": 19.5965417867435, + "_NEventsBest_": 81.0, + "_CumPctRespBest_": 90.0, "_Value_": 1.0, - "_NEvents_": 19.4524495677233, + "_NEvents_": 17.6368876080691, "_LiftBest_": 20.0, "_PartInd_": "2", - "_Resp_": 21.8566849075543, + "_Resp_": 21.7739353186039, "_Column_": "actual" }, "rowNumber": 44 @@ -1600,24 +1600,24 @@ "_column_": "predict", "_RespBest_": 0.0, "_DataRole_": "TEST", - "_CumResp_": 43.7133698151086, + "_CumResp_": 43.5478706372078, "_PctRespBest_": 0.0, - "_Gain_": 3.37133698151086, - "_CumLift_": 4.37133698151086, + "_Gain_": 3.35478706372078, + "_CumLift_": 4.35478706372078, "_Event_": "1", "_TargetName_": null, - "_PctResp_": 21.6138328530259, + "_PctResp_": 19.5965417867435, "_GainBest_": 9.0, "_CumLiftBest_": 10.0, - "_Lift_": 4.37133698151086, - "_CumPctResp_": 21.6138328530259, + "_Lift_": 4.35478706372078, + "_CumPctResp_": 19.5965417867435, "_NEventsBest_": 0.0, - "_CumPctRespBest_": 49.4444444444444, + "_CumPctRespBest_": 45.0, "_Value_": 1.0, - "_NEvents_": 19.4524495677233, + 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21.8566849075543, + "_Resp_": 21.7739353186039, "_Column_": "actual" }, "rowNumber": 46 @@ -1662,24 +1662,24 @@ "_column_": "predict", "_RespBest_": 0.0, "_DataRole_": "TEST", - "_CumResp_": 84.4115743592542, + "_CumResp_": 84.0954069961703, "_PctRespBest_": 0.0, - "_Gain_": 3.22057871796271, - "_CumLift_": 4.22057871796271, + "_Gain_": 3.20477034980851, + "_CumLift_": 4.20477034980851, "_Event_": "1", "_TargetName_": null, - "_PctResp_": 18.6321694184069, + "_PctResp_": 16.8962409363227, "_GainBest_": 4.0, "_CumLiftBest_": 5.0, - "_Lift_": 3.76830392731826, - "_CumPctResp_": 20.8684169943711, + "_Lift_": 3.75472020807172, + "_CumPctResp_": 18.9214665741383, "_NEventsBest_": 0.0, - "_CumPctRespBest_": 24.7222222222222, + "_CumPctRespBest_": 22.5, "_Value_": 0.0, - "_NEvents_": 16.7689524765662, + "_NEvents_": 15.2066168426904, "_LiftBest_": 0.0, "_PartInd_": "2", - "_Resp_": 18.8415196365913, + "_Resp_": 18.7736010403586, "_Column_": "actual" }, "rowNumber": 47 @@ -1693,24 +1693,24 @@ 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"_Event_": "1", "_TargetName_": null, - "_PctResp_": 0.97154753643303, + "_PctResp_": 0.90215128383067, "_GainBest_": 1.5, "_CumLiftBest_": 2.5, - "_Lift_": 0.19649276017746, - "_CumPctResp_": 10.9199822654021, + "_Lift_": 0.20047806307348, + "_CumPctResp_": 9.9118089289845, "_NEventsBest_": 0.0, - "_CumPctRespBest_": 12.3611111111111, + "_CumPctRespBest_": 11.25, "_Value_": 0.0, - "_NEvents_": 0.87439278278972, + "_NEvents_": 0.8119361554476, "_LiftBest_": 0.0, "_PartInd_": "2", - "_Resp_": 0.98246380088733, + "_Resp_": 1.00239031536741, "_Column_": "actual" }, "rowNumber": 51 @@ -1817,24 +1817,24 @@ "_column_": "predict", "_RespBest_": 0.0, "_DataRole_": "TEST", - "_CumResp_": 89.3238933636909, + "_CumResp_": 89.1073585730074, "_PctRespBest_": 0.0, - "_Gain_": 0.98497540808202, - "_CumLift_": 1.98497540808202, + "_Gain_": 0.98016352384461, + "_CumLift_": 1.98016352384461, "_Event_": "1", "_TargetName_": null, - "_PctResp_": 0.97154753643303, + "_PctResp_": 0.90215128383067, 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a/examples/data/hmeqModels/DecisionTreeClassifier/score_DecisionTreeClassifier.py b/examples/data/hmeqModels/DecisionTreeClassifier/score_DecisionTreeClassifier.py index e06aaea9..9754016f 100644 --- a/examples/data/hmeqModels/DecisionTreeClassifier/score_DecisionTreeClassifier.py +++ b/examples/data/hmeqModels/DecisionTreeClassifier/score_DecisionTreeClassifier.py @@ -16,73 +16,40 @@ def score(LOAN, MORTDUE, VALUE, YOJ, DEROG, DELINQ, CLAGE, NINQ, CLNO, DEBTINC): global model except NameError: with open(Path(settings.pickle_path) / "DecisionTreeClassifier.pickle", "rb") as pickle_model: - model = pickle.load(pickle_model) + model = pickle.load(pickle_model) - - try: - if math.isnan(LOAN): - LOAN = 18607.96979865772 - except TypeError: - LOAN = 18607.96979865772 - try: - if math.isnan(MORTDUE): - MORTDUE = 73760.817199559 - except TypeError: - MORTDUE = 73760.817199559 - try: - if math.isnan(VALUE): - VALUE = 101776.04874145007 - except TypeError: - VALUE = 101776.04874145007 - try: - if math.isnan(YOJ): - YOJ = 8.922268135904499 - except TypeError: - YOJ = 8.922268135904499 - try: - if math.isnan(DEROG): - DEROG = 0.2545696877380046 - except TypeError: - DEROG = 0.2545696877380046 - try: - if math.isnan(DELINQ): - DELINQ = 0.4494423791821561 - except TypeError: - DELINQ = 0.4494423791821561 - try: - if math.isnan(CLAGE): - CLAGE = 179.7662751900465 - except TypeError: - CLAGE = 179.7662751900465 - try: - if math.isnan(NINQ): - NINQ = 1.1860550458715597 - except TypeError: - NINQ = 1.1860550458715597 - try: - if math.isnan(CLNO): - CLNO = 21.29609620076682 - except TypeError: - CLNO = 21.29609620076682 - try: - if math.isnan(DEBTINC): - DEBTINC = 33.779915349235246 - except TypeError: - DEBTINC = 33.779915349235246 - - input_array = pd.DataFrame([[LOAN, MORTDUE, VALUE, YOJ, DEROG, DELINQ, CLAGE, NINQ, CLNO, DEBTINC]], - columns=["LOAN", "MORTDUE", "VALUE", "YOJ", "DEROG", "DELINQ", "CLAGE", "NINQ", "CLNO", "DEBTINC"], - dtype=float) - prediction = model.predict_proba(input_array) + index=None + if not isinstance(LOAN, pd.Series): + index=[0] + input_array = pd.DataFrame( + {"LOAN": LOAN, "MORTDUE": MORTDUE, "VALUE": VALUE, "YOJ": YOJ, "DEROG": DEROG, + "DELINQ": DELINQ, "CLAGE": CLAGE, "NINQ": NINQ, "CLNO": CLNO, "DEBTINC": + DEBTINC}, index=index + ) + input_array = impute_missing_values(input_array) + prediction = model.predict_proba(input_array).tolist() # Check for numpy values and convert to a CAS readable representation if isinstance(prediction, np.ndarray): - prediction = prediction.tolist()[0] - - if prediction[0] > prediction[1]: - EM_CLASSIFICATION = "1" + prediction = prediction.tolist() + + if input_array.shape[0] == 1: + if prediction[0][1] > 0.5: + EM_CLASSIFICATION = "1" + else: + EM_CLASSIFICATION = "0" + return EM_CLASSIFICATION, prediction[0][1] else: - EM_CLASSIFICATION = "0" - - return EM_CLASSIFICATION, prediction[0] \ No newline at end of file + df = pd.DataFrame(prediction) + proba = df[1] + classifications = np.where(df[1] > 0.5, '1', '0') + return pd.DataFrame({'EM_CLASSIFICATION': classifications, 'EM_EVENTPROBABILITY': proba}) + +def impute_missing_values(data): + impute_values = \ + {'DEBTINC': 33.779915349235246, 'LOAN': 18607.96979865772, 'DELINQ': + 0.4494423791821561, 'YOJ': 8.922268135904499, 'NINQ': 1.1860550458715597, + 'VALUE': 101776.04874145007, 'DEROG': 0.2545696877380046, 'CLNO': + 21.29609620076682, 'CLAGE': 179.7662751900465, 'MORTDUE': 73760.817199559} + return data.replace(' .', np.nan).fillna(impute_values).apply(pd.to_numeric, errors='ignore') diff --git a/examples/data/hmeqModels/GradientBoosting/GradientBoosting.pickle b/examples/data/hmeqModels/GradientBoosting/GradientBoosting.pickle index 28b393bc331ac48746037322a975f5fccf825505..e2d06bbeb62225be73b848ec4f46fd79febd2789 100644 GIT binary patch literal 1350424 zcmd?ScU%+87dITF3WA8eAgG94v7m^^48?*VSU@Z&9RkvuV8N)MqNt!j6j4xV7NmD@ z>53wP3Zfz+NU>uD5%Jwkn6QSMo7~*z^Ld}&eey>pvpZ+bnVB=^eCN#Uh9(qpPDFr0 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zWjx$(96t>?u6NvIo-q>%jzn*tpsnG=P@nKff1ikdl(1*sF}*2L_Bj6keS4ptNFYW< z{txZ)dum;NEM8LRES+^5$6pB&Kegw?O(gtub*>Nh^!E1&iL@pXr7uCqLF3S)e}8VX zrRIw(T2rW+q)HgaUvp1C#VkynNce97{$7DWK3g}-{~6OTnJ}5KMmpgVtU2C;e*@~K BZ@d5i diff --git a/examples/data/hmeqModels/GradientBoosting/ModelProperties.json b/examples/data/hmeqModels/GradientBoosting/ModelProperties.json index 4bd7f38b..abe138d7 100644 --- a/examples/data/hmeqModels/GradientBoosting/ModelProperties.json +++ b/examples/data/hmeqModels/GradientBoosting/ModelProperties.json @@ -2,16 +2,19 @@ "name": "GradientBoosting", "description": "Description for the GradientBoosting model.", "scoreCodeType": "python", - "trainTable": "", + "trainTable": "cas-shared-default/Public/GradientBoosting_train_data", "trainCodeType": "Python", - "algorithm": "", + "algorithm": "GradientBoostingClassifier", "function": "Classification", "targetVariable": "BAD", "targetEvent": "1", - "targetLevel": "BINARY", + "targetLevel": "Binary", "eventProbVar": "P_1", "modeler": "sasdemo", "tool": "Python 3", - "toolVersion": "3.8.16", - "properties": [] + "toolVersion": "3.11.7", + "properties": [], + "eventPercentage": "0.20182166826462", + "selectionStatistic": "_RASE_", + "selectionStatisticValue": "0.297599900859" } \ No newline at end of file diff --git a/examples/data/hmeqModels/GradientBoosting/dmcas_fitstat.json b/examples/data/hmeqModels/GradientBoosting/dmcas_fitstat.json index c8894406..bbf36ebb 100644 --- a/examples/data/hmeqModels/GradientBoosting/dmcas_fitstat.json +++ b/examples/data/hmeqModels/GradientBoosting/dmcas_fitstat.json @@ -222,35 +222,37 @@ "_MCE_": 0.7986577181208, "_ASE_": 0.08856570099128, "_MCLL_": 0.01103827946881, - "_KS_": null, + "_KS_": 1.0, "_KSPostCutoff_": null, "_DIV_": 4172.0, "_TAU_": null, "_KSCut_": null, - "_C_": null, - "_PartInd_": null + "_C_": 0.99851205124364, + "_PartInd_": null, + "_KS2_": 0.99702410248728 }, "rowNumber": 2, "header": null }, { "dataMap": { - "_RASE_": 0.30459073530239, + "_RASE_": 0.3041562329411, "_NObs_": 1788.0, "_GINI_": null, "_GAMMA_": null, "_formattedPartition_": " 2", "_DataRole_": "TEST", - "_MCE_": 0.91946308724832, - "_ASE_": 0.09277551603205, - "_MCLL_": 0.06438996345867, - "_KS_": null, + "_MCE_": 0.91890380313199, + "_ASE_": 0.09251101403692, + "_MCLL_": 0.06438996345872, + "_KS_": 1.0, "_KSPostCutoff_": null, "_DIV_": 1788.0, "_TAU_": null, "_KSCut_": null, - "_C_": null, - "_PartInd_": null + "_C_": 0.92167277167277, + "_PartInd_": null, + "_KS2_": 0.84334554334554 }, "rowNumber": 3, "header": null diff --git a/examples/data/hmeqModels/GradientBoosting/dmcas_lift.json b/examples/data/hmeqModels/GradientBoosting/dmcas_lift.json index 7e6cd318..521a5d98 100644 --- a/examples/data/hmeqModels/GradientBoosting/dmcas_lift.json +++ b/examples/data/hmeqModels/GradientBoosting/dmcas_lift.json @@ -1564,29 +1564,29 @@ "dataMap": { "_NObs_": 90.0, "_Depth_": 5.0, - "_CumRespBest_": 60.4026845637584, + "_CumRespBest_": 60.0, "_formattedPartition_": " 2", "_column_": "predict", - "_RespBest_": 60.4026845637584, + "_RespBest_": 60.0, "_DataRole_": "TEST", - "_CumResp_": 25.0662437382743, + "_CumResp_": 25.07204610951, "_PctRespBest_": 100.0, - "_Gain_": 4.01324874765487, - "_CumLift_": 5.01324874765487, + "_Gain_": 4.01440922190201, + "_CumLift_": 5.01440922190201, "_Event_": "1", "_TargetName_": null, - "_PctResp_": 41.4985590778098, - "_GainBest_": 11.0805369127516, - "_CumLiftBest_": 12.0805369127516, - "_Lift_": 5.01324874765487, - "_CumPctResp_": 41.4985590778098, + "_PctResp_": 41.7867435158501, + "_GainBest_": 11.0, + "_CumLiftBest_": 12.0, + "_Lift_": 5.01440922190201, + "_CumPctResp_": 41.7867435158501, "_NEventsBest_": 90.0, "_CumPctRespBest_": 100.0, "_Value_": 1.0, - "_NEvents_": 37.3487031700288, - "_LiftBest_": 12.0805369127516, + "_NEvents_": 37.6080691642651, + "_LiftBest_": 12.0, "_PartInd_": "2", - "_Resp_": 25.0662437382743, + "_Resp_": 25.07204610951, "_Column_": "actual" }, "rowNumber": 44 @@ -1598,26 +1598,26 @@ "_CumRespBest_": 100.0, "_formattedPartition_": " 2", "_column_": "predict", - "_RespBest_": 39.5973154362416, + "_RespBest_": 40.0, "_DataRole_": "TEST", - "_CumResp_": 50.1324874765487, - "_PctRespBest_": 65.5555555555555, - "_Gain_": 4.01324874765487, - "_CumLift_": 5.01324874765487, + "_CumResp_": 50.1440922190201, + "_PctRespBest_": 66.6666666666666, + "_Gain_": 4.01440922190201, + "_CumLift_": 5.01440922190201, "_Event_": "1", "_TargetName_": null, - "_PctResp_": 41.4985590778098, + "_PctResp_": 41.7867435158501, "_GainBest_": 9.0, "_CumLiftBest_": 10.0, - "_Lift_": 5.01324874765487, - "_CumPctResp_": 41.4985590778098, - "_NEventsBest_": 59.0, - "_CumPctRespBest_": 82.7777777777777, + "_Lift_": 5.01440922190201, + "_CumPctResp_": 41.7867435158501, + "_NEventsBest_": 60.0, + "_CumPctRespBest_": 83.3333333333333, "_Value_": 1.0, - "_NEvents_": 37.3487031700288, - "_LiftBest_": 7.91946308724832, + "_NEvents_": 37.6080691642651, + "_LiftBest_": 8.0, "_PartInd_": "2", - "_Resp_": 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"_Specificity_": 0.87614399023795, - "_FHALF_": 0.46844502277163, + "_Specificity_": 0.87667887667887, + "_FHALF_": 0.47139141742522, "_PartInd_": "2", - "_C_": 0.92129347162904, - "_GINI_": 0.84258694325808, - "_GAMMA_": 0.990230944326, - "_TAU_": 0.12880059690356, - "_FNR_": 0.03355704697986 + "_C_": 0.92167277167277, + "_GINI_": 0.84334554334554, + "_GAMMA_": 0.990345552741, + "_TAU_": 0.12970258729151, + "_FNR_": 0.03333333333333 }, "rowNumber": 300 } diff --git a/examples/data/hmeqModels/GradientBoosting/score_GradientBoosting.py b/examples/data/hmeqModels/GradientBoosting/score_GradientBoosting.py index 8f893904..45a948fb 100644 --- a/examples/data/hmeqModels/GradientBoosting/score_GradientBoosting.py +++ b/examples/data/hmeqModels/GradientBoosting/score_GradientBoosting.py @@ -16,73 +16,40 @@ def score(LOAN, MORTDUE, VALUE, YOJ, DEROG, DELINQ, CLAGE, NINQ, CLNO, DEBTINC): global model except NameError: with open(Path(settings.pickle_path) / "GradientBoosting.pickle", "rb") as pickle_model: - model = pickle.load(pickle_model) + model = pickle.load(pickle_model) - - try: - if math.isnan(LOAN): - LOAN = 18607.96979865772 - except TypeError: - LOAN = 18607.96979865772 - try: - if math.isnan(MORTDUE): - MORTDUE = 73760.817199559 - except TypeError: - MORTDUE = 73760.817199559 - try: - if math.isnan(VALUE): - VALUE = 101776.04874145007 - except TypeError: - VALUE = 101776.04874145007 - try: - if math.isnan(YOJ): - YOJ = 8.922268135904499 - except TypeError: - YOJ = 8.922268135904499 - try: - if math.isnan(DEROG): - DEROG = 0.2545696877380046 - except TypeError: - DEROG = 0.2545696877380046 - try: - if math.isnan(DELINQ): - DELINQ = 0.4494423791821561 - except TypeError: - DELINQ = 0.4494423791821561 - try: - if math.isnan(CLAGE): - CLAGE = 179.7662751900465 - except TypeError: - CLAGE = 179.7662751900465 - try: - if math.isnan(NINQ): - NINQ = 1.1860550458715597 - except TypeError: - NINQ = 1.1860550458715597 - try: - if math.isnan(CLNO): - CLNO = 21.29609620076682 - except TypeError: - CLNO = 21.29609620076682 - try: - if math.isnan(DEBTINC): - DEBTINC = 33.779915349235246 - except TypeError: - DEBTINC = 33.779915349235246 - - input_array = pd.DataFrame([[LOAN, MORTDUE, VALUE, YOJ, DEROG, DELINQ, CLAGE, NINQ, CLNO, DEBTINC]], - columns=["LOAN", "MORTDUE", "VALUE", "YOJ", "DEROG", "DELINQ", "CLAGE", "NINQ", "CLNO", "DEBTINC"], - dtype=float) - prediction = model.predict_proba(input_array) + index=None + if not isinstance(LOAN, pd.Series): + index=[0] + input_array = pd.DataFrame( + {"LOAN": LOAN, "MORTDUE": MORTDUE, "VALUE": VALUE, "YOJ": YOJ, "DEROG": DEROG, + "DELINQ": DELINQ, "CLAGE": CLAGE, "NINQ": NINQ, "CLNO": CLNO, "DEBTINC": + DEBTINC}, index=index + ) + input_array = impute_missing_values(input_array) + prediction = model.predict_proba(input_array).tolist() # Check for numpy values and convert to a CAS readable representation if isinstance(prediction, np.ndarray): - prediction = prediction.tolist()[0] - - if prediction[0] > prediction[1]: - EM_CLASSIFICATION = "1" + prediction = prediction.tolist() + + if input_array.shape[0] == 1: + if prediction[0][1] > 0.5: + EM_CLASSIFICATION = "1" + else: + EM_CLASSIFICATION = "0" + return EM_CLASSIFICATION, prediction[0][1] else: - EM_CLASSIFICATION = "0" - - return EM_CLASSIFICATION, prediction[0] \ No newline at end of file + df = pd.DataFrame(prediction) + proba = df[1] + classifications = np.where(df[1] > 0.5, '1', '0') + return pd.DataFrame({'EM_CLASSIFICATION': classifications, 'EM_EVENTPROBABILITY': proba}) + +def impute_missing_values(data): + impute_values = \ + {'DEBTINC': 33.779915349235246, 'LOAN': 18607.96979865772, 'DELINQ': + 0.4494423791821561, 'YOJ': 8.922268135904499, 'NINQ': 1.1860550458715597, + 'VALUE': 101776.04874145007, 'DEROG': 0.2545696877380046, 'CLNO': + 21.29609620076682, 'CLAGE': 179.7662751900465, 'MORTDUE': 73760.817199559} + return data.replace(' .', np.nan).fillna(impute_values).apply(pd.to_numeric, errors='ignore') diff --git a/examples/data/hmeqModels/RandomForest/ModelProperties.json b/examples/data/hmeqModels/RandomForest/ModelProperties.json index 632af1c8..0f345631 100644 --- a/examples/data/hmeqModels/RandomForest/ModelProperties.json +++ b/examples/data/hmeqModels/RandomForest/ModelProperties.json @@ -2,16 +2,19 @@ "name": "RandomForest", "description": "Description for the RandomForest model.", "scoreCodeType": "python", - "trainTable": "", + "trainTable": "cas-shared-default/Public/RandomForest_train_data", "trainCodeType": "Python", - "algorithm": "", + "algorithm": "RandomForestClassifier", "function": "Classification", "targetVariable": "BAD", "targetEvent": "1", - "targetLevel": "BINARY", + "targetLevel": "Binary", "eventProbVar": "P_1", "modeler": "sasdemo", "tool": "Python 3", - "toolVersion": "3.8.16", - "properties": [] + "toolVersion": "3.11.7", + "properties": [], + "eventPercentage": "0.20182166826462", + "selectionStatistic": "_RASE_", + "selectionStatisticValue": 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return pd.DataFrame({'EM_CLASSIFICATION': classifications, 'EM_EVENTPROBABILITY': proba}) + +def impute_missing_values(data): + impute_values = \ + {'DEBTINC': 33.779915349235246, 'LOAN': 18607.96979865772, 'DELINQ': + 0.4494423791821561, 'YOJ': 8.922268135904499, 'NINQ': 1.1860550458715597, + 'VALUE': 101776.04874145007, 'DEROG': 0.2545696877380046, 'CLNO': + 21.29609620076682, 'CLAGE': 179.7662751900465, 'MORTDUE': 73760.817199559} + return data.replace(' .', np.nan).fillna(impute_values).apply(pd.to_numeric, errors='ignore') diff --git a/examples/pzmm_binary_classification_model_import.ipynb b/examples/pzmm_binary_classification_model_import.ipynb index 458b5014..cb85ae6c 100644 --- a/examples/pzmm_binary_classification_model_import.ipynb +++ b/examples/pzmm_binary_classification_model_import.ipynb @@ -44,7 +44,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 116, "metadata": { "Collapsed": "false" }, @@ -70,7 +70,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 117, "metadata": { "Collapsed": "false" }, @@ -94,7 +94,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 118, "metadata": { "Collapsed": "false" }, @@ -105,7 +105,7 @@ "(5960, 13)" ] }, - "execution_count": 3, + "execution_count": 118, "metadata": {}, "output_type": "execute_result" } @@ -117,7 +117,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 119, "metadata": { "Collapsed": "false" }, @@ -259,7 +259,7 @@ "4 331.113972 0.0 34.0 40.566552 " ] }, - "execution_count": 4, + "execution_count": 119, "metadata": {}, "output_type": "execute_result" } @@ -270,18 +270,29 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 120, "metadata": { "Collapsed": "false" }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "

" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "hmeq_data.hist(figsize=(15,15), layout=(4, 4));" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 121, "metadata": { "Collapsed": "false" }, @@ -294,7 +305,7 @@ " dtype='object')" ] }, - "execution_count": 6, + "execution_count": 121, "metadata": {}, "output_type": "execute_result" } @@ -314,7 +325,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 122, "metadata": { "Collapsed": "false" }, @@ -331,7 +342,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 123, "metadata": { "Collapsed": "false" }, @@ -353,7 +364,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 124, "metadata": { "Collapsed": "false" }, @@ -371,7 +382,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 125, "metadata": { "Collapsed": "false" }, @@ -387,7 +398,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 126, "metadata": { "Collapsed": "false" }, @@ -421,63 +432,63 @@ " \n", " \n", " DEBTINC\n", - " 36.16%\n", - " 26.14%\n", - " 51.18%\n", + " 58.35%\n", + " 35.36%\n", + " 39.53%\n", " \n", " \n", - " CLAGE\n", - " 12.6%\n", - " 10.87%\n", - " 7.76%\n", + " DELINQ\n", + " 18.57%\n", + " 15.16%\n", + " 12.25%\n", " \n", " \n", - " DELINQ\n", - " 12.18%\n", - " 9.82%\n", - " 14.68%\n", + " CLAGE\n", + " 8.07%\n", + " 9.49%\n", + " 10.39%\n", " \n", " \n", - " VALUE\n", - " 7.16%\n", - " 9.42%\n", - " 4.77%\n", + " DEROG\n", + " 4.86%\n", + " 9.28%\n", + " 6.28%\n", " \n", " \n", - " LOAN\n", - " 6.97%\n", - " 8.98%\n", - " 3.54%\n", + " VALUE\n", + " 3.19%\n", + " 5.75%\n", + " 7.38%\n", " \n", " \n", " YOJ\n", - " 6.75%\n", - " 6.88%\n", - " 2.04%\n", + " 2.7%\n", + " 3.59%\n", + " 3.77%\n", " \n", " \n", " MORTDUE\n", - " 6.15%\n", - " 8.46%\n", - " 2.03%\n", + " 2.0%\n", + " 5.17%\n", + " 6.4%\n", " \n", " \n", " CLNO\n", - " 5.97%\n", - " 8.16%\n", - " 4.2%\n", + " 1.2%\n", + " 5.52%\n", + " 5.9%\n", " \n", " \n", - " DEROG\n", - " 3.46%\n", - " 6.47%\n", - " 7.65%\n", + " NINQ\n", + " 0.88%\n", + " 3.93%\n", + " 2.79%\n", " \n", " \n", - " NINQ\n", - " 2.59%\n", - " 4.8%\n", - " 2.15%\n", + " LOAN\n", + " 0.17%\n", + " 6.74%\n", + " 5.32%\n", " \n", " \n", "\n", @@ -485,19 +496,19 @@ ], "text/plain": [ " DecisionTree RandomForest GradientBoosting\n", - "DEBTINC 36.16% 26.14% 51.18%\n", - "CLAGE 12.6% 10.87% 7.76%\n", - "DELINQ 12.18% 9.82% 14.68%\n", - "VALUE 7.16% 9.42% 4.77%\n", - "LOAN 6.97% 8.98% 3.54%\n", - "YOJ 6.75% 6.88% 2.04%\n", - "MORTDUE 6.15% 8.46% 2.03%\n", - "CLNO 5.97% 8.16% 4.2%\n", - "DEROG 3.46% 6.47% 7.65%\n", - "NINQ 2.59% 4.8% 2.15%" + "DEBTINC 58.35% 35.36% 39.53%\n", + "DELINQ 18.57% 15.16% 12.25%\n", + "CLAGE 8.07% 9.49% 10.39%\n", + "DEROG 4.86% 9.28% 6.28%\n", + "VALUE 3.19% 5.75% 7.38%\n", + "YOJ 2.7% 3.59% 3.77%\n", + "MORTDUE 2.0% 5.17% 6.4%\n", + "CLNO 1.2% 5.52% 5.9%\n", + "NINQ 0.88% 3.93% 2.79%\n", + "LOAN 0.17% 6.74% 5.32%" ] }, - "execution_count": 11, + "execution_count": 126, "metadata": {}, "output_type": "execute_result" } @@ -511,7 +522,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 127, "metadata": { "Collapsed": "false" }, @@ -520,18 +531,18 @@ "name": "stdout", "output_type": "stream", "text": [ - "[[1427 14]\n", - " [ 272 75]]\n", + "[[1428 13]\n", + " [ 279 68]]\n", " precision recall f1-score support\n", "\n", " 0 0.84 0.99 0.91 1441\n", - " 1 0.84 0.22 0.34 347\n", + " 1 0.84 0.20 0.32 347\n", "\n", " accuracy 0.84 1788\n", - " macro avg 0.84 0.60 0.63 1788\n", - "weighted avg 0.84 0.84 0.80 1788\n", + " macro avg 0.84 0.59 0.61 1788\n", + "weighted avg 0.84 0.84 0.79 1788\n", "\n", - "Decision Tree Model Accuracy = 84.0%\n" + "Decision Tree Model Accuracy = 83.67%\n" ] } ], @@ -545,7 +556,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 128, "metadata": { "Collapsed": "false" }, @@ -554,18 +565,18 @@ "name": "stdout", "output_type": "stream", "text": [ - "[[1440 1]\n", - " [ 246 101]]\n", + "[[1439 2]\n", + " [ 258 89]]\n", " precision recall f1-score support\n", "\n", " 0 0.85 1.00 0.92 1441\n", - " 1 0.99 0.29 0.45 347\n", + " 1 0.98 0.26 0.41 347\n", "\n", - " accuracy 0.86 1788\n", - " macro avg 0.92 0.65 0.69 1788\n", - "weighted avg 0.88 0.86 0.83 1788\n", + " accuracy 0.85 1788\n", + " macro avg 0.91 0.63 0.66 1788\n", + "weighted avg 0.87 0.85 0.82 1788\n", "\n", - "Random Forest Model Accuracy = 86.19%\n" + "Random Forest Model Accuracy = 85.46%\n" ] } ], @@ -579,7 +590,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 129, "metadata": {}, "outputs": [ { @@ -587,17 +598,17 @@ "output_type": "stream", "text": [ "[[1436 5]\n", - " [ 203 144]]\n", + " [ 202 145]]\n", " precision recall f1-score support\n", "\n", " 0 0.88 1.00 0.93 1441\n", - " 1 0.97 0.41 0.58 347\n", + " 1 0.97 0.42 0.58 347\n", "\n", " accuracy 0.88 1788\n", " macro avg 0.92 0.71 0.76 1788\n", "weighted avg 0.89 0.88 0.86 1788\n", "\n", - "Gradient Boosting Model Accuracy = 88.37%\n" + "Gradient Boosting Model Accuracy = 88.42%\n" ] } ], @@ -620,7 +631,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 130, "metadata": { "Collapsed": "false" }, @@ -629,9 +640,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "Model DecisionTreeClassifier was successfully pickled and saved to ~\\data\\hmeqModels\\DecisionTreeClassifier\\DecisionTreeClassifier.pickle.\n", - "Model RandomForest was successfully pickled and saved to ~\\data\\hmeqModels\\RandomForest\\RandomForest.pickle.\n", - "Model GradientBoosting was successfully pickled and saved to ~\\data\\hmeqModels\\GradientBoosting\\GradientBoosting.pickle.\n" + "Model DecisionTreeClassifier was successfully pickled and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\DecisionTreeClassifier\\DecisionTreeClassifier.pickle.\n", + "Model RandomForest was successfully pickled and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\RandomForest\\RandomForest.pickle.\n", + "Model GradientBoosting was successfully pickled and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\GradientBoosting\\GradientBoosting.pickle.\n" ] } ], @@ -657,7 +668,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 131, "metadata": { "Collapsed": "false" }, @@ -666,18 +677,18 @@ "name": "stdout", "output_type": "stream", "text": [ - "inputVar.json was successfully written and saved to ~\\data\\hmeqModels\\DecisionTreeClassifier\\inputVar.json\n", - "outputVar.json was successfully written and saved to ~\\data\\hmeqModels\\DecisionTreeClassifier\\outputVar.json\n", - "ModelProperties.json was successfully written and saved to ~\\data\\hmeqModels\\DecisionTreeClassifier\\ModelProperties.json\n", - "fileMetadata.json was successfully written and saved to ~\\data\\hmeqModels\\DecisionTreeClassifier\\fileMetadata.json\n", - "inputVar.json was successfully written and saved to ~\\data\\hmeqModels\\RandomForest\\inputVar.json\n", - "outputVar.json was successfully written and saved to ~\\data\\hmeqModels\\RandomForest\\outputVar.json\n", - "ModelProperties.json was successfully written and saved to ~\\data\\hmeqModels\\RandomForest\\ModelProperties.json\n", - "fileMetadata.json was successfully written and saved to ~\\data\\hmeqModels\\RandomForest\\fileMetadata.json\n", - "inputVar.json was successfully written and saved to ~\\data\\hmeqModels\\GradientBoosting\\inputVar.json\n", - "outputVar.json was successfully written and saved to ~\\data\\hmeqModels\\GradientBoosting\\outputVar.json\n", - "ModelProperties.json was successfully written and saved to ~\\data\\hmeqModels\\GradientBoosting\\ModelProperties.json\n", - "fileMetadata.json was successfully written and saved to ~\\data\\hmeqModels\\GradientBoosting\\fileMetadata.json\n" + "inputVar.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\DecisionTreeClassifier\\inputVar.json\n", + "outputVar.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\DecisionTreeClassifier\\outputVar.json\n", + "ModelProperties.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\DecisionTreeClassifier\\ModelProperties.json\n", + "fileMetadata.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\DecisionTreeClassifier\\fileMetadata.json\n", + "inputVar.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\RandomForest\\inputVar.json\n", + "outputVar.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\RandomForest\\outputVar.json\n", + "ModelProperties.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\RandomForest\\ModelProperties.json\n", + "fileMetadata.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\RandomForest\\fileMetadata.json\n", + "inputVar.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\GradientBoosting\\inputVar.json\n", + "outputVar.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\GradientBoosting\\outputVar.json\n", + "ModelProperties.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\GradientBoosting\\ModelProperties.json\n", + "fileMetadata.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\GradientBoosting\\fileMetadata.json\n" ] } ], @@ -717,7 +728,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 132, "metadata": { "Collapsed": "false" }, @@ -726,15 +737,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "dmcas_fitstat.json was successfully written and saved to ~\\data\\hmeqModels\\DecisionTreeClassifier\\dmcas_fitstat.json\n", - "dmcas_roc.json was successfully written and saved to ~\\data\\hmeqModels\\DecisionTreeClassifier\\dmcas_roc.json\n", - "dmcas_lift.json was successfully written and saved to ~\\data\\hmeqModels\\DecisionTreeClassifier\\dmcas_lift.json\n", - "dmcas_fitstat.json was successfully written and saved to ~\\data\\hmeqModels\\RandomForest\\dmcas_fitstat.json\n", - "dmcas_roc.json was successfully written and saved to ~\\data\\hmeqModels\\RandomForest\\dmcas_roc.json\n", - "dmcas_lift.json was successfully written and saved to ~\\data\\hmeqModels\\RandomForest\\dmcas_lift.json\n", - "dmcas_fitstat.json was successfully written and saved to ~\\data\\hmeqModels\\GradientBoosting\\dmcas_fitstat.json\n", - "dmcas_roc.json was successfully written and saved to ~\\data\\hmeqModels\\GradientBoosting\\dmcas_roc.json\n", - "dmcas_lift.json was successfully written and saved to ~\\data\\hmeqModels\\GradientBoosting\\dmcas_lift.json\n" + "dmcas_fitstat.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\DecisionTreeClassifier\\dmcas_fitstat.json\n", + "dmcas_roc.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\DecisionTreeClassifier\\dmcas_roc.json\n", + "dmcas_lift.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\DecisionTreeClassifier\\dmcas_lift.json\n", + "dmcas_relativeimportance.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\DecisionTreeClassifier\\dmcas_relativeimportance.json\n", + "dmcas_misc.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\DecisionTreeClassifier\\dmcas_misc.json\n", + "dmcas_fitstat.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\RandomForest\\dmcas_fitstat.json\n", + "dmcas_roc.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\RandomForest\\dmcas_roc.json\n", + "dmcas_lift.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\RandomForest\\dmcas_lift.json\n", + "dmcas_relativeimportance.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\RandomForest\\dmcas_relativeimportance.json\n", + "dmcas_misc.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\RandomForest\\dmcas_misc.json\n", + "dmcas_fitstat.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\GradientBoosting\\dmcas_fitstat.json\n", + "dmcas_roc.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\GradientBoosting\\dmcas_roc.json\n", + "dmcas_lift.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\GradientBoosting\\dmcas_lift.json\n", + "dmcas_relativeimportance.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\GradientBoosting\\dmcas_relativeimportance.json\n", + "dmcas_misc.json was successfully written and saved to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\GradientBoosting\\dmcas_misc.json\n" ] } ], @@ -772,9 +789,9 @@ " selection_statistic='_RASE_',\n", " )\n", " \n", - "username = getpass.getpass()\n", - "password = getpass.getpass()\n", - "host = \"demo.sas.com\" # Changes required by user\n", + "username = \"sasuser\"\n", + "password = \"[REDACTED]\"\n", + "host = \"base.ingress-nginx.wenbao-gc1-m1.modelmanager.sashq-d.openstack.sas.com\" # Changes required by user\n", "sess = Session(host, username, password, protocol=\"http\") # For TLS-enabled servers, change protocol value to \"https\"\n", "conn = sess.as_swat() # Connect to SWAT through the sasctl authenticated connection\n", "\n", @@ -786,35 +803,66 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 133, "metadata": { "Collapsed": "false" }, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model score code was written successfully to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\DecisionTreeClassifier\\score_DecisionTreeClassifier.py and uploaded to SAS Model Manager.\n", + "All model files were zipped to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\DecisionTreeClassifier.\n" + ] + }, { "name": "stderr", "output_type": "stream", "text": [ - "~\\sasctl\\pzmm\\write_score_code.py:1059: UserWarning: Due to the ambiguity of the provided metrics and prediction return types, the score code assumes that a classification and the target event probability should be returned.\n", - " warn(\n", - "~\\sasctl\\pzmm\\import_model.py:45: UserWarning: No project with the name or UUID HMEQModels was found.\n", - " warn(f\"No project with the name or UUID {project} was found.\")\n" + "c:\\Users\\sapotl\\AppData\\Local\\anaconda3\\Lib\\site-packages\\sasctl\\pzmm\\write_score_code.py:1500: UserWarning: Due to the ambiguity of the provided metrics and prediction return types, the score code assumes that a classification and the target event probability should be returned.\n", + " warn(\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Model score code was written successfully to ~\\data\\hmeqModels\\DecisionTreeClassifier\\score_DecisionTreeClassifier.py and uploaded to SAS Model Manager.\n", - "All model files were zipped to ~\\data\\hmeqModels\\DecisionTreeClassifier.\n", - "A new project named HMEQModels was created.\n", - "Model was successfully imported into SAS Model Manager as DecisionTreeClassifier with the following UUID: 82cf6fb7-c845-48ad-8f0c-9e572104335d.\n", - "Model score code was written successfully to ~\\data\\hmeqModels\\RandomForest\\score_RandomForest.py and uploaded to SAS Model Manager.\n", - "All model files were zipped to ~\\data\\hmeqModels\\RandomForest.\n", - "Model was successfully imported into SAS Model Manager as RandomForest with the following UUID: 44bfd538-8e02-4d04-99cd-fe1dacbabdfd.\n", - "Model score code was written successfully to ~\\data\\hmeqModels\\GradientBoosting\\score_GradientBoosting.py and uploaded to SAS Model Manager.\n", - "All model files were zipped to ~\\data\\hmeqModels\\GradientBoosting.\n", - "Model was successfully imported into SAS Model Manager as GradientBoosting with the following UUID: a248bde8-f767-4c05-8791-63700efd9288.\n" + "Model was successfully imported into SAS Model Manager as DecisionTreeClassifier with the following UUID: 81806d99-6070-4bd0-8207-646e42eb797e.\n", + "Model score code was written successfully to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\RandomForest\\score_RandomForest.py and uploaded to SAS Model Manager.\n", + "All model files were zipped to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\RandomForest.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "c:\\Users\\sapotl\\AppData\\Local\\anaconda3\\Lib\\site-packages\\sasctl\\pzmm\\write_score_code.py:1500: UserWarning: Due to the ambiguity of the provided metrics and prediction return types, the score code assumes that a classification and the target event probability should be returned.\n", + " warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model was successfully imported into SAS Model Manager as RandomForest with the following UUID: 7bf4273f-d54b-4201-8107-f3503e12a43f.\n", + "Model score code was written successfully to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\GradientBoosting\\score_GradientBoosting.py and uploaded to SAS Model Manager.\n", + "All model files were zipped to c:\\Users\\sapotl\\OneDrive - SAS\\Desktop\\sasctlofficial\\python-sasctl\\examples\\data\\hmeqModels\\GradientBoosting.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "c:\\Users\\sapotl\\AppData\\Local\\anaconda3\\Lib\\site-packages\\sasctl\\pzmm\\write_score_code.py:1500: UserWarning: Due to the ambiguity of the provided metrics and prediction return types, the score code assumes that a classification and the target event probability should be returned.\n", + " warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model was successfully imported into SAS Model Manager as GradientBoosting with the following UUID: db434720-48ea-4fc2-95d2-b20e472f78e7.\n" ] } ], @@ -836,16 +884,22 @@ " # Reinitialize the score_code variable when writing more than one model's score code\n", " pzmm.ScoreCode.score_code = \"\"" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(pzmm.ImportModel.get_model_properties(\"id\"))" + ] } ], "metadata": { - "interpreter": { - "hash": "f9708d3f38eeab835578f0695c8890716ee809285281a28db6e379a5abca1310" - }, "kernelspec": { - "display_name": "dev-py38", + "display_name": "base", "language": "python", - "name": "dev-py38" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -857,7 +911,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.16" + "version": "3.11.7" }, "latex_envs": { "LaTeX_envs_menu_present": true, diff --git a/examples/pzmm_regression_model_import.ipynb b/examples/pzmm_regression_model_import.ipynb index c0c2ad53..59c73a6e 100644 --- a/examples/pzmm_regression_model_import.ipynb +++ b/examples/pzmm_regression_model_import.ipynb @@ -494,13 +494,10 @@ } ], "metadata": { - "interpreter": { - "hash": "f9708d3f38eeab835578f0695c8890716ee809285281a28db6e379a5abca1310" - }, "kernelspec": { - "display_name": "dev-py38", + "display_name": "base", "language": "python", - "name": "dev-py38" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -512,7 +509,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.16" + "version": "3.11.7" }, "latex_envs": { "LaTeX_envs_menu_present": true, diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index 6e492177..e5884147 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -74,8 +74,8 @@ def create_score_definition( model = cls._model_respository.get_model(model_id) if model.status_code >= 400: - raise HTTPError( - "This model may not exist in a project or the model may not exist at all. See error: " + model.json() + raise HTTPError({ + f"This model may not exist in a project or the model may not exist at all. See error: {model.json()}"} ) model_project_id = model.json()["projectId"] model_project_version_id = model.json()["projectVersionId"] @@ -98,14 +98,14 @@ def create_score_definition( table = cls._cas_management.get_table(server_name, library_name, table_name) if table.status_code >= 400 and not table_file: - raise HTTPError("This table may not exist in CAS. Please include the `table_file` argument in the function call if it doesn't exist. See error" + table.json()) + raise HTTPError(f"This table may not exist in CAS. Please include the `table_file` argument in the function call if it doesn't exist. See error {table.json()}") elif table.status_code >= 400 and table_file: cls._cas_management.upload_file( str(table_file), table_name ) # do I need to add a check if the file doesn't exist or does upload_file take care of that? - uploaded_table = cls._cas_management.get_table(server_name, library_name, table_name) - if uploaded_table.status_code >= 400: - raise HTTPError("The file failed to upload properly or another error occurred. See the error: " + uploaded_table.json()) + table = cls._cas_management.get_table(server_name, library_name, table_name) + if table.status_code >= 400: + raise HTTPError(f"The file failed to upload properly or another error occurred. See the error: {table.json()}") # Checks if the inputted table exists, and if not, uploads a file to create a new table save_score_def = { diff --git a/tests/unit/test_score_executions.py b/tests/unit/test_score_executions.py new file mode 100644 index 00000000..93abfde7 --- /dev/null +++ b/tests/unit/test_score_executions.py @@ -0,0 +1,48 @@ +#!/usr/bin/env python +# encoding: utf-8 +# +# Copyright © 2024, SAS Institute Inc., Cary, NC, USA. All Rights Reserved. +# SPDX-License-Identifier: Apache-2.0 + +import json +import os +import pickle +import random +import tempfile +import unittest +from pathlib import Path +from unittest import mock + +import numpy as np +import pandas as pd +import pytest +from requests import HTTPError + +import sasctl.pzmm as pzmm +from sasctl import current_session +from sasctl.core import RestObj, VersionInfo +from sasctl._services.score_definitions import ScoreDefinitions as sd + +def test_create_score_execution(): + """ + Test Cases: + - Valid score definition id? + -yes + -no + - Valid execution id? + + -Valid count key? + + """ + + with mock.patch( + "sasctl._services.score_definitions.ScoreDefinitions.get_definition" + ) as get_definition: + with mock.patch( + "sasctl._services.score_execution.ScoreExecution.get_execution" + ) as get_execution: + with mock.patch( + "sasctl._services.score_execution.ScoreExecution.delete_execution" + ) as delete_execution: + exit() + #raise HTTP error? \ No newline at end of file From 27705148c0837e73c3abcf22073c9706a482eeed Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Tue, 16 Jul 2024 11:49:35 -0400 Subject: [PATCH 27/86] Adding fail cases for get_table and upload_file --- src/sasctl/_services/score_definitions.py | 8 ++-- src/sasctl/_services/score_execution.py | 16 +++---- tests/unit/test_score_definitions.py | 57 +++++++++++++++++++++++ 3 files changed, 69 insertions(+), 12 deletions(-) diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index e5884147..911a8218 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -77,14 +77,14 @@ def create_score_definition( raise HTTPError({ f"This model may not exist in a project or the model may not exist at all. See error: {model.json()}"} ) - model_project_id = model.json()["projectId"] - model_project_version_id = model.json()["projectVersionId"] - model_name = model.json()["name"] + model_project_id = model.get("projectId") + model_project_version_id = model.get("projectVersionId") + model_name = model.get("name") # Checking if the model exists and if it's in a project try: inputMapping = [] - for input_item in model.json()["inputVariables"]: + for input_item in model.get("inputVariables"): var = { "mappingValue": input_item["name"], "mappingType": "datasource", diff --git a/src/sasctl/_services/score_execution.py b/src/sasctl/_services/score_execution.py index 8561fe45..d35a4517 100644 --- a/src/sasctl/_services/score_execution.py +++ b/src/sasctl/_services/score_execution.py @@ -57,11 +57,11 @@ def create_score_execution( score_definition = sd.get_definition(score_definition_id) if score_definition.status_code >= 400: raise HTTPError(score_definition.json()) - score_exec_name = score_definition.json()["name"] - model_uri = score_definition.json()["objectDescriptor"]["uri"] - model_name = score_definition.json()["objectDescriptor"]["name"] - model_input_library = score_definition.json()["inputData"]["libraryName"] - model_table_name = score_definition.json()["inputData"]["tableName"] + score_exec_name = score_definition.get("name") + model_uri = score_definition.get("objectDescriptor", ["uri"]) + model_name = score_definition.get("objectDescriptor", ["name"]) + model_input_library = score_definition.get("inputData", ["libraryName"]) + model_table_name = score_definition.get("inputData", ["tableName"]) # Defining a default output table name if none is provided if not output_table_name: @@ -72,11 +72,11 @@ def create_score_execution( score_execution = cls.get( f"/executions?filter=eq(scoreExecutionRequest.scoreDefinitionId,%27{score_definition_id}%27)" ) - execution_count = score_execution.json()[ + execution_count = score_execution.get( "count" - ] # Exception catch location + ) # Exception catch location if execution_count == 1: - execution_id = score_execution.json()["items"][0]["id"] + execution_id = score_execution.get("items", [0], ["id"]) deleted_score_execution = cls.delete_execution(execution_id) print(deleted_score_execution) except KeyError: diff --git a/tests/unit/test_score_definitions.py b/tests/unit/test_score_definitions.py index 2a5ea1fd..d23b0036 100644 --- a/tests/unit/test_score_definitions.py +++ b/tests/unit/test_score_definitions.py @@ -56,6 +56,24 @@ def test_create_score_definition(): model_id = "12345", table_name = "test_table" ) + # get_model.return_value.status_code = 200 + # get_model.return_value.json.return_value = { + # "id": "12345", + # "projectId": "54321", + # "projectVersionId": "67890", + # "name": "test_model" + # "inputVariables": {"A", "B", "C"} #look at syntax combine square brackets and curly bracket + # } + # sd.create_score_definition( + # score_def_name = "test_create_sd", + # model_id = "12345", + # table_name = "test_table", + # mappings = { + # {"mappingVariable": "A", "datasource": "datasource", "variableName": "A"}, + # {"mappingVariable": "B", "datasource": "datasource", "variableName": "B"}, + # {"mappingVariable": "C", "datasource": "datasource", "variableName": "C"} + # } + # ) get_model.return_value.status_code = 200 get_model.return_value.json.return_value = { @@ -71,6 +89,45 @@ def test_create_score_definition(): model_id = "12345", table_name = "test_table" ) + get_table.return_value.status_code = 404 + upload_file.return_value = None + get_table.return_value.status_code = 404 + with pytest.raises(HTTPError): + sd.create_score_definition( + score_def_name = "test_create_sd", + model_id = "12345", + table_name = "test_table", + table_file = "test_path" + ) + + get_table.return_value.status_code = 404 + upload_file.return_value = RestObj + get_table.return_value.status_code = 200 + response = sd.create_score_definition( + score_def_name = "test_create_sd", + model_id = "12345", + table_name = "test_table", + table_file = "test_path" + ) + assert response + + + + + # get_table.return_value.status_code = 200 + # get_table.return_value.json.return_value = { + # "tableName": "test_table" + # } + # sd.create_score_definition( + # score_def_name = "test_create_sd", + # model_id = "12345", + # table_name = "test_table" + # ) + + + + + # # Test for valid model id, no input mapping, get_table succeeded, and post succeeds From e433643d62433ca04ac7af2f9cf8039312f1230d Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Wed, 17 Jul 2024 14:54:19 -0400 Subject: [PATCH 28/86] First version of all test cases for score definition --- src/sasctl/_services/score_definitions.py | 35 ++-- tests/unit/test_score_definitions.py | 207 ++++++++++------------ 2 files changed, 114 insertions(+), 128 deletions(-) diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index 911a8218..87dc999b 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -28,9 +28,12 @@ class ScoreDefinitions(Service): _cas_management = CASManagement() _model_respository = ModelRepository() - list_definitions, get_definition, update_definition, delete_definition = ( - Service._crud_funcs("/definitions", "definition") - ) + ( + list_definitions, + get_definition, + update_definition, + delete_definition, + ) = Service._crud_funcs("/definitions", "definition") @classmethod def create_score_definition( @@ -72,10 +75,12 @@ def create_score_definition( """ model = cls._model_respository.get_model(model_id) - + if model.status_code >= 400: - raise HTTPError({ - f"This model may not exist in a project or the model may not exist at all. See error: {model.json()}"} + raise HTTPError( + { + f"This model may not exist in a project or the model may not exist at all. See error: {model.json()}" + } ) model_project_id = model.get("projectId") model_project_version_id = model.get("projectVersionId") @@ -98,21 +103,25 @@ def create_score_definition( table = cls._cas_management.get_table(server_name, library_name, table_name) if table.status_code >= 400 and not table_file: - raise HTTPError(f"This table may not exist in CAS. Please include the `table_file` argument in the function call if it doesn't exist. See error {table.json()}") - elif table.status_code >= 400 and table_file: + raise HTTPError( + f"This table may not exist in CAS. Please include the `table_file` argument in the function call if it doesn't exist. See error {table.json()}" + ) + elif table.status_code >= 400 and table_file: cls._cas_management.upload_file( str(table_file), table_name ) # do I need to add a check if the file doesn't exist or does upload_file take care of that? table = cls._cas_management.get_table(server_name, library_name, table_name) if table.status_code >= 400: - raise HTTPError(f"The file failed to upload properly or another error occurred. See the error: {table.json()}") + raise HTTPError( + f"The file failed to upload properly or another error occurred. See the error: {table.json()}" + ) # Checks if the inputted table exists, and if not, uploads a file to create a new table save_score_def = { "name": score_def_name, "description": description, "objectDescriptor": { - "uri": f"/modelManagement/models/{model_id}", + "uri": f"/modelRepository/models/{model_id}", "name": f"{model_name}({model_version})", "type": "sas.models.model", }, @@ -136,9 +145,7 @@ def create_score_definition( headers_score_def = {"Content-Type": "application/json"} - new_score_def = cls.post( + return cls.post( "/definitions", data=json.dumps(save_score_def), headers=headers_score_def ) - - return new_score_def - # The response information of the score definition can be seen as a JSON as well as the RestOBJ + # The response information of the score definition can be seen as a JSON as well as a RestOBJ diff --git a/tests/unit/test_score_definitions.py b/tests/unit/test_score_definitions.py index d23b0036..9bc7ceaf 100644 --- a/tests/unit/test_score_definitions.py +++ b/tests/unit/test_score_definitions.py @@ -23,132 +23,111 @@ from sasctl.core import RestObj, VersionInfo, request from sasctl._services.score_definitions import ScoreDefinitions as sd + def test_create_score_definition(): """ Test Cases: - - Valid model id? - - yes - - no - - Valid input mapping? - - yes - - no - -Valid table name? - -yes - -no - -Valid file? - -yes - -no + - Valid model id with input mapping and valid table name + - Invalid model id + - Valid table name without input mapping + - Invalid table name with invalid file + - Invalid table name with valid file and without input mapping + """ - + with mock.patch("sasctl.core.Session._get_authorization_token"): + current_session("example.com", "username", "password") + with mock.patch( "sasctl._services.model_repository.ModelRepository.get_model" ) as get_model: - with mock.patch( + with mock.patch( "sasctl._services.cas_management.CASManagement.get_table" ) as get_table: with mock.patch( "sasctl._services.cas_management.CASManagement.upload_file" ) as upload_file: - get_model.return_value.status_code = 404 - with pytest.raises(HTTPError): - sd.create_score_definition( - score_def_name = "test_create_sd", - model_id = "12345", - table_name = "test_table" + with mock.patch( + "sasctl._services.score_definitions.ScoreDefinitions.post" + ) as post: + get_model.return_value.status_code = 404 + with pytest.raises(HTTPError): + sd.create_score_definition( + score_def_name="test_create_sd", + model_id="12345", + table_name="test_table", + ) + + get_model.return_value.status_code = 200 + get_model.return_value.json.return_value = { + "id": "12345", + "projectId": "54321", + "projectVersionId": "67890", + "name": "test_model", + } + get_table.return_value.status_code = 404 + with pytest.raises(HTTPError): + sd.create_score_definition( + score_def_name="test_create_sd", + model_id="12345", + table_name="test_table", + ) + get_table.return_value.status_code = 404 + upload_file.return_value = None + get_table.return_value.status_code = 404 + with pytest.raises(HTTPError): + sd.create_score_definition( + score_def_name="test_create_sd", + model_id="12345", + table_name="test_table", + table_file="test_path", + ) + + get_table.return_value.status_code = 404 + upload_file.return_value = RestObj + get_table.return_value.status_code = 200 + get_table.return_value.json.return_value = { + "tableName": "test_table" + } + response = sd.create_score_definition( + score_def_name="test_create_sd", + model_id="12345", + table_name="test_table", + table_file="test_path", ) - # get_model.return_value.status_code = 200 - # get_model.return_value.json.return_value = { - # "id": "12345", - # "projectId": "54321", - # "projectVersionId": "67890", - # "name": "test_model" - # "inputVariables": {"A", "B", "C"} #look at syntax combine square brackets and curly bracket - # } - # sd.create_score_definition( - # score_def_name = "test_create_sd", - # model_id = "12345", - # table_name = "test_table", - # mappings = { - # {"mappingVariable": "A", "datasource": "datasource", "variableName": "A"}, - # {"mappingVariable": "B", "datasource": "datasource", "variableName": "B"}, - # {"mappingVariable": "C", "datasource": "datasource", "variableName": "C"} - # } - # ) - - get_model.return_value.status_code = 200 - get_model.return_value.json.return_value = { - "id": "12345", - "projectId": "54321", - "projectVersionId": "67890", - "name": "test_model", - } - get_table.return_value.status_code = 404 - with pytest.raises(HTTPError): - sd.create_score_definition( - score_def_name = "test_create_sd", - model_id = "12345", - table_name = "test_table" + assert response + + get_table.return_value.status_code = 200 + get_table.return_value.json.return_value = { + "tableName": "test_table" + } + response = sd.create_score_definition( + score_def_name="test_create_sd", + model_id="12345", + table_name="test_table", + table_file="test_path", ) - get_table.return_value.status_code = 404 - upload_file.return_value = None - get_table.return_value.status_code = 404 - with pytest.raises(HTTPError): - sd.create_score_definition( - score_def_name = "test_create_sd", - model_id = "12345", - table_name = "test_table", - table_file = "test_path" - ) - - get_table.return_value.status_code = 404 - upload_file.return_value = RestObj - get_table.return_value.status_code = 200 - response = sd.create_score_definition( - score_def_name = "test_create_sd", - model_id = "12345", - table_name = "test_table", - table_file = "test_path" - ) - assert response - - - - - # get_table.return_value.status_code = 200 - # get_table.return_value.json.return_value = { - # "tableName": "test_table" - # } - # sd.create_score_definition( - # score_def_name = "test_create_sd", - # model_id = "12345", - # table_name = "test_table" - # ) + assert response - - - - - - # # Test for valid model id, no input mapping, get_table succeeded, and post succeeds - - # get_table.return_value = RestObj() - # raise_for_status.return_value = None - - - - # assert response - - # Test for invalid model id - #get_model.return_value = RestObj() - #with pytest.raises( - #HTTPError - #): #test tget_Table since we don't know what the return value is restobj - #sd.create_score_definition( - #score_def_name = "test_create_sd", - #model_id = "12345", - #table_name = "test_table", - #) - #Test for valid and invalid for each - #Start with testing invalid and realize you can work from the last call to the first because the last call working means the first call must have worked - - \ No newline at end of file + get_model.return_value.status_code = 200 + get_model.return_value.json.return_value = { + "id": "12345", + "projectId": "54321", + "projectVersionId": "67890", + "name": "test_model", + "inputVariables": [ + {"name": "first"}, + {"name": "second"}, + {"name": "third"}, + ], + } + get_table.return_value.status_code = 200 + get_table.return_value.json.return_value = { + "tableName": "test_table" + } + response = sd.create_score_definition( + score_def_name="test_create_sd", + model_id="12345", + table_name="test_table", + ) + assert response + assert post.call_count == 3 From 00f358e765cd30ebe8470baa738f35710508d3a9 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Wed, 17 Jul 2024 15:02:17 -0400 Subject: [PATCH 29/86] Reformatting --- src/sasctl/_services/model_repository.py | 7 ++++--- src/sasctl/_services/score_execution.py | 15 ++++++++------- tests/unit/test_score_execution.py | 7 ++++--- tests/unit/test_score_executions.py | 7 ++++--- 4 files changed, 20 insertions(+), 16 deletions(-) diff --git a/src/sasctl/_services/model_repository.py b/src/sasctl/_services/model_repository.py index 0971a125..37a4534f 100644 --- a/src/sasctl/_services/model_repository.py +++ b/src/sasctl/_services/model_repository.py @@ -359,9 +359,10 @@ def create_model( model["scoreCodeType"] = score_code_type or model.get("scoreCodeType") model["trainTable"] = training_table or model.get("trainTable") - model["classificationEventProbabilityVariableName"] = ( - event_prob_variable - or model.get("classificationEventProbabilityVariableName") + model[ + "classificationEventProbabilityVariableName" + ] = event_prob_variable or model.get( + "classificationEventProbabilityVariableName" ) model["classificationTargetEventValue"] = event_target_value or model.get( "classificationTargetEventValue" diff --git a/src/sasctl/_services/score_execution.py b/src/sasctl/_services/score_execution.py index d35a4517..2b381ffe 100644 --- a/src/sasctl/_services/score_execution.py +++ b/src/sasctl/_services/score_execution.py @@ -19,9 +19,12 @@ class ScoreExecution(Service): _SERVICE_ROOT = "/scoreExecution" - list_executions, get_execution, update_execution, delete_execution = ( - Service._crud_funcs("/executions", "execution") - ) + ( + list_executions, + get_execution, + update_execution, + delete_execution, + ) = Service._crud_funcs("/executions", "execution") @classmethod def create_score_execution( @@ -71,10 +74,8 @@ def create_score_execution( try: score_execution = cls.get( f"/executions?filter=eq(scoreExecutionRequest.scoreDefinitionId,%27{score_definition_id}%27)" - ) - execution_count = score_execution.get( - "count" - ) # Exception catch location + ) + execution_count = score_execution.get("count") # Exception catch location if execution_count == 1: execution_id = score_execution.get("items", [0], ["id"]) deleted_score_execution = cls.delete_execution(execution_id) diff --git a/tests/unit/test_score_execution.py b/tests/unit/test_score_execution.py index 93abfde7..7dcfcc09 100644 --- a/tests/unit/test_score_execution.py +++ b/tests/unit/test_score_execution.py @@ -23,6 +23,7 @@ from sasctl.core import RestObj, VersionInfo from sasctl._services.score_definitions import ScoreDefinitions as sd + def test_create_score_execution(): """ Test Cases: @@ -32,9 +33,9 @@ def test_create_score_execution(): - Valid execution id? -Valid count key? - + """ - + with mock.patch( "sasctl._services.score_definitions.ScoreDefinitions.get_definition" ) as get_definition: @@ -45,4 +46,4 @@ def test_create_score_execution(): "sasctl._services.score_execution.ScoreExecution.delete_execution" ) as delete_execution: exit() - #raise HTTP error? \ No newline at end of file + # raise HTTP error? diff --git a/tests/unit/test_score_executions.py b/tests/unit/test_score_executions.py index 93abfde7..7dcfcc09 100644 --- a/tests/unit/test_score_executions.py +++ b/tests/unit/test_score_executions.py @@ -23,6 +23,7 @@ from sasctl.core import RestObj, VersionInfo from sasctl._services.score_definitions import ScoreDefinitions as sd + def test_create_score_execution(): """ Test Cases: @@ -32,9 +33,9 @@ def test_create_score_execution(): - Valid execution id? -Valid count key? - + """ - + with mock.patch( "sasctl._services.score_definitions.ScoreDefinitions.get_definition" ) as get_definition: @@ -45,4 +46,4 @@ def test_create_score_execution(): "sasctl._services.score_execution.ScoreExecution.delete_execution" ) as delete_execution: exit() - #raise HTTP error? \ No newline at end of file + # raise HTTP error? From 2ef46a4ff6d76c570f9550c8c7340c91c8d9f444 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Wed, 17 Jul 2024 15:07:57 -0400 Subject: [PATCH 30/86] Reformatting with black version 24.4.2 --- src/sasctl/_services/model_repository.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/src/sasctl/_services/model_repository.py b/src/sasctl/_services/model_repository.py index 37a4534f..0971a125 100644 --- a/src/sasctl/_services/model_repository.py +++ b/src/sasctl/_services/model_repository.py @@ -359,10 +359,9 @@ def create_model( model["scoreCodeType"] = score_code_type or model.get("scoreCodeType") model["trainTable"] = training_table or model.get("trainTable") - model[ - "classificationEventProbabilityVariableName" - ] = event_prob_variable or model.get( - "classificationEventProbabilityVariableName" + model["classificationEventProbabilityVariableName"] = ( + event_prob_variable + or model.get("classificationEventProbabilityVariableName") ) model["classificationTargetEventValue"] = event_target_value or model.get( "classificationTargetEventValue" From 91fc771115da49d874750ff75851d1058433ade1 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Wed, 17 Jul 2024 15:35:59 -0400 Subject: [PATCH 31/86] Skipping this file for build --- tests/unit/test_score_execution.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/unit/test_score_execution.py b/tests/unit/test_score_execution.py index 7dcfcc09..b440a8e7 100644 --- a/tests/unit/test_score_execution.py +++ b/tests/unit/test_score_execution.py @@ -45,5 +45,5 @@ def test_create_score_execution(): with mock.patch( "sasctl._services.score_execution.ScoreExecution.delete_execution" ) as delete_execution: - exit() + pytest.skip() # raise HTTP error? From 0791fdc225bf98ef06ee6bfc5f6224b6c2c92c06 Mon Sep 17 00:00:00 2001 From: Sophia Rowland Date: Thu, 27 Jun 2024 13:18:27 -0400 Subject: [PATCH 32/86] Adding new notebook for Azure Open AI example --- .../register_Azure_Open_AI_REST_Call.ipynb | 388 ++++++++++++++++++ 1 file changed, 388 insertions(+) create mode 100644 examples/register_Azure_Open_AI_REST_Call.ipynb diff --git a/examples/register_Azure_Open_AI_REST_Call.ipynb b/examples/register_Azure_Open_AI_REST_Call.ipynb new file mode 100644 index 00000000..5d99c16c --- /dev/null +++ b/examples/register_Azure_Open_AI_REST_Call.ipynb @@ -0,0 +1,388 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "3e928632-2b60-4eea-b296-1b196a29b3a4", + "metadata": {}, + "source": [ + "Copyright © 2024, SAS Institute Inc., Cary, NC, USA. All Rights Reserved. SPDX-License-Identifier: Apache-2.0\n", + "# Using Azure OpenAI GPT Models in SAS Viya\n", + "In this notebook, we will walk through the steps required for leveraging a GPT-3.5-Turbo model from Azure OpenAI in SAS® Model Manager® and SAS® Intelligent Decisioning®. \n", + "*** \n", + "## Table of Contents \n", + "1. [Introduction](#Introduction)\n", + "1. [Deploying a GPT Model in Azure OpenAI](#Deploying-a-GPT-Model-in-Azure-OpenAI)\n", + "1. [Considerations for Key Management](#Considerations-for-Key-Management)\n", + "1. [Integration with SAS Model Manager](#Integration-with-SAS-Model-Manager)\n", + "1. [Integration with SAS Intelligent Decisioning](#Integration-with-SAS-Intelligent-Decisioning)\n", + "1. [Conclusion](#Conclusion)\n", + "***\n", + "## Introduction \n", + "[Azure OpenAI Service](https://azure.microsoft.com/en-us/products/ai-services/openai-service/) provides access to Large Language Models (LLMs) through REST API, their Python SDK, and a web-based interface in the Azure OpenAI studio. Various models are available out of the box, including GPT-4, GPT-4 Turbo with Vision, GPT-3.5-Turbo, and Embeddings model series. You can read more about Azure OpenAI Service [here](https://learn.microsoft.com/en-us/azure/ai-services/openai/overview). To incorporate these models in SAS Intelligent Decisioning and SAS Model Manager, we will create a Python function and scoring code calling the REST API of a GPT-3.5-Turbo model deployed in Azure OpenAI. At the time of writing this notebook, the Python SDK does not support all calls to each model type, but that may change in the future. Additionally, we will walk through the steps required for deploying the model, based on what is required at the time of writing. \n", + "*** \n", + "## Deploying a GPT Model in Azure OpenAI\n", + "At the time of writing, access to Azure OpenAI service must be requested and approved. You can determine if you qualify for access and submit your request via [this form]( https://customervoice.microsoft.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR7en2Ais5pxKtso_Pz4b1_xUNTZBNzRKNlVQSFhZMU9aV09EVzYxWFdORCQlQCN0PWcu). Once access is granted, you must create an Azure OpenAI Service resource and deploy your model. [This tutorial](https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/create-resource?pivots=web-portal) walks through setting up an Azure OpenAI Service and deploying a model in a few simple steps. For this example, I’ve used GPT-3.5-Turbo, but not all models are available in all regions. Next, I recommend walking through [this tutorial](https://learn.microsoft.com/en-us/azure/ai-services/openai/quickstart?pivots=rest-api&tabs=command-line%2Cpython) with REST as your preferred method. Importantly, save your endpoint, API-key, and deployment name. We will need them for the next steps. Run the cell below and you can save each of them via the input boxes that appear. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ec2aebc5-a4c6-4048-84cc-b0d9b15e9ed4", + "metadata": {}, + "outputs": [], + "source": [ + "import getpass\n", + "\n", + "endpoint = input(\"Endpoint: \")\n", + "deployment_name = input(\"Deployment name: \")\n", + "api_key = getpass.getpass(\"API Key: \")" + ] + }, + { + "cell_type": "markdown", + "id": "89abd7f2-200a-4b90-a029-d87513544775", + "metadata": {}, + "source": [ + "***\n", + "## Considerations for Key Management\n", + "Even though the cell above collects your API key, it uses the GetPass package to hide your key from view. With our endpoint, deployment name, and API key, anyone can make calls to our deployed LLM. Each call incurs a cost, so we need to prevent unauthorized usage. We want to take steps to protect our API key from falling into the wrong hands, but we need to use our API key in our score code to call our deployed LLM. Let’s outline a few key management options and discuss the potential risks of each. \n", + "\n", + "First, we can hardcode our key into the score code used in SAS Model Manager and SAS Intelligent Decisioning. This will give anyone with access to our models or Python code files on SAS Viya the ability to view our key, and thus, use our model. We can restrict access to these resources in SAS Viya by leveraging the [access control rules](https://go.documentation.sas.com/doc/en/sasadmincdc/v_049/evfun/n1uw3er96phzpfn1pxvnf01f6sw3.htm) built into SAS Viya so only a select few can see our models or Python code. \n", + "\n", + "We can make this approach a bit better by encoding our key using the Base64 package and then adding logic into our score code to decode our key prior to make the REST API call. Anyone can decode our encoded key, but now our key is no longer stored plain text. You can encode your key via:" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "9e99e596-b923-4c18-9a7f-6ba1132f86fb", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'ZXhhbXBsZV9rZXk='" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import base64\n", + "key = 'example_key'\n", + "en = base64.b64encode(key.encode('ascii')).decode('ascii')\n", + "en" + ] + }, + { + "cell_type": "markdown", + "id": "6c645cd4-06a6-4637-bdf8-0acebba79954", + "metadata": {}, + "source": [ + "And you can decode your key by: " + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "bbf669bd-473d-4f0b-b5f8-e3543abd8aa7", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'example_key'" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "de = base64.b64decode(en.encode('ascii')).decode('ascii')\n", + "de" + ] + }, + { + "cell_type": "markdown", + "id": "978fd715-96b1-496c-8222-c30e862edcb4", + "metadata": {}, + "source": [ + "Anyone with access to our model, decision, or deployment can use it to make a call to our deployed LLM. If we want to restrict usage to only folks with our key, we can add our key or our encoded key as an input to the model or decision. When calling the deployed model or decision, the individual must also pass the key as an input variable. When performing score tests in CAS or publishing validation, this will write the key to the CAS table, where it may be viewable to others. Additionally, when scoring via MAS, this may write the key to the log viewable by administrators. \n", + "\n", + "Finally, with help from an administrator, you can save the keys as Environment variables Python environment within SAS Viya. This allows anyone with access to the model, decision, or deployment access to our deployed LLM, but this does hide our key from others. For example, in a Python environment where the model to be executed, we can save an environment variable like so: " + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "6ddd8878-ebe6-43ee-b088-035334e8dba3", + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "os.environ['my_gpt_key'] = key" + ] + }, + { + "cell_type": "markdown", + "id": "f2c70757-bec8-49d9-ba7b-9e216c3da0f3", + "metadata": {}, + "source": [ + "And use it our code, like so: " + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "f6b38665-2dba-49a3-98e9-535135e5c40c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'example_key'" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "k = os.environ['my_gpt_key']\n", + "k" + ] + }, + { + "cell_type": "markdown", + "id": "f59bb4f6-936e-4ebd-86de-a0fb1bdb8183", + "metadata": {}, + "source": [ + "The key management techniques above can be combined to select the best level of security for your needs. You will need to update the code blocks below to take advantage of the techniques you’ve chosen. \n", + "*** \n", + "## Integration with SAS Model Manager\n", + "To run our model in SAS Model Manager, we need to write our score code and save it as a .py file. We also need to specify the inputs to our score code, the outputs the score code generates, and properties of the model. Then we can register it all into SAS Model Manager directly from this notebook using the python-sasctl package. First, let’s use python-sasctl to authenticate to our target SAS Viya environment. Run the cell below to input your information to create a session with SAS Viya. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8366fa36-4b33-4b1b-9729-dba501cecd51", + "metadata": {}, + "outputs": [], + "source": [ + "from sasctl import Session\n", + "from sasctl.services import model_repository as mr, model_management as mm\n", + "\n", + "host = input(\"Hostname: \")\n", + "username = input(\"Username: \")\n", + "password = getpass.getpass(\"Password: \")\n", + "\n", + "sess = Session(host, username, password)\n", + "sess" + ] + }, + { + "cell_type": "markdown", + "id": "4dcbf808-b3d1-430f-88c5-92bc65cbd83b", + "metadata": {}, + "source": [ + "Next, let’s write our score code. Keep in mind your chosen key management techniques and edit the score code to reflect your choice. In the block below, you need to: \n", + "1. Pick a name for your model and update the write file line to match your chosen name. This will write the file to your current directory, but you can edit this line to save the file to another directory. \n", + "1. Update the endpoint and deployment name within the URL string.\n", + "1. Update the key variable to reflect your key management strategy as well as make any necessary changes within SAS Viya.\n", + "\n", + "Run the block to write the score code file. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d0563c76-91a3-4c85-87f2-d99e13144899", + "metadata": {}, + "outputs": [], + "source": [ + "%%writefile [INSERT-YOUR-MODEL-NAME].py\n", + "import requests\n", + "\n", + "def score(prompt):\n", + " \"Output: answer_llm,finish_reason\"\n", + " \n", + " url = '[INSERT-YOUR-ENDPOINT]/openai/deployments/[INSERT-YOUR-DEPLOYMENT-NAME]/chat/completions?api-version=2023-05-15'\n", + "\n", + " k = '[INSERT-YOUR-API-KEY]'\n", + "\t\n", + " h = {\"Accept\": \"application/json\", \"Content-type\": \"application/json; charset=utf-8\", \"api-key\": k}\n", + "\n", + " data = {\"messages\":[{\"role\": \"user\", \"content\": prompt}]}\n", + "\n", + " response = requests.post(url, json = data , headers = h )\n", + "\n", + " jsonResponse = response.json() \n", + " finish_reason = jsonResponse[\"choices\"][0]['finish_reason']\n", + " answer_llm = jsonResponse[\"choices\"][0]['message']['content']\n", + "\n", + "\n", + " return answer_llm,finish_reason" + ] + }, + { + "cell_type": "markdown", + "id": "d90363ad-b7ec-4195-97e9-e56f1e3cf92f", + "metadata": {}, + "source": [ + "Next, let’s add our file to SAS Model Manager and update its properties. In the blow below, you need to:\n", + "1. Add the name of your project in SAS Model Manager, your chosen name for the model, and the algorithm from your deployed LLM, such as GPT 3-5 Turbo, in the first three lines of code.\n", + "1. Update the add_model_content function with your model name in the two indicated locations. \n", + "Once the code block has run, you can open your project in SAS Model Manager to find your model! From SAS Model Manager, you can run the model in a score test or deploy it to other destinations, including a container. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c66efa86-6e80-4f35-aee4-ebd92c55c725", + "metadata": {}, + "outputs": [], + "source": [ + "# Update these variable to match your project\n", + "project = '[INSERT-YOUR-PROJECT-NAME]'\n", + "model_name = '[INSERT-YOUR-MODEL-NAME]'\n", + "algorithm = '[INSERT-YOUR-LLM-ALGORITHM]'\n", + "\n", + "# Specify input variables and output variables\n", + "inputvariables = [{'name': 'prompt', 'role': 'input', 'type': 'string', 'level': 'nominal', 'length': 500}]\n", + "outputvariables = [{'name': 'answer_llm', 'role': 'output', 'type': 'string', 'level': 'nominal', 'length': 500}, {'name': 'finish_reason', 'role': 'output', 'type': 'string', 'level': 'nominal', 'length': 15}]\n", + "\n", + "# Create the model\n", + "model = mr.create_model(\n", + " model=model_name,\n", + " project=project,\n", + " algorithm=algorithm,\n", + " modeler=username,\n", + " tool='Python 3',\n", + " function = \"Text Generation\",\n", + " score_code_type = 'Python',\n", + " input_variables = inputvariables,\n", + " output_variables = outputvariables\n", + ")\n", + "\n", + "# Add score code\n", + "scorefile = mr.add_model_content(\n", + " model,\n", + " open('[INSERT-YOUR-MODEL-NAME].py', 'rb'),\n", + " name='[INSERT-YOUR-MODEL-NAME].py',\n", + " role='score'\n", + ")\n" + ] + }, + { + "cell_type": "markdown", + "id": "0c758627-6995-4184-af93-966a8c6eacb2", + "metadata": {}, + "source": [ + "***\n", + "## Integration with SAS Intelligent Decisioning \n", + "We can use the Python model we just developed and registered to SAS Model Manager within our decision flow as a model. But, if you don’t have SAS Model Manager, no need to worry! We can leverage a Python code file in SAS Intelligent Decisioning instead. To run the GPT-3.5 model, we need to create an execute function that we will then copy and paste the code into the Python code files in SAS Intelligent Decisioning. The same concerns apply for key management, so update the code block below to reflect your key management strategy. In the code block below, you need to: \n", + "1. Update the endpoint and deployment name within the URL string. \n", + "1. Update the key variable to reflect your key management strategy as well as make any necessary changes within SAS Viya. \n", + "1. Copy the code block into a Python code file in SAS Intelligent Decisioning. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a13e819d-4ba8-4174-b7ed-f9df56af8e1b", + "metadata": {}, + "outputs": [], + "source": [ + "''' List all output parameters as comma-separated values in the \"Output:\" docString. Do not specify \"None\" if there is no output parameter. '''\n", + "''' List all Python packages that are not built-in packages in the \"DependentPackages:\" docString. Separate the package names with commas on a single line. '''\n", + "\n", + "\n", + "import requests\n", + "\n", + "def execute (prompt):\n", + " 'Output:answer_llm,finish_reason'\n", + " 'DependentPackages: requests'\n", + " \n", + " url = '[INSERT-YOUR-ENDPOINT]/openai/deployments/[INSERT-YOUR-DEPLOYMENT-NAME]/chat/completions?api-version=2023-05-15'\n", + "\n", + " k = '[INSERT-YOUR-API-KEY]'\n", + "\t\n", + " h = {\"Accept\": \"application/json\", \"Content-type\": \"application/json; charset=utf-8\", \"api-key\": k}\n", + "\n", + " data = {\"messages\":[{\"role\": \"user\", \"content\": prompt}]}\n", + "\n", + " response = requests.post(url, json = data , headers = h )\n", + "\n", + " jsonResponse = response.json() \n", + " finish_reason = jsonResponse[\"choices\"][0]['finish_reason']\n", + " answer_llm = jsonResponse[\"choices\"][0]['message']['content']\n", + "\n", + "\n", + " return answer_llm,finish_reason\n" + ] + }, + { + "cell_type": "markdown", + "id": "6640cc88-94ac-4cb8-926c-715045635c08", + "metadata": {}, + "source": [ + "Once you add those changes to your code block above, it becomes a valid Python function and you can run here using the execute function to test it, like so: " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "06b09883-9c08-4647-a7f3-3de062fcf212", + "metadata": {}, + "outputs": [], + "source": [ + "execute(\"Write a tagline for an ice cream shop.\")" + ] + }, + { + "cell_type": "markdown", + "id": "bd0be03a-3765-4649-8a69-9decaee5a55b", + "metadata": {}, + "source": [ + "*** \n", + "## Conclusion\n", + "Now, you are all set to leverage a GPT-3.5-Turbo model deployed in Azure OpenAI in SAS Model Manager or SAS Intelligent Decisioning where it can be managed with other models in your organizations, combined with business logic, orchestrated with other models, and deployed into destinations within SAS Viya or beyond using containers." + ] + }, + { + "cell_type": "markdown", + "id": "31afee6d-b46b-4560-9c8a-33bcb41f2e93", + "metadata": {}, + "source": [ + "***" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 3b7aba0aecba361f2f5d9fb106eb57cbb91f04b8 Mon Sep 17 00:00:00 2001 From: Sophia Rowland Date: Thu, 27 Jun 2024 13:20:23 -0400 Subject: [PATCH 33/86] Update register_Azure_Open_AI_REST_Call.ipynb --- examples/register_Azure_Open_AI_REST_Call.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/register_Azure_Open_AI_REST_Call.ipynb b/examples/register_Azure_Open_AI_REST_Call.ipynb index 5d99c16c..a1480e6b 100644 --- a/examples/register_Azure_Open_AI_REST_Call.ipynb +++ b/examples/register_Azure_Open_AI_REST_Call.ipynb @@ -6,7 +6,7 @@ "metadata": {}, "source": [ "Copyright © 2024, SAS Institute Inc., Cary, NC, USA. All Rights Reserved. SPDX-License-Identifier: Apache-2.0\n", - "# Using Azure OpenAI GPT Models in SAS Viya\n", + "# Register Azure OpenAI GPT Model REST API Calls\n", "In this notebook, we will walk through the steps required for leveraging a GPT-3.5-Turbo model from Azure OpenAI in SAS® Model Manager® and SAS® Intelligent Decisioning®. \n", "*** \n", "## Table of Contents \n", From ec82f3f30bb2c85ceba30619fa322838e21d89b6 Mon Sep 17 00:00:00 2001 From: Sophia Rowland Date: Thu, 27 Jun 2024 13:23:27 -0400 Subject: [PATCH 34/86] Update README.md Updating Readme for new notebook --- examples/README.md | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/examples/README.md b/examples/README.md index 48b179d3..83832de7 100644 --- a/examples/README.md +++ b/examples/README.md @@ -37,6 +37,8 @@ Tasks and Services - [Modeling with Python & SAS AutoML](#modeling-with-python--sas-automl) - [Making direct REST API calls](#making-direct-rest-api-calls) +- [Register Azure OpenAI GPT Model REST API Calls](#register-Azure-OpenAI-GPT-Model-REST-API-Calls) + --- Register binary classification models ------------------------------------- @@ -206,3 +208,12 @@ Level: Advanced Demonstrates using `sasctl` to make REST calls over HTTP(S) directly to the SAS microservices. Use if you need to customize behavior or use functionality not yet exposed through higher-level `sasctl` functions. + + +Register Azure OpenAI GPT Model REST API Calls +-------------------------- +Filename: [register_Azure_Open_AI_REST_Call.ipynb](register_Azure_Open_AI_REST_Call.ipynb) + +Level: Intermediate + +Leverages a GPT-3.5-Turbo model from Azure OpenAI in SAS® Model Manager® and SAS® Intelligent Decisioning®. From c2e0ba29f7eb452522aa825f66c0b57b1bed9cf4 Mon Sep 17 00:00:00 2001 From: Kristen Aponte Date: Thu, 27 Jun 2024 18:45:32 -0400 Subject: [PATCH 35/86] Edited new Azure OpenAI GPT model example. --- examples/README.md | 11 ++-- ...Azure_OpenAI_model_using_REST_calls.ipynb} | 61 +++++++++---------- 2 files changed, 36 insertions(+), 36 deletions(-) rename examples/{register_Azure_Open_AI_REST_Call.ipynb => register_Azure_OpenAI_model_using_REST_calls.ipynb} (57%) diff --git a/examples/README.md b/examples/README.md index 83832de7..f91fe482 100644 --- a/examples/README.md +++ b/examples/README.md @@ -37,7 +37,9 @@ Tasks and Services - [Modeling with Python & SAS AutoML](#modeling-with-python--sas-automl) - [Making direct REST API calls](#making-direct-rest-api-calls) -- [Register Azure OpenAI GPT Model REST API Calls](#register-Azure-OpenAI-GPT-Model-REST-API-Calls) +- [Register an Azure OpenAI GPT model using REST API calls](#register-Azure-OpenAI-GPT-Model-REST-API-Calls) + +- Using Azure OpenAI GPT Models --- Register binary classification models @@ -209,11 +211,10 @@ Demonstrates using `sasctl` to make REST calls over HTTP(S) directly to the SAS Use if you need to customize behavior or use functionality not yet exposed through higher-level `sasctl` functions. - -Register Azure OpenAI GPT Model REST API Calls +Register an Azure OpenAI GPT Model Using REST API Calls -------------------------- -Filename: [register_Azure_Open_AI_REST_Call.ipynb](register_Azure_Open_AI_REST_Call.ipynb) +Filename: [register_Azure_OpenAI_model_using_REST_calls.ipynb](register_Azure_OpenAI_model_using_REST_calls.ipynb) Level: Intermediate -Leverages a GPT-3.5-Turbo model from Azure OpenAI in SAS® Model Manager® and SAS® Intelligent Decisioning®. +Leverages a GPT-3.5-Turbo model from Azure OpenAI in SAS® Model Manager and SAS® Intelligent Decisioning. diff --git a/examples/register_Azure_Open_AI_REST_Call.ipynb b/examples/register_Azure_OpenAI_model_using_REST_calls.ipynb similarity index 57% rename from examples/register_Azure_Open_AI_REST_Call.ipynb rename to examples/register_Azure_OpenAI_model_using_REST_calls.ipynb index a1480e6b..637ded8b 100644 --- a/examples/register_Azure_Open_AI_REST_Call.ipynb +++ b/examples/register_Azure_OpenAI_model_using_REST_calls.ipynb @@ -6,8 +6,8 @@ "metadata": {}, "source": [ "Copyright © 2024, SAS Institute Inc., Cary, NC, USA. All Rights Reserved. SPDX-License-Identifier: Apache-2.0\n", - "# Register Azure OpenAI GPT Model REST API Calls\n", - "In this notebook, we will walk through the steps required for leveraging a GPT-3.5-Turbo model from Azure OpenAI in SAS® Model Manager® and SAS® Intelligent Decisioning®. \n", + "# Register Azure OpenAI GPT Model Using REST API Calls\n", + "This notebook example, walks you through the steps required for leveraging a GPT-3.5-Turbo model from Azure OpenAI in SAS® Model Manager and SAS® Intelligent Decisioning. \n", "*** \n", "## Table of Contents \n", "1. [Introduction](#Introduction)\n", @@ -18,10 +18,10 @@ "1. [Conclusion](#Conclusion)\n", "***\n", "## Introduction \n", - "[Azure OpenAI Service](https://azure.microsoft.com/en-us/products/ai-services/openai-service/) provides access to Large Language Models (LLMs) through REST API, their Python SDK, and a web-based interface in the Azure OpenAI studio. Various models are available out of the box, including GPT-4, GPT-4 Turbo with Vision, GPT-3.5-Turbo, and Embeddings model series. You can read more about Azure OpenAI Service [here](https://learn.microsoft.com/en-us/azure/ai-services/openai/overview). To incorporate these models in SAS Intelligent Decisioning and SAS Model Manager, we will create a Python function and scoring code calling the REST API of a GPT-3.5-Turbo model deployed in Azure OpenAI. At the time of writing this notebook, the Python SDK does not support all calls to each model type, but that may change in the future. Additionally, we will walk through the steps required for deploying the model, based on what is required at the time of writing. \n", + "[Azure OpenAI Service](https://azure.microsoft.com/en-us/products/ai-services/openai-service/) provides access to Large Language Models (LLMs) through REST API, their Python SDK, and a web-based interface in the Azure OpenAI studio. Various models are available out of the box, including GPT-4, GPT-4 Turbo with Vision, GPT-3.5-Turbo, and Embeddings model series. For more information about the Azure OpenAI Service, [this article](https://learn.microsoft.com/en-us/azure/ai-services/openai/overview). To incorporate these models in SAS Intelligent Decisioning and SAS Model Manager, you create a Python function and score code by calling the REST API of a GPT-3.5-Turbo model deployed in Azure OpenAI. At the time of writing this notebook, the Python SDK does not support all calls to each model type, but that might change in the future. This example also walks you through the steps that are required for deploying the model, based on what was required when this example was created. \n", "*** \n", "## Deploying a GPT Model in Azure OpenAI\n", - "At the time of writing, access to Azure OpenAI service must be requested and approved. You can determine if you qualify for access and submit your request via [this form]( https://customervoice.microsoft.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR7en2Ais5pxKtso_Pz4b1_xUNTZBNzRKNlVQSFhZMU9aV09EVzYxWFdORCQlQCN0PWcu). Once access is granted, you must create an Azure OpenAI Service resource and deploy your model. [This tutorial](https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/create-resource?pivots=web-portal) walks through setting up an Azure OpenAI Service and deploying a model in a few simple steps. For this example, I’ve used GPT-3.5-Turbo, but not all models are available in all regions. Next, I recommend walking through [this tutorial](https://learn.microsoft.com/en-us/azure/ai-services/openai/quickstart?pivots=rest-api&tabs=command-line%2Cpython) with REST as your preferred method. Importantly, save your endpoint, API-key, and deployment name. We will need them for the next steps. Run the cell below and you can save each of them via the input boxes that appear. " + "Access to Azure OpenAI service must be requested and approved. You can determine whether you qualify for access and submit your request using [this form]( https://customervoice.microsoft.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR7en2Ais5pxKtso_Pz4b1_xUNTZBNzRKNlVQSFhZMU9aV09EVzYxWFdORCQlQCN0PWcu). After access is granted, you must create an Azure OpenAI Service resource and deploy your model. [This tutorial](https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/create-resource?pivots=web-portal) walks you through setting up an Azure OpenAI Service and deploying a model in a few simple steps. GPT-3.5-Turbo is used for this example, but not all models are available in all regions. Next, it is recommended that you walk through [this tutorial](https://learn.microsoft.com/en-us/azure/ai-services/openai/quickstart?pivots=rest-api&tabs=command-line%2Cpython) with REST as your preferred method. Make sure that you save your endpoint, API-key, and deployment name, because they are needed for the next steps. Run the cell below and then save each of them using the input boxes that appear. " ] }, { @@ -45,11 +45,11 @@ "source": [ "***\n", "## Considerations for Key Management\n", - "Even though the cell above collects your API key, it uses the GetPass package to hide your key from view. With our endpoint, deployment name, and API key, anyone can make calls to our deployed LLM. Each call incurs a cost, so we need to prevent unauthorized usage. We want to take steps to protect our API key from falling into the wrong hands, but we need to use our API key in our score code to call our deployed LLM. Let’s outline a few key management options and discuss the potential risks of each. \n", + "Even though the cell above collects your API key, it uses the GetPass package to hide your key from view. With the endpoint, deployment name, and API key, anyone can make calls to the deployed LLM. Each call incurs a cost, so you need to prevent unauthorized usage. You should take steps to protect the API key from falling into the wrong hands, but you must use the API key in the score code to call the deployed LLM. Here are a few key management options and the potential risks of each. \n", "\n", - "First, we can hardcode our key into the score code used in SAS Model Manager and SAS Intelligent Decisioning. This will give anyone with access to our models or Python code files on SAS Viya the ability to view our key, and thus, use our model. We can restrict access to these resources in SAS Viya by leveraging the [access control rules](https://go.documentation.sas.com/doc/en/sasadmincdc/v_049/evfun/n1uw3er96phzpfn1pxvnf01f6sw3.htm) built into SAS Viya so only a select few can see our models or Python code. \n", + "First, you can include the key in the score code used in SAS Model Manager and SAS Intelligent Decisioning. This gives anyone with access to the models or Python code files in SAS Viya the ability to view the key, and thus, use the model. You can restrict access to these resources in SAS Viya by leveraging the [access control rules](https://documentation.sas.com/?cdcId=sasadmincdc&cdcVersion=default&docsetId=evfun&docsetTarget=n1uw3er96phzpfn1pxvnf01f6sw3.htm) that are built into SAS Viya so that only a select few can view the models or Python code. \n", "\n", - "We can make this approach a bit better by encoding our key using the Base64 package and then adding logic into our score code to decode our key prior to make the REST API call. Anyone can decode our encoded key, but now our key is no longer stored plain text. You can encode your key via:" + "This approach can be made a bit better by encoding the key using the Base64 package and then adding logic into the score code to decode the key prior to making the REST API call. Anyone can decode the encoded key, but now the key is no longer stored as plain text. You can encode your key using this code:" ] }, { @@ -81,7 +81,7 @@ "id": "6c645cd4-06a6-4637-bdf8-0acebba79954", "metadata": {}, "source": [ - "And you can decode your key by: " + "And you can decode your key by using this code: " ] }, { @@ -111,9 +111,9 @@ "id": "978fd715-96b1-496c-8222-c30e862edcb4", "metadata": {}, "source": [ - "Anyone with access to our model, decision, or deployment can use it to make a call to our deployed LLM. If we want to restrict usage to only folks with our key, we can add our key or our encoded key as an input to the model or decision. When calling the deployed model or decision, the individual must also pass the key as an input variable. When performing score tests in CAS or publishing validation, this will write the key to the CAS table, where it may be viewable to others. Additionally, when scoring via MAS, this may write the key to the log viewable by administrators. \n", + "Anyone with access to the model, decision, or deployment can use it to make a call to the deployed LLM. If you want to restrict usage to only individuals with the key, you can add the key or the encoded key as an input to a model or decision. When calling the deployed model or decision, the individual must also pass the key as an input variable. When performing score tests or publishing validation tests in CAS, this writes the key to the CAS table, where it can be viewable to others. Also, when scoring using the SAS Micro Analytic Service, this can write the key to the log viewable by administrators. \n", "\n", - "Finally, with help from an administrator, you can save the keys as Environment variables Python environment within SAS Viya. This allows anyone with access to the model, decision, or deployment access to our deployed LLM, but this does hide our key from others. For example, in a Python environment where the model to be executed, we can save an environment variable like so: " + "Finally, with help from an administrator, you can save the keys as environment variables in the Python environment within SAS Viya. This enables anyone with access to the model, decision, or deployment access to the deployed LLM, but this does hide the key from others. For example, in a Python environment where the model is executed, you can save an environment variable in this way: " ] }, { @@ -132,7 +132,7 @@ "id": "f2c70757-bec8-49d9-ba7b-9e216c3da0f3", "metadata": {}, "source": [ - "And use it our code, like so: " + "And use the code, like so: " ] }, { @@ -162,10 +162,10 @@ "id": "f59bb4f6-936e-4ebd-86de-a0fb1bdb8183", "metadata": {}, "source": [ - "The key management techniques above can be combined to select the best level of security for your needs. You will need to update the code blocks below to take advantage of the techniques you’ve chosen. \n", + "The key management techniques above can be combined to select the best level of security for your needs. You must update the code blocks below to take advantage of the techniques that you have chosen. \n", "*** \n", "## Integration with SAS Model Manager\n", - "To run our model in SAS Model Manager, we need to write our score code and save it as a .py file. We also need to specify the inputs to our score code, the outputs the score code generates, and properties of the model. Then we can register it all into SAS Model Manager directly from this notebook using the python-sasctl package. First, let’s use python-sasctl to authenticate to our target SAS Viya environment. Run the cell below to input your information to create a session with SAS Viya. " + "To run the model in SAS Model Manager, you must write the score code and save it as a Python (.py) file. You also must specify the inputs in the score code. The score code generates the outputs, and properties of the model. You can then register it all into SAS Model Manager directly from this notebook using the python-sasctl package. First, use python-sasctl to authenticate with the target SAS Viya environment. Run the cell below to specify your information to create a session with SAS Viya. " ] }, { @@ -178,8 +178,8 @@ "from sasctl import Session\n", "from sasctl.services import model_repository as mr, model_management as mm\n", "\n", - "host = input(\"Hostname: \")\n", - "username = input(\"Username: \")\n", + "host = input(\"Host name: \")\n", + "username = input(\"User name: \")\n", "password = getpass.getpass(\"Password: \")\n", "\n", "sess = Session(host, username, password)\n", @@ -191,12 +191,11 @@ "id": "4dcbf808-b3d1-430f-88c5-92bc65cbd83b", "metadata": {}, "source": [ - "Next, let’s write our score code. Keep in mind your chosen key management techniques and edit the score code to reflect your choice. In the block below, you need to: \n", - "1. Pick a name for your model and update the write file line to match your chosen name. This will write the file to your current directory, but you can edit this line to save the file to another directory. \n", - "1. Update the endpoint and deployment name within the URL string.\n", - "1. Update the key variable to reflect your key management strategy as well as make any necessary changes within SAS Viya.\n", - "\n", - "Run the block to write the score code file. " + "Next, write the score code. Keep in mind your chosen key management techniques and edit the score code to reflect your choice. In the code block below, you must perform these steps: \n", + "1. Choose a name for your model and update the `writefile` line with that name. This writes the file to your current directory, but you can edit this line to save the file to another directory. \n", + "2. Update the endpoint and deployment name within the URL string.\n", + "3. Update the key variable to reflect your key management strategy as well as make any necessary changes within SAS Viya.\n", + "4. Run the block to write the score code file. " ] }, { @@ -235,10 +234,10 @@ "id": "d90363ad-b7ec-4195-97e9-e56f1e3cf92f", "metadata": {}, "source": [ - "Next, let’s add our file to SAS Model Manager and update its properties. In the blow below, you need to:\n", - "1. Add the name of your project in SAS Model Manager, your chosen name for the model, and the algorithm from your deployed LLM, such as GPT 3-5 Turbo, in the first three lines of code.\n", - "1. Update the add_model_content function with your model name in the two indicated locations. \n", - "Once the code block has run, you can open your project in SAS Model Manager to find your model! From SAS Model Manager, you can run the model in a score test or deploy it to other destinations, including a container. " + "Next, add the file to SAS Model Manager and update its properties. In the below code block, you must perform these steps:\n", + "1. In the first three lines of code, specify the name of your project in SAS Model Manager, the name of your model, and the algorithm from your deployed LLM, such as GPT 3.5 Turbo. \n", + "2. Update the add_model_content function with your model name in the two indicated locations. \n", + "After the code block has run, you can open your project in SAS Model Manager to find your model. Using SAS Model Manager, you can run score test for the model, or deploy it to other destinations, including a container. " ] }, { @@ -248,7 +247,7 @@ "metadata": {}, "outputs": [], "source": [ - "# Update these variable to match your project\n", + "# Update these variables to match your project\n", "project = '[INSERT-YOUR-PROJECT-NAME]'\n", "model_name = '[INSERT-YOUR-MODEL-NAME]'\n", "algorithm = '[INSERT-YOUR-LLM-ALGORITHM]'\n", @@ -286,10 +285,10 @@ "source": [ "***\n", "## Integration with SAS Intelligent Decisioning \n", - "We can use the Python model we just developed and registered to SAS Model Manager within our decision flow as a model. But, if you don’t have SAS Model Manager, no need to worry! We can leverage a Python code file in SAS Intelligent Decisioning instead. To run the GPT-3.5 model, we need to create an execute function that we will then copy and paste the code into the Python code files in SAS Intelligent Decisioning. The same concerns apply for key management, so update the code block below to reflect your key management strategy. In the code block below, you need to: \n", + "You can include the Python model that you just developed and registered in SAS Model Manager within a decision flow. But, if you do not have SAS Model Manager, no need to worry, you can leverage a Python code file in SAS Intelligent Decisioning instead. To run the GPT-3.5 model, you must create an execute function that you can then copy and paste into the Python code files in SAS Intelligent Decisioning. The same concerns apply to key management, so update the below code block to reflect your key management strategy. In the code block below, you must perform these steps: \n", "1. Update the endpoint and deployment name within the URL string. \n", - "1. Update the key variable to reflect your key management strategy as well as make any necessary changes within SAS Viya. \n", - "1. Copy the code block into a Python code file in SAS Intelligent Decisioning. " + "2. Update the key variable to reflect your key management strategy as well as make any necessary changes within SAS Viya. \n", + "3. Copy the code block into a Python code file in SAS Intelligent Decisioning. " ] }, { @@ -332,7 +331,7 @@ "id": "6640cc88-94ac-4cb8-926c-715045635c08", "metadata": {}, "source": [ - "Once you add those changes to your code block above, it becomes a valid Python function and you can run here using the execute function to test it, like so: " + "After you add those changes to the above code block, it becomes a valid Python function, and then you can run it using the execute function to test it. " ] }, { @@ -352,7 +351,7 @@ "source": [ "*** \n", "## Conclusion\n", - "Now, you are all set to leverage a GPT-3.5-Turbo model deployed in Azure OpenAI in SAS Model Manager or SAS Intelligent Decisioning where it can be managed with other models in your organizations, combined with business logic, orchestrated with other models, and deployed into destinations within SAS Viya or beyond using containers." + "Now, you are all set to leverage a GPT-3.5-Turbo model that is deployed in Azure OpenAI with SAS Model Manager or SAS Intelligent Decisioning. It can then be managed with other models within your organization, combined with business logic, orchestrated with other models, and deployed into destinations within SAS Viya or beyond using containers." ] }, { From 1a16cd44afc00d3f472fe05c45e53501e22cfdc3 Mon Sep 17 00:00:00 2001 From: Kristen Aponte Date: Thu, 27 Jun 2024 18:54:48 -0400 Subject: [PATCH 36/86] Edited examples README.md file. --- examples/README.md | 8 +++----- 1 file changed, 3 insertions(+), 5 deletions(-) diff --git a/examples/README.md b/examples/README.md index f91fe482..947d4f82 100644 --- a/examples/README.md +++ b/examples/README.md @@ -37,9 +37,7 @@ Tasks and Services - [Modeling with Python & SAS AutoML](#modeling-with-python--sas-automl) - [Making direct REST API calls](#making-direct-rest-api-calls) -- [Register an Azure OpenAI GPT model using REST API calls](#register-Azure-OpenAI-GPT-Model-REST-API-Calls) - -- Using Azure OpenAI GPT Models +- [Register an Azure OpenAI GPT model using REST API calls](#register-an-azure-openai-gpt-model-using-rest-api-calls) --- Register binary classification models @@ -98,11 +96,11 @@ Generates a requirements.json file which includes the minimal number of dependen Create and update custom model KPIs ----------------------------------- -Filename: [pzmm_custom_kpis.ipynb](pzmm_custom_kpis.ipynb) +Filename: [pzmm_custom_kpis.ipynb](pzmm_custom_kpi_model_parameters.ipynb) Level: Intermediate -Create and update custom model parameters and kpis on SAS Model Manager +Create and update custom model parameters and kpis on SAS Model Manager. Register a SAS classification model From 7c95b564f509e4c4acd31dbc681aa7dc7e281e90 Mon Sep 17 00:00:00 2001 From: djm21 Date: Fri, 28 Jun 2024 15:36:29 -0500 Subject: [PATCH 37/86] updated casing in model properties so they are correctly read --- src/sasctl/pzmm/write_json_files.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/src/sasctl/pzmm/write_json_files.py b/src/sasctl/pzmm/write_json_files.py index 1d772ac5..904ea7e4 100644 --- a/src/sasctl/pzmm/write_json_files.py +++ b/src/sasctl/pzmm/write_json_files.py @@ -355,17 +355,17 @@ def write_model_properties_json( ) if not target_values: - model_function = model_function if model_function else "Prediction" + model_function = model_function if model_function else "prediction" target_level = "Interval" target_event = "" event_prob_var = "" elif isinstance(target_values, list) and len(target_values) == 2: - model_function = model_function if model_function else "Classification" + model_function = model_function if model_function else "classification" target_level = "Binary" target_event = str(target_values[0]) event_prob_var = f"P_{target_values[0]}" elif isinstance(target_values, list) and len(target_values) > 2: - model_function = model_function if model_function else "Classification" + model_function = model_function if model_function else "classification" target_level = "Nominal" target_event = "" event_prob_var = "" @@ -2410,7 +2410,7 @@ def upload_training_data( "either delete/rename the old table or give a new name to the current table." ) - return server + "/" + caslib + "/" + train_data_name + return server + "/" + caslib + "/" + train_data_name.upper() @staticmethod def generate_outcome_average( @@ -2730,7 +2730,7 @@ def generate_variable_importance( @classmethod def generate_misc(cls, model_files: Union[str, Path, dict]): """ - Generates the dmcas_relativeimportance.json file, which is used to determine variable importance + Generates the dmcas_misc.json file, which is used to determine variable importance Parameters ---------- From 2ecab5de3e2e1551027cc425f8770fb24142ae7d Mon Sep 17 00:00:00 2001 From: djm21 Date: Mon, 10 Jun 2024 12:43:05 -0400 Subject: [PATCH 38/86] GitHub test changes --- .github/workflows/build-test-deploy.yml | 7 ++++++- tox.ini | 4 +++- 2 files changed, 9 insertions(+), 2 deletions(-) diff --git a/.github/workflows/build-test-deploy.yml b/.github/workflows/build-test-deploy.yml index 3d1fa501..666780af 100644 --- a/.github/workflows/build-test-deploy.yml +++ b/.github/workflows/build-test-deploy.yml @@ -21,8 +21,13 @@ jobs: LANG: en_US.UTF-8 strategy: matrix: - python-version: ['3.6', '3.7', '3.8', '3.9', '3.10'] + python-version: ['3.6', '3.7', '3.8', '3.9', '3.10', '3.11', '3.12'] os-version: ['ubuntu-20.04', 'windows-latest', 'macos-latest'] + exclude: + - python-version: '3.6' + os-version: 'macos-latest' + - python-version: '3.7' + os-version: 'macos-latest' # Pinned Ubuntu version to 20.04 since no Python 3.6 builds available on ubuntu-latest (22.04) as of 2022-12-7. # os-version: [ubuntu-latest, windows-latest, macos-latest] diff --git a/tox.ini b/tox.ini index 0851d626..c3de3946 100644 --- a/tox.ini +++ b/tox.ini @@ -12,7 +12,7 @@ [tox] -envlist = py{36,37,38,39,310,311}-tests-{clean,unit,integration} +envlist = py{36,37,38,39,310,311,312}-tests-{clean,unit,integration} # Allow execution even if all Python versions are not present skip_missing_interpreters = {env:TOX_SKIP_MISSING_INTERPRETERS:True} @@ -26,6 +26,7 @@ python = 3.9: py39 3.10: py310 3.11: py311 + 3.12: py312 [testenv] skip_install = @@ -38,6 +39,7 @@ basepython = py39: python3.9 py310: python3.10 py311: python3.11 + py312: python3.12 deps = clean: coverage From 6a35e5b28e70ffaa127d5bbac08b5b771d70b080 Mon Sep 17 00:00:00 2001 From: djm21 Date: Mon, 10 Jun 2024 13:17:16 -0400 Subject: [PATCH 39/86] Updated xgboost version in tox.ini file --- tox.ini | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tox.ini b/tox.ini index c3de3946..a9a88fb8 100644 --- a/tox.ini +++ b/tox.ini @@ -52,7 +52,7 @@ deps = tests: cython # required to install pandas from source tests: swat >= 1.8 tests: kerberos ; platform_system != "Windows" and platform_system != "Darwin" - tests: xgboost == 0.82 + tests: xgboost == 1.7.3 tests: urllib3 < 2.0.0 tests: nbconvert tests: nbformat From d33a1a412142d7ed507aebdc232fd2c7ccf8fc09 Mon Sep 17 00:00:00 2001 From: djm21 Date: Mon, 10 Jun 2024 13:24:34 -0400 Subject: [PATCH 40/86] remove tests for python 3.6 and 3.7 to allow for compatibility with xgboost version 1.7.3 --- .github/workflows/build-test-deploy.yml | 6 +----- tox.ini | 6 +----- 2 files changed, 2 insertions(+), 10 deletions(-) diff --git a/.github/workflows/build-test-deploy.yml b/.github/workflows/build-test-deploy.yml index 666780af..5df7030f 100644 --- a/.github/workflows/build-test-deploy.yml +++ b/.github/workflows/build-test-deploy.yml @@ -21,13 +21,9 @@ jobs: LANG: en_US.UTF-8 strategy: matrix: - python-version: ['3.6', '3.7', '3.8', '3.9', '3.10', '3.11', '3.12'] + python-version: ['3.8', '3.9', '3.10', '3.11', '3.12'] os-version: ['ubuntu-20.04', 'windows-latest', 'macos-latest'] exclude: - - python-version: '3.6' - os-version: 'macos-latest' - - python-version: '3.7' - os-version: 'macos-latest' # Pinned Ubuntu version to 20.04 since no Python 3.6 builds available on ubuntu-latest (22.04) as of 2022-12-7. # os-version: [ubuntu-latest, windows-latest, macos-latest] diff --git a/tox.ini b/tox.ini index a9a88fb8..f9f25356 100644 --- a/tox.ini +++ b/tox.ini @@ -12,7 +12,7 @@ [tox] -envlist = py{36,37,38,39,310,311,312}-tests-{clean,unit,integration} +envlist = py{38,39,310,311,312}-tests-{clean,unit,integration} # Allow execution even if all Python versions are not present skip_missing_interpreters = {env:TOX_SKIP_MISSING_INTERPRETERS:True} @@ -20,8 +20,6 @@ skip_missing_interpreters = {env:TOX_SKIP_MISSING_INTERPRETERS:True} # Required by tox-gh-actions GH action. Maps GH Python runtime to tox envlist. [gh-actions] python = - 3.6: py36 - 3.7: py37 3.8: py38 3.9: py39 3.10: py310 @@ -33,8 +31,6 @@ skip_install = clean: true basepython = - py36: python3.6 - py37: python3.7 py38: python3.8 py39: python3.9 py310: python3.10 From 65f9c9c45ceaa522db2adb6e730f3b9437efcfd7 Mon Sep 17 00:00:00 2001 From: djm21 Date: Mon, 10 Jun 2024 13:25:22 -0400 Subject: [PATCH 41/86] fix formatting error in build-test-deploy.yml --- .github/workflows/build-test-deploy.yml | 1 - 1 file changed, 1 deletion(-) diff --git a/.github/workflows/build-test-deploy.yml b/.github/workflows/build-test-deploy.yml index 5df7030f..b5f2d808 100644 --- a/.github/workflows/build-test-deploy.yml +++ b/.github/workflows/build-test-deploy.yml @@ -23,7 +23,6 @@ jobs: matrix: python-version: ['3.8', '3.9', '3.10', '3.11', '3.12'] os-version: ['ubuntu-20.04', 'windows-latest', 'macos-latest'] - exclude: # Pinned Ubuntu version to 20.04 since no Python 3.6 builds available on ubuntu-latest (22.04) as of 2022-12-7. # os-version: [ubuntu-latest, windows-latest, macos-latest] From 50d115f01ad9d978590ebd9c1bda714d38428767 Mon Sep 17 00:00:00 2001 From: djm21 Date: Mon, 10 Jun 2024 13:39:11 -0400 Subject: [PATCH 42/86] update GitHub scoring to allow for compatibility with swat --- .github/workflows/build-test-deploy.yml | 2 +- tox.ini | 4 +--- 2 files changed, 2 insertions(+), 4 deletions(-) diff --git a/.github/workflows/build-test-deploy.yml b/.github/workflows/build-test-deploy.yml index b5f2d808..d25e2d02 100644 --- a/.github/workflows/build-test-deploy.yml +++ b/.github/workflows/build-test-deploy.yml @@ -21,7 +21,7 @@ jobs: LANG: en_US.UTF-8 strategy: matrix: - python-version: ['3.8', '3.9', '3.10', '3.11', '3.12'] + python-version: ['3.8', '3.9', '3.10', '3.11'] os-version: ['ubuntu-20.04', 'windows-latest', 'macos-latest'] # Pinned Ubuntu version to 20.04 since no Python 3.6 builds available on ubuntu-latest (22.04) as of 2022-12-7. # os-version: [ubuntu-latest, windows-latest, macos-latest] diff --git a/tox.ini b/tox.ini index f9f25356..70cfed8e 100644 --- a/tox.ini +++ b/tox.ini @@ -12,7 +12,7 @@ [tox] -envlist = py{38,39,310,311,312}-tests-{clean,unit,integration} +envlist = py{38,39,310,311}-tests-{clean,unit,integration} # Allow execution even if all Python versions are not present skip_missing_interpreters = {env:TOX_SKIP_MISSING_INTERPRETERS:True} @@ -24,7 +24,6 @@ python = 3.9: py39 3.10: py310 3.11: py311 - 3.12: py312 [testenv] skip_install = @@ -35,7 +34,6 @@ basepython = py39: python3.9 py310: python3.10 py311: python3.11 - py312: python3.12 deps = clean: coverage From ece3f172afd8086b686e92a52cbd70aefb742f6a Mon Sep 17 00:00:00 2001 From: djm21 Date: Mon, 10 Jun 2024 14:47:32 -0400 Subject: [PATCH 43/86] change to conftest.py to try to fix issues with GitHub actions --- tests/conftest.py | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/tests/conftest.py b/tests/conftest.py index 768d9586..7b47ae9f 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -633,12 +633,12 @@ def pytest_runtest_makereport(item, call): # The id of the test is deteremined by its parameterization. We just want to know if the test was # for Viya 3.5 or 2020.01, 2022.09, etc. Try to check the parameter assigned to known fixtures like # `session`. If that fails, we'll just use the id generated by pytest. - if "session" in item.callspec.params: - key = item.callspec.params["session"] - elif "cas_session" in item.callspec.params: - key = item.callspec.params["cas_session"] - else: - key = item.callspec.id + # if "session" in item.callspec.params: + # key = item.callspec.params["session"] + # elif "cas_session" in item.callspec.params: + # key = item.callspec.params["cas_session"] + # else: + key = item.callspec.id # Track that this test was the last test to fail for this Viya version parent._previousfailed[key] = item From 818f0bf3ced1c6e8aab19b695c3c03e71a4901f0 Mon Sep 17 00:00:00 2001 From: djm21 Date: Mon, 8 Jul 2024 11:46:30 -0700 Subject: [PATCH 44/86] pinned scikit-learn to 1.5.0 for tox testing --- tox.ini | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tox.ini b/tox.ini index 70cfed8e..f1f9b49b 100644 --- a/tox.ini +++ b/tox.ini @@ -41,7 +41,7 @@ deps = tests: pytest-cov tests: betamax >= 0.8.1 tests: betamax_serializers >= 0.2.0 - tests: scikit-learn + tests: scikit-learn == 1.5.0 tests: pandas < 2.0.0 tests: cython # required to install pandas from source tests: swat >= 1.8 From 7c82b08043f95959316f824a951106dab3e1f6d5 Mon Sep 17 00:00:00 2001 From: djm21 Date: Mon, 8 Jul 2024 11:50:40 -0700 Subject: [PATCH 45/86] scikit-learn version less than 1.5.0 for python versions that do not support 1.5.0 --- tox.ini | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tox.ini b/tox.ini index f1f9b49b..5b4aee6a 100644 --- a/tox.ini +++ b/tox.ini @@ -41,7 +41,7 @@ deps = tests: pytest-cov tests: betamax >= 0.8.1 tests: betamax_serializers >= 0.2.0 - tests: scikit-learn == 1.5.0 + tests: scikit-learn <= 1.5.0 tests: pandas < 2.0.0 tests: cython # required to install pandas from source tests: swat >= 1.8 From c4c3cdee42361305df9f85f3fb6000eb6e2fe23f Mon Sep 17 00:00:00 2001 From: djm21 Date: Mon, 8 Jul 2024 11:56:33 -0700 Subject: [PATCH 46/86] changed scikit-learn to less than 1.5.0 in tox.ini --- tox.ini | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tox.ini b/tox.ini index 5b4aee6a..42732b1e 100644 --- a/tox.ini +++ b/tox.ini @@ -41,7 +41,7 @@ deps = tests: pytest-cov tests: betamax >= 0.8.1 tests: betamax_serializers >= 0.2.0 - tests: scikit-learn <= 1.5.0 + tests: scikit-learn < 1.5.0 tests: pandas < 2.0.0 tests: cython # required to install pandas from source tests: swat >= 1.8 From 7b92264054842ee0ba4eb63b4dada233cb079c8a Mon Sep 17 00:00:00 2001 From: djm21 Date: Mon, 8 Jul 2024 12:00:59 -0700 Subject: [PATCH 47/86] further changes to github testing --- .github/workflows/build-test-deploy.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/build-test-deploy.yml b/.github/workflows/build-test-deploy.yml index d25e2d02..828153e1 100644 --- a/.github/workflows/build-test-deploy.yml +++ b/.github/workflows/build-test-deploy.yml @@ -45,7 +45,7 @@ jobs: run: | # Setup tox & code coverage pip install --upgrade pip - pip install tox tox-gh-actions pytest pytest-cov scikit-learn + pip install tox tox-gh-actions pytest pytest-cov 'scikit-learn<=1.5.0' - name: Run Tests run: | From dbc9f99de39df929b4f33742bea247a6a6323a9a Mon Sep 17 00:00:00 2001 From: djm21 Date: Mon, 8 Jul 2024 12:21:57 -0700 Subject: [PATCH 48/86] more changes to github testing --- .github/workflows/build-test-deploy.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/build-test-deploy.yml b/.github/workflows/build-test-deploy.yml index 828153e1..87a3e55f 100644 --- a/.github/workflows/build-test-deploy.yml +++ b/.github/workflows/build-test-deploy.yml @@ -45,7 +45,7 @@ jobs: run: | # Setup tox & code coverage pip install --upgrade pip - pip install tox tox-gh-actions pytest pytest-cov 'scikit-learn<=1.5.0' + pip install tox tox-gh-actions pytest pytest-cov 'scikit-learn<=1.5.0' 'numpy<2.0.0' - name: Run Tests run: | From 32ed7e0e883d73787d175df59618e7f0b6479936 Mon Sep 17 00:00:00 2001 From: djm21 Date: Mon, 8 Jul 2024 13:27:16 -0700 Subject: [PATCH 49/86] change numpy to be less than version 2.0.0 in tox tests --- tox.ini | 1 + 1 file changed, 1 insertion(+) diff --git a/tox.ini b/tox.ini index 42732b1e..7dc2558f 100644 --- a/tox.ini +++ b/tox.ini @@ -43,6 +43,7 @@ deps = tests: betamax_serializers >= 0.2.0 tests: scikit-learn < 1.5.0 tests: pandas < 2.0.0 + tests: numpy < 2.0.0 tests: cython # required to install pandas from source tests: swat >= 1.8 tests: kerberos ; platform_system != "Windows" and platform_system != "Darwin" From 78ac0fd6dd24e6fe9afb3c8d304817716d379aea Mon Sep 17 00:00:00 2001 From: djm21 Date: Mon, 8 Jul 2024 13:36:29 -0700 Subject: [PATCH 50/86] updated unit tests to align with code changes --- tests/unit/test_write_json_files.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/unit/test_write_json_files.py b/tests/unit/test_write_json_files.py index 2dc7e8cf..dc9e18d3 100644 --- a/tests/unit/test_write_json_files.py +++ b/tests/unit/test_write_json_files.py @@ -262,7 +262,7 @@ def test_write_model_properties_json(): target_values=None, ) assert "ModelProperties.json" in prop_dict - assert json.loads(prop_dict["ModelProperties.json"])["function"] == "Prediction" + assert json.loads(prop_dict["ModelProperties.json"])["function"] == "prediction" assert json.loads(prop_dict["ModelProperties.json"])["targetLevel"] == "Interval" assert json.loads(prop_dict["ModelProperties.json"])["targetEvent"] == "" assert json.loads(prop_dict["ModelProperties.json"])["eventProbVar"] == "" @@ -270,7 +270,7 @@ def test_write_model_properties_json(): prop_dict = jf.write_model_properties_json( model_name="Test_Model", target_variable="BAD", target_values=[1, 0] ) - assert json.loads(prop_dict["ModelProperties.json"])["function"] == "Classification" + assert json.loads(prop_dict["ModelProperties.json"])["function"] == "classification" assert json.loads(prop_dict["ModelProperties.json"])["targetLevel"] == "Binary" assert json.loads(prop_dict["ModelProperties.json"])["targetEvent"] == "1" assert json.loads(prop_dict["ModelProperties.json"])["eventProbVar"] == "P_1" From a081f4959d88410fd8bdd7d1b64801f3dd904353 Mon Sep 17 00:00:00 2001 From: djm21 Date: Mon, 8 Jul 2024 14:04:51 -0700 Subject: [PATCH 51/86] prep for release --- CHANGELOG.md | 10 ++++++++++ src/sasctl/__init__.py | 2 +- 2 files changed, 11 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index c038d6a8..98b28fab 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -5,6 +5,16 @@ Unreleased - Add `model_info` class to better capture model information. - Test `/examples` Jupyter notebooks within normal test suite. +v1.10.4 (2024-07-08) +---------- +**Improvements** +- Added example Jupyter notebook for OpenAI models. + +**Buxfixes** +- Dropped support for Python 3.6 and Python 3.7, as those are no longer officially supported versions. +- Added `dmcas_misc.json` template file for model card generation. +- Updated generation of `ModelProperties.json` to allow for model card generation immediately upon upload. + v1.10.3 (2024-04-12) ---------- **Bugfixes** diff --git a/src/sasctl/__init__.py b/src/sasctl/__init__.py index 3929f3a9..e0e1d917 100644 --- a/src/sasctl/__init__.py +++ b/src/sasctl/__init__.py @@ -4,7 +4,7 @@ # Copyright © 2019, SAS Institute Inc., Cary, NC, USA. All Rights Reserved. # SPDX-License-Identifier: Apache-2.0 -__version__ = "1.10.3" +__version__ = "1.10.4" __author__ = "SAS" __credits__ = [ "Yi Jian Ching", From c70553983712541a8bb8ad9a1adbe9f8f90fdd42 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Thu, 18 Jul 2024 15:58:08 -0400 Subject: [PATCH 52/86] Updating files for testing --- src/sasctl/_services/score_execution.py | 26 +++++++++++--------- tests/unit/test_score_definitions.py | 32 +++++++++++++++++++++++++ tests/unit/test_score_execution.py | 24 +++++++++++++++++-- 3 files changed, 69 insertions(+), 13 deletions(-) diff --git a/src/sasctl/_services/score_execution.py b/src/sasctl/_services/score_execution.py index 2b381ffe..74266e93 100644 --- a/src/sasctl/_services/score_execution.py +++ b/src/sasctl/_services/score_execution.py @@ -70,18 +70,22 @@ def create_score_execution( if not output_table_name: output_table_name = f"{model_name}_{score_definition_id}" - # Deleting any score executions that are already executing the same score definition - try: - score_execution = cls.get( - f"/executions?filter=eq(scoreExecutionRequest.scoreDefinitionId,%27{score_definition_id}%27)" + # Getting all score executions that are using the inputted score_definition_id + + score_execution = cls.list_executions(filter=f"eq(scoreDefinitionId, '{score_definition_id}')") + + if score_execution.status_code >= 400: + raise HTTPError( + { + f"Something went wrong in the GET statement. See error: {score_execution.json()}" + } ) - execution_count = score_execution.get("count") # Exception catch location - if execution_count == 1: - execution_id = score_execution.get("items", [0], ["id"]) - deleted_score_execution = cls.delete_execution(execution_id) - print(deleted_score_execution) - except KeyError: - print("There may not be a score execution already running.") + + # Checking the count of the execution list to see if there are any score executions for this score_definition_id already running + execution_count = score_execution.get("count") # Exception catch location + if execution_count == 1: + execution_id = score_execution.get("items", [0], ["id"]) + deleted_execution = cls.delete_execution(execution_id) headers_score_exec = {"Content-Type": "application/json"} diff --git a/tests/unit/test_score_definitions.py b/tests/unit/test_score_definitions.py index 9bc7ceaf..e98ed9a1 100644 --- a/tests/unit/test_score_definitions.py +++ b/tests/unit/test_score_definitions.py @@ -36,6 +36,38 @@ def test_create_score_definition(): """ with mock.patch("sasctl.core.Session._get_authorization_token"): current_session("example.com", "username", "password") + + TARGET = { + "name": MODEL_NAME, + "projectId": PROJECT_ID, + "modeler": USER, + "description": "model description", + "function": "Classification", + "algorithm": "Dummy Algorithm", + "tool": "pytest", + "champion": True, + "role": "champion", + "immutable": True, + "retrainable": True, + "scoreCodeType": None, + "targetVariable": None, + "trainTable": None, + "classificationEventProbabilityVariableName": None, + "classificationTargetEventValue": None, + "location": None, + "properties": [ + {"name": "custom1", "value": 123, "type": "numeric"}, + {"name": "custom2", "value": "somevalue", "type": "string"}, + # {'name': 'customDate', 'value': 1672462800000, 'type': 'date'}, + {"name": "customDateTime", "value": 1672481272000, "type": "dateTime"}, + ], + "inputVariables": [], + "outputVariables": [], + "version": 2, + } + + # Passed params should be set correctly + target = copy.deepcopy(TARGET) with mock.patch( "sasctl._services.model_repository.ModelRepository.get_model" diff --git a/tests/unit/test_score_execution.py b/tests/unit/test_score_execution.py index b440a8e7..f14364a4 100644 --- a/tests/unit/test_score_execution.py +++ b/tests/unit/test_score_execution.py @@ -22,6 +22,7 @@ from sasctl import current_session from sasctl.core import RestObj, VersionInfo from sasctl._services.score_definitions import ScoreDefinitions as sd +from sasctl._services.score_execution import ScoreExecution as se def test_create_score_execution(): @@ -32,9 +33,12 @@ def test_create_score_execution(): -no - Valid execution id? - -Valid count key? + -Valid count key? -> treated like input mapping -> no because i think it's required + - output table -> treat like input mapping but within the create_score_execution step (do I for library and server in score definition thought?) """ + with mock.patch("sasctl.core.Session._get_authorization_token"): + current_session("example.com", "username", "password") with mock.patch( "sasctl._services.score_definitions.ScoreDefinitions.get_definition" @@ -45,5 +49,21 @@ def test_create_score_execution(): with mock.patch( "sasctl._services.score_execution.ScoreExecution.delete_execution" ) as delete_execution: - pytest.skip() + with mock.patch( + "sasctl._services.score_execution.ScoreExecution.post" + ) as post: + get_definition.return_value.status_code = 404 + with pytest.raises(HTTPError): + se.create_score_execution( + score_definition_id="12345", + ) + get_definition.return_value.status_code = 200 + get_execution.return_value.status_code = 400 #we might need a separate try except here to show that 404 statement is weird and should exit the program + with pytest.raises(HTTPError): + se.create_score_execution( + score_definition_id="12345", + ) + #stdout or pytest.raises but without ending program? + + #pytest.skip() # raise HTTP error? From af938c5f13d604427f31e33de87e1db760a857f7 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Thu, 18 Jul 2024 16:34:25 -0400 Subject: [PATCH 53/86] Adding proper return value for successfu; get_definition call --- tests/unit/test_score_execution.py | 31 +++++++++++++++++++++++++----- 1 file changed, 26 insertions(+), 5 deletions(-) diff --git a/tests/unit/test_score_execution.py b/tests/unit/test_score_execution.py index f14364a4..831927d4 100644 --- a/tests/unit/test_score_execution.py +++ b/tests/unit/test_score_execution.py @@ -34,7 +34,7 @@ def test_create_score_execution(): - Valid execution id? -Valid count key? -> treated like input mapping -> no because i think it's required - - output table -> treat like input mapping but within the create_score_execution step (do I for library and server in score definition thought?) + - output table -> treat like input mapping but within the create_score_execution step (do I for library and server in score definition thought? but I think you need a target step here too) """ with mock.patch("sasctl.core.Session._get_authorization_token"): @@ -44,8 +44,8 @@ def test_create_score_execution(): "sasctl._services.score_definitions.ScoreDefinitions.get_definition" ) as get_definition: with mock.patch( - "sasctl._services.score_execution.ScoreExecution.get_execution" - ) as get_execution: + "sasctl._services.score_execution.ScoreExecution.list_executions" + ) as list_executions: with mock.patch( "sasctl._services.score_execution.ScoreExecution.delete_execution" ) as delete_execution: @@ -58,12 +58,33 @@ def test_create_score_execution(): score_definition_id="12345", ) get_definition.return_value.status_code = 200 - get_execution.return_value.status_code = 400 #we might need a separate try except here to show that 404 statement is weird and should exit the program + get_definition.return_value.json.return_value = { + "inputData": { + "libraryName": "cas-shared-default", + "tableName": "" + }, + "name": "publish_automated_1720400011_2024-07-08T00:54:41.859Z", + "objectDescriptor": { + "name": "test_model", + "type": "sas.publish.example", + "uri": "/modelPublish/models/example" + } + } + list_executions.return_value.status_code = 400 #we might need a separate try except here to show that 404 statement is weird and should exit the program with pytest.raises(HTTPError): se.create_score_execution( score_definition_id="12345", ) - #stdout or pytest.raises but without ending program? + + list_executions.return_value.status_code = 200 + list_executions.return_value.json.return_value = { + "count": 1 + } + delete_execution.return_value.status_code = 2 + + #pytest.skip() # raise HTTP error? +#notes -> how to test count because it should only delete if count == 1 so how do I test that if/else +#notes -> output table case, again TARGET? \ No newline at end of file From cb775bf51a114cde6de05452990b81cf167f4e9c Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Fri, 19 Jul 2024 10:36:24 -0400 Subject: [PATCH 54/86] Raised http error for failed delete API call --- src/sasctl/_services/score_execution.py | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) diff --git a/src/sasctl/_services/score_execution.py b/src/sasctl/_services/score_execution.py index 74266e93..a24d1e85 100644 --- a/src/sasctl/_services/score_execution.py +++ b/src/sasctl/_services/score_execution.py @@ -77,7 +77,7 @@ def create_score_execution( if score_execution.status_code >= 400: raise HTTPError( { - f"Something went wrong in the GET statement. See error: {score_execution.json()}" + f"Something went wrong in the LIST_EXECUTIONS statement. See error: {score_execution.json()}" } ) @@ -85,7 +85,13 @@ def create_score_execution( execution_count = score_execution.get("count") # Exception catch location if execution_count == 1: execution_id = score_execution.get("items", [0], ["id"]) - deleted_execution = cls.delete_execution(execution_id) + deleted_execution = cls.delete_execution(execution_id) + if deleted_execution.status_code >= 400: + raise HTTPError( + { + f"Something went wrong in the DELETE statement. See error: {score_execution.json()}" + } + ) headers_score_exec = {"Content-Type": "application/json"} From d026241f910f1cbf47b4a6acc06905c55d1abfc2 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Fri, 19 Jul 2024 12:06:54 -0400 Subject: [PATCH 55/86] tests: adjustment to score_execution tests --- src/sasctl/_services/score_execution.py | 2 +- tests/unit/test_score_execution.py | 28 ++++++++++++++++++------- 2 files changed, 21 insertions(+), 9 deletions(-) diff --git a/src/sasctl/_services/score_execution.py b/src/sasctl/_services/score_execution.py index a24d1e85..49f711c1 100644 --- a/src/sasctl/_services/score_execution.py +++ b/src/sasctl/_services/score_execution.py @@ -89,7 +89,7 @@ def create_score_execution( if deleted_execution.status_code >= 400: raise HTTPError( { - f"Something went wrong in the DELETE statement. See error: {score_execution.json()}" + f"Something went wrong in the DELETE statement. See error: {deleted_execution.json()}" } ) diff --git a/tests/unit/test_score_execution.py b/tests/unit/test_score_execution.py index 831927d4..5edcf7d7 100644 --- a/tests/unit/test_score_execution.py +++ b/tests/unit/test_score_execution.py @@ -12,6 +12,7 @@ import unittest from pathlib import Path from unittest import mock +from unittest.mock import MagicMock import numpy as np import pandas as pd @@ -55,7 +56,7 @@ def test_create_score_execution(): get_definition.return_value.status_code = 404 with pytest.raises(HTTPError): se.create_score_execution( - score_definition_id="12345", + score_definition_id="12345" ) get_definition.return_value.status_code = 200 get_definition.return_value.json.return_value = { @@ -63,7 +64,7 @@ def test_create_score_execution(): "libraryName": "cas-shared-default", "tableName": "" }, - "name": "publish_automated_1720400011_2024-07-08T00:54:41.859Z", + "name": "score_def_name", "objectDescriptor": { "name": "test_model", "type": "sas.publish.example", @@ -73,16 +74,27 @@ def test_create_score_execution(): list_executions.return_value.status_code = 400 #we might need a separate try except here to show that 404 statement is weird and should exit the program with pytest.raises(HTTPError): se.create_score_execution( - score_definition_id="12345", + score_definition_id="12345" ) - list_executions.return_value.status_code = 200 - list_executions.return_value.json.return_value = { - "count": 1 - } - delete_execution.return_value.status_code = 2 + mock_response = MagicMock() + mock_response.status_code = 200 + mock_response.json.return_value = {"count": 1} + list_executions.return_value = mock_response + delete_execution.return_value.status_code = 404 + with pytest.raises(HTTPError): + se.create_score_execution( + score_definition_id="12345" + ) + # delete_execution.return_value.status_code = 200 + # response = se.create_score_execution( + # score_definition_id="12345" + # ) + # assert response + +test_create_score_execution() #pytest.skip() # raise HTTP error? From 000d1231ae9774eee65f1f4920edaf7cbbc8564d Mon Sep 17 00:00:00 2001 From: Scott-Lindauer_sasinst Date: Fri, 19 Jul 2024 12:24:53 -0400 Subject: [PATCH 56/86] reformat: adjust score_execution.py to use same style of internal service call --- src/sasctl/_services/score_execution.py | 5 ++- tests/unit/test_score_executions.py | 49 ------------------------- 2 files changed, 3 insertions(+), 51 deletions(-) delete mode 100644 tests/unit/test_score_executions.py diff --git a/src/sasctl/_services/score_execution.py b/src/sasctl/_services/score_execution.py index 49f711c1..99f5e5e2 100644 --- a/src/sasctl/_services/score_execution.py +++ b/src/sasctl/_services/score_execution.py @@ -2,7 +2,7 @@ from requests import HTTPError -from .score_definitions import ScoreDefinitions as sd +from .score_definitions import ScoreDefinitions from .service import Service @@ -18,6 +18,7 @@ class ScoreExecution(Service): """ _SERVICE_ROOT = "/scoreExecution" + _score_definitions = ScoreDefinitions() ( list_executions, @@ -57,7 +58,7 @@ def create_score_execution( """ # Gets information about the scoring object from the score definition and raises an exception if the score definition does not exist - score_definition = sd.get_definition(score_definition_id) + score_definition = cls._score_definitions.get_definition(score_definition_id) if score_definition.status_code >= 400: raise HTTPError(score_definition.json()) score_exec_name = score_definition.get("name") diff --git a/tests/unit/test_score_executions.py b/tests/unit/test_score_executions.py deleted file mode 100644 index 7dcfcc09..00000000 --- a/tests/unit/test_score_executions.py +++ /dev/null @@ -1,49 +0,0 @@ -#!/usr/bin/env python -# encoding: utf-8 -# -# Copyright © 2024, SAS Institute Inc., Cary, NC, USA. All Rights Reserved. -# SPDX-License-Identifier: Apache-2.0 - -import json -import os -import pickle -import random -import tempfile -import unittest -from pathlib import Path -from unittest import mock - -import numpy as np -import pandas as pd -import pytest -from requests import HTTPError - -import sasctl.pzmm as pzmm -from sasctl import current_session -from sasctl.core import RestObj, VersionInfo -from sasctl._services.score_definitions import ScoreDefinitions as sd - - -def test_create_score_execution(): - """ - Test Cases: - - Valid score definition id? - -yes - -no - - Valid execution id? - - -Valid count key? - - """ - - with mock.patch( - "sasctl._services.score_definitions.ScoreDefinitions.get_definition" - ) as get_definition: - with mock.patch( - "sasctl._services.score_execution.ScoreExecution.get_execution" - ) as get_execution: - with mock.patch( - "sasctl._services.score_execution.ScoreExecution.delete_execution" - ) as delete_execution: - exit() - # raise HTTP error? From f0984c4542ba4b146111344300d9d2539ed6dac6 Mon Sep 17 00:00:00 2001 From: Scott-Lindauer_sasinst Date: Fri, 19 Jul 2024 12:25:11 -0400 Subject: [PATCH 57/86] tests: fix test_score_execution json reading error --- tests/unit/test_score_execution.py | 10 +++------- 1 file changed, 3 insertions(+), 7 deletions(-) diff --git a/tests/unit/test_score_execution.py b/tests/unit/test_score_execution.py index 5edcf7d7..44c98f2f 100644 --- a/tests/unit/test_score_execution.py +++ b/tests/unit/test_score_execution.py @@ -76,11 +76,9 @@ def test_create_score_execution(): se.create_score_execution( score_definition_id="12345" ) - - mock_response = MagicMock() - mock_response.status_code = 200 - mock_response.json.return_value = {"count": 1} - list_executions.return_value = mock_response + + list_executions.status_code = 200 + list_executions.return_value.json.return_value = {"count": 1} delete_execution.return_value.status_code = 404 with pytest.raises(HTTPError): @@ -93,8 +91,6 @@ def test_create_score_execution(): # score_definition_id="12345" # ) # assert response - -test_create_score_execution() #pytest.skip() # raise HTTP error? From ae4197785f48c7db180cbf839b8557cbadea1b45 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Tue, 23 Jul 2024 11:08:35 -0400 Subject: [PATCH 58/86] Adding frameworks for the rest of score_execution unit tests --- src/sasctl/_services/score_execution.py | 7 +----- tests/unit/test_score_execution.py | 32 ++++++++++++++++++------- 2 files changed, 25 insertions(+), 14 deletions(-) diff --git a/src/sasctl/_services/score_execution.py b/src/sasctl/_services/score_execution.py index 99f5e5e2..fa118a04 100644 --- a/src/sasctl/_services/score_execution.py +++ b/src/sasctl/_services/score_execution.py @@ -74,12 +74,9 @@ def create_score_execution( # Getting all score executions that are using the inputted score_definition_id score_execution = cls.list_executions(filter=f"eq(scoreDefinitionId, '{score_definition_id}')") - if score_execution.status_code >= 400: raise HTTPError( - { - f"Something went wrong in the LIST_EXECUTIONS statement. See error: {score_execution.json()}" - } + f"Something went wrong in the LIST_EXECUTIONS statement. See error: {score_execution.json()}" ) # Checking the count of the execution list to see if there are any score executions for this score_definition_id already running @@ -89,9 +86,7 @@ def create_score_execution( deleted_execution = cls.delete_execution(execution_id) if deleted_execution.status_code >= 400: raise HTTPError( - { f"Something went wrong in the DELETE statement. See error: {deleted_execution.json()}" - } ) headers_score_exec = {"Content-Type": "application/json"} diff --git a/tests/unit/test_score_execution.py b/tests/unit/test_score_execution.py index 44c98f2f..b6f2062d 100644 --- a/tests/unit/test_score_execution.py +++ b/tests/unit/test_score_execution.py @@ -71,26 +71,42 @@ def test_create_score_execution(): "uri": "/modelPublish/models/example" } } - list_executions.return_value.status_code = 400 #we might need a separate try except here to show that 404 statement is weird and should exit the program + list_executions.return_value.status_code = 400 #test case worked with .return_value.status_code but caused an HTTP error that said error with list_Executions with pytest.raises(HTTPError): se.create_score_execution( score_definition_id="12345" ) - list_executions.status_code = 200 + list_executions.status_code = 200 #why does this not have a return value and how is this related to different score_Defintion instantiation in score_execution list_executions.return_value.json.return_value = {"count": 1} - delete_execution.return_value.status_code = 404 with pytest.raises(HTTPError): se.create_score_execution( score_definition_id="12345" ) + #Test cases that don't work or I haven't tested + delete_execution.return_value.status_code = 200 + response = se.create_score_execution( + score_definition_id="3456" + ) + assert response + + list_executions.status_code = 200 #shouldn't this work with 200 response and not give me a type rror >= since it's not running 400 statement + + list_executions.return_value.json.return_value = {"count": 0} + response = se.create_score_execution( + score_definition_id="12345" + ) + assert response + + list_executions.status_code = 200 + list_executions.return_value.json.return_value = {"count": 0} + response = se.create_score_execution( + score_definition_id="12345", + output_table_name = "test_output_table" + ) + assert response #target needed here to test with and without specified output_table_name - # delete_execution.return_value.status_code = 200 - # response = se.create_score_execution( - # score_definition_id="12345" - # ) - # assert response #pytest.skip() # raise HTTP error? From 2a3607f438e38a52ce4e8ec1fed914000791368a Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Fri, 26 Jul 2024 15:46:10 -0400 Subject: [PATCH 59/86] Pushing with all successful test cases --- src/sasctl/_services/score_execution.py | 34 +++---- tests/unit/test_score_definitions.py | 57 +++++------- tests/unit/test_score_execution.py | 116 +++++++++++++++--------- 3 files changed, 115 insertions(+), 92 deletions(-) diff --git a/src/sasctl/_services/score_execution.py b/src/sasctl/_services/score_execution.py index fa118a04..4816b0af 100644 --- a/src/sasctl/_services/score_execution.py +++ b/src/sasctl/_services/score_execution.py @@ -62,44 +62,46 @@ def create_score_execution( if score_definition.status_code >= 400: raise HTTPError(score_definition.json()) score_exec_name = score_definition.get("name") - model_uri = score_definition.get("objectDescriptor", ["uri"]) - model_name = score_definition.get("objectDescriptor", ["name"]) - model_input_library = score_definition.get("inputData", ["libraryName"]) - model_table_name = score_definition.get("inputData", ["tableName"]) + model_uri = score_definition.get("objectDescriptor", "uri") + model_name = score_definition.get("objectDescriptor", "name") + model_input_library = score_definition.get("inputData", "libraryName") + model_table_name = score_definition.get("inputData", "tableName") # Defining a default output table name if none is provided if not output_table_name: output_table_name = f"{model_name}_{score_definition_id}" # Getting all score executions that are using the inputted score_definition_id - - score_execution = cls.list_executions(filter=f"eq(scoreDefinitionId, '{score_definition_id}')") + + score_execution = cls.list_executions( + filter=f"eq(scoreDefinitionId, '{score_definition_id}')" + ) if score_execution.status_code >= 400: raise HTTPError( - f"Something went wrong in the LIST_EXECUTIONS statement. See error: {score_execution.json()}" + f"Something went wrong in the LIST_EXECUTIONS statement. See error: {score_execution.json()}" ) - + # Checking the count of the execution list to see if there are any score executions for this score_definition_id already running execution_count = score_execution.get("count") # Exception catch location if execution_count == 1: - execution_id = score_execution.get("items", [0], ["id"]) + execution_id = score_execution.get("items", 0, "id") deleted_execution = cls.delete_execution(execution_id) if deleted_execution.status_code >= 400: raise HTTPError( - f"Something went wrong in the DELETE statement. See error: {deleted_execution.json()}" - ) + f"Something went wrong in the DELETE statement. See error: {deleted_execution.json()}" + ) headers_score_exec = {"Content-Type": "application/json"} create_score_exec = { - "name": score_exec_name, + "name": f"{score_exec_name}", "description": description, "hints": { - "objectURI": model_uri, - "inputTableName": model_table_name, - "inputLibraryName": model_input_library, + "objectURI": f"{model_uri}", + "inputTableName": f"{model_table_name}", + "inputLibraryName": f"{model_input_library}", }, - "scoreDefinitionId": score_definition_id, + "scoreDefinitionId": f"{score_definition_id}", "outputTable": { "tableName": output_table_name, "libraryName": output_library_name, diff --git a/tests/unit/test_score_definitions.py b/tests/unit/test_score_definitions.py index e98ed9a1..947dc414 100644 --- a/tests/unit/test_score_definitions.py +++ b/tests/unit/test_score_definitions.py @@ -10,6 +10,7 @@ import random import tempfile import unittest +import copy from pathlib import Path from unittest import mock @@ -31,44 +32,25 @@ def test_create_score_definition(): - Invalid model id - Valid table name without input mapping - Invalid table name with invalid file - - Invalid table name with valid file and without input mapping + - Invalid table name with valid file + - Invalid table name without table file argument """ + # Mocking a session to allow the post call to go through with mock.patch("sasctl.core.Session._get_authorization_token"): current_session("example.com", "username", "password") - - TARGET = { - "name": MODEL_NAME, - "projectId": PROJECT_ID, - "modeler": USER, - "description": "model description", - "function": "Classification", - "algorithm": "Dummy Algorithm", - "tool": "pytest", - "champion": True, - "role": "champion", - "immutable": True, - "retrainable": True, - "scoreCodeType": None, - "targetVariable": None, - "trainTable": None, - "classificationEventProbabilityVariableName": None, - "classificationTargetEventValue": None, - "location": None, - "properties": [ - {"name": "custom1", "value": 123, "type": "numeric"}, - {"name": "custom2", "value": "somevalue", "type": "string"}, - # {'name': 'customDate', 'value': 1672462800000, 'type': 'date'}, - {"name": "customDateTime", "value": 1672481272000, "type": "dateTime"}, - ], - "inputVariables": [], - "outputVariables": [], - "version": 2, - } - # Passed params should be set correctly - target = copy.deepcopy(TARGET) + # TARGET = { + # "mappings": [ + # {"mappingValue": "first", "mappingType": "datasource", "variableName": "first"}, + # {"mappingValue": "second", "mappingType": "datasource", "variableName": "second"}, + # {"mappingValue": "third", "mappingType": "datasource", "variableName": "third"} + # ] + # } + # target = copy.deepcopy(TARGET) + + # Mocking the REST API calls and functions with mock.patch( "sasctl._services.model_repository.ModelRepository.get_model" ) as get_model: @@ -81,6 +63,7 @@ def test_create_score_definition(): with mock.patch( "sasctl._services.score_definitions.ScoreDefinitions.post" ) as post: + # Invalid model id test case get_model.return_value.status_code = 404 with pytest.raises(HTTPError): sd.create_score_definition( @@ -89,6 +72,7 @@ def test_create_score_definition(): table_name="test_table", ) + # Valid model id but invalid table name with no table_file argument test case get_model.return_value.status_code = 200 get_model.return_value.json.return_value = { "id": "12345", @@ -103,6 +87,8 @@ def test_create_score_definition(): model_id="12345", table_name="test_table", ) + + # Invalid table name with a table_file argument that doesn't work test case get_table.return_value.status_code = 404 upload_file.return_value = None get_table.return_value.status_code = 404 @@ -114,6 +100,7 @@ def test_create_score_definition(): table_file="test_path", ) + # Valid table_file argument that successfully creates a table test case get_table.return_value.status_code = 404 upload_file.return_value = RestObj get_table.return_value.status_code = 200 @@ -128,6 +115,7 @@ def test_create_score_definition(): ) assert response + # Valid table_name argument test case get_table.return_value.status_code = 200 get_table.return_value.json.return_value = { "tableName": "test_table" @@ -140,6 +128,7 @@ def test_create_score_definition(): ) assert response + # Checking response with inputVariables in model elements get_model.return_value.status_code = 200 get_model.return_value.json.return_value = { "id": "12345", @@ -163,3 +152,7 @@ def test_create_score_definition(): ) assert response assert post.call_count == 3 + + # data = post.call_args + # json_data = json.loads(data.kwargs["data"]) + # assert target["mappings"] == json_data["mappings"] diff --git a/tests/unit/test_score_execution.py b/tests/unit/test_score_execution.py index b6f2062d..81a758c7 100644 --- a/tests/unit/test_score_execution.py +++ b/tests/unit/test_score_execution.py @@ -10,6 +10,7 @@ import random import tempfile import unittest +import copy from pathlib import Path from unittest import mock from unittest.mock import MagicMock @@ -26,21 +27,40 @@ from sasctl._services.score_execution import ScoreExecution as se +# Creating a CustomMock for list_executions to avoid a TypeError when comparing status code from mock with >= 400 in score_execution +class CustomMock: + def __init__(self, status_code, json_info): + self.status_code = status_code + self.json_info = json_info + + def get(self, key1, key2=None, key3=None): + if key2 is None and key3 is None: + return self.json_info[key1] + else: + return self.json_info[key1][key2][key3] + + def test_create_score_execution(): """ Test Cases: - - Valid score definition id? - -yes - -no - - Valid execution id? - - -Valid count key? -> treated like input mapping -> no because i think it's required - - output table -> treat like input mapping but within the create_score_execution step (do I for library and server in score definition thought? but I think you need a target step here too) + - Valid score definition id and invalid list_executions argument + - Invalid score definition id + - Valid list_executions argument with execution already running but invalid delete_execution argument + - Valid list_executions argument with execution already running but valid delete_execution argument + - Valid list_executions argument without execution already running + - With output table specified within create_score_execution arguments """ + + # Mocking a session to allow the post call to go through with mock.patch("sasctl.core.Session._get_authorization_token"): - current_session("example.com", "username", "password") + current_session("example.com", "username", "password") + # Mocking what a successful score execution post would be if the user specified an output table + TARGET = {"outputTable": {"tableName": "example_table"}} + # Creating a target to compare post call responses to + target = copy.deepcopy(TARGET) + # Mocking the REST API calls and functions with mock.patch( "sasctl._services.score_definitions.ScoreDefinitions.get_definition" ) as get_definition: @@ -51,64 +71,72 @@ def test_create_score_execution(): "sasctl._services.score_execution.ScoreExecution.delete_execution" ) as delete_execution: with mock.patch( - "sasctl._services.score_execution.ScoreExecution.post" + "sasctl._services.score_execution.ScoreExecution.post" ) as post: + # Invalid score definition id test case get_definition.return_value.status_code = 404 with pytest.raises(HTTPError): - se.create_score_execution( - score_definition_id="12345" - ) + se.create_score_execution(score_definition_id="12345") + + # Valid score definition id and invalid list_executions argument test case get_definition.return_value.status_code = 200 get_definition.return_value.json.return_value = { "inputData": { "libraryName": "cas-shared-default", - "tableName": "" + "tableName": "test_table", }, "name": "score_def_name", "objectDescriptor": { "name": "test_model", "type": "sas.publish.example", - "uri": "/modelPublish/models/example" - } + "uri": "/modelPublish/models/example", + }, } - list_executions.return_value.status_code = 400 #test case worked with .return_value.status_code but caused an HTTP error that said error with list_Executions + list_executions.return_value.status_code = 404 with pytest.raises(HTTPError): - se.create_score_execution( - score_definition_id="12345" - ) + se.create_score_execution(score_definition_id="12345") - list_executions.status_code = 200 #why does this not have a return value and how is this related to different score_Defintion instantiation in score_execution - list_executions.return_value.json.return_value = {"count": 1} + # Valid list_executions argument with execution already running but invalid delete_execution argument test case + list_mock_execution = CustomMock( + status_code=200, + json_info={"count": 1, "items": [{"id": "1234"}]}, + ) + list_executions.return_value = list_mock_execution delete_execution.return_value.status_code = 404 with pytest.raises(HTTPError): - se.create_score_execution( - score_definition_id="12345" - ) - #Test cases that don't work or I haven't tested - delete_execution.return_value.status_code = 200 - response = se.create_score_execution( - score_definition_id="3456" + se.create_score_execution(score_definition_id="12345") + + # Valid list_executions argument with execution already running but valid delete_execution argument test case + list_executions.return_value = list_mock_execution + delete_execution.return_value.status_code = 200 + response = se.create_score_execution(score_definition_id="3456") + assert response + + # Valid list_executions argument without execution already running test case + list_mock_execution_diff_count = CustomMock( + status_code=200, + json_info={"count": 0, "items": [{"id": "1234"}]}, ) + list_executions.return_value = list_mock_execution_diff_count + response = se.create_score_execution(score_definition_id="12345") assert response - list_executions.status_code = 200 #shouldn't this work with 200 response and not give me a type rror >= since it's not running 400 statement - - list_executions.return_value.json.return_value = {"count": 0} + # Checking whether the output table name remained the default empty string or the default changed as writted in score_execution + data = post.call_args + json_data = json.loads(data.kwargs["data"]) + assert json_data["outputTable"]["tableName"] != "" + + # With output table specified within create_score_execution arguments test case response = se.create_score_execution( - score_definition_id="12345" + score_definition_id="12345", output_table_name="example_table" ) assert response + assert post.call_count == 3 - list_executions.status_code = 200 - list_executions.return_value.json.return_value = {"count": 0} - response = se.create_score_execution( - score_definition_id="12345", - output_table_name = "test_output_table" + # Checking whether specified output table name or the default output table name is in the response + data = post.call_args + json_data = json.loads(data.kwargs["data"]) + assert ( + target["outputTable"]["tableName"] + == json_data["outputTable"]["tableName"] ) - assert response #target needed here to test with and without specified output_table_name - - - #pytest.skip() - # raise HTTP error? -#notes -> how to test count because it should only delete if count == 1 so how do I test that if/else -#notes -> output table case, again TARGET? \ No newline at end of file From 410b9cc3437742397fef849be3ee21eaf69a2b39 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Tue, 30 Jul 2024 16:00:40 -0400 Subject: [PATCH 60/86] Fixed mapping issue in score_definitions --- src/sasctl/_services/score_definitions.py | 22 +++++++-- tests/unit/test_score_definitions.py | 55 ++++++++++++----------- 2 files changed, 48 insertions(+), 29 deletions(-) diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index 87dc999b..947c9eff 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -6,10 +6,15 @@ import json from typing import Union -from ..core import current_session, delete, get, sasctl_command -from .cas_management import CASManagement -from .model_repository import ModelRepository -from .service import Service +# from ..core import current_session, delete, get, sasctl_command +from sasctl.core import current_session, delete, get, sasctl_command +from sasctl._services.cas_management import CASManagement +from sasctl._services.model_repository import ModelRepository +from sasctl._services.service import Service + +# from .cas_management import CASManagement +# from .model_repository import ModelRepository +# from .service import Service class ScoreDefinitions(Service): @@ -96,6 +101,7 @@ def create_score_definition( "variableName": input_item["name"], } inputMapping.append(var) + except: print("This model does not have the optional 'inputVariables' parameter.") @@ -149,3 +155,11 @@ def create_score_definition( "/definitions", data=json.dumps(save_score_def), headers=headers_score_def ) # The response information of the score definition can be seen as a JSON as well as a RestOBJ + + +score_def = ScoreDefinitions() +print( + score_def.create_score_definition( + "test_name", "69ed3f2f-b4c2-43e7-9f9c-24d009e20e16", "HMEQPERF_1_Q1" + ) +) diff --git a/tests/unit/test_score_definitions.py b/tests/unit/test_score_definitions.py index 947dc414..6347b5ff 100644 --- a/tests/unit/test_score_definitions.py +++ b/tests/unit/test_score_definitions.py @@ -25,6 +25,18 @@ from sasctl._services.score_definitions import ScoreDefinitions as sd +class CustomMock: + def __init__(self, status_code, json_info): + self.status_code = status_code + self.json_info = json_info + + def get(self, key1, key2=None, key3=None): + if key2 is None and key3 is None: + return self.json_info[key1] + else: + return self.json_info[key1][key2][key3] + + def test_create_score_definition(): """ Test Cases: @@ -40,16 +52,6 @@ def test_create_score_definition(): with mock.patch("sasctl.core.Session._get_authorization_token"): current_session("example.com", "username", "password") - # TARGET = { - # "mappings": [ - # {"mappingValue": "first", "mappingType": "datasource", "variableName": "first"}, - # {"mappingValue": "second", "mappingType": "datasource", "variableName": "second"}, - # {"mappingValue": "third", "mappingType": "datasource", "variableName": "third"} - # ] - # } - - # target = copy.deepcopy(TARGET) - # Mocking the REST API calls and functions with mock.patch( "sasctl._services.model_repository.ModelRepository.get_model" @@ -129,18 +131,21 @@ def test_create_score_definition(): assert response # Checking response with inputVariables in model elements - get_model.return_value.status_code = 200 - get_model.return_value.json.return_value = { - "id": "12345", - "projectId": "54321", - "projectVersionId": "67890", - "name": "test_model", - "inputVariables": [ - {"name": "first"}, - {"name": "second"}, - {"name": "third"}, - ], - } + model_mock_execution = CustomMock( + status_code=200, + json_info={ + "id": "12345", + "projectId": "54321", + "projectVersionId": "67890", + "name": "test_model", + "inputVariables": [ + {"name": "first"}, + {"name": "second"}, + {"name": "third"}, + ], + }, + ) + get_model.return_value = model_mock_execution get_table.return_value.status_code = 200 get_table.return_value.json.return_value = { "tableName": "test_table" @@ -153,6 +158,6 @@ def test_create_score_definition(): assert response assert post.call_count == 3 - # data = post.call_args - # json_data = json.loads(data.kwargs["data"]) - # assert target["mappings"] == json_data["mappings"] + data = post.call_args + json_data = json.loads(data.kwargs["data"]) + assert json_data["mappings"] != [] From 3af08ffe573d645d99f72846b53e4b7fe626d429 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Tue, 30 Jul 2024 16:35:55 -0400 Subject: [PATCH 61/86] Fixed import statements --- src/sasctl/_services/score_definitions.py | 13 ++++--------- 1 file changed, 4 insertions(+), 9 deletions(-) diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index 947c9eff..79020a50 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -6,15 +6,10 @@ import json from typing import Union -# from ..core import current_session, delete, get, sasctl_command -from sasctl.core import current_session, delete, get, sasctl_command -from sasctl._services.cas_management import CASManagement -from sasctl._services.model_repository import ModelRepository -from sasctl._services.service import Service - -# from .cas_management import CASManagement -# from .model_repository import ModelRepository -# from .service import Service +from ..core import current_session, delete, get, sasctl_command +from .cas_management import CASManagement +from .model_repository import ModelRepository +from .service import Service class ScoreDefinitions(Service): From 172dddd33d6d815a6263e588d8ca2800a5bef75f Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Tue, 30 Jul 2024 16:54:17 -0400 Subject: [PATCH 62/86] Removed extra print statement and Class call --- src/sasctl/_services/score_definitions.py | 8 -------- 1 file changed, 8 deletions(-) diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index 79020a50..2db77d7e 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -150,11 +150,3 @@ def create_score_definition( "/definitions", data=json.dumps(save_score_def), headers=headers_score_def ) # The response information of the score definition can be seen as a JSON as well as a RestOBJ - - -score_def = ScoreDefinitions() -print( - score_def.create_score_definition( - "test_name", "69ed3f2f-b4c2-43e7-9f9c-24d009e20e16", "HMEQPERF_1_Q1" - ) -) From 26fe616d008f42f1ac3fa530a3bf04f4ad2b46b1 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Fri, 2 Aug 2024 15:40:16 -0400 Subject: [PATCH 63/86] Corrected status code comparisons --- src/sasctl/_services/score_definitions.py | 16 +++---- src/sasctl/_services/score_execution.py | 14 +++--- tests/unit/test_score_definitions.py | 52 ++++++++++------------- tests/unit/test_score_execution.py | 37 ++++++++-------- 4 files changed, 55 insertions(+), 64 deletions(-) diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index 2db77d7e..22c96af4 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -6,7 +6,7 @@ import json from typing import Union -from ..core import current_session, delete, get, sasctl_command +from ..core import current_session, delete, get, sasctl_command, RestObj from .cas_management import CASManagement from .model_repository import ModelRepository from .service import Service @@ -76,10 +76,10 @@ def create_score_definition( model = cls._model_respository.get_model(model_id) - if model.status_code >= 400: + if not model: raise HTTPError( { - f"This model may not exist in a project or the model may not exist at all. See error: {model.json()}" + f"This model may not exist in a project or the model may not exist at all." } ) model_project_id = model.get("projectId") @@ -103,18 +103,18 @@ def create_score_definition( # Optional mapping - Maps the variables in the data to the variables of the score object. It's not necessary to create a score definition. table = cls._cas_management.get_table(server_name, library_name, table_name) - if table.status_code >= 400 and not table_file: + if not table and not table_file: raise HTTPError( - f"This table may not exist in CAS. Please include the `table_file` argument in the function call if it doesn't exist. See error {table.json()}" + f"This table may not exist in CAS. Please include the `table_file` argument in the function call if it doesn't exist." ) - elif table.status_code >= 400 and table_file: + elif not table and table_file: cls._cas_management.upload_file( str(table_file), table_name ) # do I need to add a check if the file doesn't exist or does upload_file take care of that? table = cls._cas_management.get_table(server_name, library_name, table_name) - if table.status_code >= 400: + if not table: raise HTTPError( - f"The file failed to upload properly or another error occurred. See the error: {table.json()}" + f"The file failed to upload properly or another error occurred." ) # Checks if the inputted table exists, and if not, uploads a file to create a new table diff --git a/src/sasctl/_services/score_execution.py b/src/sasctl/_services/score_execution.py index 4816b0af..5f350381 100644 --- a/src/sasctl/_services/score_execution.py +++ b/src/sasctl/_services/score_execution.py @@ -59,8 +59,8 @@ def create_score_execution( # Gets information about the scoring object from the score definition and raises an exception if the score definition does not exist score_definition = cls._score_definitions.get_definition(score_definition_id) - if score_definition.status_code >= 400: - raise HTTPError(score_definition.json()) + if not score_definition: + raise HTTPError score_exec_name = score_definition.get("name") model_uri = score_definition.get("objectDescriptor", "uri") model_name = score_definition.get("objectDescriptor", "name") @@ -76,10 +76,8 @@ def create_score_execution( score_execution = cls.list_executions( filter=f"eq(scoreDefinitionId, '{score_definition_id}')" ) - if score_execution.status_code >= 400: - raise HTTPError( - f"Something went wrong in the LIST_EXECUTIONS statement. See error: {score_execution.json()}" - ) + if not score_execution: + raise HTTPError(f"Something went wrong in the LIST_EXECUTIONS statement.") # Checking the count of the execution list to see if there are any score executions for this score_definition_id already running execution_count = score_execution.get("count") # Exception catch location @@ -87,9 +85,7 @@ def create_score_execution( execution_id = score_execution.get("items", 0, "id") deleted_execution = cls.delete_execution(execution_id) if deleted_execution.status_code >= 400: - raise HTTPError( - f"Something went wrong in the DELETE statement. See error: {deleted_execution.json()}" - ) + raise HTTPError(f"Something went wrong in the DELETE statement.") headers_score_exec = {"Content-Type": "application/json"} diff --git a/tests/unit/test_score_definitions.py b/tests/unit/test_score_definitions.py index 6347b5ff..516bd835 100644 --- a/tests/unit/test_score_definitions.py +++ b/tests/unit/test_score_definitions.py @@ -26,8 +26,7 @@ class CustomMock: - def __init__(self, status_code, json_info): - self.status_code = status_code + def __init__(self, json_info): self.json_info = json_info def get(self, key1, key2=None, key3=None): @@ -66,7 +65,7 @@ def test_create_score_definition(): "sasctl._services.score_definitions.ScoreDefinitions.post" ) as post: # Invalid model id test case - get_model.return_value.status_code = 404 + get_model.return_value = None with pytest.raises(HTTPError): sd.create_score_definition( score_def_name="test_create_sd", @@ -75,14 +74,16 @@ def test_create_score_definition(): ) # Valid model id but invalid table name with no table_file argument test case - get_model.return_value.status_code = 200 - get_model.return_value.json.return_value = { - "id": "12345", - "projectId": "54321", - "projectVersionId": "67890", - "name": "test_model", - } - get_table.return_value.status_code = 404 + get_model_mock = CustomMock( + json_info={ + "id": "12345", + "projectId": "54321", + "projectVersionId": "67890", + "name": "test_model", + }, + ) + get_model.return_value = get_model_mock + get_table.return_value = None with pytest.raises(HTTPError): sd.create_score_definition( score_def_name="test_create_sd", @@ -91,9 +92,9 @@ def test_create_score_definition(): ) # Invalid table name with a table_file argument that doesn't work test case - get_table.return_value.status_code = 404 + get_table.return_value = None upload_file.return_value = None - get_table.return_value.status_code = 404 + get_table.return_value = None with pytest.raises(HTTPError): sd.create_score_definition( score_def_name="test_create_sd", @@ -103,12 +104,12 @@ def test_create_score_definition(): ) # Valid table_file argument that successfully creates a table test case - get_table.return_value.status_code = 404 + get_table.return_value = None upload_file.return_value = RestObj - get_table.return_value.status_code = 200 - get_table.return_value.json.return_value = { - "tableName": "test_table" - } + get_table_mock = CustomMock( + json_info={"tableName": "test_table"}, + ) + get_table.return_value = get_table_mock response = sd.create_score_definition( score_def_name="test_create_sd", model_id="12345", @@ -118,10 +119,7 @@ def test_create_score_definition(): assert response # Valid table_name argument test case - get_table.return_value.status_code = 200 - get_table.return_value.json.return_value = { - "tableName": "test_table" - } + get_table.return_value = get_table_mock response = sd.create_score_definition( score_def_name="test_create_sd", model_id="12345", @@ -131,8 +129,7 @@ def test_create_score_definition(): assert response # Checking response with inputVariables in model elements - model_mock_execution = CustomMock( - status_code=200, + get_model_mock = CustomMock( json_info={ "id": "12345", "projectId": "54321", @@ -145,11 +142,8 @@ def test_create_score_definition(): ], }, ) - get_model.return_value = model_mock_execution - get_table.return_value.status_code = 200 - get_table.return_value.json.return_value = { - "tableName": "test_table" - } + get_model.return_value = get_model_mock + get_table.return_value = get_table_mock response = sd.create_score_definition( score_def_name="test_create_sd", model_id="12345", diff --git a/tests/unit/test_score_execution.py b/tests/unit/test_score_execution.py index 81a758c7..4b06a1dc 100644 --- a/tests/unit/test_score_execution.py +++ b/tests/unit/test_score_execution.py @@ -29,13 +29,14 @@ # Creating a CustomMock for list_executions to avoid a TypeError when comparing status code from mock with >= 400 in score_execution class CustomMock: - def __init__(self, status_code, json_info): - self.status_code = status_code + def __init__(self, json_info): self.json_info = json_info def get(self, key1, key2=None, key3=None): if key2 is None and key3 is None: return self.json_info[key1] + elif key2 and not key3: + return self.json_info[key1][key2] else: return self.json_info[key1][key2][key3] @@ -74,31 +75,32 @@ def test_create_score_execution(): "sasctl._services.score_execution.ScoreExecution.post" ) as post: # Invalid score definition id test case - get_definition.return_value.status_code = 404 + get_definition.return_value = None with pytest.raises(HTTPError): se.create_score_execution(score_definition_id="12345") # Valid score definition id and invalid list_executions argument test case - get_definition.return_value.status_code = 200 - get_definition.return_value.json.return_value = { - "inputData": { - "libraryName": "cas-shared-default", - "tableName": "test_table", + get_definition_mock = CustomMock( + json_info={ + "inputData": { + "libraryName": "cas-shared-default", + "tableName": "test_table", + }, + "name": "score_def_name", + "objectDescriptor": { + "name": "test_model", + "type": "sas.publish.example", + "uri": "/modelPublish/models/example", + }, }, - "name": "score_def_name", - "objectDescriptor": { - "name": "test_model", - "type": "sas.publish.example", - "uri": "/modelPublish/models/example", - }, - } - list_executions.return_value.status_code = 404 + ) + get_definition.return_value = get_definition_mock + list_executions.return_value = None with pytest.raises(HTTPError): se.create_score_execution(score_definition_id="12345") # Valid list_executions argument with execution already running but invalid delete_execution argument test case list_mock_execution = CustomMock( - status_code=200, json_info={"count": 1, "items": [{"id": "1234"}]}, ) list_executions.return_value = list_mock_execution @@ -114,7 +116,6 @@ def test_create_score_execution(): # Valid list_executions argument without execution already running test case list_mock_execution_diff_count = CustomMock( - status_code=200, json_info={"count": 0, "items": [{"id": "1234"}]}, ) list_executions.return_value = list_mock_execution_diff_count From 2a58f5f2c6d9dfba0c21155a7193b694e7b4edb3 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Fri, 2 Aug 2024 16:17:03 -0400 Subject: [PATCH 64/86] Fixed incorrect get_table syntax --- src/sasctl/_services/score_definitions.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index 22c96af4..4d31e31c 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -102,7 +102,7 @@ def create_score_definition( # Optional mapping - Maps the variables in the data to the variables of the score object. It's not necessary to create a score definition. - table = cls._cas_management.get_table(server_name, library_name, table_name) + table = cls._cas_management.get_table(table_name, library_name, server_name) if not table and not table_file: raise HTTPError( f"This table may not exist in CAS. Please include the `table_file` argument in the function call if it doesn't exist." @@ -111,7 +111,7 @@ def create_score_definition( cls._cas_management.upload_file( str(table_file), table_name ) # do I need to add a check if the file doesn't exist or does upload_file take care of that? - table = cls._cas_management.get_table(server_name, library_name, table_name) + table = cls._cas_management.get_table(table_name, library_name, server_name) if not table: raise HTTPError( f"The file failed to upload properly or another error occurred." From 3cd5a2a7c5eda638a54c4fe1e35866a968152051 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Mon, 19 Aug 2024 08:27:11 -0400 Subject: [PATCH 65/86] filter changed --- src/sasctl/_services/score_execution.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/src/sasctl/_services/score_execution.py b/src/sasctl/_services/score_execution.py index 5f350381..155b27f5 100644 --- a/src/sasctl/_services/score_execution.py +++ b/src/sasctl/_services/score_execution.py @@ -73,8 +73,11 @@ def create_score_execution( # Getting all score executions that are using the inputted score_definition_id - score_execution = cls.list_executions( - filter=f"eq(scoreDefinitionId, '{score_definition_id}')" + # score_execution = cls.list_executions( + # filter=f"eq(scoreDefinitionId, '{score_definition_id}')" + # ) + score_execution = cls.get("scoreExecution/executions", + filter=f"filter=eq(scoreExecutionRequest.scoreDefinitionId,%{score_definition_id}%27)" ) if not score_execution: raise HTTPError(f"Something went wrong in the LIST_EXECUTIONS statement.") From a68d2d3297b2b86ae40cb633dd74129242519a10 Mon Sep 17 00:00:00 2001 From: Scott-Lindauer_sasinst Date: Wed, 14 Aug 2024 12:16:14 -0400 Subject: [PATCH 66/86] chore: add score-definitions and score-execution service into services.py --- src/sasctl/services.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/src/sasctl/services.py b/src/sasctl/services.py index 6b93c80e..38e67bdb 100644 --- a/src/sasctl/services.py +++ b/src/sasctl/services.py @@ -21,6 +21,8 @@ from ._services.report_images import ReportImages as report_images from ._services.reports import Reports as reports from ._services.saslogon import SASLogon as saslogon +from ._services.score_definitions import ScoreDefinitions as score_definitions +from ._services.score_execution import ScoreExecution as score_execution from ._services.sentiment_analysis import SentimentAnalysis as sentiment_analysis from ._services.text_categorization import TextCategorization as text_categorization from ._services.text_parsing import TextParsing as text_parsing From 913fe03a3de3ca8898ad8fb56e39ad838f56dd9c Mon Sep 17 00:00:00 2001 From: Scott-Lindauer_sasinst Date: Wed, 14 Aug 2024 12:16:51 -0400 Subject: [PATCH 67/86] chore: fix spelling errors --- src/sasctl/_services/score_definitions.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index 4d31e31c..e0b6d173 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -26,7 +26,7 @@ class ScoreDefinitions(Service): _SERVICE_ROOT = "/scoreDefinitions" _cas_management = CASManagement() - _model_respository = ModelRepository() + _model_repository = ModelRepository() ( list_definitions, @@ -74,7 +74,7 @@ def create_score_definition( """ - model = cls._model_respository.get_model(model_id) + model = cls._model_repository.get_model(model_id) if not model: raise HTTPError( From 2f54f8cc7dbdd09beefe856fc5823fb41629562c Mon Sep 17 00:00:00 2001 From: Scott-Lindauer_sasinst Date: Wed, 14 Aug 2024 12:17:21 -0400 Subject: [PATCH 68/86] fix: proper call to the object uri in modelManagement for score definitions --- src/sasctl/_services/score_definitions.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index e0b6d173..fb290d55 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -122,7 +122,7 @@ def create_score_definition( "name": score_def_name, "description": description, "objectDescriptor": { - "uri": f"/modelRepository/models/{model_id}", + "uri": f"/modelManagement/models/{model_id}", "name": f"{model_name}({model_version})", "type": "sas.models.model", }, From f250b5ff871552b223a4e4a88a4567106966bba4 Mon Sep 17 00:00:00 2001 From: Scott-Lindauer_sasinst Date: Wed, 14 Aug 2024 12:17:38 -0400 Subject: [PATCH 69/86] feat: change base score definition to use CAS Gateway --- src/sasctl/_services/score_definitions.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index fb290d55..b2b85193 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -124,7 +124,7 @@ def create_score_definition( "objectDescriptor": { "uri": f"/modelManagement/models/{model_id}", "name": f"{model_name}({model_version})", - "type": "sas.models.model", + "type": "sas.models.model.python", }, "inputData": { "type": "CASTable", From 4f9ab4dad6a27ebce80dc6050f12f90013f8c79e Mon Sep 17 00:00:00 2001 From: Scott-Lindauer_sasinst Date: Fri, 16 Aug 2024 10:01:13 -0400 Subject: [PATCH 70/86] refactor: swap model_id to model for ease of use in argument choice --- src/sasctl/_services/score_definitions.py | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index b2b85193..a954ee7a 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -39,7 +39,7 @@ class ScoreDefinitions(Service): def create_score_definition( cls, score_def_name: str, - model_id: str, + model: Union[str, dict], table_name: str, table_file: Union[str, Path] = None, description: str = "", @@ -53,8 +53,8 @@ def create_score_definition( -------- score_def_name: str Name of score definition. - model_id: str - A user-inputted model if where the model exists in a project. + model : str or dict + The name or id of the model, or a dictionary representation of the model. table_name: str A user-inputted table name in CAS Management. table_file: str or Path, optional @@ -74,7 +74,8 @@ def create_score_definition( """ - model = cls._model_repository.get_model(model_id) + model = cls._model_repository.get_model(model) + model_id = model.id if not model: raise HTTPError( From fa248a2d4821dca90985877395e265d929110b16 Mon Sep 17 00:00:00 2001 From: Scott-Lindauer_sasinst Date: Fri, 16 Aug 2024 10:06:17 -0400 Subject: [PATCH 71/86] feat: add new task to score models in SAS Model Manager --- src/sasctl/tasks.py | 31 +++++++++++++++++++++++++++++++ 1 file changed, 31 insertions(+) diff --git a/src/sasctl/tasks.py b/src/sasctl/tasks.py index add40892..6904e100 100644 --- a/src/sasctl/tasks.py +++ b/src/sasctl/tasks.py @@ -13,6 +13,8 @@ import pickle # skipcq BAN-B301 import re import sys +from pathlib import Path +from typing import Union from warnings import warn import pandas as pd @@ -30,6 +32,8 @@ from .services import model_management as mm from .services import model_publish as mp from .services import model_repository as mr +from .services import score_definitions as sd +from .services import score_execution as se from .utils.misc import installed_packages from .utils.pymas import from_pickle @@ -1008,3 +1012,30 @@ def get_project_kpis( kpiTableDf = kpiTableDf.apply(lambda x: x.str.strip()).replace([".", ""], None) return kpiTableDf + + +def score_model_with_cas( + score_def_name: str, + model: Union[str, dict], + table_name: str, + table_file: Union[str, Path] = None, + description: str = "", + server_name: str = "cas-shared-default", + library_name: str = "Public", + model_version: str = "latest" +): + score_definition = sd.create_score_definition( + score_def_name, + model, + table_name, + table_file=table_file, + description=description, + server_name=server_name, + library_name=library_name, + model_version=model_version + ) + score_execution = se.create_score_execution(score_definition.id) + score_execution_poll = se.poll_score_execution_state(score_execution) + print(score_execution_poll) + score_results = se.get_score_execution_results(score_execution) + return score_results From bde6304c353052a70dbf13f7b3dc4a0e1e4045cc Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Wed, 21 Aug 2024 23:58:20 -0400 Subject: [PATCH 72/86] Added docstrings and removed list_executions unit tests in test_score_execution.py --- tests/unit/test_score_execution.py | 120 +++++++++++------------------ 1 file changed, 44 insertions(+), 76 deletions(-) diff --git a/tests/unit/test_score_execution.py b/tests/unit/test_score_execution.py index 4b06a1dc..f0090155 100644 --- a/tests/unit/test_score_execution.py +++ b/tests/unit/test_score_execution.py @@ -65,79 +65,47 @@ def test_create_score_execution(): with mock.patch( "sasctl._services.score_definitions.ScoreDefinitions.get_definition" ) as get_definition: - with mock.patch( - "sasctl._services.score_execution.ScoreExecution.list_executions" - ) as list_executions: - with mock.patch( - "sasctl._services.score_execution.ScoreExecution.delete_execution" - ) as delete_execution: - with mock.patch( - "sasctl._services.score_execution.ScoreExecution.post" - ) as post: - # Invalid score definition id test case - get_definition.return_value = None - with pytest.raises(HTTPError): - se.create_score_execution(score_definition_id="12345") - - # Valid score definition id and invalid list_executions argument test case - get_definition_mock = CustomMock( - json_info={ - "inputData": { - "libraryName": "cas-shared-default", - "tableName": "test_table", - }, - "name": "score_def_name", - "objectDescriptor": { - "name": "test_model", - "type": "sas.publish.example", - "uri": "/modelPublish/models/example", - }, - }, - ) - get_definition.return_value = get_definition_mock - list_executions.return_value = None - with pytest.raises(HTTPError): - se.create_score_execution(score_definition_id="12345") - - # Valid list_executions argument with execution already running but invalid delete_execution argument test case - list_mock_execution = CustomMock( - json_info={"count": 1, "items": [{"id": "1234"}]}, - ) - list_executions.return_value = list_mock_execution - delete_execution.return_value.status_code = 404 - with pytest.raises(HTTPError): - se.create_score_execution(score_definition_id="12345") - - # Valid list_executions argument with execution already running but valid delete_execution argument test case - list_executions.return_value = list_mock_execution - delete_execution.return_value.status_code = 200 - response = se.create_score_execution(score_definition_id="3456") - assert response - - # Valid list_executions argument without execution already running test case - list_mock_execution_diff_count = CustomMock( - json_info={"count": 0, "items": [{"id": "1234"}]}, - ) - list_executions.return_value = list_mock_execution_diff_count - response = se.create_score_execution(score_definition_id="12345") - assert response - - # Checking whether the output table name remained the default empty string or the default changed as writted in score_execution - data = post.call_args - json_data = json.loads(data.kwargs["data"]) - assert json_data["outputTable"]["tableName"] != "" - - # With output table specified within create_score_execution arguments test case - response = se.create_score_execution( - score_definition_id="12345", output_table_name="example_table" - ) - assert response - assert post.call_count == 3 - - # Checking whether specified output table name or the default output table name is in the response - data = post.call_args - json_data = json.loads(data.kwargs["data"]) - assert ( - target["outputTable"]["tableName"] - == json_data["outputTable"]["tableName"] - ) + with mock.patch("sasctl._services.score_execution.ScoreExecution.post") as post: + # Invalid score definition id test case + get_definition.return_value = None + with pytest.raises(HTTPError): + se.create_score_execution(score_definition_id="12345") + + # Valid score definition id and invalid list_executions argument test case + get_definition_mock = CustomMock( + json_info={ + "inputData": { + "libraryName": "cas-shared-default", + "tableName": "test_table", + }, + "name": "score_def_name", + "objectDescriptor": { + "name": "test_model", + "type": "sas.publish.example", + "uri": "/modelPublish/models/example", + }, + }, + ) + get_definition.return_value = get_definition_mock + response = se.create_score_execution(score_definition_id="3456") + assert response + + # Checking whether the output table name remained the default empty string or the default changed as writted in score_execution + data = post.call_args + json_data = json.loads(data.kwargs["data"]) + assert json_data["outputTable"]["tableName"] != "" + + # With output table specified within create_score_execution arguments test case + response = se.create_score_execution( + score_definition_id="12345", output_table_name="example_table" + ) + assert response + assert post.call_count == 2 + + # Checking whether specified output table name or the default output table name is in the response + data = post.call_args + json_data = json.loads(data.kwargs["data"]) + assert ( + target["outputTable"]["tableName"] + == json_data["outputTable"]["tableName"] + ) From 21808ec68db554c6746228e135441f934fd38398 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Thu, 22 Aug 2024 00:01:36 -0400 Subject: [PATCH 73/86] Added this to fix code quality linting error --- src/sasctl/tasks.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/sasctl/tasks.py b/src/sasctl/tasks.py index 6904e100..2af7780c 100644 --- a/src/sasctl/tasks.py +++ b/src/sasctl/tasks.py @@ -1022,7 +1022,7 @@ def score_model_with_cas( description: str = "", server_name: str = "cas-shared-default", library_name: str = "Public", - model_version: str = "latest" + model_version: str = "latest", ): score_definition = sd.create_score_definition( score_def_name, @@ -1032,7 +1032,7 @@ def score_model_with_cas( description=description, server_name=server_name, library_name=library_name, - model_version=model_version + model_version=model_version, ) score_execution = se.create_score_execution(score_definition.id) score_execution_poll = se.poll_score_execution_state(score_execution) From 73092a487809ad55a12adf6ee428fcf6e2ba1f9e Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Thu, 29 Aug 2024 23:26:49 -0400 Subject: [PATCH 74/86] Edited test_score_definitions for syntax issue --- src/sasctl/_services/score_definitions.py | 2 +- tests/unit/test_score_definitions.py | 15 ++++++++------- 2 files changed, 9 insertions(+), 8 deletions(-) diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index a954ee7a..50c4d2e6 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -75,7 +75,6 @@ def create_score_definition( """ model = cls._model_repository.get_model(model) - model_id = model.id if not model: raise HTTPError( @@ -83,6 +82,7 @@ def create_score_definition( f"This model may not exist in a project or the model may not exist at all." } ) + model_id = model.id model_project_id = model.get("projectId") model_project_version_id = model.get("projectVersionId") model_name = model.get("name") diff --git a/tests/unit/test_score_definitions.py b/tests/unit/test_score_definitions.py index 516bd835..1edea133 100644 --- a/tests/unit/test_score_definitions.py +++ b/tests/unit/test_score_definitions.py @@ -26,8 +26,9 @@ class CustomMock: - def __init__(self, json_info): + def __init__(self, json_info, id=""): self.json_info = json_info + self.id = id def get(self, key1, key2=None, key3=None): if key2 is None and key3 is None: @@ -69,7 +70,7 @@ def test_create_score_definition(): with pytest.raises(HTTPError): sd.create_score_definition( score_def_name="test_create_sd", - model_id="12345", + model="12345", table_name="test_table", ) @@ -87,7 +88,7 @@ def test_create_score_definition(): with pytest.raises(HTTPError): sd.create_score_definition( score_def_name="test_create_sd", - model_id="12345", + model="12345", table_name="test_table", ) @@ -98,7 +99,7 @@ def test_create_score_definition(): with pytest.raises(HTTPError): sd.create_score_definition( score_def_name="test_create_sd", - model_id="12345", + model="12345", table_name="test_table", table_file="test_path", ) @@ -112,7 +113,7 @@ def test_create_score_definition(): get_table.return_value = get_table_mock response = sd.create_score_definition( score_def_name="test_create_sd", - model_id="12345", + model="12345", table_name="test_table", table_file="test_path", ) @@ -122,7 +123,7 @@ def test_create_score_definition(): get_table.return_value = get_table_mock response = sd.create_score_definition( score_def_name="test_create_sd", - model_id="12345", + model="12345", table_name="test_table", table_file="test_path", ) @@ -146,7 +147,7 @@ def test_create_score_definition(): get_table.return_value = get_table_mock response = sd.create_score_definition( score_def_name="test_create_sd", - model_id="12345", + model="12345", table_name="test_table", ) assert response From 7520ca014dd4360dce93ed04736cc23b19807f16 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Thu, 10 Oct 2024 18:23:00 -0400 Subject: [PATCH 75/86] black reformatting --- tests/unit/test_score_definitions.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/unit/test_score_definitions.py b/tests/unit/test_score_definitions.py index 1edea133..39d79498 100644 --- a/tests/unit/test_score_definitions.py +++ b/tests/unit/test_score_definitions.py @@ -26,7 +26,7 @@ class CustomMock: - def __init__(self, json_info, id=""): + def __init__(self, json_info, id=""): self.json_info = json_info self.id = id From 63c2068f6f07a0999d7d70bd576347d2fd89d264 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Thu, 10 Oct 2024 18:29:39 -0400 Subject: [PATCH 76/86] checking black formatting --- tests/unit/test_score_definitions.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/unit/test_score_definitions.py b/tests/unit/test_score_definitions.py index 39d79498..8a75294a 100644 --- a/tests/unit/test_score_definitions.py +++ b/tests/unit/test_score_definitions.py @@ -52,7 +52,7 @@ def test_create_score_definition(): with mock.patch("sasctl.core.Session._get_authorization_token"): current_session("example.com", "username", "password") - # Mocking the REST API calls and functions + # Mocking the REST API calls and methods with mock.patch( "sasctl._services.model_repository.ModelRepository.get_model" ) as get_model: From b88c928146b4d306e1dabc476bc247e00c759fc3 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Fri, 18 Oct 2024 15:03:58 -0400 Subject: [PATCH 77/86] added cas gateway optional parameter --- src/sasctl/_services/score_definitions.py | 15 ++++++++++++--- 1 file changed, 12 insertions(+), 3 deletions(-) diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index 50c4d2e6..6146878e 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -4,7 +4,7 @@ from pathlib import Path import json -from typing import Union +from typing import Union, Optional from ..core import current_session, delete, get, sasctl_command, RestObj from .cas_management import CASManagement @@ -41,6 +41,7 @@ def create_score_definition( score_def_name: str, model: Union[str, dict], table_name: str, + use_cas_gateway: Optional[bool] = False, table_file: Union[str, Path] = None, description: str = "", server_name: str = "cas-shared-default", @@ -57,6 +58,8 @@ def create_score_definition( The name or id of the model, or a dictionary representation of the model. table_name: str A user-inputted table name in CAS Management. + use_cas_gateway: bool, optional + Determines whether object uses CAS Gateway or not. table_file: str or Path, optional A user-provided path to an uploadable file. Defaults to None. description: str, optional @@ -73,6 +76,12 @@ def create_score_definition( RestObj """ + # Changes object descriptor type to either use or not use CAS Gateway + object_descriptor_type: str + if use_cas_gateway: + object_descriptor_type = "sas.models.model.python" + else: + object_descriptor_type = "sas.models.model.ds2" model = cls._model_repository.get_model(model) @@ -120,12 +129,12 @@ def create_score_definition( # Checks if the inputted table exists, and if not, uploads a file to create a new table save_score_def = { - "name": score_def_name, + "name": model_name, # used to be score_def_name "description": description, "objectDescriptor": { "uri": f"/modelManagement/models/{model_id}", "name": f"{model_name}({model_version})", - "type": "sas.models.model.python", + "type": f"{object_descriptor_type}", }, "inputData": { "type": "CASTable", From c8b1c70a8b35a66ccf0aa164bf1b37db12698679 Mon Sep 17 00:00:00 2001 From: Samya Potlapalli Date: Fri, 18 Oct 2024 17:23:53 -0400 Subject: [PATCH 78/86] Add files via upload Updated example with score testing --- pzmm_binary_classification_model_import.ipynb | 555 ++++++++++++++++++ 1 file changed, 555 insertions(+) create mode 100644 pzmm_binary_classification_model_import.ipynb diff --git a/pzmm_binary_classification_model_import.ipynb b/pzmm_binary_classification_model_import.ipynb new file mode 100644 index 00000000..bfcb4b6a --- /dev/null +++ b/pzmm_binary_classification_model_import.ipynb @@ -0,0 +1,555 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "Collapsed": "false" + }, + "source": [ + "Copyright © 2023, SAS Institute Inc., Cary, NC, USA. All Rights Reserved.\n", + "SPDX-License-Identifier: Apache-2.0" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "Collapsed": "false" + }, + "source": [ + "# HMEQ Dataset : Build and Import Trained Binary Classification Models into SAS Model Manager\n", + "\n", + "This notebook provides an example of how to build and train a simple Python model and then import the model into SAS Model Manager (on either SAS Viya 3.5 or SAS Viya 4) using the HMEQ data set. Lines of code that must be modified by the user, such as directory paths or the host server are noted with the comment \"_Changes required by user._\".\n", + "\n", + "_**Note:** If you download only this notebook and not the rest of the repository, you must also download the hmeq.csv file from the data folder in the examples directory. These files are used when executing this notebook example._\n", + "\n", + "Here are the steps shown in this notebook:\n", + "\n", + "1. Import, review, and preprocess data for model training.\n", + "2. Build, train, and assess a scikit-learn decision tree, random forest, and gradient boosting model.\n", + "3. Serialize the models into separate pickle files.\n", + "4. Write the metadata JSON files needed for importing into SAS Model Manager as well as optional files for fit statistics and ROC/Lift charts.\n", + "4. Write a score code Python file for model scoring.\n", + "5. Zip the pickle, JSON, and score code files into an archive file.\n", + "6. Import the ZIP archive file to SAS Model Manager via the Session object and relevant function call." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "Collapsed": "false" + }, + "source": [ + "### Python Package Imports" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "Collapsed": "false" + }, + "outputs": [], + "source": [ + "# Standard Library\n", + "from pathlib import Path\n", + "import warnings\n", + "\n", + "# Third Party\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import pandas as pd\n", + "from sklearn.ensemble import GradientBoostingClassifier, RandomForestClassifier\n", + "from sklearn.metrics import classification_report, confusion_matrix\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "\n", + "# Application Specific\n", + "import sasctl.pzmm as pzmm\n", + "from sasctl import Session" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "Collapsed": "false" + }, + "outputs": [], + "source": [ + "# Global Package Options\n", + "pd.options.mode.chained_assignment = None # default=\"warn\"\n", + "plt.rc(\"font\", size=14)\n", + "# Ignore warnings from pandas about SWAT using a feature that will be depreciated soon\n", + "warnings.simplefilter(action=\"ignore\", category=FutureWarning)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "Collapsed": "false" + }, + "source": [ + "### Import and Review Data Set" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "Collapsed": "false" + }, + "outputs": [], + "source": [ + "hmeq_data = pd.read_csv(\"data/hmeq.csv\", sep= \",\")\n", + "hmeq_data.shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "Collapsed": "false" + }, + "outputs": [], + "source": [ + "hmeq_data.head()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "Collapsed": "false" + }, + "outputs": [], + "source": [ + "hmeq_data.hist(figsize=(15,15), layout=(4, 4));" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "Collapsed": "false" + }, + "outputs": [], + "source": [ + "hmeq_data.columns" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "Collapsed": "false" + }, + "source": [ + "### Preprocess Data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "Collapsed": "false" + }, + "outputs": [], + "source": [ + "predictor_columns = [\"LOAN\", \"MORTDUE\", \"VALUE\", \"YOJ\", \"DEROG\", \"DELINQ\", \"CLAGE\", \"NINQ\", \"CLNO\", \"DEBTINC\"]\n", + "\n", + "target_column = \"BAD\"\n", + "x = hmeq_data[predictor_columns]\n", + "y = hmeq_data[target_column]\n", + "\n", + "x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.3, random_state=42)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "Collapsed": "false" + }, + "outputs": [], + "source": [ + "# For missing values, impute the data set's mean value\n", + "x_test.fillna(x_test.mean(), inplace=True)\n", + "x_train.fillna(x_train.mean(), inplace=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "Collapsed": "false" + }, + "source": [ + "### Create, Train, and Assess Model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "Collapsed": "false" + }, + "outputs": [], + "source": [ + "dtc = DecisionTreeClassifier(max_depth=7, min_samples_split=2, min_samples_leaf=2, max_leaf_nodes=500)\n", + "dtc = dtc.fit(x_train, y_train)\n", + "\n", + "rfc = RandomForestClassifier(n_estimators=120, max_depth=9, max_leaf_nodes=850, min_samples_split=5, min_samples_leaf=4)\n", + "rfc = rfc.fit(x_train, y_train)\n", + "\n", + "gbc = GradientBoostingClassifier(learning_rate=0.1, n_estimators=600, max_depth=4, min_samples_leaf=1, min_samples_split=2, max_leaf_nodes=500)\n", + "gbc = gbc.fit(x_train, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "Collapsed": "false" + }, + "outputs": [], + "source": [ + "# Calculate the importance of a predictor \n", + "def sort_feature_importance(model, data):\n", + " features = {}\n", + " for importance, name in sorted(zip(model.feature_importances_, data.columns), reverse=True):\n", + " features[name] = str(np.round(importance*100, 2)) + \"%\"\n", + " return features" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "Collapsed": "false" + }, + "outputs": [], + "source": [ + "importances = pd.DataFrame.from_dict(sort_feature_importance(dtc, x_train), orient=\"index\").rename(columns={0: \"DecisionTree\"})\n", + "importances[\"RandomForest\"] = pd.DataFrame.from_dict(sort_feature_importance(rfc, x_train), orient=\"index\")\n", + "importances[\"GradientBoosting\"] = pd.DataFrame.from_dict(sort_feature_importance(gbc, x_train), orient=\"index\")\n", + "importances" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "Collapsed": "false" + }, + "outputs": [], + "source": [ + "y_dtc_predict = dtc.predict(x_test)\n", + "y_dtc_proba = dtc.predict_proba(x_test)\n", + "print(confusion_matrix(y_test, y_dtc_predict))\n", + "print(classification_report(y_test, y_dtc_predict))\n", + "print(\"Decision Tree Model Accuracy = \" + str(np.round(dtc.score(x_test, y_test)*100,2)) + \"%\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "Collapsed": "false" + }, + "outputs": [], + "source": [ + "y_rfc_predict = rfc.predict(x_test)\n", + "y_rfc_proba = rfc.predict_proba(x_test)\n", + "print(confusion_matrix(y_test, y_rfc_predict))\n", + "print(classification_report(y_test, y_rfc_predict))\n", + "print(\"Random Forest Model Accuracy = \" + str(np.round(rfc.score(x_test, y_test)*100,2)) + \"%\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "y_gbc_predict = gbc.predict(x_test)\n", + "y_gbc_proba = gbc.predict_proba(x_test)\n", + "print(confusion_matrix(y_test, y_gbc_predict))\n", + "print(classification_report(y_test, y_gbc_predict))\n", + "print(\"Gradient Boosting Model Accuracy = \" + str(np.round(gbc.score(x_test, y_test)*100,2)) + \"%\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "Collapsed": "false" + }, + "source": [ + "### Register Model in SAS Model Manager with pzmm" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "Collapsed": "false" + }, + "outputs": [], + "source": [ + "# Model names within SAS Model Manager\n", + "model_prefix = [\"DecisionTreeClassifier\", \"RandomForest\", \"GradientBoosting\"]\n", + "# Directory location for the model files\n", + "zip_folder = [Path.cwd() / \"data/hmeqModels/DecisionTreeClassifier/\",\n", + " Path.cwd() / \"data/hmeqModels/RandomForest/\",\n", + " Path.cwd() / \"data/hmeqModels/GradientBoosting\"] # Changes required by user\n", + "model = [dtc, rfc, gbc]\n", + "# Output variables expected in SAS Model Manager. If a classification value is expected to be output, it should be the first metric.\n", + "score_metrics = [\"EM_CLASSIFICATION\", \"EM_EVENTPROBABILITY\"]\n", + "\n", + "# Serialize the models to a pickle format\n", + "for (mod, prefix, path) in zip(model, model_prefix, zip_folder):\n", + " pzmm.PickleModel.pickle_trained_model(\n", + " model_prefix=prefix,\n", + " trained_model=mod,\n", + " pickle_path=path\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "Collapsed": "false" + }, + "outputs": [], + "source": [ + "def write_json_files(data, predict, target, path, prefix): \n", + " # Write input variable mapping to a json file\n", + " pzmm.JSONFiles.write_var_json(input_data=data[predict], is_input=True, json_path=path)\n", + " \n", + " # Set output variables and assign an event threshold, then write output variable mapping\n", + " output_var = pd.DataFrame(columns=score_metrics, data=[[\"A\", 0.5]]) # data argument includes example expected types for outputs\n", + " pzmm.JSONFiles.write_var_json(output_var, is_input=False, json_path=path)\n", + " \n", + " # Write model properties to a json file\n", + " pzmm.JSONFiles.write_model_properties_json(\n", + " model_name=prefix, \n", + " target_variable=target, # Target variable to make predictions about (BAD in this case)\n", + " target_values=[\"1\", \"0\"], # Possible values for the target variable (1 or 0 for binary classification of BAD)\n", + " json_path=path, \n", + " model_desc=f\"Description for the {prefix} model.\",\n", + " model_algorithm=\"\",\n", + " modeler=\"sasdemo\",\n", + " )\n", + " \n", + " # Write model metadata to a json file so that SAS Model Manager can properly identify all model files\n", + " pzmm.JSONFiles.write_file_metadata_json(model_prefix=prefix, json_path=path)\n", + "\n", + "for (prefix, path) in zip(model_prefix, zip_folder):\n", + " write_json_files(hmeq_data, predictor_columns, target_column, path, prefix)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "Collapsed": "false" + }, + "outputs": [], + "source": [ + "import getpass\n", + "def write_model_stats(x_train, y_train, test_predict, test_proba, y_test, model, path, prefix):\n", + " # Calculate train predictions\n", + " train_predict = model.predict(x_train)\n", + " train_proba = model.predict_proba(x_train)\n", + " \n", + " # Assign data to lists of actual and predicted values\n", + " train_data = pd.concat([y_train.reset_index(drop=True), pd.Series(train_predict), pd.Series(data=train_proba[:,1])], axis=1)\n", + " test_data = pd.concat([y_test.reset_index(drop=True), pd.Series(test_predict), pd.Series(data=test_proba[:,1])], axis=1)\n", + " \n", + " # Calculate the model statistics, ROC chart, and Lift chart; then write to json files\n", + " pzmm.JSONFiles.calculate_model_statistics(\n", + " target_value=1, \n", + " prob_value=0.5, \n", + " train_data=train_data, \n", + " test_data=test_data, \n", + " json_path=path\n", + " )\n", + "\n", + " full_training_data = pd.concat([y_train.reset_index(drop=True), x_train.reset_index(drop=True)], axis=1)\n", + "\n", + " pzmm.JSONFiles.generate_model_card(\n", + " model_prefix=prefix,\n", + " model_files = path,\n", + " algorithm = str(type(model).__name__),\n", + " train_data = full_training_data,\n", + " train_predictions=train_predict,\n", + " target_type='classification',\n", + " target_value=1,\n", + " interval_vars=predictor_columns,\n", + " selection_statistic='_RASE_',\n", + " )\n", + " \n", + "username = getpass.getpass()\n", + "password = getpass.getpass()\n", + "host = \"demo.sas.com\"# Changes required by user\n", + "sess = Session(host, username, password, protocol=\"http\") # For TLS-enabled servers, change protocol value to \"https\"\n", + "conn = sess.as_swat() # Connect to SWAT through the sasctl authenticated connection\n", + "\n", + "test_predict = [y_dtc_predict, y_rfc_predict, y_gbc_predict]\n", + "test_proba = [y_dtc_proba, y_rfc_proba, y_gbc_proba]\n", + "for (mod, pred, proba, path, prefix) in zip(model, test_predict, test_proba, zip_folder, model_prefix):\n", + " write_model_stats(x_train, y_train, pred, proba, y_test, mod, path, prefix)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "Collapsed": "false" + }, + "outputs": [], + "source": [ + "for (prefix, path) in zip(model_prefix, zip_folder):\n", + " pzmm.ImportModel.import_model(\n", + " model_files=path, # Where are the model files?\n", + " model_prefix=prefix, # What is the model name?\n", + " project=\"HMEQModels\", # What is the project name?\n", + " input_data=x, # What does example input data look like?\n", + " predict_method=[dtc.predict_proba, [int, int]], # What is the predict method and what does it return?\n", + " score_metrics=score_metrics, # What are the output variables?\n", + " overwrite_model=True, # Overwrite the model if it already exists?\n", + " target_values=[\"0\", \"1\"], # What are the expected values of the target variable?\n", + " target_index=1, # What is the index of the target value in target_values?\n", + " model_file_name=prefix + \".pickle\", # How was the model file serialized?\n", + " missing_values=True # Does the data include missing values?\n", + " )\n", + " # Reinitialize the score_code variable when writing more than one model's score code\n", + " pzmm.ScoreCode.score_code = \"\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Implementing Score Testing" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import requests\n", + "import sys\n", + "\n", + "from sasctl._services.score_definitions import ScoreDefinitions as sd # Importing ScoreDefinitions service\n", + "from sasctl._services.score_execution import ScoreExecution as se # Importing ScoreExecution service" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Creating the score definition for this model using the model UUID generated two steps before\n", + "score_definition = sd.create_score_definition(\n", + " \"example_score_def_name\", # Name of the score_definition, which can be any string\n", + " \"model_id\", # Use Model UUID generated two steps before\n", + " \"table_name\", # Table name for input data, which must exist in host server or it will throw an HTTP error and prompt you to upload a data file\n", + " # True, # Uncomment 'True' if your Viya version is compatible with CAS Gateway\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Executing the score definition\n", + "score_execution = se.create_score_execution(\n", + " score_definition.get(\"id\") # Score definition id created in the previous cell\n", + ")\n", + "\n", + "# Prints score_execution_id\n", + "print(score_execution)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can view our scored model information within Model Manager under Projects -> Choose your model -> Scoring. \n", + "***" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "base", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.0" + }, + "latex_envs": { + "LaTeX_envs_menu_present": true, + "autoclose": true, + "autocomplete": true, + "bibliofile": "biblio.bib", + "cite_by": "apalike", + "current_citInitial": 1, + "eqLabelWithNumbers": true, + "eqNumInitial": 1, + "hotkeys": { + "equation": "Ctrl-E", + "itemize": "Ctrl-I" + }, + "labels_anchors": false, + "latex_user_defs": false, + "report_style_numbering": false, + "user_envs_cfg": false + }, + "varInspector": { + "cols": { + "lenName": 16, + "lenType": 16, + "lenVar": 40 + }, + "kernels_config": { + "python": { + "delete_cmd_postfix": "", + "delete_cmd_prefix": "del ", + "library": "var_list.py", + "varRefreshCmd": "print(var_dic_list())" + }, + "r": { + "delete_cmd_postfix": ") ", + "delete_cmd_prefix": "rm(", + "library": "var_list.r", + "varRefreshCmd": "cat(var_dic_list()) " + } + }, + "types_to_exclude": [ + "module", + "function", + "builtin_function_or_method", + "instance", + "_Feature" + ], + "window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} From b7347b3431c91f67f225e70b0312111aab8bd087 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Fri, 18 Oct 2024 17:59:59 -0400 Subject: [PATCH 79/86] score testing example --- examples/score_testing_example.ipynb | 72 +++ pzmm_binary_classification_model_import.ipynb | 555 ------------------ 2 files changed, 72 insertions(+), 555 deletions(-) create mode 100644 examples/score_testing_example.ipynb delete mode 100644 pzmm_binary_classification_model_import.ipynb diff --git a/examples/score_testing_example.ipynb b/examples/score_testing_example.ipynb new file mode 100644 index 00000000..cfc172e7 --- /dev/null +++ b/examples/score_testing_example.ipynb @@ -0,0 +1,72 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "***\n", + "# Implementing Score Testing\n", + "\n", + "_**Note:** Before running this example, you will need to run an example that creates a model on a Viya server and copy the UUID. This will be used as a create_score_definition function parameter._" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import requests\n", + "import sys\n", + "\n", + "from sasctl._services.score_definitions import ScoreDefinitions as sd # Importing ScoreDefinitions service\n", + "from sasctl._services.score_execution import ScoreExecution as se # Importing ScoreExecution service" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Creating the score definition for this model using the model UUID generated two steps before\n", + "score_definition = sd.create_score_definition(\n", + " \"example_score_def_name\", # Name of the score_definition, which can be any string\n", + " \"model_id\", # Use Model UUID generated two steps before\n", + " \"table_name\", # Table name for input data, which must exist in host server or it will throw an HTTP error and prompt you to upload a data file\n", + " # True, # Uncomment 'True' if your Viya version is compatible with CAS Gateway\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Executing the score definition\n", + "score_execution = se.create_score_execution(\n", + " score_definition.get(\"id\") # Score definition id created in the previous cell\n", + ")\n", + "\n", + "# Prints score_execution_id\n", + "print(score_execution)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can view our scored model information within Model Manager under Projects -> Choose your model -> Scoring. \n", + "***" + ] + } + ], + "metadata": { + "language_info": { + "name": "python" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/pzmm_binary_classification_model_import.ipynb b/pzmm_binary_classification_model_import.ipynb deleted file mode 100644 index bfcb4b6a..00000000 --- a/pzmm_binary_classification_model_import.ipynb +++ /dev/null @@ -1,555 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "Collapsed": "false" - }, - "source": [ - "Copyright © 2023, SAS Institute Inc., Cary, NC, USA. All Rights Reserved.\n", - "SPDX-License-Identifier: Apache-2.0" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "Collapsed": "false" - }, - "source": [ - "# HMEQ Dataset : Build and Import Trained Binary Classification Models into SAS Model Manager\n", - "\n", - "This notebook provides an example of how to build and train a simple Python model and then import the model into SAS Model Manager (on either SAS Viya 3.5 or SAS Viya 4) using the HMEQ data set. Lines of code that must be modified by the user, such as directory paths or the host server are noted with the comment \"_Changes required by user._\".\n", - "\n", - "_**Note:** If you download only this notebook and not the rest of the repository, you must also download the hmeq.csv file from the data folder in the examples directory. These files are used when executing this notebook example._\n", - "\n", - "Here are the steps shown in this notebook:\n", - "\n", - "1. Import, review, and preprocess data for model training.\n", - "2. Build, train, and assess a scikit-learn decision tree, random forest, and gradient boosting model.\n", - "3. Serialize the models into separate pickle files.\n", - "4. Write the metadata JSON files needed for importing into SAS Model Manager as well as optional files for fit statistics and ROC/Lift charts.\n", - "4. Write a score code Python file for model scoring.\n", - "5. Zip the pickle, JSON, and score code files into an archive file.\n", - "6. Import the ZIP archive file to SAS Model Manager via the Session object and relevant function call." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "Collapsed": "false" - }, - "source": [ - "### Python Package Imports" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "Collapsed": "false" - }, - "outputs": [], - "source": [ - "# Standard Library\n", - "from pathlib import Path\n", - "import warnings\n", - "\n", - "# Third Party\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "import pandas as pd\n", - "from sklearn.ensemble import GradientBoostingClassifier, RandomForestClassifier\n", - "from sklearn.metrics import classification_report, confusion_matrix\n", - "from sklearn.model_selection import train_test_split\n", - "from sklearn.tree import DecisionTreeClassifier\n", - "\n", - "# Application Specific\n", - "import sasctl.pzmm as pzmm\n", - "from sasctl import Session" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "Collapsed": "false" - }, - "outputs": [], - "source": [ - "# Global Package Options\n", - "pd.options.mode.chained_assignment = None # default=\"warn\"\n", - "plt.rc(\"font\", size=14)\n", - "# Ignore warnings from pandas about SWAT using a feature that will be depreciated soon\n", - "warnings.simplefilter(action=\"ignore\", category=FutureWarning)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "Collapsed": "false" - }, - "source": [ - "### Import and Review Data Set" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "Collapsed": "false" - }, - "outputs": [], - "source": [ - "hmeq_data = pd.read_csv(\"data/hmeq.csv\", sep= \",\")\n", - "hmeq_data.shape" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "Collapsed": "false" - }, - "outputs": [], - "source": [ - "hmeq_data.head()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "Collapsed": "false" - }, - "outputs": [], - "source": [ - "hmeq_data.hist(figsize=(15,15), layout=(4, 4));" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "Collapsed": "false" - }, - "outputs": [], - "source": [ - "hmeq_data.columns" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "Collapsed": "false" - }, - "source": [ - "### Preprocess Data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "Collapsed": "false" - }, - "outputs": [], - "source": [ - "predictor_columns = [\"LOAN\", \"MORTDUE\", \"VALUE\", \"YOJ\", \"DEROG\", \"DELINQ\", \"CLAGE\", \"NINQ\", \"CLNO\", \"DEBTINC\"]\n", - "\n", - "target_column = \"BAD\"\n", - "x = hmeq_data[predictor_columns]\n", - "y = hmeq_data[target_column]\n", - "\n", - "x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.3, random_state=42)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "Collapsed": "false" - }, - "outputs": [], - "source": [ - "# For missing values, impute the data set's mean value\n", - "x_test.fillna(x_test.mean(), inplace=True)\n", - "x_train.fillna(x_train.mean(), inplace=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "Collapsed": "false" - }, - "source": [ - "### Create, Train, and Assess Model" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "Collapsed": "false" - }, - "outputs": [], - "source": [ - "dtc = DecisionTreeClassifier(max_depth=7, min_samples_split=2, min_samples_leaf=2, max_leaf_nodes=500)\n", - "dtc = dtc.fit(x_train, y_train)\n", - "\n", - "rfc = RandomForestClassifier(n_estimators=120, max_depth=9, max_leaf_nodes=850, min_samples_split=5, min_samples_leaf=4)\n", - "rfc = rfc.fit(x_train, y_train)\n", - "\n", - "gbc = GradientBoostingClassifier(learning_rate=0.1, n_estimators=600, max_depth=4, min_samples_leaf=1, min_samples_split=2, max_leaf_nodes=500)\n", - "gbc = gbc.fit(x_train, y_train)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "Collapsed": "false" - }, - "outputs": [], - "source": [ - "# Calculate the importance of a predictor \n", - "def sort_feature_importance(model, data):\n", - " features = {}\n", - " for importance, name in sorted(zip(model.feature_importances_, data.columns), reverse=True):\n", - " features[name] = str(np.round(importance*100, 2)) + \"%\"\n", - " return features" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "Collapsed": "false" - }, - "outputs": [], - "source": [ - "importances = pd.DataFrame.from_dict(sort_feature_importance(dtc, x_train), orient=\"index\").rename(columns={0: \"DecisionTree\"})\n", - "importances[\"RandomForest\"] = pd.DataFrame.from_dict(sort_feature_importance(rfc, x_train), orient=\"index\")\n", - "importances[\"GradientBoosting\"] = pd.DataFrame.from_dict(sort_feature_importance(gbc, x_train), orient=\"index\")\n", - "importances" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "Collapsed": "false" - }, - "outputs": [], - "source": [ - "y_dtc_predict = dtc.predict(x_test)\n", - "y_dtc_proba = dtc.predict_proba(x_test)\n", - "print(confusion_matrix(y_test, y_dtc_predict))\n", - "print(classification_report(y_test, y_dtc_predict))\n", - "print(\"Decision Tree Model Accuracy = \" + str(np.round(dtc.score(x_test, y_test)*100,2)) + \"%\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "Collapsed": "false" - }, - "outputs": [], - "source": [ - "y_rfc_predict = rfc.predict(x_test)\n", - "y_rfc_proba = rfc.predict_proba(x_test)\n", - "print(confusion_matrix(y_test, y_rfc_predict))\n", - "print(classification_report(y_test, y_rfc_predict))\n", - "print(\"Random Forest Model Accuracy = \" + str(np.round(rfc.score(x_test, y_test)*100,2)) + \"%\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "y_gbc_predict = gbc.predict(x_test)\n", - "y_gbc_proba = gbc.predict_proba(x_test)\n", - "print(confusion_matrix(y_test, y_gbc_predict))\n", - "print(classification_report(y_test, y_gbc_predict))\n", - "print(\"Gradient Boosting Model Accuracy = \" + str(np.round(gbc.score(x_test, y_test)*100,2)) + \"%\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "Collapsed": "false" - }, - "source": [ - "### Register Model in SAS Model Manager with pzmm" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "Collapsed": "false" - }, - "outputs": [], - "source": [ - "# Model names within SAS Model Manager\n", - "model_prefix = [\"DecisionTreeClassifier\", \"RandomForest\", \"GradientBoosting\"]\n", - "# Directory location for the model files\n", - "zip_folder = [Path.cwd() / \"data/hmeqModels/DecisionTreeClassifier/\",\n", - " Path.cwd() / \"data/hmeqModels/RandomForest/\",\n", - " Path.cwd() / \"data/hmeqModels/GradientBoosting\"] # Changes required by user\n", - "model = [dtc, rfc, gbc]\n", - "# Output variables expected in SAS Model Manager. If a classification value is expected to be output, it should be the first metric.\n", - "score_metrics = [\"EM_CLASSIFICATION\", \"EM_EVENTPROBABILITY\"]\n", - "\n", - "# Serialize the models to a pickle format\n", - "for (mod, prefix, path) in zip(model, model_prefix, zip_folder):\n", - " pzmm.PickleModel.pickle_trained_model(\n", - " model_prefix=prefix,\n", - " trained_model=mod,\n", - " pickle_path=path\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "Collapsed": "false" - }, - "outputs": [], - "source": [ - "def write_json_files(data, predict, target, path, prefix): \n", - " # Write input variable mapping to a json file\n", - " pzmm.JSONFiles.write_var_json(input_data=data[predict], is_input=True, json_path=path)\n", - " \n", - " # Set output variables and assign an event threshold, then write output variable mapping\n", - " output_var = pd.DataFrame(columns=score_metrics, data=[[\"A\", 0.5]]) # data argument includes example expected types for outputs\n", - " pzmm.JSONFiles.write_var_json(output_var, is_input=False, json_path=path)\n", - " \n", - " # Write model properties to a json file\n", - " pzmm.JSONFiles.write_model_properties_json(\n", - " model_name=prefix, \n", - " target_variable=target, # Target variable to make predictions about (BAD in this case)\n", - " target_values=[\"1\", \"0\"], # Possible values for the target variable (1 or 0 for binary classification of BAD)\n", - " json_path=path, \n", - " model_desc=f\"Description for the {prefix} model.\",\n", - " model_algorithm=\"\",\n", - " modeler=\"sasdemo\",\n", - " )\n", - " \n", - " # Write model metadata to a json file so that SAS Model Manager can properly identify all model files\n", - " pzmm.JSONFiles.write_file_metadata_json(model_prefix=prefix, json_path=path)\n", - "\n", - "for (prefix, path) in zip(model_prefix, zip_folder):\n", - " write_json_files(hmeq_data, predictor_columns, target_column, path, prefix)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "Collapsed": "false" - }, - "outputs": [], - "source": [ - "import getpass\n", - "def write_model_stats(x_train, y_train, test_predict, test_proba, y_test, model, path, prefix):\n", - " # Calculate train predictions\n", - " train_predict = model.predict(x_train)\n", - " train_proba = model.predict_proba(x_train)\n", - " \n", - " # Assign data to lists of actual and predicted values\n", - " train_data = pd.concat([y_train.reset_index(drop=True), pd.Series(train_predict), pd.Series(data=train_proba[:,1])], axis=1)\n", - " test_data = pd.concat([y_test.reset_index(drop=True), pd.Series(test_predict), pd.Series(data=test_proba[:,1])], axis=1)\n", - " \n", - " # Calculate the model statistics, ROC chart, and Lift chart; then write to json files\n", - " pzmm.JSONFiles.calculate_model_statistics(\n", - " target_value=1, \n", - " prob_value=0.5, \n", - " train_data=train_data, \n", - " test_data=test_data, \n", - " json_path=path\n", - " )\n", - "\n", - " full_training_data = pd.concat([y_train.reset_index(drop=True), x_train.reset_index(drop=True)], axis=1)\n", - "\n", - " pzmm.JSONFiles.generate_model_card(\n", - " model_prefix=prefix,\n", - " model_files = path,\n", - " algorithm = str(type(model).__name__),\n", - " train_data = full_training_data,\n", - " train_predictions=train_predict,\n", - " target_type='classification',\n", - " target_value=1,\n", - " interval_vars=predictor_columns,\n", - " selection_statistic='_RASE_',\n", - " )\n", - " \n", - "username = getpass.getpass()\n", - "password = getpass.getpass()\n", - "host = \"demo.sas.com\"# Changes required by user\n", - "sess = Session(host, username, password, protocol=\"http\") # For TLS-enabled servers, change protocol value to \"https\"\n", - "conn = sess.as_swat() # Connect to SWAT through the sasctl authenticated connection\n", - "\n", - "test_predict = [y_dtc_predict, y_rfc_predict, y_gbc_predict]\n", - "test_proba = [y_dtc_proba, y_rfc_proba, y_gbc_proba]\n", - "for (mod, pred, proba, path, prefix) in zip(model, test_predict, test_proba, zip_folder, model_prefix):\n", - " write_model_stats(x_train, y_train, pred, proba, y_test, mod, path, prefix)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "Collapsed": "false" - }, - "outputs": [], - "source": [ - "for (prefix, path) in zip(model_prefix, zip_folder):\n", - " pzmm.ImportModel.import_model(\n", - " model_files=path, # Where are the model files?\n", - " model_prefix=prefix, # What is the model name?\n", - " project=\"HMEQModels\", # What is the project name?\n", - " input_data=x, # What does example input data look like?\n", - " predict_method=[dtc.predict_proba, [int, int]], # What is the predict method and what does it return?\n", - " score_metrics=score_metrics, # What are the output variables?\n", - " overwrite_model=True, # Overwrite the model if it already exists?\n", - " target_values=[\"0\", \"1\"], # What are the expected values of the target variable?\n", - " target_index=1, # What is the index of the target value in target_values?\n", - " model_file_name=prefix + \".pickle\", # How was the model file serialized?\n", - " missing_values=True # Does the data include missing values?\n", - " )\n", - " # Reinitialize the score_code variable when writing more than one model's score code\n", - " pzmm.ScoreCode.score_code = \"\"" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Implementing Score Testing" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import requests\n", - "import sys\n", - "\n", - "from sasctl._services.score_definitions import ScoreDefinitions as sd # Importing ScoreDefinitions service\n", - "from sasctl._services.score_execution import ScoreExecution as se # Importing ScoreExecution service" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Creating the score definition for this model using the model UUID generated two steps before\n", - "score_definition = sd.create_score_definition(\n", - " \"example_score_def_name\", # Name of the score_definition, which can be any string\n", - " \"model_id\", # Use Model UUID generated two steps before\n", - " \"table_name\", # Table name for input data, which must exist in host server or it will throw an HTTP error and prompt you to upload a data file\n", - " # True, # Uncomment 'True' if your Viya version is compatible with CAS Gateway\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Executing the score definition\n", - "score_execution = se.create_score_execution(\n", - " score_definition.get(\"id\") # Score definition id created in the previous cell\n", - ")\n", - "\n", - "# Prints score_execution_id\n", - "print(score_execution)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can view our scored model information within Model Manager under Projects -> Choose your model -> Scoring. \n", - "***" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "base", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.0" - }, - "latex_envs": { - "LaTeX_envs_menu_present": true, - "autoclose": true, - "autocomplete": true, - "bibliofile": "biblio.bib", - "cite_by": "apalike", - "current_citInitial": 1, - "eqLabelWithNumbers": true, - "eqNumInitial": 1, - "hotkeys": { - "equation": "Ctrl-E", - "itemize": "Ctrl-I" - }, - "labels_anchors": false, - "latex_user_defs": false, - "report_style_numbering": false, - "user_envs_cfg": false - }, - "varInspector": { - "cols": { - "lenName": 16, - "lenType": 16, - "lenVar": 40 - }, - "kernels_config": { - "python": { - "delete_cmd_postfix": "", - "delete_cmd_prefix": "del ", - "library": "var_list.py", - "varRefreshCmd": "print(var_dic_list())" - }, - "r": { - "delete_cmd_postfix": ") ", - "delete_cmd_prefix": "rm(", - "library": "var_list.r", - "varRefreshCmd": "cat(var_dic_list()) " - } - }, - "types_to_exclude": [ - "module", - "function", - "builtin_function_or_method", - "instance", - "_Feature" - ], - "window_display": false - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} From b7210ab2a8f5b9265673e2789591f72854bf5da2 Mon Sep 17 00:00:00 2001 From: samyarpotlapalli Date: Tue, 22 Oct 2024 20:28:34 -0400 Subject: [PATCH 80/86] pushing correct version --- src/sasctl/_services/score_definitions.py | 1 + src/sasctl/_services/score_execution.py | 188 ++++++++++++++++++---- 2 files changed, 162 insertions(+), 27 deletions(-) diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index 6146878e..0b4d13c6 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -13,6 +13,7 @@ class ScoreDefinitions(Service): + """ Used for creating and maintaining score definitions. diff --git a/src/sasctl/_services/score_execution.py b/src/sasctl/_services/score_execution.py index 155b27f5..a9a54b90 100644 --- a/src/sasctl/_services/score_execution.py +++ b/src/sasctl/_services/score_execution.py @@ -1,12 +1,20 @@ import json +import time +import warnings +from distutils.version import StrictVersion +from typing import Union +import pandas as pd from requests import HTTPError +from .cas_management import CASManagement +from ..core import current_session from .score_definitions import ScoreDefinitions from .service import Service class ScoreExecution(Service): + """ The Score Execution API is used to produce a score by executing the mapped code generated by score objects using the score definition. @@ -18,7 +26,9 @@ class ScoreExecution(Service): """ _SERVICE_ROOT = "/scoreExecution" + _cas_management = CASManagement() _score_definitions = ScoreDefinitions() + _services = Service() ( list_executions, @@ -57,39 +67,21 @@ def create_score_execution( """ - # Gets information about the scoring object from the score definition and raises an exception if the score definition does not exist + # Gets information about the scoring object from the score definition score_definition = cls._score_definitions.get_definition(score_definition_id) if not score_definition: raise HTTPError score_exec_name = score_definition.get("name") - model_uri = score_definition.get("objectDescriptor", "uri") - model_name = score_definition.get("objectDescriptor", "name") - model_input_library = score_definition.get("inputData", "libraryName") - model_table_name = score_definition.get("inputData", "tableName") + model_uuid = score_definition.get("objectDescriptor").get("uri").split("/")[-1] + model_uri = f"/modelManagement/models/{model_uuid}" + model_name = score_definition.get("objectDescriptor").get("name") + model_input_library = score_definition.get("inputData").get("libraryName") + model_table_name = score_definition.get("inputData").get("tableName") # Defining a default output table name if none is provided if not output_table_name: output_table_name = f"{model_name}_{score_definition_id}" - # Getting all score executions that are using the inputted score_definition_id - - # score_execution = cls.list_executions( - # filter=f"eq(scoreDefinitionId, '{score_definition_id}')" - # ) - score_execution = cls.get("scoreExecution/executions", - filter=f"filter=eq(scoreExecutionRequest.scoreDefinitionId,%{score_definition_id}%27)" - ) - if not score_execution: - raise HTTPError(f"Something went wrong in the LIST_EXECUTIONS statement.") - - # Checking the count of the execution list to see if there are any score executions for this score_definition_id already running - execution_count = score_execution.get("count") # Exception catch location - if execution_count == 1: - execution_id = score_execution.get("items", 0, "id") - deleted_execution = cls.delete_execution(execution_id) - if deleted_execution.status_code >= 400: - raise HTTPError(f"Something went wrong in the DELETE statement.") - headers_score_exec = {"Content-Type": "application/json"} create_score_exec = { @@ -109,9 +101,151 @@ def create_score_execution( } # Creating the score execution - new_score_execution = cls.post( - "scoreExecution/executions", + score_execution = cls.post( + "executions", data=json.dumps(create_score_exec), headers=headers_score_exec, ) - return new_score_execution + + return score_execution + + @classmethod + def poll_score_execution_state( + cls, score_execution: Union[dict, str], timeout: int = 300 + ): + """Checks the state of the score execution. + + Parameters + -------- + score_execution: str or dict + A running score_execution. + timeout: int + Time limit for checking the score_execution state. + + Returns + ------- + String + + """ + if type(score_execution) is str: + exec_id = score_execution + else: + exec_id = score_execution.get("id") + + start_poll = time.time() + while time.time() - start_poll < timeout: + score_execution_state = cls.get(f"executions/{exec_id}/state") + if score_execution_state == "completed": + print("Score execution state is 'completed'") + return "completed" + elif score_execution_state == "failed": + # TODO: Grab score execution logs and return those + print("The score execution state is failed.") + return "failed" + elif time.time() - start_poll > timeout: + print("The score execution is still running, but polling time ran out.") + return "timeout" + + @classmethod + def get_score_execution_results( + cls, + score_execution: Union[dict, str], + ): + """Generates an output table for the score_execution results. + + Parameters + -------- + score_execution: str or dict + A running score_execution. + + Returns + ------- + Table reference + + """ + try: + import swat + except ImportError: + swat = None + + if type(score_execution) is str: + score_execution = cls.get_execution(score_execution) + + server_name = score_execution.get("outputTable").get("serverName") + library_name = score_execution.get("outputTable").get("libraryName") + table_name = score_execution.get("outputTable").get("tableName") + + # If swat is not available, then + if not swat: + output_table = cls._no_gateway_get_results( + server_name, library_name, table_name + ) + return output_table + else: + session = current_session() + cas = session.as_swat() + response = cas.loadActionSet("gateway") + if not response: + output_table = cls._no_gateway_get_results( + server_name, library_name, table_name + ) + return output_table + else: + gateway_code = f""" +import pandas as pd +import numpy as np + +table = gateway.read_table({{"caslib": "{library_name}", "name": "{table_name}"}}) + +gateway.return_table("Execution Results", df = table, label = "label", title = "title")""" + + output_table = cas.gateway.runlang( + code=gateway_code, single=True, timeout_millis=10000 + ) + output_table = pd.DataFrame(output_table["Execution Results"]) + return output_table + + @classmethod + def _no_gateway_get_results(cls, server_name, library_name, table_name): + """Helper method that builds the output table. + + Parameters + -------- + server_name: str + CAS server where original table is stored. + library_name: CAS library where original table is stored. + table_name: Table that contains row and columns information to build the output table + + Returns + ------- + Pandas Dataframe + + """ + if pd.__version__ >= StrictVersion("1.0.3"): + from pandas import json_normalize + else: + from pandas.io.json import json_normalize + + warnings.warn( + "Without swat installed, the amount of rows from the output table that " + "can be collected are memory limited by the CAS worker." + ) + + output_columns = cls._cas_management.get( + f"servers/{server_name}/" + f"caslibs/{library_name}/" + f"tables/{table_name}/columns?limit=10000" + ) + columns = json_normalize(output_columns.json(), "items") + column_names = columns["names"].to_list() + + output_rows = cls._services.get( + f"casRowSets/servers/{server_name}" + f"caslibs/{library_name}" + f"tables/{table_name}/rows?limit=10000" + ) + output_table = pd.DataFrame( + json_normalize(output_rows.json()["items"])["cells"].to_list(), + columns=column_names, + ) + return output_table From b3f4358dcc9ab572cd0332cafa033a1d8e8ec1bc Mon Sep 17 00:00:00 2001 From: djm21 Date: Tue, 22 Oct 2024 17:36:10 -0700 Subject: [PATCH 81/86] Use gateway with score_model_with_cas call --- src/sasctl/tasks.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/src/sasctl/tasks.py b/src/sasctl/tasks.py index 26ad159d..b3f5a7d4 100644 --- a/src/sasctl/tasks.py +++ b/src/sasctl/tasks.py @@ -980,6 +980,7 @@ def score_model_with_cas( server_name: str = "cas-shared-default", library_name: str = "Public", model_version: str = "latest", + use_cas_gateway: bool = False ): score_definition = sd.create_score_definition( score_def_name, @@ -990,6 +991,7 @@ def score_model_with_cas( server_name=server_name, library_name=library_name, model_version=model_version, + use_cas_gateway=use_cas_gateway ) score_execution = se.create_score_execution(score_definition.id) score_execution_poll = se.poll_score_execution_state(score_execution) From fa4de17a3f6650bed7cc09017df1b9d5bd88e180 Mon Sep 17 00:00:00 2001 From: djm21 Date: Mon, 28 Oct 2024 15:29:51 -0700 Subject: [PATCH 82/86] black reformatting --- src/sasctl/_services/score_definitions.py | 1 - src/sasctl/_services/score_execution.py | 1 - src/sasctl/tasks.py | 4 ++-- 3 files changed, 2 insertions(+), 4 deletions(-) diff --git a/src/sasctl/_services/score_definitions.py b/src/sasctl/_services/score_definitions.py index 0b4d13c6..6146878e 100644 --- a/src/sasctl/_services/score_definitions.py +++ b/src/sasctl/_services/score_definitions.py @@ -13,7 +13,6 @@ class ScoreDefinitions(Service): - """ Used for creating and maintaining score definitions. diff --git a/src/sasctl/_services/score_execution.py b/src/sasctl/_services/score_execution.py index a9a54b90..eeac893e 100644 --- a/src/sasctl/_services/score_execution.py +++ b/src/sasctl/_services/score_execution.py @@ -14,7 +14,6 @@ class ScoreExecution(Service): - """ The Score Execution API is used to produce a score by executing the mapped code generated by score objects using the score definition. diff --git a/src/sasctl/tasks.py b/src/sasctl/tasks.py index b3f5a7d4..1da7d3fb 100644 --- a/src/sasctl/tasks.py +++ b/src/sasctl/tasks.py @@ -980,7 +980,7 @@ def score_model_with_cas( server_name: str = "cas-shared-default", library_name: str = "Public", model_version: str = "latest", - use_cas_gateway: bool = False + use_cas_gateway: bool = False, ): score_definition = sd.create_score_definition( score_def_name, @@ -991,7 +991,7 @@ def score_model_with_cas( server_name=server_name, library_name=library_name, model_version=model_version, - use_cas_gateway=use_cas_gateway + use_cas_gateway=use_cas_gateway, ) score_execution = se.create_score_execution(score_definition.id) score_execution_poll = se.poll_score_execution_state(score_execution) From 58ececb8d0deab54d3793f8687e6209774e7b94f Mon Sep 17 00:00:00 2001 From: Scott-Lindauer_sasinst Date: Tue, 29 Oct 2024 14:02:55 -0400 Subject: [PATCH 83/86] fix: revert examples back to their state on the main branch --- .../DecisionTreeClassifier.pickle | Bin 9036 -> 8180 bytes .../DecisionTreeClassifier.zip | Bin 451495 -> 439383 bytes .../DecisionTreeClassifier2.pickle | Bin 0 -> 9019 bytes .../DecisionTreeClassifier2.zip | Bin 0 -> 462645 bytes .../ModelProperties.json | 13 +- .../DecisionTreeClassifier/dmcas_fitstat.json | 16 +- .../DecisionTreeClassifier/dmcas_lift.json | 364 +- .../DecisionTreeClassifier/dmcas_roc.json | 3586 ++++----- .../score_DecisionTreeClassifier.py | 95 +- .../score_DecisionTreeClassifier2.py | 55 + .../GradientBoosting/GradientBoosting.pickle | Bin 1350424 -> 1214738 bytes .../GradientBoosting/GradientBoosting.zip | Bin 1792885 -> 1644992 bytes .../GradientBoosting/GradientBoosting2.pickle | Bin 0 -> 1348098 bytes .../GradientBoosting/GradientBoosting2.zip | Bin 0 -> 3007583 bytes .../GradientBoosting/ModelProperties.json | 13 +- .../GradientBoosting/dmcas_fitstat.json | 22 +- .../GradientBoosting/dmcas_lift.json | 314 +- .../GradientBoosting/dmcas_roc.json | 3190 ++++---- .../score_GradientBoosting.py | 95 +- .../score_GradientBoosting2.py | 55 + .../RandomForest/ModelProperties.json | 13 +- .../RandomForest/RandomForest.pickle | Bin 1805903 -> 1609252 bytes .../hmeqModels/RandomForest/RandomForest.zip | Bin 2248588 -> 2039934 bytes .../RandomForest/RandomForest2.pickle | Bin 0 -> 1784860 bytes .../hmeqModels/RandomForest/RandomForest2.zip | Bin 0 -> 3837665 bytes .../RandomForest/dmcas_fitstat.json | 30 +- .../hmeqModels/RandomForest/dmcas_lift.json | 700 +- .../hmeqModels/RandomForest/dmcas_roc.json | 6776 ++++++++--------- .../RandomForest/score_RandomForest.py | 95 +- .../RandomForest/score_RandomForest2.py | 55 + .../pzmm_generate_complete_model_card.ipynb | 1794 +++++ examples/pzmm_regression_model_import.ipynb | 9 +- 32 files changed, 9668 insertions(+), 7622 deletions(-) create mode 100644 examples/data/hmeqModels/DecisionTreeClassifier/DecisionTreeClassifier2.pickle create mode 100644 examples/data/hmeqModels/DecisionTreeClassifier/DecisionTreeClassifier2.zip create mode 100644 examples/data/hmeqModels/DecisionTreeClassifier/score_DecisionTreeClassifier2.py create mode 100644 examples/data/hmeqModels/GradientBoosting/GradientBoosting2.pickle create mode 100644 examples/data/hmeqModels/GradientBoosting/GradientBoosting2.zip create mode 100644 examples/data/hmeqModels/GradientBoosting/score_GradientBoosting2.py create mode 100644 examples/data/hmeqModels/RandomForest/RandomForest2.pickle create mode 100644 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"cas-shared-default/Public/DecisionTreeClassifier_train_data", + "trainTable": "", "trainCodeType": "Python", - "algorithm": "DecisionTreeClassifier", + "algorithm": "", "function": "Classification", "targetVariable": "BAD", "targetEvent": "1", - "targetLevel": "Binary", + "targetLevel": "BINARY", "eventProbVar": "P_1", "modeler": "sasdemo", "tool": "Python 3", - "toolVersion": "3.11.7", - "properties": [], - "eventPercentage": "0.20182166826462", - "selectionStatistic": "_RASE_", - "selectionStatisticValue": "0.33514616799162" + "toolVersion": "3.8.16", + "properties": [] } \ No newline at end of file diff --git a/examples/data/hmeqModels/DecisionTreeClassifier/dmcas_fitstat.json b/examples/data/hmeqModels/DecisionTreeClassifier/dmcas_fitstat.json index 3b0f0cdb..163db488 100644 --- a/examples/data/hmeqModels/DecisionTreeClassifier/dmcas_fitstat.json +++ b/examples/data/hmeqModels/DecisionTreeClassifier/dmcas_fitstat.json @@ -222,14 +222,13 @@ "_MCE_": 0.88710450623202, "_ASE_": 0.11232295391947, "_MCLL_": 0.99896429012045, - "_KS_": 1.0, + "_KS_": null, "_KSPostCutoff_": null, "_DIV_": 4172.0, "_TAU_": null, "_KSCut_": null, - "_C_": 0.85770092470509, - "_PartInd_": null, - "_KS2_": 0.71540184941018 + "_C_": null, + "_PartInd_": null }, "rowNumber": 2, "header": null @@ -244,15 +243,14 @@ "_DataRole_": "TEST", "_MCE_": 0.99328859060402, "_ASE_": 0.10439243746467, - "_MCLL_": 0.1674139049754, - "_KS_": 1.0, + "_MCLL_": 0.18029189766592, + "_KS_": null, "_KSPostCutoff_": null, "_DIV_": 1788.0, "_TAU_": null, "_KSCut_": null, - "_C_": 0.83803076656035, - "_PartInd_": null, - "_KS2_": 0.6760615331207 + "_C_": null, + "_PartInd_": null }, "rowNumber": 3, "header": null diff --git a/examples/data/hmeqModels/DecisionTreeClassifier/dmcas_lift.json b/examples/data/hmeqModels/DecisionTreeClassifier/dmcas_lift.json index 47531d9d..1ba21ee6 100644 --- a/examples/data/hmeqModels/DecisionTreeClassifier/dmcas_lift.json +++ b/examples/data/hmeqModels/DecisionTreeClassifier/dmcas_lift.json @@ -1569,24 +1569,24 @@ "_column_": "predict", "_RespBest_": 100.0, "_DataRole_": "TEST", - "_CumResp_": 21.7739353186039, - "_PctRespBest_": 90.0, - "_Gain_": 3.35478706372078, - "_CumLift_": 4.35478706372078, + "_CumResp_": 21.8566849075543, + "_PctRespBest_": 98.8888888888889, + "_Gain_": 3.37133698151086, + "_CumLift_": 4.37133698151086, "_Event_": "1", "_TargetName_": null, - "_PctResp_": 19.5965417867435, + "_PctResp_": 21.6138328530259, "_GainBest_": 19.0, "_CumLiftBest_": 20.0, - "_Lift_": 4.35478706372078, - "_CumPctResp_": 19.5965417867435, - "_NEventsBest_": 81.0, - "_CumPctRespBest_": 90.0, + "_Lift_": 4.37133698151086, + "_CumPctResp_": 21.6138328530259, + "_NEventsBest_": 89.0, + "_CumPctRespBest_": 98.8888888888889, "_Value_": 1.0, - "_NEvents_": 17.6368876080691, + "_NEvents_": 19.4524495677233, "_LiftBest_": 20.0, "_PartInd_": "2", - "_Resp_": 21.7739353186039, + "_Resp_": 21.8566849075543, "_Column_": "actual" }, "rowNumber": 44 @@ -1600,24 +1600,24 @@ "_column_": "predict", "_RespBest_": 0.0, "_DataRole_": "TEST", - "_CumResp_": 43.5478706372078, + "_CumResp_": 43.7133698151086, "_PctRespBest_": 0.0, - "_Gain_": 3.35478706372078, - "_CumLift_": 4.35478706372078, + "_Gain_": 3.37133698151086, + "_CumLift_": 4.37133698151086, "_Event_": "1", "_TargetName_": null, - "_PctResp_": 19.5965417867435, + "_PctResp_": 21.6138328530259, "_GainBest_": 9.0, "_CumLiftBest_": 10.0, - "_Lift_": 4.35478706372078, - "_CumPctResp_": 19.5965417867435, + "_Lift_": 4.37133698151086, + "_CumPctResp_": 21.6138328530259, "_NEventsBest_": 0.0, - "_CumPctRespBest_": 45.0, + "_CumPctRespBest_": 49.4444444444444, "_Value_": 1.0, - "_NEvents_": 17.6368876080691, + "_NEvents_": 19.4524495677233, "_LiftBest_": 0.0, "_PartInd_": "2", - "_Resp_": 21.7739353186039, + "_Resp_": 21.8566849075543, "_Column_": "actual" }, "rowNumber": 45 @@ -1631,24 +1631,24 @@ "_column_": "predict", "_RespBest_": 0.0, "_DataRole_": "TEST", - "_CumResp_": 65.3218059558117, + "_CumResp_": 65.5700547226629, "_PctRespBest_": 0.0, - "_Gain_": 3.35478706372078, - "_CumLift_": 4.35478706372078, + "_Gain_": 3.37133698151086, + "_CumLift_": 4.37133698151086, "_Event_": "1", "_TargetName_": null, - "_PctResp_": 19.5965417867435, + "_PctResp_": 21.6138328530259, "_GainBest_": 5.66666666666666, "_CumLiftBest_": 6.66666666666666, - "_Lift_": 4.35478706372078, - "_CumPctResp_": 19.5965417867435, + "_Lift_": 4.37133698151086, + "_CumPctResp_": 21.6138328530259, "_NEventsBest_": 0.0, - "_CumPctRespBest_": 30.0, + "_CumPctRespBest_": 32.9629629629629, "_Value_": 1.0, - "_NEvents_": 17.6368876080691, + "_NEvents_": 19.4524495677233, "_LiftBest_": 0.0, "_PartInd_": "2", - "_Resp_": 21.7739353186039, + "_Resp_": 21.8566849075543, "_Column_": "actual" }, "rowNumber": 46 @@ -1662,24 +1662,24 @@ "_column_": "predict", "_RespBest_": 0.0, "_DataRole_": "TEST", - "_CumResp_": 84.0954069961703, + "_CumResp_": 84.4115743592542, "_PctRespBest_": 0.0, - "_Gain_": 3.20477034980851, - "_CumLift_": 4.20477034980851, + "_Gain_": 3.22057871796271, + "_CumLift_": 4.22057871796271, "_Event_": "1", "_TargetName_": null, - "_PctResp_": 16.8962409363227, + "_PctResp_": 18.6321694184069, "_GainBest_": 4.0, "_CumLiftBest_": 5.0, - "_Lift_": 3.75472020807172, - "_CumPctResp_": 18.9214665741383, + "_Lift_": 3.76830392731826, + "_CumPctResp_": 20.8684169943711, "_NEventsBest_": 0.0, - "_CumPctRespBest_": 22.5, + "_CumPctRespBest_": 24.7222222222222, "_Value_": 0.0, - "_NEvents_": 15.2066168426904, + "_NEvents_": 16.7689524765662, "_LiftBest_": 0.0, "_PartInd_": "2", - "_Resp_": 18.7736010403586, + "_Resp_": 18.8415196365913, "_Column_": "actual" }, "rowNumber": 47 @@ -1693,24 +1693,24 @@ "_column_": "predict", "_RespBest_": 0.0, "_DataRole_": "TEST", - "_CumResp_": 85.0977973115377, + "_CumResp_": 85.3940381601416, "_PctRespBest_": 0.0, - "_Gain_": 2.40391189246151, - "_CumLift_": 3.40391189246151, + "_Gain_": 2.41576152640566, + "_CumLift_": 3.41576152640566, "_Event_": "1", "_TargetName_": null, - "_PctResp_": 0.90215128383067, + "_PctResp_": 0.97154753643303, "_GainBest_": 3.0, "_CumLiftBest_": 4.0, - "_Lift_": 0.20047806307348, - "_CumPctResp_": 15.3176035160768, + "_Lift_": 0.19649276017746, + "_CumPctResp_": 16.8890431027835, "_NEventsBest_": 0.0, - "_CumPctRespBest_": 18.0, + "_CumPctRespBest_": 19.7777777777777, "_Value_": 0.0, - "_NEvents_": 0.8119361554476, + "_NEvents_": 0.87439278278972, "_LiftBest_": 0.0, "_PartInd_": "2", - "_Resp_": 1.00239031536741, + "_Resp_": 0.98246380088733, "_Column_": "actual" }, "rowNumber": 48 @@ -1724,24 +1724,24 @@ "_column_": "predict", "_RespBest_": 0.0, "_DataRole_": "TEST", - "_CumResp_": 86.1001876269052, + "_CumResp_": 86.3765019610289, "_PctRespBest_": 0.0, - "_Gain_": 1.87000625423017, - "_CumLift_": 2.87000625423017, + "_Gain_": 1.87921673203429, + "_CumLift_": 2.87921673203429, "_Event_": "1", "_TargetName_": null, - "_PctResp_": 0.90215128383067, + "_PctResp_": 0.97154753643303, "_GainBest_": 2.33333333333333, "_CumLiftBest_": 3.33333333333333, - "_Lift_": 0.20047806307348, - "_CumPctResp_": 12.9150281440357, + "_Lift_": 0.19649276017746, + "_CumPctResp_": 14.2361271750584, "_NEventsBest_": 0.0, - "_CumPctRespBest_": 15.0, + "_CumPctRespBest_": 16.4814814814814, "_Value_": 0.0, - "_NEvents_": 0.8119361554476, + "_NEvents_": 0.87439278278972, "_LiftBest_": 0.0, "_PartInd_": "2", - "_Resp_": 1.00239031536741, + "_Resp_": 0.98246380088733, "_Column_": "actual" }, "rowNumber": 49 @@ -1755,24 +1755,24 @@ "_column_": "predict", "_RespBest_": 0.0, "_DataRole_": "TEST", - "_CumResp_": 87.1025779422726, + "_CumResp_": 87.3589657619162, "_PctRespBest_": 0.0, - "_Gain_": 1.48864508406493, - "_CumLift_": 2.48864508406493, + "_Gain_": 1.49597045034046, + "_CumLift_": 2.49597045034046, "_Event_": "1", "_TargetName_": null, - "_PctResp_": 0.90215128383067, + "_PctResp_": 0.97154753643303, "_GainBest_": 1.85714285714285, 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b/examples/data/hmeqModels/DecisionTreeClassifier/score_DecisionTreeClassifier.py @@ -16,40 +16,73 @@ def score(LOAN, MORTDUE, VALUE, YOJ, DEROG, DELINQ, CLAGE, NINQ, CLNO, DEBTINC): global model except NameError: with open(Path(settings.pickle_path) / "DecisionTreeClassifier.pickle", "rb") as pickle_model: - model = pickle.load(pickle_model) + model = pickle.load(pickle_model) - index=None - if not isinstance(LOAN, pd.Series): - index=[0] - input_array = pd.DataFrame( - {"LOAN": LOAN, "MORTDUE": MORTDUE, "VALUE": VALUE, "YOJ": YOJ, "DEROG": DEROG, - "DELINQ": DELINQ, "CLAGE": CLAGE, "NINQ": NINQ, "CLNO": CLNO, "DEBTINC": - DEBTINC}, index=index - ) - input_array = impute_missing_values(input_array) - prediction = model.predict_proba(input_array).tolist() + + try: + if math.isnan(LOAN): + LOAN = 18607.96979865772 + except TypeError: + LOAN = 18607.96979865772 + try: + if math.isnan(MORTDUE): + MORTDUE = 73760.817199559 + except TypeError: + MORTDUE = 73760.817199559 + try: + if math.isnan(VALUE): + VALUE = 101776.04874145007 + except TypeError: + VALUE = 101776.04874145007 + try: + if math.isnan(YOJ): + YOJ = 8.922268135904499 + except TypeError: + YOJ = 8.922268135904499 + try: + if math.isnan(DEROG): + DEROG = 0.2545696877380046 + except TypeError: + DEROG = 0.2545696877380046 + try: + if math.isnan(DELINQ): + DELINQ = 0.4494423791821561 + except TypeError: + DELINQ = 0.4494423791821561 + try: + if math.isnan(CLAGE): + CLAGE = 179.7662751900465 + except TypeError: + CLAGE = 179.7662751900465 + try: + if math.isnan(NINQ): + NINQ = 1.1860550458715597 + except TypeError: + NINQ = 1.1860550458715597 + try: + if math.isnan(CLNO): + CLNO = 21.29609620076682 + except TypeError: + CLNO = 21.29609620076682 + try: + if math.isnan(DEBTINC): + DEBTINC = 33.779915349235246 + except TypeError: + DEBTINC = 33.779915349235246 + + input_array = pd.DataFrame([[LOAN, MORTDUE, VALUE, YOJ, DEROG, DELINQ, CLAGE, NINQ, CLNO, DEBTINC]], + columns=["LOAN", "MORTDUE", "VALUE", "YOJ", "DEROG", "DELINQ", "CLAGE", "NINQ", "CLNO", "DEBTINC"], + dtype=float) + prediction = model.predict_proba(input_array) # Check for numpy values and convert to a CAS readable representation if isinstance(prediction, np.ndarray): - prediction = prediction.tolist() - - if input_array.shape[0] == 1: - if prediction[0][1] > 0.5: - EM_CLASSIFICATION = "1" - else: - EM_CLASSIFICATION = "0" - return EM_CLASSIFICATION, prediction[0][1] + prediction = prediction.tolist()[0] + + if prediction[0] > prediction[1]: + EM_CLASSIFICATION = "1" else: - df = pd.DataFrame(prediction) - proba = df[1] - classifications = np.where(df[1] > 0.5, '1', '0') - return pd.DataFrame({'EM_CLASSIFICATION': classifications, 'EM_EVENTPROBABILITY': proba}) - -def impute_missing_values(data): - impute_values = \ - {'DEBTINC': 33.779915349235246, 'LOAN': 18607.96979865772, 'DELINQ': - 0.4494423791821561, 'YOJ': 8.922268135904499, 'NINQ': 1.1860550458715597, - 'VALUE': 101776.04874145007, 'DEROG': 0.2545696877380046, 'CLNO': - 21.29609620076682, 'CLAGE': 179.7662751900465, 'MORTDUE': 73760.817199559} - return data.replace(' .', np.nan).fillna(impute_values).apply(pd.to_numeric, errors='ignore') + EM_CLASSIFICATION = "0" + + return EM_CLASSIFICATION, prediction[0] \ No newline at end of file diff --git a/examples/data/hmeqModels/DecisionTreeClassifier/score_DecisionTreeClassifier2.py b/examples/data/hmeqModels/DecisionTreeClassifier/score_DecisionTreeClassifier2.py new file mode 100644 index 00000000..0a5554a9 --- /dev/null +++ b/examples/data/hmeqModels/DecisionTreeClassifier/score_DecisionTreeClassifier2.py @@ -0,0 +1,55 @@ +import math +import pickle +import pandas as pd +import numpy as np +from pathlib import Path + +import settings + +with open(Path(settings.pickle_path) / "DecisionTreeClassifier2.pickle", "rb") as pickle_model: + model = pickle.load(pickle_model) + +def score(LOAN, MORTDUE, VALUE, YOJ, DEROG, DELINQ, CLAGE, NINQ, CLNO, DEBTINC): + "Output: EM_CLASSIFICATION, EM_EVENTPROBABILITY" + + try: + global model + except NameError: + with open(Path(settings.pickle_path) / "DecisionTreeClassifier2.pickle", "rb") as pickle_model: + model = pickle.load(pickle_model) + + + index=None + if not isinstance(LOAN, pd.Series): + index=[0] + input_array = pd.DataFrame( + {"LOAN": LOAN, "MORTDUE": MORTDUE, "VALUE": VALUE, "YOJ": YOJ, "DEROG": DEROG, + "DELINQ": DELINQ, "CLAGE": CLAGE, "NINQ": NINQ, "CLNO": CLNO, "DEBTINC": + DEBTINC}, index=index + ) + input_array = impute_missing_values(input_array) + prediction = model.predict_proba(input_array).tolist() + + # Check for numpy values and convert to a CAS readable representation + if isinstance(prediction, np.ndarray): + prediction = prediction.tolist() + + if input_array.shape[0] == 1: + if prediction[0][1] > 0.5: + EM_CLASSIFICATION = "1" + else: + EM_CLASSIFICATION = "0" + return EM_CLASSIFICATION, prediction[0][1] + else: + df = pd.DataFrame(prediction) + proba = df[1] + classifications = np.where(df[1] > 0.5, '1', '0') + return pd.DataFrame({'EM_CLASSIFICATION': classifications, 'EM_EVENTPROBABILITY': proba}) + +def impute_missing_values(data): + impute_values = \ + {'VALUE': 101776.04874145007, 'DEBTINC': 33.779915349235246, 'NINQ': + 1.1860550458715597, 'DELINQ': 0.4494423791821561, 'CLAGE': 179.7662751900465, + 'MORTDUE': 73760.817199559, 'DEROG': 0.2545696877380046, 'YOJ': + 8.922268135904499, 'CLNO': 21.29609620076682, 'LOAN': 18607.96979865772} + return data.replace(' .', np.nan).fillna(impute_values).apply(pd.to_numeric, errors='ignore') diff --git a/examples/data/hmeqModels/GradientBoosting/GradientBoosting.pickle b/examples/data/hmeqModels/GradientBoosting/GradientBoosting.pickle index e2d06bbeb62225be73b848ec4f46fd79febd2789..28b393bc331ac48746037322a975f5fccf825505 100644 GIT binary patch literal 1214738 zcmdpfc|29$*Z(ypR8peBkVue4kGD^ZfIBef)8cbI)0Ouf6u(YrXecYwt^D4*AH!K%)KyEOxT8 zHZ^p#-C}C%WNKq%ZMsGOq)~9dG6hFN6AM#Y=Y4i|PRhw;h`P$gg)DYneQ>L-8y}qHf 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