Merge branch 'develop' into misc/rename-nlp-example

CONTRIBUTING.md

@@ -50,15 +50,17 @@ general guidelines that cover both:
 A friendly ping in the comment thread to the submitter or a contributor can help
 draw attention if your issue is blocking.
 
+### Good First Issues for New Contributors
+
 The best way to start is to check the
-[`good-first-issue`](https://github.com/zenml-io/zenml/labels/good%20first%20issue)
+[`good-first-issue`](https://github.com/issues?q=is%3Aopen+is%3Aissue+archived%3Afalse+user%3Azenml-io+label%3A%22good+first+issue%22)
 label on the issue board. The core team creates these issues as necessary
 smaller tasks that you can work on to get deeper into ZenML internals. These
 should generally require relatively simple changes, probably affecting just one
 or two files which we think are ideal for people new to ZenML.
 
 The next step after that would be to look at the
-[`good-second-issue`](https://github.com/zenml-io/zenml/labels/good%20second%20issue)
+[`good-second-issue`](https://github.com/issues?q=is%3Aopen+is%3Aissue+archived%3Afalse+user%3Azenml-io+label%3A%22good+second+issue%22)
 label on the issue board. These are a bit more complex, might involve more
 files, but should still be well-defined and achievable to people relatively new
 to ZenML.

README.md

@@ -84,7 +84,9 @@
     ·
     <a href="https://zenml.io/discussion">Vote New Features</a>
     ·
-    <a href="https://blog.zenml.io/">Read Blog</a>
+    <a href="https://www.zenml.io/blog">Read Blog</a>
+    ·
+    <a href="https://github.com/issues?q=is%3Aopen+is%3Aissue+archived%3Afalse+user%3Azenml-io+label%3A%22good+first+issue%22">Contribute to Open Source</a>
     ·
     <a href="https://www.zenml.io/company#team">Meet the Team</a>
     <br />
@@ -277,9 +279,10 @@ and you can directly influence the roadmap as follows:
 
 # 🙌 Contributing and Community
 
-We would love to develop ZenML together with our community! Best way to get
+We would love to develop ZenML together with our community! The best way to get
 started is to select any issue from the [`good-first-issue`
-label](https://github.com/zenml-io/zenml/labels/good%20first%20issue). If you
+label](https://github.com/issues?q=is%3Aopen+is%3Aissue+archived%3Afalse+user%3Azenml-io+label%3A%22good+first+issue%22)
+and open up a Pull Request! If you
 would like to contribute, please review our [Contributing
 Guide](CONTRIBUTING.md) for all relevant details.
 

pyproject.toml

@@ -162,7 +162,7 @@ types-psutil = { version = "^5.8.13", optional = true }
 types-passlib = { version = "^1.7.7", optional = true }
 
 # mlstacks dependencies
-mlstacks = { version = "0.7.11", optional = true }
+mlstacks = { version = "0.8.0", optional = true }
 
 [tool.poetry.extras]
 server = [

src/zenml/__init__.py

@@ -42,6 +42,7 @@
     save_artifact,
     load_artifact,
 )
+from zenml.model.utils import log_model_metadata
 from zenml.artifacts.artifact_config import ArtifactConfig
 from zenml.artifacts.external_artifact import ExternalArtifact
 from zenml.model.model_version import ModelVersion
@@ -57,6 +58,7 @@
     "get_step_context",
     "load_artifact",
     "log_artifact_metadata",
+    "log_model_metadata",
     "ModelVersion",
     "pipeline",
     "save_artifact",

src/zenml/model/utils.py

@@ -125,6 +125,33 @@ def log_model_version_metadata(
 
     This function can be used to log metadata for existing model versions.
 
+    Args:
+        metadata: The metadata to log.
+        model_name: The name of the model to log metadata for. Can
+            be omitted when being called inside a step with configured
+            `model_version` in decorator.
+        model_version: The version of the model to log metadata for. Can
+            be omitted when being called inside a step with configured
+            `model_version` in decorator.
+    """
+    logger.warning(
+        "`log_model_version_metadata` is deprecated. Please use "
+        "`log_model_metadata` instead."
+    )
+    log_model_metadata(
+        metadata=metadata, model_name=model_name, model_version=model_version
+    )
+
+
+def log_model_metadata(
+    metadata: Dict[str, "MetadataType"],
+    model_name: Optional[str] = None,
+    model_version: Optional[Union[ModelStages, int, str]] = None,
+) -> None:
+    """Log model version metadata.
+
+    This function can be used to log metadata for existing model versions.
+
     Args:
         metadata: The metadata to log.
         model_name: The name of the model to log metadata for. Can

src/zenml/models/v2/base/scoped.py

@@ -175,15 +175,10 @@ def apply_filter(
         Returns:
             The query with filter applied.
         """
-        from sqlmodel import or_
-
         query = super().apply_filter(query=query, table=table)
 
         if self.scope_user:
-            scope_filter = or_(
-                getattr(table, "user_id") == self.scope_user,
-            )
-            query = query.where(scope_filter)
+            query = query.where(getattr(table, "user_id") == self.scope_user)
 
         return query
 

src/zenml/zen_stores/schemas/component_schemas.py

@@ -86,9 +86,9 @@ class StackComponentSchema(NamedSchema, table=True):
         back_populates="stack_component",
     )
 
-    run_or_step_logs: Optional["LogsSchema"] = Relationship(
+    run_or_step_logs: List["LogsSchema"] = Relationship(
         back_populates="artifact_store",
-        sa_relationship_kwargs={"cascade": "delete", "uselist": False},
+        sa_relationship_kwargs={"cascade": "delete", "uselist": True},
     )
 
     connector_id: Optional[UUID] = build_foreign_key_field(

src/zenml/zen_stores/schemas/pipeline_run_schemas.py

@@ -223,8 +223,6 @@ def to_model(self, hydrate: bool = False) -> "PipelineRunResponse":
         }
 
         if self.deployment is not None:
-            steps = {s.name: s.to_model() for s in self.step_runs}
-
             deployment = self.deployment.to_model()
 
             config = deployment.pipeline_configuration
@@ -237,8 +235,6 @@ def to_model(self, hydrate: bool = False) -> "PipelineRunResponse":
             code_reference = deployment.code_reference
 
         elif self.pipeline_configuration is not None:
-            steps = {step.name: step.to_model() for step in self.step_runs}
-
             config = PipelineConfiguration.parse_raw(
                 self.pipeline_configuration
             )
@@ -274,6 +270,8 @@ def to_model(self, hydrate: bool = False) -> "PipelineRunResponse":
         )
         metadata = None
         if hydrate:
+            steps = {step.name: step.to_model() for step in self.step_runs}
+
             metadata = PipelineRunResponseMetadata(
                 workspace=self.workspace.to_model(),
                 run_metadata=run_metadata,

src/zenml/zen_stores/sql_zen_store.py

@@ -5453,13 +5453,14 @@ def _update_pipeline_run_status(
         )
 
         if new_status != pipeline_run.status:
-            pipeline_run.status = new_status
+            run_update = PipelineRunUpdate(status=new_status)
             if new_status in {
                 ExecutionStatus.COMPLETED,
                 ExecutionStatus.FAILED,
             }:
-                pipeline_run.end_time = datetime.utcnow()
+                run_update.end_time = datetime.utcnow()
 
+            pipeline_run.update(run_update)
             session.add(pipeline_run)
 
     # ----------------------------- Users -----------------------------

tests/integration/functional/model/test_model_version.py

@@ -20,7 +20,7 @@
 from zenml.client import Client
 from zenml.enums import ModelStages
 from zenml.model.model_version import ModelVersion
-from zenml.model.utils import log_model_version_metadata
+from zenml.model.utils import log_model_metadata
 from zenml.models import TagRequest
 
 MODEL_NAME = "super_model"
@@ -64,7 +64,7 @@ def __exit__(self, exc_type, exc_value, exc_traceback):
 @step
 def step_metadata_logging_functional():
     """Functional logging using implicit ModelVersion from context."""
-    log_model_version_metadata({"foo": "bar"})
+    log_model_metadata({"foo": "bar"})
     assert get_step_context().model_version.metadata["foo"] == "bar"
 
 
@@ -357,17 +357,17 @@ def test_metadata_logging_functional(self, clean_client: "Client"):
         )
         mv._get_or_create_model_version()
 
-        log_model_version_metadata(
+        log_model_metadata(
             {"foo": "bar"}, model_name=mv.name, model_version=mv.number
         )
 
         assert len(mv.metadata) == 1
         assert mv.metadata["foo"] == "bar"
 
         with pytest.raises(ValueError):
-            log_model_version_metadata({"foo": "bar"})
+            log_model_metadata({"foo": "bar"})
 
-        log_model_version_metadata(
+        log_model_metadata(
             {"bar": "foo"}, model_name=mv.name, model_version="latest"
         )