From 97e9af63b537d8adfb73f65917ad4641b6ddc32d Mon Sep 17 00:00:00 2001 From: Gaurav Mishra Date: Thu, 2 Nov 2023 17:10:53 +0530 Subject: [PATCH 1/2] chore(repo): make reuse compliant Make the repo reuse compliant. Also, reformat the files. --- .gitignore | 5 +- .reuse/dep5 | 40 ++ LICENSES/LGPL-2.1-only.txt | 504 ++++++++++++++++++ README.md | 8 +- Safaa/MANIFEST.in | 5 + Safaa/setup.py | 18 +- Safaa/src/safaa/Safaa.py | 162 +++--- Safaa/src/safaa/__init__.py | 3 + Safaa/src/safaa/configs/train.cfg | 5 +- Safaa/src/safaa/models/__init__.py | 3 + .../safaa/models/declutter_model/config.cfg | 9 +- .../safaa/models/entity_recognizer/config.cfg | 9 +- datasets/README.md | 10 +- utility/NER/data_conversion.py | 53 +- utility/false_positive_detection/test.py | 33 +- utility/false_positive_detection/train.py | 32 +- 16 files changed, 779 insertions(+), 120 deletions(-) create mode 100644 .reuse/dep5 create mode 100644 LICENSES/LGPL-2.1-only.txt diff --git a/.gitignore b/.gitignore index 68bc17f..dca973e 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,6 @@ +# SPDX-FileCopyrightText: © 2023 abdelrahmanjamal5565@gmail.com +# +# SPDX-License-Identifier: LGPL-2.1-only # Byte-compiled / optimized / DLL files __pycache__/ *.py[cod] @@ -157,4 +160,4 @@ cython_debug/ # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore # and can be added to the global gitignore or merged into this file. For a more nuclear # option (not recommended) you can uncomment the following to ignore the entire idea folder. -#.idea/ +.idea/ diff --git a/.reuse/dep5 b/.reuse/dep5 new file mode 100644 index 0000000..849996e --- /dev/null +++ b/.reuse/dep5 @@ -0,0 +1,40 @@ +Format: https://www.debian.org/doc/packaging-manuals/copyright-format/1.0/ +Upstream-Name: safaa +Source: https://github.com/fossology/safaa/ +Upstream-Contact: FOSSology +Disclaimer: This file is offered as-is, without any warranty. + +Files: + Safaa/src/safaa/models/declutter_model/meta.json + Safaa/src/safaa/models/declutter_model/ner/cfg + Safaa/src/safaa/models/declutter_model/ner/model + Safaa/src/safaa/models/declutter_model/ner/moves + Safaa/src/safaa/models/declutter_model/tok2vec/cfg + Safaa/src/safaa/models/declutter_model/tok2vec/model + Safaa/src/safaa/models/declutter_model/tokenizer + Safaa/src/safaa/models/declutter_model/vocab/key2row + Safaa/src/safaa/models/declutter_model/vocab/lookups.bin + Safaa/src/safaa/models/declutter_model/vocab/strings.json + Safaa/src/safaa/models/declutter_model/vocab/vectors + Safaa/src/safaa/models/declutter_model/vocab/vectors.cfg + Safaa/src/safaa/models/entity_recognizer/meta.json + Safaa/src/safaa/models/entity_recognizer/ner/cfg + Safaa/src/safaa/models/entity_recognizer/ner/model + Safaa/src/safaa/models/entity_recognizer/ner/moves + Safaa/src/safaa/models/entity_recognizer/tok2vec/cfg + Safaa/src/safaa/models/entity_recognizer/tok2vec/model + Safaa/src/safaa/models/entity_recognizer/tokenizer + Safaa/src/safaa/models/entity_recognizer/vocab/key2row + Safaa/src/safaa/models/entity_recognizer/vocab/lookups.bin + Safaa/src/safaa/models/entity_recognizer/vocab/strings.json + Safaa/src/safaa/models/entity_recognizer/vocab/vectors + Safaa/src/safaa/models/entity_recognizer/vocab/vectors.cfg + Safaa/src/safaa/models/false_positive_detection_model.pkl + Safaa/src/safaa/models/false_positive_detection_vectorizer.pkl + datasets/declutter_dataset.spacy + datasets/entity_recognition_dataset.spacy + datasets/false_positive_detection_dataset.csv + datasets/json/declutter_dataset.jsonl + datasets/json/declutter_dataset_full.jsonl +Copyright: © 2023 abdelrahmanjamal5565@gmail.com +License: LGPL-2.1-only diff --git a/LICENSES/LGPL-2.1-only.txt b/LICENSES/LGPL-2.1-only.txt new file mode 100644 index 0000000..8000a6f --- /dev/null +++ b/LICENSES/LGPL-2.1-only.txt @@ -0,0 +1,504 @@ + GNU LESSER GENERAL PUBLIC LICENSE + Version 2.1, February 1999 + + Copyright (C) 1991, 1999 Free Software Foundation, Inc. + 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA + Everyone is permitted to copy and distribute verbatim copies + of this license document, but changing it is not allowed. + +[This is the first released version of the Lesser GPL. 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See the GNU + Lesser General Public License for more details. + + You should have received a copy of the GNU Lesser General Public + License along with this library; if not, write to the Free Software + Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 + USA + +Also add information on how to contact you by electronic and paper mail. + +You should also get your employer (if you work as a programmer) or your +school, if any, to sign a "copyright disclaimer" for the library, if +necessary. Here is a sample; alter the names: + + Yoyodyne, Inc., hereby disclaims all copyright interest in the + library `Frob' (a library for tweaking knobs) written by James Random + Hacker. + + , 1 April 1990 + Ty Coon, President of Vice + +That's all there is to it! diff --git a/README.md b/README.md index a84e2cd..17c004d 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,12 @@ + # Safaa -Safaa is a Python package designed for handling false positive detection in copyright notices. Additionally, it can declutter copyright notices, removing unnecessary extra text. +Safaa is a Python package designed for handling false positive detection in copyright notices. +Additionally, it can declutter copyright notices, removing unnecessary extra text. ## Features diff --git a/Safaa/MANIFEST.in b/Safaa/MANIFEST.in index fdf7c58..fc2fb91 100644 --- a/Safaa/MANIFEST.in +++ b/Safaa/MANIFEST.in @@ -1,2 +1,7 @@ +# SPDX-FileCopyrightText: © 2023 abdelrahmanjamal5565@gmail.com +# +# SPDX-License-Identifier: LGPL-2.1-only +# Manifest syntax https://docs.python.org/2/distutils/sourcedist.html + recursive-include src/safaa/models * recursive-include src/safaa/configs * diff --git a/Safaa/setup.py b/Safaa/setup.py index 7a90ec0..f5904db 100644 --- a/Safaa/setup.py +++ b/Safaa/setup.py @@ -1,18 +1,22 @@ +# SPDX-FileCopyrightText: © 2023 abdelrahmanjamal5565@gmail.com +# +# SPDX-License-Identifier: LGPL-2.1-only + from setuptools import setup, find_packages setup( name='safaa', version='0.0.1', - url='https://github.com/fossology/copyrightfpd', + url='https://github.com/fossology/safaa', author='Abdelrahman Jamal', author_email='abdelrahmanjamal5565@gmail.com', description="""Created as a part of the 2023 Google Summer of Code project: - Reducing Fossology\'s False Positive Copyrights, the purpose is to be able to - predict whether a given copyright output from the Fossology software + Reducing Fossology\'s False Positive Copyrights, the purpose is to be able + to predict whether a given copyright output from the Fossology software is a false positive or not. It is also able to remove extra text from a copyright notice.""", - packages=find_packages(where='src',), - package_dir = {"": "src"}, + packages=find_packages(where='src', ), + package_dir={"": "src"}, install_requires=[ 'spacy>=3.0.0', 'joblib>=1.0.0', @@ -20,8 +24,8 @@ 'scikit-learn>=1.3.0', ], classifiers=[ - 'Programming Language :: Python :: 3', - 'License :: OSI Approved :: GNU Lesser General Public License v2.1 (LGPLv2.1)', + 'Programming Language :: Python :: 3', + 'License :: OSI Approved :: GNU Lesser General Public License v2.1 (LGPLv2.1)', ], include_package_data=True, include_dirs=[], diff --git a/Safaa/src/safaa/Safaa.py b/Safaa/src/safaa/Safaa.py index bdeb0fc..2f066d7 100644 --- a/Safaa/src/safaa/Safaa.py +++ b/Safaa/src/safaa/Safaa.py @@ -1,3 +1,7 @@ +# SPDX-FileCopyrightText: © 2023 abdelrahmanjamal5565@gmail.com +# +# SPDX-License-Identifier: LGPL-2.1-only + """ SafaaAgent: A module for handling false positive detection in copyright notices. """ @@ -5,7 +9,7 @@ import os import re import spacy -from joblib import load, dump +from joblib import load, dump import pkg_resources import shutil @@ -14,28 +18,34 @@ LOCAL_MODEL_DIR = '/home/fossy/Safaa' CONFIGS_DIR = pkg_resources.resource_filename(__name__, 'configs') + class SafaaAgent: def __init__(self, use_local_model=True, model_dir=None): - """ - Initializes the SafaaAgent with the necessary models. - - Parameters: - use_local_model (bool): Flag to use local models if available. - model_dir (str): Custom directory path for models. Defaults to None. - """ - - # Determine the model directory based on the provided arguments - model_dir = model_dir if model_dir else (LOCAL_MODEL_DIR if use_local_model and os.path.exists(LOCAL_MODEL_DIR) else DEFAULT_MODEL_DIR) - - # Construct the file paths for each model - self.false_positive_detector_path = os.path.join(model_dir, 'false_positive_detection_model.pkl') - self.vectorizer_path = os.path.join(model_dir, 'false_positive_detection_vectorizer.pkl') - self.entity_recognizer_path = os.path.join(model_dir, 'entity_recognizer') - self.declutter_model_path = os.path.join(model_dir, 'declutter_model') - - # Load the models from the constructed file paths - self._load_models() - + """ + Initializes the SafaaAgent with the necessary models. + + Parameters: + use_local_model (bool): Flag to use local models if available. + model_dir (str): Custom directory path for models. Defaults to None. + """ + + # Determine the model directory based on the provided arguments + model_dir = model_dir if model_dir else ( + LOCAL_MODEL_DIR if use_local_model and os.path.exists( + LOCAL_MODEL_DIR) else DEFAULT_MODEL_DIR) + + # Construct the file paths for each model + self.false_positive_detector_path = os.path.join(model_dir, + 'false_positive_detection_model.pkl') + self.vectorizer_path = os.path.join(model_dir, + 'false_positive_detection_vectorizer.pkl') + self.entity_recognizer_path = os.path.join(model_dir, + 'entity_recognizer') + self.declutter_model_path = os.path.join(model_dir, 'declutter_model') + + # Load the models from the constructed file paths + self._load_models() + def _load_models(self): """ Loads models from file paths. @@ -53,10 +63,10 @@ def _load_models(self): # Load the Declutter model using spaCy self.declutter_model = spacy.load(self.declutter_model_path) - def preprocess_data(self, data): """ - Preprocesses the given data by performing various text cleaning and transformation tasks. + Preprocesses the given data by performing various text cleaning and + transformation tasks. Parameters: data (iterable): The data to preprocess. @@ -75,7 +85,7 @@ def preprocess_data(self, data): data = self._perform_text_substitutions(data) return data - + def _ensure_list_of_strings(self, data): """ Ensures the data is a list of strings. @@ -95,13 +105,13 @@ def _ensure_list_of_strings(self, data): data = data.to_list() # Ensure each item in the list is a string return [str(item) for item in data] - + def _replace_entities(self, data): """ Replaces detected copyright holder entities with ' ENTITY '. Uses the entity_recognizer model to identify copyright holder entities, - which are often name or organization entities, and replaces them with + which are often name or organization entities, and replaces them with the string ' ENTITY '. Parameters: @@ -117,16 +127,18 @@ def _replace_entities(self, data): doc = self.entity_recognizer(sentence) new_sentence = doc.text for entity in doc.ents: - # If the entity is a copyright holder entity, replace it with ' ENTITY ' + # If the entity is a copyright holder entity, replace it with + # ' ENTITY ' if entity.label_ == 'ENT': - new_sentence = re.sub(re.escape(entity.text), ' ENTITY ', new_sentence) + new_sentence = re.sub(re.escape(entity.text), ' ENTITY ', + new_sentence) new_data.append(new_sentence) return new_data - def _perform_text_substitutions(self, data): """ - Performs a series of text substitutions to clean and standardize the data. + Performs a series of text substitutions to clean and standardize the + data. This includes: - Replacing four-digit numbers (assumed to be years) with ' DATE '. @@ -151,7 +163,9 @@ def _perform_text_substitutions(self, data): (r'©', ' COPYRIGHTSYMBOL '), (r'\(c\)', ' COPYRIGHTSYMBOL '), (r'\(C\)', ' COPYRIGHTSYMBOL '), - (r"""(?:[a-z0-9!#$%&'*+/=?^_`{|}~-]+(?:\.[a-z0-9!#$%&'*+/=?^_`{|}~-]+)*|"(?:[\x01-\x08\x0b\x0c\x0e-\x1f\x21\x23-\x5b\x5d-\x7f]|\\[\x01-\x09\x0b\x0c\x0e-\x7f])*")@(?:(?:[a-z0-9](?:[a-z0-9-]*[a-z0-9])?\.)+[a-z0-9](?:[a-z0-9-]*[a-z0-9])?|\[(?:(?:(2(5[0-5]|[0-4][0-9])|1[0-9][0-9]|[1-9]?[0-9]))\.){3}(?:(2(5[0-5]|[0-4][0-9])|1[0-9][0-9]|[1-9]?[0-9])|[a-z0-9-]*[a-z0-9]:(?:[\x01-\x08\x0b\x0c\x0e-\x1f\x21-\x5a\x53-\x7f]|\\[\x01-\x09\x0b\x0c\x0e-\x7f])+)\])""", ' EMAIL '), + ( + r"""(?:[a-z0-9!#$%&'*+/=?^_`{|}~-]+(?:\.[a-z0-9!#$%&'*+/=?^_`{|}~-]+)*|"(?:[\x01-\x08\x0b\x0c\x0e-\x1f\x21\x23-\x5b\x5d-\x7f]|\\[\x01-\x09\x0b\x0c\x0e-\x7f])*")@(?:(?:[a-z0-9](?:[a-z0-9-]*[a-z0-9])?\.)+[a-z0-9](?:[a-z0-9-]*[a-z0-9])?|\[(?:(?:(2(5[0-5]|[0-4][0-9])|1[0-9][0-9]|[1-9]?[0-9]))\.){3}(?:(2(5[0-5]|[0-4][0-9])|1[0-9][0-9]|[1-9]?[0-9])|[a-z0-9-]*[a-z0-9]:(?:[\x01-\x08\x0b\x0c\x0e-\x1f\x21-\x5a\x53-\x7f]|\\[\x01-\x09\x0b\x0c\x0e-\x7f])+)\])""", + ' EMAIL '), (r'[^a-zA-Z0-9]', ' ') ] # Perform the substitutions for each pattern in the list @@ -159,14 +173,15 @@ def _perform_text_substitutions(self, data): data = [re.sub(pattern, replacement, sentence) for sentence in data] # Convert text to lowercase and strip extra whitespace return [sentence.lower().strip() for sentence in data] - + def predict(self, data, threshold=0.5): """ Predicts false positives in the given data. Parameters: data (iterable): The data to predict. - threshold (float): The probability threshold for classification. Defaults to 0.5. + threshold (float): The probability threshold for classification. + Defaults to 0.5. Returns: list: The predictions. @@ -182,16 +197,20 @@ def predict(self, data, threshold=0.5): if hasattr(self.false_positive_detector, 'predict_proba'): # Get probability predictions from the model predictions = self.false_positive_detector.predict_proba(data) - # Classify based on the given threshold. If the threshhold is not met, automatically sets the - # prediction to true - return ['f' if prediction[1] >= threshold else 't' for prediction in predictions] - - # Get binary predictions from the model if probability prediction is not supported - return ['f' if prediction == 1 else 't' for prediction in self.false_positive_detector.predict(data)] - + # Classify based on the given threshold. If the threshhold is not + # met, automatically sets the prediction to true + return ['f' if prediction[1] >= threshold else 't' for prediction in + predictions] + + # Get binary predictions from the model if probability prediction is not + # supported + return ['f' if prediction == 1 else 't' for prediction in + self.false_positive_detector.predict(data)] + def declutter(self, data, predictions): """ - Cleans up a copyright notice by removing extra text based on the predictions. + Cleans up a copyright notice by removing extra text based on the + predictions. Parameters: data (iterable): The data to declutter. @@ -202,16 +221,18 @@ def declutter(self, data, predictions): """ # Iterate over each sentence and its corresponding prediction - # Remove text from sentences marked as false positives, and keep the entities (copyrights) in other sentences + # Remove text from sentences marked as false positives, and keep the + # entities (copyrights) in other sentences return [ - '' if prediction == 'f' else ' '.join([ent.text for ent in self.declutter_model(sentence).ents]) + '' if prediction == 'f' else ' '.join( + [ent.text for ent in self.declutter_model(sentence).ents]) for sentence, prediction in zip(data, predictions) ] def train_false_positive_detector_model(self, data, labels): """ Trains the false positive detector model from scratch. - + Parameters: data (iterable): The data to train the model on. labels (iterable): The labels for the training data. @@ -224,11 +245,12 @@ def train_false_positive_detector_model(self, data, labels): # Train the false positive detector model self.false_positive_detector.fit(vectorized_data, labels) - def train_ner_model(self, train_path, dev_path, declutter_model=False, config_path=None): + def train_ner_model(self, train_path, dev_path, declutter_model=False, + config_path=None): """ Trains the named entity recognition model using the provided training and development datasets. - + Parameters: train_path (str): The path to the training data file. Should be a .spacy file dev_path (str): The path to the development data file. Should be a .spacy file @@ -244,9 +266,10 @@ def train_ner_model(self, train_path, dev_path, declutter_model=False, config_pa with open(config_file_path, 'r', encoding='utf-8') as file: cfg_contents = file.read() - # Update the training and development data paths in the configuration contents + # Update the training and development data paths in the configuration + # contents updated_cfg_contents = re.sub( - r'train\s*=\s*".*"', f'train = "{train_path}"', + r'train\s*=\s*".*"', f'train = "{train_path}"', re.sub(r'dev\s*=\s*".*"', f'dev = "{dev_path}"', cfg_contents) ) @@ -257,23 +280,26 @@ def train_ner_model(self, train_path, dev_path, declutter_model=False, config_pa # Determine the model directory paths tmp_model_path = os.path.join(LOCAL_MODEL_DIR, 'tmp') - new_model_dir = 'declutter_model' if declutter_model else 'entity_recognizer' + new_model_dir = 'declutter_model' if declutter_model else \ + 'entity_recognizer' new_model_path = os.path.join(LOCAL_MODEL_DIR, new_model_dir) # Create the new model directory if it doesn't exist os.makedirs(new_model_path, exist_ok=True) # Construct the training command and execute it - train_command = f"python -m spacy train '{tmp_cfg_path}' --output '{tmp_model_path}'" + train_command = (f"python -m spacy train '{tmp_cfg_path}' " + f"--output '{tmp_model_path}'") os.system(train_command) # Move the trained model files to the new model directory - self._move_files(os.path.join(tmp_model_path, 'model-best'), new_model_path) + self._move_files(os.path.join(tmp_model_path, 'model-best'), + new_model_path) # Clean up the temporary files and directories os.remove(tmp_cfg_path) shutil.rmtree(tmp_model_path) - + def _move_files(self, src_dir, dst_dir): """ Internal helper method to move files from one directory to another. @@ -288,35 +314,41 @@ def _move_files(self, src_dir, dst_dir): # Construct full paths for source and destination src_item_path = os.path.join(src_dir, item) dst_item_path = os.path.join(dst_dir, item) - # Move each item from the source directory to the destination directory + # Move each item from the source directory to the destination + # directory shutil.move(src_item_path, dst_item_path) def save(self, path=None): """ Saves the trained models and vectorizer to the specified path. - - Make sure the directory you have permissions to the directory that you are - saving to. - + + Make sure the directory you have permissions to the directory that you + are saving to. + Parameters: - path (str): The path to save the models and vectorizer to. Defaults to None. + path (str): The path to save the models and vectorizer to. Defaults to + None. """ # Determine the directory path to save the models and vectorizer save_path = path or '/home/fossy/Safaa' - + # Create the directory if it does not exist os.makedirs(save_path, exist_ok=True) # Check directory permissions if not os.access(path, os.W_OK): - print(f"Write permissions are not granted for the directory: {save_path}") + print("Write permissions are not granted for the directory: " + f"{save_path}") return - + # Construct the full paths for the model and vectorizer files - false_positive_detector_path = os.path.join(save_path, 'false_positive_detection_model.pkl') - vectorizer_path = os.path.join(save_path, 'false_positive_detection_vectorizer.pkl') + false_positive_detector_path = os.path.join(save_path, + 'false_positive_detection_model.pkl') + vectorizer_path = os.path.join(save_path, + 'false_positive_detection_vectorizer.pkl') - # Save the false positive detector model and vectorizer to the specified paths + # Save the false positive detector model and vectorizer to the specified + # paths dump(self.false_positive_detector, false_positive_detector_path) - dump(self.vectorizer, vectorizer_path) \ No newline at end of file + dump(self.vectorizer, vectorizer_path) diff --git a/Safaa/src/safaa/__init__.py b/Safaa/src/safaa/__init__.py index e69de29..eb2bbc8 100644 --- a/Safaa/src/safaa/__init__.py +++ b/Safaa/src/safaa/__init__.py @@ -0,0 +1,3 @@ +# SPDX-FileCopyrightText: © 2023 abdelrahmanjamal5565@gmail.com +# +# SPDX-License-Identifier: LGPL-2.1-only diff --git a/Safaa/src/safaa/configs/train.cfg b/Safaa/src/safaa/configs/train.cfg index c282f9a..1fa2f9a 100644 --- a/Safaa/src/safaa/configs/train.cfg +++ b/Safaa/src/safaa/configs/train.cfg @@ -1,3 +1,6 @@ +; SPDX-FileCopyrightText: © 2023 abdelrahmanjamal5565@gmail.com +; +; SPDX-License-Identifier: LGPL-2.1-only [paths] train = "" dev = "" @@ -141,4 +144,4 @@ after_init = null [initialize.components] -[initialize.tokenizer] \ No newline at end of file +[initialize.tokenizer] diff --git a/Safaa/src/safaa/models/__init__.py b/Safaa/src/safaa/models/__init__.py index e69de29..eb2bbc8 100644 --- a/Safaa/src/safaa/models/__init__.py +++ b/Safaa/src/safaa/models/__init__.py @@ -0,0 +1,3 @@ +# SPDX-FileCopyrightText: © 2023 abdelrahmanjamal5565@gmail.com +# +# SPDX-License-Identifier: LGPL-2.1-only diff --git a/Safaa/src/safaa/models/declutter_model/config.cfg b/Safaa/src/safaa/models/declutter_model/config.cfg index d22f932..5dce917 100644 --- a/Safaa/src/safaa/models/declutter_model/config.cfg +++ b/Safaa/src/safaa/models/declutter_model/config.cfg @@ -1,6 +1,9 @@ +; SPDX-FileCopyrightText: © 2023 abdelrahmanjamal5565@gmail.com +; +; SPDX-License-Identifier: LGPL-2.1-only [paths] -train = "/home/jimbo/Desktop/GSoC23/Fossology-Reducing-Copyrights/NER_datasets/spacy_compatible/declutter-data/4000-cleaned-up-data-train.spacy" -dev = "/home/jimbo/Desktop/GSoC23/Fossology-Reducing-Copyrights/NER_datasets/spacy_compatible/declutter-data/4000-cleaned-up-data-valid.spacy" +train = "4000-cleaned-up-data-train.spacy" +dev = "4000-cleaned-up-data-valid.spacy" vectors = null init_tok2vec = null @@ -141,4 +144,4 @@ after_init = null [initialize.components] -[initialize.tokenizer] \ No newline at end of file +[initialize.tokenizer] diff --git a/Safaa/src/safaa/models/entity_recognizer/config.cfg b/Safaa/src/safaa/models/entity_recognizer/config.cfg index 95ac99e..b839bb7 100644 --- a/Safaa/src/safaa/models/entity_recognizer/config.cfg +++ b/Safaa/src/safaa/models/entity_recognizer/config.cfg @@ -1,6 +1,9 @@ +; SPDX-FileCopyrightText: © 2023 abdelrahmanjamal5565@gmail.com +; +; SPDX-License-Identifier: LGPL-2.1-only [paths] -train = "/home/jimbo/Desktop/GSoC23/Fossology-Reducing-Copyrights/NER_datasets/spacy_compatible/copyright-data/enitre-dataset-semi-supervised-train.spacy" -dev = "/home/jimbo/Desktop/GSoC23/Fossology-Reducing-Copyrights/NER_datasets/spacy_compatible/copyright-data/enitre-dataset-semi-supervised-valid.spacy" +train = "entire-dataset-semi-supervised-train.spacy" +dev = "entire-dataset-semi-supervised-valid.spacy" vectors = null init_tok2vec = null @@ -141,4 +144,4 @@ after_init = null [initialize.components] -[initialize.tokenizer] \ No newline at end of file +[initialize.tokenizer] diff --git a/datasets/README.md b/datasets/README.md index 9c19f4a..bbbf25b 100644 --- a/datasets/README.md +++ b/datasets/README.md @@ -1,14 +1,20 @@ + # Dataset Information ## False Positive Detection Dataset -Constructed from Multiple Github Repositiroes +Constructed from Multiple GitHub Repositories - Fossology - Tensorflow - Kubernetes - Additional dataset provided by Siemens ## Declutter -Constructed from the false positive detection dataset text after removing non-english examples and false positives. **Currently only the first 4000 rows are labeled and that is what is included in the dataset.** +Constructed from the false positive detection dataset text after removing non-english examples and false positives. +**Currently only the first 4000 rows are labeled and that is what is included in the dataset.** ## Entity Recognition Similar to declutter, it's also constructed from the false positive detection dataset. But only using 1500 examples. diff --git a/utility/NER/data_conversion.py b/utility/NER/data_conversion.py index 80fa71c..d461c74 100644 --- a/utility/NER/data_conversion.py +++ b/utility/NER/data_conversion.py @@ -1,9 +1,14 @@ +# SPDX-FileCopyrightText: © 2023 abdelrahmanjamal5565@gmail.com +# +# SPDX-License-Identifier: LGPL-2.1-only + from tqdm import tqdm import json import re import spacy from sklearn.model_selection import train_test_split + def text_to_json(sentences): """ Convert list of sentences to a specific JSON format. @@ -15,6 +20,7 @@ def text_to_json(sentences): new_json.append({'text': sentence, "labels": labels}) return new_json + def text_to_json_model_assisted(sentences, model): """ Convert list of sentences to a JSON format using a model for predictions. @@ -30,34 +36,41 @@ def text_to_json_model_assisted(sentences, model): new_json.append({'text': sentence.text, "labels": labels}) return new_json + def text_to_json_labels_separate(sentences, labels, entity_name): """ - Convert list of sentences and labels to a JSON format with specific entity name. + Convert list of sentences and labels to a JSON format with specific entity + name. """ new_json = list() - for sentence, label in tqdm(zip(sentences, labels)): + for sentence, label in tqdm(zip(sentences, labels)): if label is None or label == '': continue # If label is empty or None, skip the iteration - + # Search for the exact match of the label in the sentence pattern = r"\b" + re.escape(label) + r"\b" match = re.search(pattern, sentence) if not match: - continue # If label is not found in the sentence, skip the iteration - - # Appending the sentence and the position of its label to the resulting JSON - new_json.append({'text': sentence, "labels": [match.start(), match.end(), entity_name]}) + continue # If label is not found in the sentence, skip + + # Appending the sentence and the position of its label to the resulting + # JSON + new_json.append({'text': sentence, + "labels": [match.start(), match.end(), entity_name]}) return new_json + def write_json_to_disk(new_json, path): """ Write a list of dictionaries in the JSONL format to disk. """ with open(path, 'w') as f: for item in new_json: - # Writing each dictionary in the list as a separate line in the JSONL file + # Writing each dictionary in the list as a separate line in the + # JSONL file f.write(json.dumps(item) + '\n') + def convert_jsonl_to_spacy(jsonl_path, spacy_path): """ Load data from a JSONL file and convert it to spaCy's training format. @@ -70,27 +83,35 @@ def convert_jsonl_to_spacy(jsonl_path, spacy_path): # Extracting entities from the JSONL line entities = [(e[0], e[1], e[2]) for e in item['labels']] data.append((text, {'entities': entities})) - + nlp = spacy.blank('en') # Creating a blank English NLP object doc_bin = spacy.tokens.DocBin() # Initializing a DocBin for efficient storage of `Doc` objects for text, annotations in data: doc = nlp.make_doc(text) # Creating a `Doc` object from text - example = spacy.training.Example.from_dict(doc, annotations) # Creating an example from the `Doc` and its annotations + example = spacy.training.Example.from_dict(doc, + annotations) # Creating an example from the `Doc` and its annotations doc_bin.add(example.reference) # Adding the `Doc` to the DocBin doc_bin.to_disk(spacy_path) # Saving the DocBin to disk + def spacy_train_test_split(file_path, split=0.2, random_state=42, shuffle=True): """ Split spaCy formatted data into training and testing sets. """ - doc_bin = spacy.tokens.DocBin().from_disk(file_path) # Loading the DocBin from disk + doc_bin = spacy.tokens.DocBin().from_disk( + file_path) # Loading the DocBin from disk nlp = spacy.load("en_core_web_sm") # Loading the English small core model - docs = list(doc_bin.get_docs(nlp.vocab)) # Retrieving `Doc` objects from the DocBin using the model's vocabulary + docs = list(doc_bin.get_docs( + nlp.vocab)) # Retrieving `Doc` objects from the DocBin using the model's vocabulary # Splitting the `Doc` objects into training and testing sets - train_docs, test_docs = train_test_split(docs, test_size=split, random_state=random_state, shuffle=shuffle) - train_doc_bin = spacy.tokens.DocBin(docs=train_docs) # Creating a DocBin for training docs - test_doc_bin = spacy.tokens.DocBin(docs=test_docs) # Creating a DocBin for testing docs - + train_docs, test_docs = train_test_split(docs, test_size=split, + random_state=random_state, + shuffle=shuffle) + train_doc_bin = spacy.tokens.DocBin( + docs=train_docs) # Creating a DocBin for training docs + test_doc_bin = spacy.tokens.DocBin( + docs=test_docs) # Creating a DocBin for testing docs + # Deriving the paths for saving the training and testing DocBins train_path = file_path.split('.spacy')[0] + '-train.spacy' test_path = file_path.split('.spacy')[0] + '-test.spacy' diff --git a/utility/false_positive_detection/test.py b/utility/false_positive_detection/test.py index 58e12c8..16f5463 100644 --- a/utility/false_positive_detection/test.py +++ b/utility/false_positive_detection/test.py @@ -1,15 +1,23 @@ -import os -import pandas as pd +# SPDX-FileCopyrightText: © 2023 abdelrahmanjamal5565@gmail.com +# +# SPDX-License-Identifier: LGPL-2.1-only + from argparse import ArgumentParser -from Safaa.Safaa import * + +import pandas as pd from sklearn.metrics import classification_report +from safaa.Safaa import * + + def main(): parser = ArgumentParser(description="Read CSV file and check model file") - parser.add_argument("--csv-file", help="Path to the CSV file - it should two columns: text and label") + parser.add_argument("--csv-file", + help="Path to the CSV file - it should two columns:" + " text and label") args = parser.parse_args() - + # Read the CSV file using Pandas try: data = pd.read_csv(args.csv_file_path) @@ -17,24 +25,27 @@ def main(): except FileNotFoundError: print(f"CSV file not found at: {args.csv_file_path}") return - + # Check if the Safaa package is installed in the fossy user pythondeps - # Simply check if a directory containing Safaa is inside /home/fossy/pythondeps + # Simply check if a directory containing Safaa is inside + # /home/fossy/pythondeps dirs = os.listdir('/home/fossy/pythondeps') dirs = [d for d in dirs if 'Safaa' in d] if len(dirs) == 0: - print("""The Safaa package is not installed in the fossy user pythondeps. - Please install by running the post-install script with the --python-experimental flag""") + print(""" + The Safaa package is not installed in the fossy user pythondeps. + Please install by running the post-install script with the --python-experimental flag""") return - + # Create an instance of the class agent = SafaaAgent() - + predictions = agent.predict(data['text'].to_list()) # Print the predictions print(classification_report(data['label'].to_list(), predictions)) + if __name__ == "__main__": main() diff --git a/utility/false_positive_detection/train.py b/utility/false_positive_detection/train.py index 7bd40b0..25fac2a 100644 --- a/utility/false_positive_detection/train.py +++ b/utility/false_positive_detection/train.py @@ -1,14 +1,22 @@ -import os -import pandas as pd +# SPDX-FileCopyrightText: © 2023 abdelrahmanjamal5565@gmail.com +# +# SPDX-License-Identifier: LGPL-2.1-only + from argparse import ArgumentParser -from Safaa.Safaa import * + +import pandas as pd + +from safaa.Safaa import * + def main(): parser = ArgumentParser(description="Read CSV file and check model file") - parser.add_argument("--csv-file", help="Path to the CSV file - it should two columns: text and label") + parser.add_argument("--csv-file", + help="Path to the CSV file - it should two columns:" + " text and label") args = parser.parse_args() - + # Read the CSV file using Pandas try: data = pd.read_csv(args.csv_file_path) @@ -16,22 +24,26 @@ def main(): except FileNotFoundError: print(f"CSV file not found at: {args.csv_file_path}") return - + # Check if the Safaa package is installed in the fossy user pythondeps - # Simply check if a directory containing Safaa is inside /home/fossy/pythondeps + # Simply check if a directory containing Safaa is inside + # /home/fossy/pythondeps dirs = os.listdir('/home/fossy/pythondeps') dirs = [d for d in dirs if 'Safaa' in d] if len(dirs) == 0: - print("""The Safaa package is not installed in the fossy user pythondeps. - Please install by running the post-install script with the --python-experimental flag""") + print(""" + The Safaa package is not installed in the fossy user pythondeps. + Please install by running the post-install script with the --python-experimental flag""") return agent = SafaaAgent() - agent.train_false_positive_detector_model(data['text'].to_list(), data['label'].to_list()) + agent.train_false_positive_detector_model(data['text'].to_list(), + data['label'].to_list()) agent.save() + if __name__ == "__main__": main() From d36aa6eaab1abfe40b49e7d21c077ed6cf3549e5 Mon Sep 17 00:00:00 2001 From: Gaurav Mishra Date: Thu, 2 Nov 2023 17:24:27 +0530 Subject: [PATCH 2/2] feat(ci): lint and publish Add new GitHub Action workflows to lint the REUSE requirements and publish package on PyPI whenever a release is tagged. Signed-off-by: Gaurav Mishra --- .github/workflows/release-publish.yml | 37 +++++++++++++++++++++++++++ .github/workflows/reuse-lint.yml | 25 ++++++++++++++++++ 2 files changed, 62 insertions(+) create mode 100644 .github/workflows/release-publish.yml create mode 100644 .github/workflows/reuse-lint.yml diff --git a/.github/workflows/release-publish.yml b/.github/workflows/release-publish.yml new file mode 100644 index 0000000..570671e --- /dev/null +++ b/.github/workflows/release-publish.yml @@ -0,0 +1,37 @@ +# SPDX-FileCopyrightText: © 2023 Siemens AG +# SPDX-FileContributor: Gaurav Mishra + +# SPDX-License-Identifier: LGPL-2.1-only + +name: Publish Release Packages + +on: + release: + types: + - published + +jobs: + pypi-publish: + runs-on: ubuntu-latest +# environment: +# name: pypi +# url: https://pypi.org/p/safaa +# permissions: +# id-token: write + steps: + - uses: actions/checkout@v4 + - name: Setup python + uses: actions/setup-python@v4 + with: + python-version: '3.8' + architecture: 'x64' + - name: Install wheel + run: python3 -m pip install --upgrade wheel + - name: Build packages + run: python3 setup.py sdist bdist_wheel + working-directory: ./Safaa + - name: Upload Packages to PyPI + uses: pypa/gh-action-pypi-publish@release/v1 + with: + user: __token__ + password: ${{ secrets.PYPI_API_TOKEN }} diff --git a/.github/workflows/reuse-lint.yml b/.github/workflows/reuse-lint.yml new file mode 100644 index 0000000..db0ad2d --- /dev/null +++ b/.github/workflows/reuse-lint.yml @@ -0,0 +1,25 @@ +# SPDX-FileCopyrightText: © 2023 Siemens AG +# SPDX-FileContributor: Gaurav Mishra + +# SPDX-License-Identifier: LGPL-2.1-only + +name: Static lints + +concurrency: + group: static-${{ github.head_ref }} + cancel-in-progress: true + +on: + push: + branches: [master] + pull_request: + branches: [master] + workflow_dispatch: + +jobs: + REUSE-Compliance-Check: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v3 + - name: REUSE Compliance Check + uses: fsfe/reuse-action@v2