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chore: setup requirements templates
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‎.env.example‎

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# -----------------------------------
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# Environment Variables
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# -----------------------------------
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ENVIRONMENT=local

‎.pre-commit-config.yaml‎

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hooks:
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- id: codespell
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args: ["--ignore-words=codespell.txt"]
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exclude: ^requirements/
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- repo: local
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hooks:
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- id: eslint

‎Makefile‎

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$(shell echo -e "ENVIRONMENT=dev" >> .env)
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endif
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.PHONY: analyze pre-commit init lint clean test build release all python-init docker-build docker-push docker-run docker-prune help
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.PHONY: analyze pre-commit init lint clean test build release all python-init help
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# Default target executed when no arguments are given to make.
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all: help
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make python-init && \
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npm install && \
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$(ACTIVATE_VENV) && \
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$(PIP) install -U 'pip<25.3' && \
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$(PIP) install -r requirements/local.txt && \
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pre-commit install && \
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deactivate

‎README.md‎

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1. Verify project requirements: [Python 3.13](https://www.python.org/)
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2. Run `make init`
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2. Run `make init`
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3. Run `source venv/bin/activate`
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## Support
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Please report bugs to the [GitHub Issues Page](https://github.com/FullStackWithLawrence/ai-algorithms/issues) for this project.

‎requirements/base.txt‎

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# -----------------------------------------------------------------------------
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# written by: Lawrence McDaniel
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# https://lawrencemcdaniel.com
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#
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# usage: Python local development requirements
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# -----------------------------------------------------------------------------
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python-dotenv==1.1.1 # for loading environment variables from .env files
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pandas==1.5.3 # for data manipulation
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kaggle==1.7.4.5 # for Kaggle api access
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seaborn==0.13.2 # for data visualization
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scikit-learn==1.5.1 # for machine learning algorithms
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scipy==1.10.1 # for scientific computing
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shap==0.43.0 # for model interpretability
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openpyxl==3.1.5 # for Excel file support from kaggle datasets
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# Azure ML SDK - essential components only
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azureml-core==1.60.0.post1
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azureml-train-core==1.60.0
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azureml-pipeline-core==1.60.0
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azureml-train-automl==1.60.0
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azureml-widgets==1.60.0
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# This file is autogenerated by pip-compile with Python 3.13
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# by the following command:
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#
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# pip-compile --cert=None --client-cert=None --index-url=None --output-file=requirements/base.txt --pip-args=None requirements/in/base.in
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#
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bleach==6.3.0
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# via kaggle
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certifi==2025.10.5
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# via
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# -r requirements/in/constraints.in
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# kaggle
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# requests
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chardet==5.2.0
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# via -r requirements/in/constraints.in
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charset-normalizer==3.4.4
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# via
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# -r requirements/in/constraints.in
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# kaggle
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# requests
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cloudpickle==3.1.2
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# via shap
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colorama==0.4.6
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# via -r requirements/in/constraints.in
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contourpy==1.3.3
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# via matplotlib
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cycler==0.12.1
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# via matplotlib
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et-xmlfile==2.0.0
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# via openpyxl
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filelock==3.20.0
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# via -r requirements/in/constraints.in
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fonttools==4.60.1
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# via matplotlib
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idna==3.11
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# via
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# -r requirements/in/constraints.in
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# kaggle
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# requests
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iniconfig==2.3.0
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# via -r requirements/in/constraints.in
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jmespath==1.0.1
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# via -r requirements/in/constraints.in
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joblib==1.5.2
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# via
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# -r requirements/in/constraints.in
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# scikit-learn
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kaggle==1.7.4.5
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# via -r requirements/in/base.in
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kiwisolver==1.4.9
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# via matplotlib
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llvmlite==0.45.1
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# via numba
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matplotlib==3.10.7
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# via seaborn
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mccabe==0.7.0
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# via -r requirements/in/constraints.in
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mdurl==0.1.2
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# via -r requirements/in/constraints.in
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more-itertools==10.8.0
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# via -r requirements/in/constraints.in
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multidict==6.7.0
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# via -r requirements/in/constraints.in
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numba==0.62.1
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# via shap
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numpy==2.3.4
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# via
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# contourpy
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# matplotlib
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# numba
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# pandas
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# scikit-learn
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# scipy
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# seaborn
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# shap
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openpyxl==3.1.5
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# via -r requirements/in/base.in
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packaging==25.0
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# via
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# matplotlib
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# shap
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pandas==2.3.3
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# via
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# -r requirements/in/base.in
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# seaborn
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# shap
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pathspec==0.12.1
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# via -r requirements/in/constraints.in
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pillow==12.0.0
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# via matplotlib
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platformdirs==4.5.0
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# via -r requirements/in/constraints.in
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pluggy==1.6.0
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# via -r requirements/in/constraints.in
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protobuf==6.33.0
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# via kaggle
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pyasn1==0.6.1
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# via
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# -r requirements/in/constraints.in
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# pyasn1-modules
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# rsa
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pyasn1-modules==0.4.2
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# via -r requirements/in/constraints.in
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pycodestyle==2.14.0
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# via -r requirements/in/constraints.in
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pycparser==2.23
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# via -r requirements/in/constraints.in
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pyflakes==3.4.0
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# via -r requirements/in/constraints.in
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pyparsing==3.2.5
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# via
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# -r requirements/in/constraints.in
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# matplotlib
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python-dateutil==2.9.0.post0
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# via
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# kaggle
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# matplotlib
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# pandas
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python-dotenv==1.2.1
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# via -r requirements/in/base.in
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python-slugify==8.0.4
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# via kaggle
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pytz==2025.2
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# via pandas
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rapidfuzz==3.14.3
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# via -r requirements/in/constraints.in
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regex==2025.11.3
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# via -r requirements/in/constraints.in
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requests==2.32.5
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# via kaggle
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rsa==4.9.1
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# via -r requirements/in/constraints.in
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scikit-learn==1.7.2
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# via
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# -r requirements/in/base.in
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# shap
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scipy==1.16.3
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# via
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# -r requirements/in/base.in
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# scikit-learn
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# shap
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seaborn==0.13.2
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# via -r requirements/in/base.in
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shap==0.49.1
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# via -r requirements/in/base.in
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six==1.17.0
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# via
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# -r requirements/in/constraints.in
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# kaggle
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# python-dateutil
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slicer==0.0.8
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# via shap
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sniffio==1.3.1
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# via -r requirements/in/constraints.in
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soupsieve==2.8
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# via -r requirements/in/constraints.in
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sqlparse==0.5.3
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# via -r requirements/in/constraints.in
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stevedore==5.5.0
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# via -r requirements/in/constraints.in
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tenacity==9.1.2
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# via -r requirements/in/constraints.in
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text-unidecode==1.3
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# via
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# kaggle
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# python-slugify
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threadpoolctl==3.6.0
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# via scikit-learn
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tomlkit==0.13.3
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# via -r requirements/in/constraints.in
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tqdm==4.67.1
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# via
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# kaggle
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# shap
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typing-extensions==4.15.0
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# via
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# -r requirements/in/constraints.in
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# shap
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tzdata==2025.2
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# via
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# -r requirements/in/constraints.in
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# pandas
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urllib3==2.5.0
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# via
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# -r requirements/in/constraints.in
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# kaggle
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# requests
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validators==0.35.0
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# via -r requirements/in/constraints.in
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vine==5.1.0
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# via -r requirements/in/constraints.in
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wcwidth==0.2.14
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# via -r requirements/in/constraints.in
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webencodings==0.5.1
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# via
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# bleach
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# kaggle
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wheel==0.45.1
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# via -r requirements/in/constraints.in
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# Azure AI SDK - essential components only
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azure-ai-ml==1.27.1
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azure-storage-blob==12.19.0
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# The following packages are considered to be unsafe in a requirements file:
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# setuptools

‎requirements/in/base.in‎

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# -----------------------------------------------------------------------------
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# written by: Lawrence McDaniel
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# https://lawrencemcdaniel.com
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#
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# usage: The common platform requirements.
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#
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# pip-compile requirements/in/base.in -o requirements/base.txt
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# -----------------------------------------------------------------------------
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-r constraints.in
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python-dotenv==1.2.1 # for loading environment variables from .env files
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pandas==2.3.3 # for data manipulation
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kaggle==1.7.4.5 # for Kaggle api access
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seaborn==0.13.2 # for data visualization
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scikit-learn==1.7.2 # for machine learning algorithms
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scipy==1.16.3 # for scientific computing
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shap==0.49.1 # for model interpretability
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openpyxl==3.1.5 # for Excel file support from kaggle datasets

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