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added data engineering lessons and code
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.gitignore

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# Data
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logs/
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stores/
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# VSCode
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.vscode/
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.idea
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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pip-wheel-metadata/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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# Flask:
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instance/
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.webassets-cache
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# Scrapy:
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.scrapy
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# Sphinx
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docs/_build/
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# PyBuilder
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target/
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# IPython
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.ipynb_checkpoints
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profile_default/
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ipython_config.py
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# pyenv
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.python-version
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# PEP 582
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__pypackages__/
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# Celery
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celerybeat-schedule
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celerybeat.pid
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# Environment
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# mkdocs
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site/
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# Airflow
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airflow/airflow.db
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# MacOS
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.DS_Store

README.md

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