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        "description": "# Configurable PySpark Pipeline\n_A configurable PySpark pipeline library._\n\n## Getting Started\n* Requirements: \n    * Python 3.5\n* install the package using pip:\n\n``` bash\n$ pip install sparkml-pipe\n```\n\n## Project Organization\n```\n\u251c\u2500\u2500 README.md          <- The top-level README for developers using this project.\n\u251c\u2500\u2500 data               <- Data for testing the library.\n\u2502\n\u251c\u2500\u2500 docs               <- A default Sphinx project; see sphinx-doc.org for details\n\u2502\n\u251c\u2500\u2500 requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.\n\u2502                         generated with `pip freeze > requirements.txt`\n\u2502\n\u251c\u2500\u2500 sparkmlpip         <- Source code for use in this project.\n\u2502   \u251c\u2500\u2500 conf           <- YAML config files for pyspark pipeline.\n\u2502   \u2502\n\u2502   \u251c\u2500\u2500 pipeline       <- pyspark model pipelines.\n\u2502   \u2502\n\u2502   \u251c\u2500\u2500 stat           <- pyspark stat pipelines.\n\u2502   \u2502\n\u2502   \u251c\u2500\u2500 test           <- test code.\n\u2502   \u2502\n\u2502   \u2514\u2500\u2500 utils          <- util functions.\n\u2502\n\u2514\u2500\u2500 setup.py           <- Metadata about your project for easy distribution.\n```\n\n\n\n## Contributing\n### checkout the codebase\n``` bash\n$ git checkout develop\n```\n### Update the PyPI version\n* Update sparkmlpipe/\\_\\_version\\_\\_.py if needed\n* Upload to PyPI\n``` bash\n$ python setup.py sdist\n$ pip install twine\n// upload to Test PyPI\n$ twine upload --repository-url https://test.pypi.org/legacy/ dist/*\n// upload to PyPI\n$ twine upload dist/*\n```\n### Installing development requirements\n``` bash\n$ pip install -r requirements.txt\n```",
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