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https://github.com/ilri/csv-metadata-quality.git
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Re-work as a proper standalone Python package
Add a setup.py so that installation is easier and a standalone CLI script called csv-metadata-quality is provided. Now the user only needs to run this from a virtual environment inside the project directory: $ pip install . Eventually I could publish this on PyPi when I settle on a more appropriate package name. See: https://packaging.python.org/tutorials/packaging-projects/ See: https://chriswarrick.com/blog/2014/09/15/python-apps-the-right-way-entry_points-and-scripts/
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from csv_metadata_quality import app
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from sys import argv
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def main():
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app.run(argv)
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if __name__ == '__main__':
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app.main(argv)
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main()
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@ -15,7 +15,7 @@ def parse_args(argv):
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return args
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def main(argv):
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def run(argv):
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args = parse_args(argv)
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# Read all fields as strings so dates don't get converted from 1998 to 1998.0
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setup.py
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setup.py
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import setuptools
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with open("README.md", "r") as fh:
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long_description = fh.read()
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install_requires = [
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'pandas',
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'python-stdnum',
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'requests',
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'requests-cache',
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'pycountry'
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]
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setuptools.setup(
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name="csv-metadata-quality",
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version="0.0.1",
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author="Alan Orth",
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author_email="aorth@mjanja.ch",
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description="A simple, but opinionated CSV quality checking and fixing pipeline.",
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license="GPLv3",
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long_description=long_description,
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long_description_content_type="text/markdown",
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url="https://github.com/alanorth/csv-metadata-quality",
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classifiers=[
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"Programming Language :: Python :: 3.6",
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"Programming Language :: Python :: 3.7",
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"License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
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"Operating System :: OS Independent",
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"Development Status :: 4 - Beta"
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],
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packages=['csv_metadata_quality'],
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entry_points={
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'console_scripts': [
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'csv-metadata-quality = csv_metadata_quality.__main__:main'
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]
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},
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install_requires=install_requires
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)
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