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Starter data science project using Python with common dependencies included... Pull requests welcome...

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PythonDataScience with pipenv

(If you are using PyCharm, pipenv may cause some difficulties. The fork for not using pipenv is here:https://github.com/DataSciencePros/PythonDataScience)

Starter data science project using Python with common dependencies included...
Pull requests welcome...

# clone this repo to local
git clone [email protected]:DrOzturk/PythonDataScience.git
# if you don't have python 3 as default, first do this
pipenv --three
# create virtual environment with dependencies defined in Pipenv file
pipenv install
# start shell in that virtual environment
pipenv shell

Adding new dependencies

If you add the new dependency using pipenv, it will be automatically added to Pipfile. ex:

pipenv install pandas

Developer Tools

Linting

  • pycodestyle : use to check if code complies with code style guide ex:
pycodestyle example_package/example.py

Setuptools

  • Command to Create the package to distribute in dist folder -.tar.gz (like dist/example_package-0.0.1.tar.gz)
python setup.py sdist
  • For More info type:
python setup.py --help-commands
  • helps in module discovery using find_packages(), so we can refer to all modules without relative import

Unit Test Running

  • Running all unit tests in the command line:
python -m unittest -v example_package/tests/test_example.py`
  • Running a specific test in a TestExample class in test_example test module:
python -m unittest example_package.tests.test_example.TestExample.test_greater_than

Clean Compiled

find . -type f -name "*.py[co]" -delete -or -type d -name "pycache" -delete

.gitignore

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