Developing this package requires the use of Conda environments to manage the required additional packages used for testing and installion.
If conda is not installed on your local computer, you can easily install the Anaconda Python3 distribution.
Note: If you encounter an Image not found error on Mac OSX, you may need an XQuartz upgrade.
Start by cloning this repository:
git clone https://github.com/data-8/datascience
Install the dependencies into a new conda environment named datascience with:
conda env create -f osx_environment.yml -n datascience
conda env create -f linux_environment.yml -n datascience
Source the environment to use the correct packages while developing:
source activate datascience
Note: The above command must be run each time you begin development on the package to activate the environment. You can install [direnv][direnv] to auto-load/unload the environment, but this is not required.
You can unload the environment when done developing with:
source deactivate
Currently, this project uses pytest for testing. To run the included tests:
First, install additional requirements for testing into the active environment with:
pip install -r requirements-tests.txt
Then, install datascience locally with:
make install
Then, run the tests:
make test
You can also use tox for testing. tox can be used for testing the package against several python versions all at once. ou must ensure that the python versions you're testing against are available globally or in your virtual environment. Currently, tox.ini is configured to test against 3.6, 3.7, and 3.8.
To test using tox:
First, install tox
pip install tox
Then, run tests with:
tox
Note: Testing with tox is currently experimental, and tox is not used in the Github action that runs on new commits and pull requests. Use at your own risk!
Documentation is generated from the docstrings in the methods and is pushed online at http://data8.org/datascience/ automatically. If you want to preview the docs locally, use these commands:
make docs # Generates docs inside doc/ folder
make serve_docs # Starts a local server to view docs
We welcome pull requests from interested members of the community to fix an issue, add a feature, or improve the documentation.
You might refer to issues tagged "good first issue" for a good first goal to work on.
I suggest breaking changes down into small pull requests, so each pull request makes a single change (e.g., fixes one issue, adds one feature).
Please do not ask to be assigned to an issue. We do not assign issues to particular individuals. Anyone who wants to contribute, can do so. If you would like to work on solving an open issue in the Github issue tracker, then go ahead. Don't ask for permission, and don't leave comments on the Github issue tracker asking to be assigned an issue. Prepare a fix, create a pull request that fixes the issue, and we will review your pull request when we are able. Do not ask whether an issue is still open -- if it is marked as open in the issue tracker, it is still open.
If you are a beginner, we cannot guide you on how to contribute. We cannot provide tutoring. Contributing to open source software requires contributors to take initiative and work on issues/feature requests they (or others) have seen in the repository and attempt to fix them without oversight from repository maintainers. Please do not ask for support on "how to get started" or "guidance on how to contribute".
python setup.py sdist
python setup.py bdist_wheel
twine upload dist/*