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PureSkill.gg Data Science Showcase

PyPI GitHub Actions

Showcase of public PureSkill.gg data set applications.

Description

TODO

Installation

This package is registered on the Python Package Index (PyPI) as pureskillgg-datascience-showcase.

Install it with

$ poetry add pureskillgg-datascience-showcase

Development and Testing

Quickstart

$ git clone https://github.com/pureskillgg/datascience-showcase.git
$ cd pyskill
$ poetry install

Run each command below in a separate terminal window:

$ make watch

Primary development tasks are defined in the Makefile.

Source Code

The source code is hosted on GitHub. Clone the project with

$ git clone https://github.com/pureskillgg/datascience-showcase.git

Requirements

You will need Python 3 and Poetry.

Install the development dependencies with

$ poetry install

Tests

Lint code with

$ make lint

Run tests with

$ make test

Run tests on changes with

$ make watch

Publishing

Use the bump2version command to release a new version. Push the created git tag which will trigger a GitHub action.

Publishing may be triggered using on the web using a workflow_dispatch on GitHub Actions.

GitHub Actions

GitHub Actions should already be configured: this section is for reference only.

The following repository secrets must be set on GitHub Actions.

  • PYPI_API_TOKEN: API token for publishing on PyPI.

These must be set manually.

Secrets for Optional GitHub Actions

The version and format GitHub actions require a user with write access to the repository including access to read and write packages. Set these additional secrets to enable the action:

  • GH_USER: The GitHub user's username.
  • GH_TOKEN: A personal access token for the user.
  • GIT_USER_NAME: The name to set for Git commits.
  • GIT_USER_EMAIL: The email to set for Git commits.
  • GPG_PRIVATE_KEY: The GPG private key.
  • GPG_PASSPHRASE: The GPG key passphrase.

Contributing

Please submit and comment on bug reports and feature requests.

To submit a patch:

  1. Fork it (https://github.com/pureskillgg/datascience-showcase/fork).
  2. Create your feature branch (git checkout -b my-new-feature).
  3. Make changes.
  4. Commit your changes (git commit -am 'Add some feature').
  5. Push to the branch (git push origin my-new-feature).
  6. Create a new Pull Request.

License

This Python package is licensed under the MIT license.

Warranty

This software is provided by the copyright holders and contributors "as is" and any express or implied warranties, including, but not limited to, the implied warranties of merchantability and fitness for a particular purpose are disclaimed. In no event shall the copyright holder or contributors be liable for any direct, indirect, incidental, special, exemplary, or consequential damages (including, but not limited to, procurement of substitute goods or services; loss of use, data, or profits; or business interruption) however caused and on any theory of liability, whether in contract, strict liability, or tort (including negligence or otherwise) arising in any way out of the use of this software, even if advised of the possibility of such damage.