Setting Up GitHub Actions for Python Code Quality with CodeFactor, wemake‑python‑styleguide, and Codecov

In this tutorial the author explains how to set up a GitHub Actions workflow for a Python project to ensure code quality, style compliance, and test coverage.

First, the article introduces CodeFactor, a free tool for static analysis of public repositories. It describes how to sign in with GitHub, add a repository, and view the list of detected issues.

Next, it shows how to configure the wemake-python-styleguide action in a pull‑request workflow. The workflow file .github/workflows/workflow-pr.yaml is provided, containing four steps: checkout, set up Python 3.8, run unit tests with pytest , and run the styleguide action with the github-pr-review reporter.

name: Python Pull Request Workflow
on: [pull_request]
jobs:
  qa:
    name: Quality check
    runs-on: ubuntu-18.04
    steps:
      - uses: actions/checkout@v1
      - name: Set up Python
        uses: actions/setup-python@master
        with:
          python-version: 3.8
      - name: Run unit tests
        run: |
          pip install pytest
          pytest
      - name: Wemake Python Stylguide
        uses: wemake-services/[email protected]
        continue-on-error: true
        with:
          reporter: 'github-pr-review'
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

The article then explains how to add Codecov to generate a coverage report. After creating a Codecov account and obtaining a token, a second workflow .github/workflows/workflow-master.yaml is defined, which runs on pushes to the master branch, installs pytest and pytest‑cov , generates an XML coverage report, and uploads it using the codecov/codecov-action@v1 action.

name: Python Master Workflow
on:
  push:
    branches:
      - 'master'
jobs:
  codecov:
    name: Codecov Workflow
    runs-on: ubuntu-18.04
    steps:
      - uses: actions/checkout@v1
      - name: Set up Python
        uses: actions/setup-python@master
        with:
          python-version: 3.8
      - name: Generate coverage report
        run: |
          pip install pytest
          pip install pytest-cov
          pytest --cov=./ --cov-report=xml
      - name: Upload coverage to Codecov
        uses: codecov/codecov-action@v1
        with:
          token: ${{ secrets.CODECOV_TOKEN }}
          file: ./coverage.xml
          flags: unittests

Finally, the author advises testing the workflows by creating a branch, opening a pull request, and checking the “Actions” tab for successful runs, as well as viewing the coverage badge on Codecov. The conclusion reminds readers that many other tools (SonarCloud, Pylint, Coveralls, DeepSource) are also available for improving Python code quality.