Create CI workflow#100
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Set Python version to 3.14 and update dependencies installation steps.
Allow tests to continue on error for better CI flow.
Added continue-on-error option for coverage report and flake8 checks.
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Review Summary
I am requesting changes because there are a few critical issues that prevent the workflow from reliably fulfilling the assignment requirements. First, the env.PythonVersion is set to 3.14 (around line 14), which is not a real Python release; this will cause actions/setup-python to fail and the workflow cannot run at all—update this to a supported 3.x version like 3.10 or 3.11 to stay compatible with Django 4. Second, the test step (Test application, around line 39) and the coverage generation step are marked with continue-on-error: true, which means failing tests or coverage issues will not fail the job, contradicting the requirement that only flake8 style and complexity checks should be non-blocking. Third, the artifact upload step (around lines 56–59) specifies only name: python-code and no path, so no Python files are actually uploaded, and the artifact requirement is not met; you should add a path such as path: . or path: ./src depending on your project structure.
To fix this, 1) set PythonVersion to a valid, supported version (e.g., 3.10), 2) remove continue-on-error from the main test and coverage steps so that failures there block the workflow, and 3) add a proper path to the upload-artifact step so your Python code is archived. Aside from these blockers, the rest of the workflow structure—triggers, job name, flake8 steps, and coverage commands—is well aligned with the requirements, so you are very close to a correct solution. Once you address these items, your workflow should both run successfully and accurately enforce the project’s CI expectations.
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Footnotes
| jobs: | ||
| python-ci: | ||
| env: | ||
| PythonVersion: 3.14 |
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Using PythonVersion: 3.14 will cause actions/setup-python to fail because Python 3.14 is not released; the description expects a real 3.8+ version for Django 4. Consider setting this to a currently supported version like 3.10 or 3.11 so the workflow can run successfully.
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| - name: Test application | ||
| run: python manage.py test | ||
| continue-on-error: true |
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This test step is marked continue-on-error: true, so failing tests won’t fail the workflow. The requirements only specify that flake8 style/complexity checks should be non-blocking; tests should normally block the workflow so that PR checks only pass when tests succeed.
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| - name: Generate coverage report | ||
| run: coverage run manage.py test | ||
| continue-on-error: true |
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Similarly to the test step, making coverage generation non-blocking means coverage failures won’t fail the workflow. For CI robustness, consider letting this step fail the job so coverage issues are visible, while keeping only the flake8 checks non-blocking as required.
| - name: Upload python code as an artifact | ||
| uses: actions/upload-artifact@v4 | ||
| with: | ||
| name: python-code |
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This artifact upload step defines only a name but no path, so no files will actually be uploaded. To satisfy the requirement to upload Python code as an artifact, add a path (e.g., path: . or path: ./src) containing the Python source you want to archive.
Updated Python version and removed continue-on-error for tests.
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Review Summary
I am approving your solution because your GitHub Actions workflow now correctly implements all the core CI requirements for this assignment. The workflow triggers on pushes to main and develop and on pull requests to main, and the run-name properly includes both github.actor and github.sha, so runs are clearly identifiable. The python-ci job sets the Python version via an environment variable (PythonVersion: 3.11), installs dependencies with pip install -r requirements.txt, runs python manage.py test, generates coverage with coverage run manage.py test, and prints the coverage report with coverage report, which matches the required behavior. You also run flake8 twice (for style and complexity) with continue-on-error: true, making those checks non-blocking as specified, and you upload the Python code as an artifact using actions/upload-artifact with a valid path.
No critical blockers remain; the only considerations are minor, such as the assumption that manage.py and requirements.txt live under ./src and the small typo in the run name (Action triggerd). If your project structure differs, you may need to adjust defaults.run.working-directory, and you can optionally fix the typo to improve readability in the Actions UI. Overall, this is a solid CI configuration that meets the task’s functional requirements and demonstrates good use of GitHub Actions.
✨ Please rate this review in the Platform's notification center1. I will be grateful for your feedback! ✨
Footnotes
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