CI: every job downloads a CPython interpreter, and that download is a recurring single point of failure
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Nadie ha tomado este issue todavía.
Evaluación
- Dificultad
- 4/5
- Tiempo estimado
- 3-5 días
- Aptitud para principiantes
- 55/100
Línea de trabajo
Comienza con template/.github/workflows/tests.yml.jinja, nightly.yml.jinja y commit-message.yml.jinja; después, compara sus equivalentes en .github/workflows. Revisa cada aparición de uv python install indicada y verifica la matriz completa de Python frente a los intérpretes proporcionados por los runners propuestos. Se considera terminado cuando los workflows siguen estando en paridad y ya no dependen de descargar CPython para estos jobs.
Escrito por el modelo de indexación a partir del texto del issue.
Descripción
What happens
Every CI job in the template, and therefore in all seven generated projects, begins with a step that downloads a CPython interpreter:
- name: Set up Python
run: uv python install ${{ matrix.python-version }}
uv python install fetches a build from the astral-sh/python-build-standalone GitHub release. When that download fails, the job dies before running a single test, and the PR goes red for a reason unrelated to its contents.
Over roughly twelve hours on 2026-08-12/13 this failed repeatedly, on main and on four separate pull requests, always at the same step:
error: Failed to install cpython-3.12.12-linux-x86_64-gnu
Caused by: Request failed after 3 retries
Caused by: Failed to download https://github.com/astral-sh/python-build-standalone/releases/download/.../cpython-3.12.12+...-x86_64-unknown-linux-gnu-install_only_stripped.tar.gz
Caused by: http2 error
Caused by: stream error received: refused stream before processing any application logic
It also appeared as 503 Service Unavailable and curl: (56) Connection died. It hit ubuntu, macOS and Windows runners, and every Python version in the matrix. uv already retries three times internally, and that was not enough.
The same outage took out other GitHub release downloads in the same window (the gitleaks install step, and Read the Docs' asdf install uv), so the cause is upstream rather than anything in this repo. The point of this issue is that our workflows put that download on the critical path when they do not have to.
Why it is worth fixing rather than re-running
- It is not rare. Five re-runs in one session, and each costs a full matrix.
- It is indistinguishable at a glance from a real failure. Every occurrence needs someone to open the job log and read which step died before they know whether to trust the red.
- It scales with the fleet: ten
uv python installsteps in the template'stests.ymlalone, times eight repositories. - The runner images already ship the interpreters we ask for.
actions/setup-pythonresolves common versions from the runner's tool cache with no network download at all.
Affected files
template/.github/workflows/:
tests.yml.jinja— 8 occurrences (lines 56, 91, 136, 193, 223, 252, 325, 358)nightly.yml.jinja— 1 (line 44)commit-message.yml.jinja— 1 (line 52)
and the same shape in this repository's own .github/workflows/{tests,nightly,commit-message}.yml, which must be kept in parity.
Options
actions/setup-pythonfor the interpreter, uv for everything else. Replace theuv python installstep withactions/setup-python, and setUV_PYTHON_PREFERENCE=only-systemso uv uses it rather than fetching its own. Versions present in the runner tool cache then need no download.- Keep
uv python installand add a retry wrapper. Smaller change, but it makes a bad minute into a slow minute rather than removing the dependency, and uv already retries three times. - Do nothing and re-run. The status quo. Worth stating explicitly, because the cost is real but bounded.
Option 1 is the one that removes the failure mode. It also needs care: setup-python and uv python install do not resolve versions identically (patch pinning, free-threaded builds, and versions newer than the runner image differ), so this should be measured on the full matrix before it fans out.
Not in scope
The astral-sh/setup-uv step that installs uv itself, and the pinned # renovate: versions on it. Those are a separate download and have not been the failing step.
- Lenguaje dominante
- Python
- Estrellas
- 5
- Forks
- 1
- Merge medio
- 1 d 4 h
- PR fusionados (30 d)
- 58
Preparar el entorno
- Sin Dockerfile ni archivo de Docker Compose
- Tiene una plantilla de pull request
- Sin guía de contribución
Primeros pasos
- Lee el issue completo y luego la guía de contribución del proyecto.
- Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
- Haz un fork del repositorio y trabaja en una rama.
- Abre un pull request que haga referencia al número del issue.
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