Pytest dev
AgentSkills library: reusable skills for AI coding agents (AI SDK, Codex, LangGraph, Supabase, Docker, Vitest, pytest, Streamlit, Zod).
npx -y skills add BjornMelin/dev-skills --skill pytest-devAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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World-class pytest engineer for Python: write/refactor tests, fix flakiness, design fixtures/markers, add coverage, speed up suites (collection/runtime), and optimize CI (GitHub Actions sharding, xdist parallelism, caching). Use when asked about pytest best practices, pytest 9.x features (subtests, strict mode, TOML config), pytest plugins (xdist/cov/asyncio/mock/httpx), or test performance/CI tuning.
SKILL.md
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pytest-dev
Produce high-signal, low-flake, fast pytest suites and CI configs, with an explicit focus on measurable wins (runtime, flake rate, coverage quality).
Default workflow
- Classify the tests
- Unit: pure functions, no I/O (preferred)
- Integration: DB/filesystem/multiprocess, slower but valuable
- System/E2E: external services or UI, keep minimal and well-gated
- Identify boundaries
- Time/clock, randomness, network, filesystem, DB, env vars, global state
- Pick the lightest seam
- Prefer fakes/stubs over deep mocks; prefer dependency injection over patching internals
- Make it deterministic
- Control time, seeds, tmp dirs; avoid order dependencies
- Measure before optimizing
- Collection time vs runtime; quantify with
--durations+ a single baseline
- Collection time vs runtime; quantify with
- Harden for CI
- Enforce marker discipline, strict config, timeouts, isolation for parallel
Quick commands
Use python3 by default. If the project uses uv, prefer uv run python.
- Smallest repro:
python3 -m pytest path/to/test_file.py -q - First failure only:
python3 -m pytest -x --maxfail=1 - Find slow tests:
python3 -m pytest --durations=20 --durations-min=0.5 - Emit JUnit for CI:
python3 -m pytest --junitxml=reports/junit.xml - Parallelize on one machine (xdist):
python3 -m pytest -n auto --dist load
Optimization playbook (high ROI)
- Reduce collection scope (
testpaths,norecursedirs, avoid importing heavy modules at import time). - Fix fixture scoping (move expensive setup up-scope; ensure isolation).
- Eliminate sleeps and retries (poll with timeouts; mock time).
- Parallelize safely (xdist; isolate worker resources: tmp/db ports).
- Shard in CI (split test files by historical timings; keep shards balanced).
Use the bundled references
Read these when needed (keep SKILL.md lean):
references/pytest_core.md: fixtures, markers, parametrization, strict mode, TOML config, subtests (pytest 9.x).references/plugins.md: plugin selection + usage patterns.references/performance.md: collection/runtime profiling and speedups.references/ci_github_actions.md: sharding, artifacts, caching, concurrency.
Use the bundled scripts
scripts/junit_slowest.py: report slowest tests/files from JUnit XML.scripts/junit_split.py: split test files into N shards using JUnit timings.scripts/run_pytest_filelist.py: run pytest for a list of test files.
Quality gates
- Tests pass in a clean environment (no hidden dependency on local state).
- No network/time dependency without explicit control.
- Parallel-safe or explicitly marked/serialized.
- CI emits machine-readable artifacts when relevant (JUnit, coverage).