python-tests

oleh nvidia

Tes Python untuk NeMo Fabric; gunakan ini saat menulis tes

npx skills add https://github.com/nvidia/nemo-fabric --skill python-tests

Python Test Style

  • Pytest is used to run tests.
  • Do not add @pytest.mark.asyncio to any test. Async tests are automatically detected and run by the async runner; the decorator is unnecessary clutter.
  • Do not add a -> None return type annotation to test functions. This is not a common convention in pytest and adds unnecessary verbosity.
  • When mocking a class, do not define a new class. Use unittest.mock.MagicMock or unittest.mock.AsyncMock, with the spec constructor argument when necessary.
  • The name of the mocked class should be prefixed with mock, not fake.
  • Prefer pytest fixtures over helper methods.
  • Do not repeat fixtures, if a fixture is needed in multiple test files, place it in a conftest.py file.
  • When creating a fixture follow this pattern:
    @pytest.fixture(name="<fixture_name>"[, scope="<scope>"])
    def <fixture_name>_fixture() -> <return_type>:
        ...
    
    Only specify the scope argument when the value is something other than "function".
  • Prefer pytest.mark.parametrize over creating individual tests for different input types.
  • If a fixture is needed for a test, but either does not return a value or the value is not used in the test, use the @pytest.mark.usefixtures decorator.
  • tests/conftest.py contains a restore_environ_fixture fixture that restores the environment variables to their original state after each test, it is defined with autouse=True so it is automatically applied to all tests. If you need to modify the environment variables in a test, do so using os.environ and the fixture will restore them after the test completes. There is no need to use monkeypatch.setenv to modify environment variables in tests.
  • Avoid defensive programming in tests. If a test fails, it should fail loudly and clearly, rather than silently passing due to defensive checks. For example
    data = results["data"]
    
    is preferred over
    data = results.get("data")
    
    Simply allow the resulting KeyError to be raised if the "data" key is not present in the results dictionary, as this will provide a clear indication of what went wrong in the test.

Common Commands

# Focused test loop
uv run pytest -k "<pattern>"

# Run all tests
uv run pytest

Do Not Write Tests For

  • Documentation.
  • Test helper code under tests/_utils/.
  • Package metadata or wheel installation behavior.

References

  • pyproject.toml
  • tests/conftest.py

Lebih banyak skill dari nvidia

compileiq-debug
nvidia
Gunakan ketika ada yang salah: Search() menggantung, semua evaluasi mengembalikan INVALID_SCORE, skor tidak kunjung membaik, setiap konfigurasi mengembalikan angka yang sama, error ptxas…
create-github-pr
nvidia
Buat pull request GitHub menggunakan gh CLI. Gunakan saat pengguna ingin membuat PR baru, mengirimkan kode untuk ditinjau, atau membuka pull request. Kata kunci pemicu -…
nemoclaw-maintainer-cross-issue-sweep
nvidia
Memindai isu terbuka lainnya untuk menemukan isu yang mungkin juga diperbaiki atau secara tidak sengaja dirusak oleh suatu PR tertentu. Menghasilkan peluang perbaikan yang berdekatan dan risiko kontradiksi dengan file:baris…
fhir-basics
nvidia
Mengajarkan agen cara kerja API FHIR R4, sumber daya apa saja yang tersedia, cara melakukan kueri dengan parameter pencarian, dan cara mengurai semua format respons dengan benar…
compileiq-validate-result
nvidia
Gunakan SETELAH Pencarian selesai dan SEBELUM mengklaim percepatan atau mengirim ACF. Muat CSV dump_results, ekstrak kandidat top-K (tujuan tunggal)…
changelog-audit
nvidia
Audit Warp CHANGELOG.md sebelum rilis: pulihkan entri yang hilang, urutkan berdasarkan dampak pengguna, perbaiki bahasa entri, bungkus baris, dan (mode cabang rilis) naikkan bandingkan…
maintain-dynamic-plugins
nvidia
Mempertahankan pemuat plugin dinamis NeMo Relay, manifes, SDK asli Rust, protokol pekerja gRPC, SDK pekerja Python, dokumen, pengujian, dan cakupan alur kerja rilis
dgx-diagnose
nvidia
Diagnosis masalah umum DGX Station GB300 — crash CUDA, penargetan GPU yang salah, bug kontainer vLLM/SGLang, masalah status MIG, kesalahan NVLink/Fabric Manager,…