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Landscape Memo

Purpose

This memo documents why pytest-gpu-proof was built rather than adopting an existing tool.

Search terms used

  • pytest gpu test plugin
  • pytest signed receipt attestation
  • pytest artifact signing
  • pytest equivalence testing
  • GPU test attestation python
  • pytest-json-report, pytest-artifacts (direct name searches)
  • sigstore python signing pytest
  • NVIDIA attestation SDK python
  • PyPI full-text search: gpu proof, gpu attestation, gpu equivalence

Existing tools evaluated

pytest-json-report

What it does: Emits a JSON report of the test session (outcomes, durations, log output).

Gap: No signing, no code fingerprinting, no GPU-specific helpers. Useful as a complement to this plugin but does not replace it.

pytest-artifacts

What it does: Collects and uploads test artifacts (logs, screenshots) to a configurable store.

Gap: No signing, no equivalence checking, no GPU concept.

GitHub artifact attestations + Sigstore

What it does: Signs GitHub Actions workflow artifacts with Sigstore keyless signing, tied to the GitHub Actions OIDC identity and logged in the Rekor transparency log.

Gap: Works only inside GitHub Actions. Cannot sign a receipt produced on a local developer machine or lab GPU. Has no pytest integration layer, no equivalence testing helpers, and no verifier that understands pytest test outcomes.

Sigstore Python client (sigstore PyPI package)

What it does: Programmatic access to Sigstore signing and verification in Python.

Gap: A library, not a pytest plugin. No GPU equivalence concept, no receipt format, no pytest hooks. Suitable as a future optional signing backend for this plugin.

NVIDIA Attestation SDK (nv-attestation-sdk)

What it does: Hardware-level attestation for NVIDIA Hopper GPUs running in Confidential Computing environments. Produces cryptographic evidence that specific code ran on specific verified GPU hardware.

Gap: Requires Hopper-generation hardware and a Confidential Computing environment. Far too heavyweight for ordinary GPU correctness testing. Solves a different problem (hardware trust) than this plugin (team workflow trust).

pytest-randomly, pytest-benchmark, pytest-cov

None of these are relevant. Included for completeness; all solve adjacent problems.

Conclusion

No maintained package combines:

  • GPU equivalence test helpers (reference vs. candidate comparison)
  • Signed receipt / attestation output
  • Local-first verification flow (SSH key, no cloud dependency)
  • Optional CI-GPU execution mode
  • GitHub-friendly verification policy (public key from github.com/{user}.keys)

Building pytest-gpu-proof as a focused, narrow package is justified. The implementation reuses cryptography (Ed25519, SSH key parsing) and standard pytest hooks rather than inventing new infrastructure.