Restore compatible Python environments

Restore the resolved virtual environment and keep the install step after it.

Prompt

Evaluate and apply this CI technique to my repository: Restore compatible Python environments.

Restore the resolved virtual environment and keep the install step after it.

Read the technique and its source-backed company examples: https://starsling.dev/ci-playbooks/techniques/cache-python-environments.md

Inspect this repository’s CI workflows, build and test commands, dependencies, and recent run timings. Identify where this technique applies and explain the expected benefit using this repository’s evidence.
Measure a baseline from recent comparable runs: elapsed time, queue time, runner minutes and failures where available. If data is unavailable, say what cannot be measured.
Compare relevant company approaches, checking prerequisites, platform differences and tradeoffs. Rank applicable options by evidence, fit and measurable opportunity; do not present company results as predictions for this repo.
Recommend the smallest safe change, show what checks and fallback paths remain, and ASK ME WHICH CHANGE TO APPROVE BEFORE EDITING ANY FILES.
Only after approval, work on a new feature branch, make one reversible change, and open a reviewable pull request. Never merge or push to a default or protected branch.
Keep required checks, test coverage, deployment and release behavior intact. Validate the change and compare equivalent runs where possible; report limitations and what should be monitored after merge.

View all playbooks

How OpenAI used this technique

Read what OpenAI changed and follow the original sources.

Restore compatible Python environments

The Python SDK added a virtual-environment cache to three jobs, keyed by operating system, architecture, resolved Python version and both lockfiles, with dependency sync still running after the restore. The repository now uses uv's built-in cache (openai/openai-python#3653).

Environment cache keyed by OS, architecture, Python version and lockfiles Source

Repository moved to uv, with uv's built-in cache in CI Source

Use it when: Dependency installation repeats on fresh CI runners despite unchanged interpreter and lockfiles.
Before applying it: Virtual environments can hold interpreter-specific paths and binaries. Key on everything that changes them, and keep the install step so a stale cache is repaired.

How OpenAI used this technique

Restore compatible Python environments

Related techniques

Bake stable dependencies into runner images

Cache package downloads and dependency stores

Cache the directories the build actually uses

Company Playbooks

Related guides

Cache workflow dependencies

Cut repeated test setup

Share setup steps across jobs

Optimize npm installs

Optimize pnpm installs