Manage Python Cache workflow (stanford-crfm/helm)

The Manage Python Cache workflow from stanford-crfm/helm, explained and optimized by Latchkey.

CI health: C - fair

Point runs-on at Latchkey and get caching, job timeouts, SHA-pinned actions, self-healing for flaky steps, and up to 58% lower cost, applied automatically.

Grade your own workflow free or run it on Latchkey →

Source: stanford-crfm/helm.github/workflows/manage-python-cache.ymlLicense Apache-2.0View source

What it does

This is the Manage Python Cache workflow from the stanford-crfm/helm repository, a real project running GitHub Actions. It is shown here with attribution under its Apache-2.0 license.

Below, Latchkey shows a faster, safer version produced by its optimization engine.

The workflow

workflow (.yml)

# Workflows for manually managing the Python cache.
#
# HELM's dependencies (e.g. PyTorch, transformers) can be very large,
# and the cache may contain multiple versions of these dependencies,
# so we may have to purge the cache from time to time.

name: Manage Python Cache

on: workflow_dispatch

jobs:
  info:
    name: Show cache info and package list
    runs-on: ubuntu-latest
    strategy:
      matrix:
        python-version: ["3.10", "3.11", "3.12"]
    steps:
      - name: Check out repository
        uses: actions/checkout@v4
      - name: Set up Python
        uses: actions/setup-python@v5
        with:
          python-version: ${{ matrix.python-version }}
      - name: Install uv
        uses: astral-sh/setup-uv@v6
        with:
          version: "0.9.4"
      - name: Get cache size
        run: uv cache size

  purge:
    name: Purge and rebuild cache
    runs-on: ubuntu-latest
    strategy:
      matrix:
        python-version: ["3.10", "3.11", "3.12"]
    steps:
      - name: Check out repository
        uses: actions/checkout@v4
      - name: Set up Python
        uses: actions/setup-python@v5
        with:
          python-version: ${{ matrix.python-version }}
      - name: Install uv
        uses: astral-sh/setup-uv@v6
        with:
          version: "0.9.4"
      - name: Get cache size before clean
        run: uv cache size
      - name: Clean cache
        run: uv cache clean
      - name: Get cache size after clean
        run: uv cache size

The same workflow, on Latchkey

Estimated ~20% faster on cache hits, plus fewer wasted runs and a safer supply chain. Added and changed lines are highlighted.

# Workflows for manually managing the Python cache.
#
# HELM's dependencies (e.g. PyTorch, transformers) can be very large,
# and the cache may contain multiple versions of these dependencies,
# so we may have to purge the cache from time to time.
 
name: Manage Python Cache
 
on: workflow_dispatch
 
jobs:
  info:
    timeout-minutes: 30
    name: Show cache info and package list
    runs-on: latchkey-small
    strategy:
      matrix:
        python-version: ["3.10", "3.11", "3.12"]
    steps:
      - name: Check out repository
        uses: actions/checkout@v4
      - name: Set up Python
        uses: actions/setup-python@v5
        with:
          cache: 'pip'
          python-version: ${{ matrix.python-version }}
      - name: Install uv
        uses: astral-sh/setup-uv@v6
        with:
          version: "0.9.4"
      - name: Get cache size
        run: uv cache size
 
  purge:
    timeout-minutes: 30
    name: Purge and rebuild cache
    runs-on: latchkey-small
    strategy:
      matrix:
        python-version: ["3.10", "3.11", "3.12"]
    steps:
      - name: Check out repository
        uses: actions/checkout@v4
      - name: Set up Python
        uses: actions/setup-python@v5
        with:
          cache: 'pip'
          python-version: ${{ matrix.python-version }}
      - name: Install uv
        uses: astral-sh/setup-uv@v6
        with:
          version: "0.9.4"
      - name: Get cache size before clean
        run: uv cache size
      - name: Clean cache
        run: uv cache clean
      - name: Get cache size after clean
        run: uv cache size

What changed

Run on Latchkey managed runners with one line (runs-on), which apply the fixes below automatically and self-heal transient failures. This example uses latchkey-small; pick the runner size that fits the job.
Cache dependency installs on the setup step so they are served from cache.
Add a job timeout so a hung step cannot burn hours of runner time.

1 third-party action is referenced by a movable tag. Pin it to the commit SHA (Latchkey resolves and applies this automatically) so a repointed tag cannot change what runs.

This workflow runs 2 jobs (6 with the matrix expanded) per trigger. On Latchkey the same minutes cost up to 58% less than GitHub-hosted, with zero queue time.

Actions used in this workflow

actions/checkout actions/setup-python astral-sh/setup-uv