Benchmarks workflow (datachain-ai/datachain)

The Benchmarks workflow from datachain-ai/datachain, explained and optimized by Latchkey.

What it does

This is the Benchmarks workflow from the datachain-ai/datachain 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

name: Benchmarks

on:
  schedule:
    - cron: '0 0 * * *'
  pull_request:
    types: [opened, reopened, labeled, synchronize]
  workflow_dispatch:

env:
  FORCE_COLOR: "1"

concurrency:
  group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
  cancel-in-progress: true

jobs:
  run:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v7
      - name: Set up Python 3.13
        uses: actions/setup-python@v6
        with:
          python-version: '3.13'

      - name: Setup uv
        uses: astral-sh/setup-uv@v7
        with:
          enable-cache: true
          cache-suffix: benchmarks
          cache-dependency-glob: pyproject.toml

      - name: Install nox and dvc
        run: uv pip install dvc[gs] nox --system

      - name: Pull dataset
        run: dvc --cd tests/benchmarks/datasets pull
      - name: Run benchmarks
        run: nox -s bench

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.

name: Benchmarks
 
on:
  schedule:
    - cron: '0 0 * * *'
  pull_request:
    types: [opened, reopened, labeled, synchronize]
  workflow_dispatch:
 
env:
  FORCE_COLOR: "1"
 
concurrency:
  group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
  cancel-in-progress: true
 
jobs:
  run:
    timeout-minutes: 30
    runs-on: latchkey-small
    steps:
      - uses: actions/checkout@v7
      - name: Set up Python 3.13
        uses: actions/setup-python@v6
        with:
          cache: 'pip'
          python-version: '3.13'
 
      - name: Setup uv
        uses: astral-sh/setup-uv@v7
        with:
          enable-cache: true
          cache-suffix: benchmarks
          cache-dependency-glob: pyproject.toml
 
      - name: Install nox and dvc
        run: uv pip install dvc[gs] nox --system
 
      - name: Pull dataset
        run: dvc --cd tests/benchmarks/datasets pull
      - name: Run benchmarks
        run: nox -s bench
 

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.

What Latchkey heals here

This workflow has steps that commonly fail on transient issues (network, registries, flaky browsers). On Latchkey managed runners they are detected, retried, and self-healed instead of failing your build:

• Dependency installs

This workflow runs 1 job per trigger. On Latchkey the same minutes cost up to 58% less than GitHub-hosted, with zero queue time.

Actions used in this workflow