CI workflow (DLR-RM/rl-baselines3-zoo)
The CI workflow from DLR-RM/rl-baselines3-zoo, explained and optimized by Latchkey.
CI health: D - needs work
Point runs-on at Latchkey and get caching, run de-duplication, job timeouts, self-healing for flaky steps, and up to 58% lower cost, applied automatically.
What it does
This is the CI workflow from the DLR-RM/rl-baselines3-zoo repository, a real project running GitHub Actions. It is shown here with attribution under its MIT license.
Below, Latchkey shows a faster, safer version produced by its optimization engine.
The workflow
# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
name: CI
on:
push:
branches: [master]
pull_request:
branches: [master]
jobs:
build:
env:
TERM: xterm-256color
FORCE_COLOR: 1
HF_TOKEN: ${{ secrets.HF_TOKEN }}
# Skip CI if [ci skip] in the commit message
if: "! contains(toJSON(github.event.commits.*.message), '[ci skip]')"
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ["3.10", "3.11", "3.12", "3.13"]
include:
# Default version
- gymnasium-version: "1.0.0"
# Add a new config to test gym<1.0
- python-version: "3.10"
gymnasium-version: "0.29.1"
steps:
- uses: actions/checkout@v6
with:
submodules: true
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v6
with:
python-version: ${{ matrix.python-version }}
- name: Install dependencies
run: |
python -m pip install --upgrade pip
# Use uv for faster downloads
pip install uv
# cpu version of pytorch
# See https://github.com/astral-sh/uv/issues/1497
# Need Pytorch 2.9+ for Python 3.13
uv pip install --system torch==2.9.1+cpu --index https://download.pytorch.org/whl/cpu
# Install full requirements (for additional envs and test tools)
uv pip install --system -r requirements.txt
# Use headless version
uv pip install --system opencv-python-headless
uv pip install --system -e .[plots,tests]
- name: Install specific version of gym
run: |
uv pip install --system gymnasium==${{ matrix.gymnasium-version }}
uv pip install --system "numpy<2"
uv pip install --system "ale-py==0.10.1"
# Only run for python 3.10, downgrade gym to 0.29.1
if: matrix.gymnasium-version != '1.0.0'
- name: Lint with ruff
run: |
make lint
- name: Check codestyle
run: |
make check-codestyle
- name: Build the doc
run: |
make doc
- name: Type check
run: |
make type
- name: Test with pytest
run: |
make pytest
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.
# This workflow will install Python dependencies, run tests and lint with a variety of Python versions # For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions name: CI on: push: branches: [master] pull_request: branches: [master] concurrency: group: ${{ github.workflow }}-${{ github.ref }} cancel-in-progress: true jobs: build: timeout-minutes: 30 env: TERM: xterm-256color FORCE_COLOR: 1 HF_TOKEN: ${{ secrets.HF_TOKEN }} # Skip CI if [ci skip] in the commit message if: "! contains(toJSON(github.event.commits.*.message), '[ci skip]')" runs-on: latchkey-small strategy: matrix: python-version: ["3.10", "3.11", "3.12", "3.13"] include: # Default version - gymnasium-version: "1.0.0" # Add a new config to test gym<1.0 - python-version: "3.10" gymnasium-version: "0.29.1" steps: - uses: actions/checkout@v6 with: submodules: true - name: Set up Python ${{ matrix.python-version }} uses: actions/setup-python@v6 with: cache: 'pip' python-version: ${{ matrix.python-version }} - name: Install dependencies run: | python -m pip install --upgrade pip # Use uv for faster downloads pip install uv # cpu version of pytorch # See https://github.com/astral-sh/uv/issues/1497 # Need Pytorch 2.9+ for Python 3.13 uv pip install --system torch==2.9.1+cpu --index https://download.pytorch.org/whl/cpu # Install full requirements (for additional envs and test tools) uv pip install --system -r requirements.txt # Use headless version uv pip install --system opencv-python-headless uv pip install --system -e .[plots,tests] - name: Install specific version of gym run: | uv pip install --system gymnasium==${{ matrix.gymnasium-version }} uv pip install --system "numpy<2" uv pip install --system "ale-py==0.10.1" # Only run for python 3.10, downgrade gym to 0.29.1 if: matrix.gymnasium-version != '1.0.0' - name: Lint with ruff run: | make lint - name: Check codestyle run: | make check-codestyle - name: Build the doc run: | make doc - name: Type check run: | make type - name: Test with pytest run: | make pytest
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 useslatchkey-small; pick the runner size that fits the job. - Cancel superseded runs when a branch or PR gets a newer push.
- 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.
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 (4 with the matrix expanded) per trigger. On Latchkey the same minutes cost up to 58% less than GitHub-hosted, with zero queue time.