dial-mpc package workflow (LeCAR-Lab/dial-mpc)

The dial-mpc package workflow from LeCAR-Lab/dial-mpc, explained and optimized by Latchkey.

What it does

This is the dial-mpc package workflow from the LeCAR-Lab/dial-mpc 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

# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python

name: dial-mpc package

on:
  push:
    branches: [ "main" ]
  pull_request:
    branches: [ "main" ]

jobs:
  build:

    runs-on: ubuntu-22.04
    strategy:
      fail-fast: false
      matrix:
        python-version: ["3.10"]

    steps:
    - uses: actions/checkout@v4
    - name: Set up Python ${{ matrix.python-version }}
      uses: actions/setup-python@v3
      with:
        python-version: ${{ matrix.python-version }}
    - name: Install
      run: |
        python -m pip install --upgrade pip
        python -m pip install flake8 pytest
        pip install .
    # - name: Lint with flake8
    #   run: |
    #     # stop the build if there are Python syntax errors or undefined names
    #     flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
    #     # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
    #     flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
    # - name: Test with pytest
    #   run: |
    #     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://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python
 
name: dial-mpc package
 
on:
  push:
    branches: [ "main" ]
  pull_request:
    branches: [ "main" ]
 
concurrency:
  group: ${{ github.workflow }}-${{ github.ref }}
  cancel-in-progress: true
 
jobs:
  build:
    timeout-minutes: 30
 
    runs-on: latchkey-small
    strategy:
      fail-fast: false
      matrix:
        python-version: ["3.10"]
 
    steps:
    - uses: actions/checkout@v4
    - name: Set up Python ${{ matrix.python-version }}
      uses: actions/setup-python@v3
      with:
        cache: 'pip'
        python-version: ${{ matrix.python-version }}
    - name: Install
      run: |
        python -m pip install --upgrade pip
        python -m pip install flake8 pytest
        pip install .
    # - name: Lint with flake8
    #   run: |
    #     # stop the build if there are Python syntax errors or undefined names
    #     flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
    #     # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
    #     flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
    # - name: Test with pytest
    #   run: |
    #     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 uses latchkey-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 per trigger. On Latchkey the same minutes cost up to 58% less than GitHub-hosted, with zero queue time.

Actions used in this workflow