Upload Python Package workflow (scrapinghub/dateparser)

The Upload Python Package workflow from scrapinghub/dateparser, explained and optimized by Latchkey.

What it does

This is the Upload Python Package workflow from the scrapinghub/dateparser repository, a real project running GitHub Actions. It is shown here with attribution under its BSD-3-Clause license.

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

The workflow

name: Upload Python Package

on:
  release:
    types: [created]

jobs:
  build:
    runs-on: ubuntu-latest

    steps:
      - uses: actions/checkout@v3
      - name: Set up Python
        uses: actions/setup-python@v5
        with:
          python-version: "3.x"
      - name: Install dependencies
        run: |
          python -m pip install --upgrade pip
          pip install build twine
      - name: Build and check
        run: |
          python -m build .
          twine check dist/*
      - name: Upload package
        uses: actions/upload-artifact@v6
        with:
          name: packages
          path: dist/
          if-no-files-found: error
          compression-level: 0

  deploy:
    needs: build
    runs-on: ubuntu-latest

    permissions:
      contents: read
      id-token: write

    environment:
      name: pypi
      url: https://pypi.org/p/dateparser

    steps:
      - name: Download package
        uses: actions/download-artifact@v7
        with:
          name: packages
          path: dist/
      - name: Publish package
        uses: pypa/gh-action-pypi-publish@release/v1
        with:
          print-hash: true
          verbose: true

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: Upload Python Package
 
on:
  release:
    types: [created]
 
jobs:
  build:
    timeout-minutes: 30
    runs-on: latchkey-small
 
    steps:
      - uses: actions/checkout@v3
      - name: Set up Python
        uses: actions/setup-python@v5
        with:
          cache: 'pip'
          python-version: "3.x"
      - name: Install dependencies
        run: |
          python -m pip install --upgrade pip
          pip install build twine
      - name: Build and check
        run: |
          python -m build .
          twine check dist/*
      - name: Upload package
        uses: actions/upload-artifact@v6
        with:
          name: packages
          path: dist/
          if-no-files-found: error
          compression-level: 0
 
  deploy:
    timeout-minutes: 30
    needs: build
    runs-on: latchkey-small
 
    permissions:
      contents: read
      id-token: write
 
    environment:
      name: pypi
      url: https://pypi.org/p/dateparser
 
    steps:
      - name: Download package
        uses: actions/download-artifact@v7
        with:
          name: packages
          path: dist/
      - name: Publish package
        uses: pypa/gh-action-pypi-publish@release/v1
        with:
          print-hash: true
          verbose: true
 

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 2 jobs per trigger. On Latchkey the same minutes cost up to 58% less than GitHub-hosted, with zero queue time.

Actions used in this workflow