Build workflow (tensorflow/graphics)

The Build workflow from tensorflow/graphics, explained and optimized by Latchkey.

CI health: D - needs work

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Source: tensorflow/graphics.github/workflows/build.ymlLicense Apache-2.0View source

What it does

This is the Build workflow from the tensorflow/graphics 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)

# Continuous integration tests executed on push and pull request actions
# see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions

name: Build

on:
  push:
    branches: [ master ]
  pull_request:
    branches: [ master ]

jobs:
  build:
    runs-on: ubuntu-latest
    steps:
    - uses: actions/checkout@v2
    - name: Set up Python
      uses: actions/setup-python@v2
      with:
        python-version: 3.8
    - name: Install system requirements
      run: |
        sudo xargs apt-get update
        sudo xargs apt-get -y install < requirements.unix
    - name: Install pip requirements
      run: |
        python -m pip install --upgrade pip
        pip install -U -r requirements.txt
        pip install -U pytest coveralls
        pip install -U flake8
        pip install -U setuptools wheel
    - name: Build ops
      run: |
        bazel build tensorflow_graphics/... --define=BASEDIR=$(pwd) --sandbox_writable_path=$(pwd)
        bazel clean --expunge
    - name: Run python tests and coverage
      env:
        GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
        MESA_GL_VERSION_OVERRIDE: 4.5
        MESA_GLSL_VERSION_OVERRIDE: 450
      run: |
        coverage run --source tensorflow_graphics -m py.test
        coveralls --service=github
    - name: Linter
      run: |
        flake8 --config=.flake8 tensorflow_graphics/
    - name: Build pip package and install
      run: |
        python setup.py sdist bdist_wheel
        pip install dist/*.whl
    - name: Test install
      run: |
        cd $(mktemp -d) && python -c 'import tensorflow_graphics as tfg'

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.

# Continuous integration tests executed on push and pull request actions
# see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
 
name: Build
 
on:
  push:
    branches: [ master ]
  pull_request:
    branches: [ master ]
 
concurrency:
  group: ${{ github.workflow }}-${{ github.ref }}
  cancel-in-progress: true
 
jobs:
  build:
    timeout-minutes: 30
    runs-on: latchkey-small
    steps:
    - uses: actions/checkout@v2
    - name: Set up Python
      uses: actions/setup-python@v2
      with:
        cache: 'pip'
        python-version: 3.8
    - name: Install system requirements
      run: |
        sudo xargs apt-get update
        sudo xargs apt-get -y install < requirements.unix
    - name: Install pip requirements
      run: |
        python -m pip install --upgrade pip
        pip install -U -r requirements.txt
        pip install -U pytest coveralls
        pip install -U flake8
        pip install -U setuptools wheel
    - name: Build ops
      run: |
        bazel build tensorflow_graphics/... --define=BASEDIR=$(pwd) --sandbox_writable_path=$(pwd)
        bazel clean --expunge
    - name: Run python tests and coverage
      env:
        GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
        MESA_GL_VERSION_OVERRIDE: 4.5
        MESA_GLSL_VERSION_OVERRIDE: 450
      run: |
        coverage run --source tensorflow_graphics -m py.test
        coveralls --service=github
    - name: Linter
      run: |
        flake8 --config=.flake8 tensorflow_graphics/
    - name: Build pip package and install
      run: |
        python setup.py sdist bdist_wheel
        pip install dist/*.whl
    - name: Test install
      run: |
        cd $(mktemp -d) && python -c 'import tensorflow_graphics as tfg'

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

actions/checkout actions/setup-python