78 lines
3.7 KiB
Markdown
78 lines
3.7 KiB
Markdown
Tips for shorter build times
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### Runner availability ###
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Currently, the biggest bottleneck when optimizing workflows is the availability
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of Windows and macOS runners. Therefore, anything that reduces the time spent in
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Windows or macOS jobs will have a positive impact on the time waiting for
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runners to become available. The usage limits for Github Actions are [described
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here][limits]. You can see a breakdown of runner usage for your jobs in the
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Github Actions tab ([example][usage]).
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### Windows is slow ###
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Performing git operations and compilation are both slow on Windows. This can
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easily mean that a Windows job takes twice as long as a Linux job. Therefore it
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makes sense to use a Windows runner only for testing Windows compatibility, and
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nothing else. Testing compatibility with other versions of Nim, code coverage
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analysis, etc. are therefore better performed on a Linux runner.
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### Parallelization ###
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Breaking up a long build job into several jobs that you run in parallel can have
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a positive impact on the wall clock time that a workflow runs. For instance, you
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might consider running unit tests and integration tests in parallel. Keep in
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mind however that availability of macOS and Windows runners is the biggest
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bottleneck. If you split a Windows job into two jobs, you now need to wait for
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two Windows runners to become available! Therefore parallelization often only
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makes sense for Linux jobs.
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### Refactoring ###
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As with any code, complex workflows are hard to read and change. You can use
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[composite actions][composite] and [reusable workflows][reusable] to refactor
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complex workflows.
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### Steps for measuring time
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Breaking up steps allows you to see the time spent in each part. For instance,
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instead of having one step where all tests are performed, you might consider
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having separate steps for e.g. unit tests and integration tests, so that you can
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see how much time is spent in each.
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### Fix slow tests ###
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Try to avoid slow unit tests. They not only slow down continuous integration,
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but also local development. If you encounter slow tests you can consider
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reworking them to stub out the slow parts that are not under test, or use
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smaller data structures for the test.
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You can use [unittest2][unittest2] together with the environment variable
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`NIMTEST_TIMING=true` to show how much time is spent in every test
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([reference][testtime]).
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### Caching ###
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Ensure that caches are updated over time. For instance if you cache the latest
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version of the Nim compiler, then you want to update the cache when a new
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version of the compiler is released. See also the documentation
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for the [cache action][cache].
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### Fail fast ###
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By default a workflow fails fast: if one job fails, the rest are cancelled. This
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might seem inconvenient, because when you're debugging an issue you often want
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to know whether you introduced a failure on all platforms, or only on a single
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one. You might be tempted to disable fail-fast, but keep in mind that this keeps
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runners busy for longer on a workflow that you know is going to fail anyway.
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Consequent runs will therefore take longer to start. Fail fast is most likely better for overall development speed.
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[usage]: https://github.com/codex-storage/nim-codex/actions/runs/3462031231/usage
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[composite]: https://docs.github.com/en/actions/creating-actions/creating-a-composite-action
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[reusable]: https://docs.github.com/en/actions/using-workflows/reusing-workflows
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[cache]: https://github.com/actions/cache/blob/main/workarounds.md#update-a-cache
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[unittest2]: https://github.com/status-im/nim-unittest2
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[testtime]: https://github.com/status-im/nim-unittest2/pull/12
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[limits]: https://docs.github.com/en/actions/learn-github-actions/usage-limits-billing-and-administration#usage-limits
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