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Version: 2.25 (deprecated)

Maintenance tasks and scripts

There's a variety of maintenance tasks that happen on different frequencies.

Update the default/known versions of a built-in tool/subsystem​

External tools (downloaded executables)​

Some tools use the ExternalTool class to download a binary from the internet, verify its size and hash, and then execute it.

To update these:

  1. For each platform and version to add:
    1. Download the archive/binary.
    2. Verify it: check signatures and/or hashes if available.
    3. Compute the sha256 hash and byte length. For example, if it's called archive.zip: tee >(shasum -a 256) >(wc -c) > /dev/null < archive.zip.
  2. Apply the new values:
    1. Adjust default_version to the new version.
    2. Add or replace to default_known_versions using the hashes and lengths above (for some tools we don't preserve older versions, especially if they have strong backwards compatibility guarantees, while for others we do retain older versions).

Example: #20469.

PEX​

The PEX external tool is a bit special, because it also appears as a requirement of the Pants project itself in 3rdparty/python/requirements.txt. To update pex, do both:

  1. Update the pex-cli subsystem, as above (in src/python/pants/backend/python/util_rules/pex_cli.py).
  2. Update the requirements file and run pants generate-lockfiles --resolve=python-default to update Pants' own lockfile.

Example: #20782.

Terraform​

The build-support/bin/terraform_tool_versions.py script can help update Terraform versions.

Python tools​

Some tools use PythonToolBase to install executable PyPI packages, using a lockfile. Pants packages a default lockfile with a specific version of the package. To update these:

  1. Adjust default_requirements and/or default_interpreter_constraints as required.
  2. Run build-support/bin/generate_builtin_lockfiles.py $scope, where $scope is the options_scope of the subsystem class.

Example: #20924.

JVM tools​

Some tools use JVMToolBase to install executable JVM packages, using a lockfile. Pants packages a default lockfile with a specific version of the package. To update these:

  1. Adjust default_version and/or default_artifacts as required.
  2. Run build-support/bin/generate_builtin_lockfiles.py $scope, where $scope is the options_scope of the subsystem class.

Example: none yet.

JS tools​

Some tools use NodeJSToolBase to install executable npm packages. To update these:

  1. Update default_version. That's all.

Example: #21007.

Python Build Standalone known versions​

The Python Build Standalone providers needs to be updated with new upstream releases. There are many artifacts here, so the hashes are stored in a json file that is updated by running:

pants run src/python/pants/backend/python/providers/python_build_standalone/scripts/generate_urls.py

Update or create FaaS complete platforms files​

The function-as-a-service (FaaS) subsystems provide some built-in PEX complete platforms JSON files, for specific runtimes. To update or create these:

AWS Lambda​

  1. Adjust PythonAwsLambdaRuntime.known_runtimes as required
  2. Run build-support/bin/generate_faas_complete_platforms.py to create any new files and update the existing ones, using AWS's published docker images

Example: #21004.

Google Cloud Functions​

  1. Adjust PythonGoogleCloudFunctionRuntime.known_runtimes as required
  2. Run build-support/bin/generate_faas_complete_platforms.py to create any new files and update the existing ones, using GCF's published docker images

Example: #21248.

Cherry-pick a pull request to an older version​

We maintain multiple versions, with main being our development branch, and various 2.*.x branches for the stable versions (see Release strategy for more details).

Cherry-picking a new pull request​

When a change needs to land in main but also one or more older versions, the usual process is:

  1. Create or review the pull request against main as usual
  2. Label it as needs-cherrypick and set milestone to the oldest release to which it should be cherry-picked
  3. Merge the pull request as normal
  4. At this point, automation kicks in and attempts to cherrypick the merged commit to the release in the milestone and any newer ones.
  5. The automation opens pull requests targeting each of the relevant 2.*.x branches for which cherry-picking succeeds.
  6. If the automation fails to do a cherry-pick, it will mark the PR as auto-cherry-picking-failed
  7. In either case, the automation will add a comment describing what happened to the original pull request.

For example, suppose main is for 2.23.x and we're still maintaining 2.20.x, 2.21.x and 2.22.x. If a pull request is labelled needs-cherrypick and has milestone 2.21.x, then merging it will attempt to cherry pick to 2.21.x and 2.22.x.

The process may fail in one of two ways:

  • The cherry-picking process failed, and tagged the PR with auto-cherry-picking-failed: follow the instructions in the comment on the pull request. (This likely means there are merge conflicts that require manual resolution.)
  • the cherry-pick hasn't (yet) run: trigger the automation manually by going to the GitHub Action, clicking on the "Run workflow" button, and providing the PR number.

Cherry-picking a merged pull request​

A pull request might merged without being configured for cherry-picking, and we decide later that it should be. To cherry-pick in this case:

  1. Label the pull request as needs-cherrypick and set milestone to the oldest release to which it should be cherry-picked
  2. Trigger the automation manually by going to the GitHub Action, clicking on the "Run workflow" button, and providing the PR number.
  3. As above, the automation may (partially) succeed or fail, and will leave a comment describing what happened.