Using Pants in CI
Suggestions for how to use Pants to speed up your CI (continuous integration).
.travis.yml
See https://github.com/pantsbuild/example-python/blob/main/.travis.yml for an example of how to configure Pants with Travis CI.
pants.ci.toml
(optional)
If you have config that you want to only use in CI, it can be helpful to create a dedicated pants.ci.toml
config file. For example:
[GLOBAL]
dynamic_ui = false
# Ensure colors are used (if your CI provider supports it).
colors = true
# Limit the maximum number of concurrent processes. Change this
# to a number that makes sense for your CI setup, based on
# the number of cores/threads.
process_execution_local_parallelism = 4
[python-setup]
# Limit the maximum number of concurrent jobs used to resolve third
# party dependencies. The max level of parallelism will be
# `process_execution_local_parallelism x resolver_jobs`, but
# often you will have one resolve process at a time.
resolver_jobs = 2
[pytest]
args = ["-vv"]
Then, in your CI script or config, set the environment variable PANTS_CONFIG_FILES
to use this new config file. Because --pants-config-files
is a list option, the below will append to the list of config files used, which will include pants.toml
by default:
export PANTS_CONFIG_FILES=pants.ci.toml
# Then, your normal CI setup
./pants test ::
...
Directories to cache
In your CI's config file, we recommend caching these directories:
$HOME/.cache/pants/setup
: the initial bootstrapping of Pants.$HOME/.cache/pants/named_caches
: caches of tools like pip and PEX.$HOME/.cache/pants/lmdb_store
: cached content for prior Pants runs.
See Troubleshooting for how to change these cache locations.
In CI, the cache must be uploaded and downloaded every run. This takes time, so there is a tradeoff where too large of a cache will slow down your CI.
You can use this script to nuke the cache when it gets too big:
function nuke_if_too_big() {
path=$1
limit_mb=$2
size_mb=$(du -m -d0 ${path} | cut -f 1)
if (( ${size_mb} > ${limit_mb} )); then
echo "${path} is too large (${size_mb}mb), nuking it."
rm -rf ${path}
fi
}
nuke_if_too_big ~/.cache/pants/lmdb_store 2048
nuke_if_too_big ~/.cache/pants/setup 256
nuke_if_too_big ~/.cache/pants/named_caches 1024
Storing Pants logs as artifacts
We recommend that you configure your CI system to store the pants log (.pantd.d/pants.log) as a build artifact, so it is available in case you need to troubleshoot CI issues.
Different CI providers and systems have different ways to configure build artifacts:
- Circle CI - Storing artifacts
- Github Actions - Storing Artifacts - example in the pants repo
- Bitbucket pipelines - Using artifacts
- Jenkins - Recording artifacts
Recommended commands
Approach #1: only run over changes files
Because Pants understands the dependencies of your code, you can use Pants to speed up your CI by only running tests and linters over files that actually made changes.
We recommend running these commands in CI:
$ ./pants --version # This will bootstrap Pants
$ ./pants --changed-since=origin/main lint
$ ./pants \
--changed-since=origin/main \
--changed-dependees=transitive \
typecheck test
Because most linters do not care about a target's dependencies, we lint all changed targets, but not any dependees of those changed targets.
Meanwhile, tests should be rerun when any changes are made to the tests or to dependencies of those tests, so we use the option --changed-dependees=transitive
. typecheck
should also run on any transitive changes.
See Advanced target selection for more information on --changed-since
and alternative techniques to select targets to run in CI.
For example, if you add a new plugin to Flake8, Pants will still only run over changed files, meaning you may miss some new lint issues.
For absolute correctness, you may want to use Approach #2. Alternatively, add conditional logic to your CI, e.g. that any changes to pants.toml
trigger using Approach #2.
Checkout
To use --changed-since
, you may want to use the Checkout action.
By default, Checkout will only fetch the latest commit, so you should set fetch-depth: 0
.
Approach #2: run over everything
Alternatively, you can simply run over all your code. Pants's caching means that you will not need to rerun on changed files.
$ ./pants --version # This will bootstrap Pants
$ ./pants lint typecheck test ::
However, when the cache gets too big, it should be nuked (see "Directories to cache"), so your CI may end up doing more work than Approach #1.