3.8. Caching#
To speed up the processing of your repository’s control center, all data retrieved from the web, including inherited extensions, GitHub repo/users data, software versions, and publications can be cached on both local devices and on GitHub servers. Each time such data is needed, PyPackIT first checks if there is an unexpired entry for it in the cache, and if not, it will fetch it from the corresponding web API and cache it for future use.
3.8.1. Location#
The cache is a YAML file stored at RepoDynamics/.metadata_cache.yaml
relative to your repository’s cache directory,
where each piece of cached data is stored as a separate entry with a timestamp.
If you run PyPackIT on a local device,
you can find the cache file in the repository’s cache directory.
However, since the cache directory is added to the .gitignore file,
it will not be pushed to the remote repository.
Instead, when project workflows are run on GHA,
the cache directory is stored and retrieved using GHA cache actions,
and can be accessed from the Actions tab of the repository.
3.8.2. Retention Time#
The retention time of each type of cached data can be set in the control center
at $.control.cache.retention_hours.
This sets the expiration time of each cached entry in hours,
for both local and GHA caches.
However, you might want to set different retention times when
running local control center synchronizations.
One way is to change $.control.cache.retention_hours
and then reset it to the original value before commiting the changes.
PyPackIT provides a more convenient way to do this:
Create a file named .local_config.yaml in the repository’s cache directory,
and set the desired retention times in it, at the same path as in the control center.
Example
control:
cache:
retention_hours:
extension: 24
repo: 24
user: 24
orcid: 1000
doi: 1000
python: 1000
If this file exists, the control center will use the values in it instead of the values in the project’s control center configuration files.