The bulk branch

Sometimes we need to do maintenance or make changes to lots of recipes at once. This happens most often when there is a new Bioconductor release: all bioconductor-* recipes need to be updated, and the corresponding packages need to be built.

This ends up taking substantial compute time on CI infrastructure. If this were run on the same CI infrastructure that processes pull requests, this might consume CI time needed for the typical functioning of the daily activity in the bioconda repository. The bulk branch is a mechanism for the Bioconda core team to perform large-scale changes on a different CI system, without tying up the CI infrastructure used by contributors on individual pull requests.

The bulk branch reads its configuration (which version of bioconda-utils and miniconda) from the bulk branch of bioconda-common.

The bulk branch immediately uploads successfully built packages to Anaconda. As such, only the bioconda core team has the ability to push to this branch.

Interacting with the bulk branch

When changes are made on the bulk branch (committed and pushed), the CI system decides whether it will run its jobs or not.

  • If any of the pushed commit messages contains the substring [ci run] the CI jobs are executed.

  • If not, no CI jobs are executed.

The reason for this behavior is that we want to avoid race conditions caused by multiple CI jobs spawned from different commits, possibly from different people, to be exectuted at the same time.

In order to simplify interactions with the bulk CI, bioconda-utils offers therefore some dedicated subcommands:

  • bulk-commit: bioconda-utils bulk-commit <message> commits the changes on your local clone of to the bulk branch while marking the commit as being eligible for a CI run (by automatically prefixing the message with [ci run]). The bulk-commit subcommand does not push the commit. This enables you to do multiple fine-grained commits and push them in one pass via a subsequent git push that triggers a single CI run.

  • bulk-trigger-ci: bioconda-utils bulk-trigger-ci creates an empty commit that is immediately pushed automatically to the bulk branch, thereby triggering a CI run. This can be used to restart the CI run in case all of the previous runs are finished without build failures but there are still packages that need to be built (and haven’t been before because the job runtime limits were reached and the CI has terminated them (usually this happens after somewhat more than 5 hours)).

Updating pinnings

Pinnings are updated for example when we are supporting a new version of Python. These are versions of base packages that are supported, and form the basis of the build string hashes at the end of conda package names. A recent example is updating pinnings to support Python 3.10.

  1. Update bioconda pinnings. This may take a few tries; you may need to make changes to match conda-forge’s pinnings. Merge these changes into the master branch of bioconda-utils (which will create or update a Release Please PR) and merge in the Release Please PR to create a new version of bioconda-utils.

  2. Allow autobump to pick up the new version and create a PR in bioconda-recipes for the new version of bioconda-utils. This usually takes an hour. Then merge the corresponding PR in bioconda-recipes. You now have a new bioconda-utils package to use which contains those pinnings.

  3. Update (see here) only on the bulk branch in bioconda-common, to match the newly-updated bioconda-utils version. Changing the pinnings will likely trigger many recipes to require rebuilding. Since the bioconda-recipes/bulk branch reads from the bioconda-common/bulk branch, this allows bulk to run a different version of bioconda-utils. Once a bulk migration is complete, you can update the master branch of bioconda-common.

  4. In bioconda-recipes, merge master into bulk to start with a clean slate. Since bulk is infrequently updated, there may be substantial conflicts caused by running the default git checkout bulk && git merge master. This tends to happen most with build numbers. But since we want to prefer using whatever is in the master branch, we can merge master into bulk, while preferring master version in any conflicts, with:

    git checkout bulk
    git merge master -s recursive -X theirs

    There may be a few remaining conflicts to fix; in all cases you should prefer what’s on the master branch.

  5. Run bioconda-utils update-pinnings in the bulk branch. This will go through all the pinnings, figure out what recipes they’re used with, and bump the recipes’ build numbers appropriately.

  6. Then, bulk-commit and push the changes.

  7. Once the CI run has finished, inspect all build failures (see handling-build-failures). For each failure, decide whether the recipe shall be skiplisted or whether you would like to fix it. In general it is advisable to fix all libraries on which many recipes depend and anything else that is obvious and easy. For the rest, mark the recipes as skiplisted in the build failure file. It will be ignored by subsequent CI runs and put into a table in the bioconda-recipes wiki. This strategy is good because the bulk branch update should be performed as fast as possible to avoid redundant work between master and bulk. Also, skiplisting democratizes the update effort.

  8. If no untreated failure remains, bulk-commit (see above) and push the changes and visit step 6-7 again. If the run has finished without any build failure and did not time out before checking all recipes, you can go on with step 7.

  9. Once all the packages have either been successfully built or skiplisted, pull the master branch and merge it into bulk. Usually, conflicts can occur here due to build-numbers having been increased in the master branch while you did your changes in bulk. For such cases (which should be not so many) you can just increase the build number to max(build_number_master, build_number_bulk) and bulk-commit all of those in a row. Repeat this until master is merged without any conflicts. Ensure that bioconda-common/ points to the same version of bioconda-utils that the bulk branch has been using. Then, merge bulk into master and push the changes.

  10. Shortly afterwards, you will find all remaining build failures in the

bioconda-recipes wiki. You can let your colleagues and the community know about the updated build failure table and ask for help. In addition, any automatic or manual updates to recipes on this list that succeed will automatically remove them from this list over time.

Handling build failures

Build failures are stored in a file build_failure.<arch>.yaml next to each failing recipe. You can list all build failures stored in the current branch of bioconda-recipes via the command bioconda-utils list-build-failures recipes config.yml. This reads the yaml files from failing recipes, and prints a table on stdout that will be sorted by the number of dependencies and package downloads, which should help for prioritizing the fixing work.

This file can look e.g. like this:

recipe_sha: 37fa4d78a2ee8b18065a0bd0f594ad1e9587bb4ac7edf1b4629a9f10fa45d0a5  # The shas256 hash of the recipe at which it failed to build.
skiplist: true # Set to true to skiplist this recipe so that it will be ignored as long as its latest commit is the one given above.
log: |2-
  <the logging output of the failed build>

Based on the log, you can decide whether and how the recipe can be fixed or whether it shall be skiplisted for fixing it later in the future. Notably, any update to the recipe automatically de-skiplists it, because the skiplist entry is only valid together with the hash listed in the first line.

It is possible to further annotate and even manually create build failure records via the bioconda-utils CLI. Check out all possibilities in the corresponding help message:

bioconda-utils annotate-build-failures --help

Skiplisted recipes from the master branch are automatically displayed in a wiki page, so that others can pick them up for providing a fix.

Updating Bioconductor

Bioconductor gets updated twice a year (spring and fall), where all BioC packages get released with updated versions at the same time. This in turn requires updating the packages on Bioconda. This is a perfect use-case for the bulk branch. The process is generally the same as above but without the pinnings updates and with some Bioconductor-specific helper scripts.

  1. Execute step 4 from above.

  2. Identify the latest BioConductor version, and update all BioConductor recipes with:

    bioconda-utils bioconductor-skeleton update-all-packages --bioc-version $BIOC_VERSION
  3. Execute step 6 from above.

  4. Execute step 7 from above. Alternatively, use the []( from the bioconda-recipes repo to help figure out what the primary root nodes are for the currently-remaining packages to be built. This looks at recently-built packages, removes them from the DAG of recipes to be built, and then reports to stdout the remaining root nodes. This information can be used to strategically edit the build-fail-blacklist file to prioritize the building of those root nodes. Once builds seem to be stabilizing, remove the temporary edits to the build-fail-blacklist.

  5. Execute step 8-10 from above.

Notes on working with bulk branch

Some unordered notes on working with the bulk branch:

  • Remember that successfully-built packages are immediately pushed to Anaconda.

  • You may want to coordinate the timing of fixes and pushes (say, via gitter). This is because the bulk branch has fail-fast: false set to allow parallel jobs to progress as much as possible. Multiple people pushing to bulk means that there is a risk of trying to build the same recipes multiple times. In such a case, only the first package will be actually uploaded and subsequent packages will a failure on the upload step. So there is no danger to the channel, it’s just poor use of CI resources.

  • The logs are awkward to read and hard to find exactly where failures occur. One way to do this is to go to the bottom where there is a report of which packages failed. This report is shown when a bulk job goes to completion (rather than timing out). Then search for that package backwards through the log. You can also look for the broad structure of the log: recipes with nothing to do will be reported in a short stanza, so you can use those as structural markers to indicate where there’s no useful log info.

  • Instead of using the search functionality in the CI logs, download the raw log (from gear menu at top right) to use your browser search functionality, which is often much easier to use (for example, Chrome shows occurrences of search term throughout the document in the scrollbar, which makes digging for the actual error a lot easier).

  • You may see a lot of output for Python packages in particular. This is because for bioconda-utils to figure out whether it needs to build the package, it needs to know what the hash is for the package. This in turn requires figuring out all the dependencies to see which of them are pinned and then using those to calculate a hash. So it may appear that it’s doing a lot of work for packages that don’t need to be rebuilt, but that work needs to be done simply to figure out if a rebuild is needed, and so this is expected.

  • For linux-64, osx-64, and osx-arm64 the bulk runs take place on GitHub Actions, and the configuration is in .github/workflows/Bulk.yml. For linux-aarch64, the builds take place on CircleCI and the configuration is in .circleci/config.yml.