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![]() This moves the diff of outpaths into the outpaths job, mainly as a preparation to allow future improvements. For example, this will allow running the purity release checks only on changed outpaths instead of the whole eval. This also removes the inefficiency introduced in the last commit about uploading the intermediate paths twice. Now, only the diff is passed on. Also, technically, the diff is now run in parallel across 4 jobs. This should be *slightly* faster than before, where outpaths from all systems were combined first and then diffed. It's probably only a few seconds, though. |
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default.nix | ||
diff.nix | ||
README.md |
Nixpkgs CI evaluation
The code in this directory is used by the eval.yml GitHub Actions workflow to evaluate the majority of Nixpkgs for all PRs, effectively making sure that when the development branches are processed by Hydra, no evaluation failures are encountered.
Furthermore it also allows local evaluation using
nix-build ci -A eval.full \
--max-jobs 4 \
--cores 2 \
--arg chunkSize 10000 \
--arg evalSystems '["x86_64-linux" "aarch64-darwin"]'
--max-jobs
: The maximum number of derivations to run at the same time. Only each supported system gets a separate derivation, so it doesn't make sense to set this higher than that number.--cores
: The number of cores to use for each job. Recommended to set this to the amount of cores on your system divided by--max-jobs
.chunkSize
: The number of attributes that are evaluated simultaneously on a single core. Lowering this decreases memory usage at the cost of increased evaluation time. If this is too high, there won't be enough chunks to process them in parallel, and will also increase evaluation time.evalSystems
: The set of systems for whichnixpkgs
should be evaluated. Defaults to the four official platforms (x86_64-linux
,aarch64-linux
,x86_64-darwin
andaarch64-darwin
).
A good default is to set chunkSize
to 10000, which leads to about 3.6GB max memory usage per core, so suitable for fully utilising machines with 4 cores and 16GB memory, 8 cores and 32GB memory or 16 cores and 64GB memory.
Note that 16GB memory is the recommended minimum, while with less than 8GB memory evaluation time suffers greatly.