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This is a suite of changes intended to dramatically speed up nogo speed.
First, there are minor changes that help efficiency significantly.
* Gob-based encoding is used internally, and JSON only used for the final
set of findings. This is done to preserve the existing format (which is
consumed by external tooling), and to facilitate manual debugging.
* Unnecessary regex compilation is elided in the configuration, and care is
taken for merges to prevent redundant entries. I'm not sure quite sure how,
but it turns out that this was consumed a significant amount of time,
presumably compiling the same regexes over and over again.
Second, this change enables bazel workers for nogo analyzers.
Workers enable persistent processes instead of creating and tearing down a
sandbox every invocation. A library is introduced to abstraction these details,
and allow the tools to still be written using standard flags, etc.
The key here is that these binaries and the core of nogo become aware of
caches with worker.Cache. This allows us to save significant time loading the
same set of files and findings over and over again. These caches are keyed by
the digests that are provided by bazel, and are capped in overall size.
Note that the worker package attempts to capture output during each run, but
tools are no longer permitted to write to stdout. This necessitated dropping
some spurious output from checklocks.
PiperOrigin-RevId: 370505732
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Presently, the standard library facts are not serialized in a deterministic
order. This means that they have the possibility to change on each iteration,
requiring a large scale re-analysis of all downstream actions, which includes
all packages.
Improve cache-ability of nogo actions by improving the determinism of the both
facts and findings. Internally, default facts should be serialized as a sorted
list for this reason already.
PiperOrigin-RevId: 370188259
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This splits the nogo rules into a separate configuration yaml file, and
allows for multiple files to be provided.
Because attrs cannot be passed down to aspects, this required that all
findings are propagated up the aspect Provider. This doesn't mean that
any extra work must be done, just that this information must be carried
through the graph, and some additional starlark complexity is required.
PiperOrigin-RevId: 339076357
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