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e843433b07
Reduce the overhead of `uv run` in large workspaces. Instead of
re-discovering the entire workspace each time we resolve the metadata of
a member, we can the discovered set of workspace members. Care needs to
be taken to not cache the discovery for `uv init`, `uv add` and `uv
remove`, which change the definitions of workspace members.
Below is apache airflow e3fe06382df4b19f2c0de40ce7c0bdc726754c74 `uv run
python` with a minimal payload. With this change, we avoid a ~350ms
overhead of each `uv run` invocation.
```
$ hyperfine --warmup 2 \
"uv run --no-dev python -c \"print('hi')\"" \
"uv-profiling run --no-dev python -c \"print('hi')\""
Benchmark 1: uv run --no-dev python -c "print('hi')"
Time (mean ± σ): 492.6 ms ± 7.0 ms [User: 393.2 ms, System: 97.1 ms]
Range (min … max): 482.3 ms … 501.5 ms 10 runs
Benchmark 2: uv-profiling run --no-dev python -c "print('hi')"
Time (mean ± σ): 129.7 ms ± 2.5 ms [User: 105.4 ms, System: 23.2 ms]
Range (min … max): 126.0 ms … 136.1 ms 22 runs
Summary
uv-profiling run --no-dev python -c "print('hi')" ran
3.80 ± 0.09 times faster than uv run --no-dev python -c "print('hi')"
```
The profile after those change below. We still spend a large chunk in
toml parsing (both `uv.lock` and `pyproject.toml`), but it's not
excessive anymore.
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| inputs | ||
| src | ||
| Cargo.toml | ||