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Use ProcessPoolExecutor instead of ThreadPoolExecutor. #250

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Use ProcessPoolExecutor instead of ThreadPoolExecutor. #250

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4 changes: 2 additions & 2 deletions refresh.template.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1142,8 +1142,8 @@ def _convert_compile_commands(aquery_output):

# Process each action from Bazelisms -> file paths and their clang commands
# Threads instead of processes because most of the execution time is farmed out to subprocesses. No need to sidestep the GIL. Might change after https://github.com/clangd/clangd/issues/123 resolved
with concurrent.futures.ThreadPoolExecutor(
max_workers=min(32, (os.cpu_count() or 1) + 4) # Backport. Default in MIN_PY=3.8. See "using very large resources implicitly on many-core machines" in https://docs.python.org/3/library/concurrent.futures.html#concurrent.futures.ThreadPoolExecutor
with concurrent.futures.ProcessPoolExecutor(
max_workers=os.cpu_count() # Default before Python 3.13, after which it is os.process_cpu_count().
) as threadpool:
outputs = threadpool.map(_get_cpp_command_for_files, aquery_output.actions)

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