35 lines
1.2 KiB
Python
35 lines
1.2 KiB
Python
"""
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EXPERIMENTAL! use with caution
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Manages 'global' ProcessPoolExecutor which is 'managed' by HPI itself, and
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can be passed down to DALs to speed up data processing.
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The reason to have it managed by HPI is because we don't want DALs instantiate pools
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themselves -- they can't cooperate and it would be hard/infeasible to control
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how many cores we want to dedicate to the DAL.
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Enabled by the env variable, specifying how many cores to dedicate
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e.g. "HPI_CPU_POOL=4 hpi query ..."
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"""
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from __future__ import annotations
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import os
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from concurrent.futures import ProcessPoolExecutor
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from typing import cast
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_NOT_SET = cast(ProcessPoolExecutor, object())
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_INSTANCE: ProcessPoolExecutor | None = _NOT_SET
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def get_cpu_pool() -> ProcessPoolExecutor | None:
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global _INSTANCE
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if _INSTANCE is _NOT_SET:
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use_cpu_pool = os.environ.get('HPI_CPU_POOL')
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if use_cpu_pool is None or int(use_cpu_pool) == 0:
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_INSTANCE = None
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else:
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# NOTE: this won't be cleaned up properly, but I guess it's fine?
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# since this it's basically a singleton for the whole process
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# , and will be destroyed when python exists
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_INSTANCE = ProcessPoolExecutor(max_workers=int(use_cpu_pool))
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return _INSTANCE
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