28 lines
891 B
Python
28 lines
891 B
Python
from __future__ import annotations
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import os
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from concurrent.futures import ThreadPoolExecutor
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# Shared executor for CPU-bound analytics (pandas/sklearn) and sync MSSQL I/O
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# (pyodbc is inherently synchronous and blocks the event loop if called directly).
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#
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# Workers are capped at 8 to avoid overwhelming the MSSQL connection pools.
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# In K8s: set ANALYTICS_WORKERS to match the pod's CPU limit.
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_WORKERS = min(8, int(os.environ.get("ANALYTICS_WORKERS", "0")) or (os.cpu_count() or 2) * 2)
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_executor: ThreadPoolExecutor | None = None
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def get_executor() -> ThreadPoolExecutor:
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global _executor
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if _executor is None:
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_executor = ThreadPoolExecutor(max_workers=_WORKERS, thread_name_prefix="analytics")
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return _executor
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def shutdown_executor() -> None:
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global _executor
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if _executor is not None:
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_executor.shutdown(wait=True)
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_executor = None
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