Clean up multiprocessing pools on failure#208
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Ensure bagit-python reliably cleans up multiprocessing pools when parallel manifest generation or validation fails with processes > 1. Successful make_bag() calls already cleaned up correctly through the normal graceful pool path. The gap was failures inside Pool.map(): worker exceptions skipped close() and join(), allowing BagIt child processes to remain alive after the caller received the error. In long-running services, those leftover children can later become orphaned or defunct when the owning worker exits. This follows up on c451b24 ("Wait for validation Pool to finish"), the validation-pool cleanup work Douglas and I did, by extending the same reliability expectation to failure paths.
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acdha
reviewed
Jun 18, 2026
| else: | ||
| pool = multiprocessing.Pool( | ||
| processes if processes else None, initializer=worker_init | ||
| hash_results = _multiprocessing_pool_map( |
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I was wondering whether we might want to refactor this to avoid buffering everything in memory (i.e. using Pool.imap so it could yield from in the utility function but I don't think it's very common that people are using this in a way where they need to worry about total RAM or can meaningfully process the results before they're all ready.
acdha
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Jun 18, 2026
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Ensure bagit-python reliably cleans up multiprocessing pools when parallel manifest generation or validation fails with processes > 1.
Successful make_bag() calls already cleaned up correctly through the normal graceful pool path. The gap was failures inside Pool.map(): worker exceptions skipped close() and join(), allowing BagIt child processes to remain alive after the caller received the error. In long-running services, those leftover children can later become orphaned or defunct when the owning worker exits.
This follows up on c451b24 ("Wait for validation Pool to finish"), the validation-pool cleanup work Douglas and I did, by extending the same reliability expectation to failure paths.