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framework

Python multiprocessing module

Standard-library module for running Python work in separate processes, providing Process, Pool, queues and selectable start methods including fork and spawn.

Known aliases

  • multiprocessing

Relationships

No evidence-backed relationships are recorded.

Current clusters

build1 publisher

Forking mid-emit hands a worker a logging lock that stays taken

Python's logging module keeps an RLock behind every handler. One shared setup_logging() therefore deadlocks a forked pool on one machine and silently drops worker records on another, and a single-OS review only ever sees one of them.

Publishers:dev.to

Reality

Evidence58
Adoption
Insufficient
Hype gap+10
Incentives20
Confidence55