multiprocessing — Manage Processes Like Threads¶
|Purpose:||Provides an API for managing processes.|
multiprocessing module includes an API for dividing work up
between multiple processes based on the API for
multiprocessing is a drop-in replacement, and can be
used instead of
threading to take advantage of multiple CPU
cores to avoid computational bottlenecks associated with Python’s
global interpreter lock.
- multiprocessing Basics
- Importable Target Functions
- Determining the Current Process
- Daemon Processes
- Waiting for Processes
- Terminating Processes
- Process Exit Status
- Subclassing Process
- Passing Messages to Processes
- Signaling between Processes
- Controlling Access to Resources
- Synchronizing Operations
- Controlling Concurrent Access to Resources
- Managing Shared State
- Shared Namespaces
- Process Pools
- Implementing MapReduce
- Standard library documentation for multiprocessing
threading– High-level API for working with threads.
- MapReduce - Wikipedia – Overview of MapReduce on Wikipedia.
- MapReduce: Simplified Data Processing on Large Clusters – Google Labs presentation and paper on MapReduce.
operator– Operator tools such as