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https://docs.python.org/2/library/multiprocessing.html #multiprocessing is a package that supports spawning processes using an #API similar to the #threading module. The multiprocessing package offers both local and remote #concurrency, effectively side-stepping the Global Interpreter Lock by using subprocesses instead of #threads. Due to this, the multiprocessing module allows the programmer to fully leverage multiple processors on a given machine. It runs on both Unix and Windows.

https://docs.python.org/3/library/multiprocessing.html multiprocessing is a package that supports spawning processes using an API similar to the threading module. The multiprocessing package offers both local and remote concurrency, effectively side-stepping the Global Interpreter Lock by using subprocesses instead of threads. Due to this, the multiprocessing module allows the programmer to fully leverage multiple processors on a given machine. It runs on both Unix and Windows. The #multiprocessing module also introduces #APIs which do not have analogs in the #threading#module. A prime example of this is the Pool object which offers a convenient means of parallelizing the execution of a function across multiple input values, distributing the input data across processes (data #parallelism). The following example demonstrates the common practice of defining such functions in a module so that child processes can successfully import that module. This basic example of data parallelism using Pool,

https://github.com/python/asyncio The #asyncio#module provides infrastructure for writing #single-threaded concurrent code using #coroutines, #multiplexing#I/O access over sockets and other resources, running network clients and servers, and other related primitives. Here is a more detailed list of the package contents: a pluggable event loop with various system-specific implementations; transport and protocol abstractions (similar to those in Twisted); concrete support for TCP, UDP, SSL, subprocess pipes, delayed calls, and others (some may be system-dependent); a Future class that mimics the one in the concurrent.futures module, but adapted for use with the event loop; #coroutines and #tasks based on yield from (PEP 380), to help write concurrent code in a sequential fashion; cancellation support for Futures and coroutines; synchronization primitives for use between coroutines in a single thread, mimicking those in the #threading module; an interface for passing work off to a threadpool, for times when you absolutely, positively have to use a library that makes blocking I/O calls. Note: The implementation of asyncio was previously called "Tulip".