a deL @s$dZddgZddlmZddlmZddlmZddl m Z ddl m Z ddl mZdd lmZerdd lmZdd lmZmZmZmZmZeejejfZed Zed Zz ddlZWneydZYn0dZdZeddZdddZdddZ dddZ!ese reZ"Z#ne Z"e!Z#dS)abConvenient parallelization of higher order functions. This module provides two helper functions, with appropriate fallbacks on Python 2 and on systems lacking support for synchronization mechanisms: - map_multiprocess - map_multithread These helpers work like Python 3's map, with two differences: - They don't guarantee the order of processing of the elements of the iterable. - The underlying process/thread pools chop the iterable into a number of chunks, so that for very long iterables using a large value for chunksize can make the job complete much faster than using the default value of 1. map_multiprocessmap_multithread)contextmanager)Pool)DEFAULT_POOLSIZE)PY2map)MYPY_CHECK_RUNNINGpool)CallableIterableIteratorTypeVarUnionSTNTFiccsBz"|VW|||n|||0dS)z>Return a context manager making sure the pool closes properly.N)closejoin terminater rU/var/www/sistema_ama/venv/lib/python3.9/site-packages/pip/_internal/utils/parallel.pyclosing4s rcCs t||S)zMake an iterator applying func to each element in iterable. This function is the sequential fallback either on Python 2 where Pool.imap* doesn't react to KeyboardInterrupt or when sem_open is unavailable. r)funciterable chunksizerrr _map_fallbackBsrcCs<tt}||||WdS1s.0YdS)zChop iterable into chunks and submit them to a process pool. For very long iterables using a large value for chunksize can make the job complete much faster than using the default value of 1. Return an unordered iterator of the results. N)r ProcessPoolimap_unorderedrrrr rrr_map_multiprocessMs r"cCs>ttt}||||WdS1s00YdS)zChop iterable into chunks and submit them to a thread pool. For very long iterables using a large value for chunksize can make the job complete much faster than using the default value of 1. Return an unordered iterator of the results. N)r ThreadPoolrr r!rrr_map_multithreadZs r$)r)r)r)$__doc____all__ contextlibrmultiprocessingrrZmultiprocessing.dummyr#pip._vendor.requests.adaptersrZpip._vendor.sixrZpip._vendor.six.movesr pip._internal.utils.typingr r typingr rrrrrrZmultiprocessing.synchronize ImportErrorZ LACK_SEM_OPENTIMEOUTrrr"r$rrrrrrs: