3 ReL @ s& d Z ddgZddlmZ ddlmZ ddlmZ ddl m Z ddlmZ ddl mZ dd lmZ erdd lmZmZmZmZmZ ddlmZ eejejf ZedZed ZyddlZW n ek r dZY nX dZdZedd ZdddZdddZ dddZ!esere Z"Z#ne Z"e!Z#dS )ab Convenient 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)PY2)map)MYPY_CHECK_RUNNING)CallableIterableIteratorUnionTypeVar)poolSTNTFi c c s* z | V W d| j | j | j X dS )z>Return a context manager making sure the pool closes properly.N)closejoin terminate)r r /builddir/build/BUILDROOT/alt-python36-pip-20.2.4-5.el9.x86_64/opt/alt/python36/lib/python3.6/site-packages/pip/_internal/utils/parallel.pyclosing4 s r c C s 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 chunksizer r r _map_fallbackB s r c C s$ t t }|j| ||S Q R X dS )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_unordered)r r r r r r r _map_multiprocessM s r c C s&