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✏️ Editing: parallel.pyc

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�l�m�Z�m�Z�m�Z�m�Z�m�Z�d�d�l�m�Z�e�e�j�e�j�f�Z�e�d���Z�e�d
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�re�Z�n�Xe�Z�d�Z�e�d������Z �d�d���Z!�d�d���Z"�d�d���Z#�e�sfe�rse!�Z$�Z%�n�e"�Z$�e#�Z%�d�S(���sb��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.
t���map_multiprocesst���map_multithreadi����(���t���contextmanager(���t���Pool(���t���DEFAULT_POOLSIZE(���t���PY2(���t���map(���t���MYPY_CHECK_RUNNING(���t���Callablet���Iterablet���Iteratort���Uniont���TypeVar(���t���poolt���St���TNi���c���������c���s/���z	�|��VWd�|��j�����|��j����|��j����Xd�S(���s>���Return a context manager making sure the pool closes properly.N(���t���closet���joint	���terminate(���R
���(����(����s����/builddir/build/BUILDROOT/alt-python27-pip-20.2.4-5.el8.x86_64/opt/alt/python27/lib/python2.7/site-packages/pip/_internal/utils/parallel.pyt���closing4���s
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���t��|��|���S(���s����Make 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���(���t���funct���iterablet	���chunksize(����(����s����/builddir/build/BUILDROOT/alt-python27-pip-20.2.4-5.el8.x86_64/opt/alt/python27/lib/python2.7/site-packages/pip/_internal/utils/parallel.pyt
���_map_fallbackB���s����c���������C���s/���t��t��������}�|�j�|��|�|���SWd�QXd�S(���s����Chop 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���t���ProcessPoolt���imap_unordered(���R���R���R���R
���(����(����s����/builddir/build/BUILDROOT/alt-python27-pip-20.2.4-5.el8.x86_64/opt/alt/python27/lib/python2.7/site-packages/pip/_internal/utils/parallel.pyt���_map_multiprocessM���s����	c���������C���s2���t��t�t�������}�|�j�|��|�|���SWd�QXd�S(���s����Chop 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���t
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