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e d�dd�Ze�rRe ZZneZeZdS )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_multiprocess�map_multithread� )�contextmanager)�Pool)�pool)�Callable�Iterable�Iterator�TypeVar�Union)�DEFAULT_POOLSIZE�S�TNTFi�� )r �returnc
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| V W d| j � | j� | j� X dS )z>Return a context manager making sure the pool closes properly.N)�close�joinZ terminate)r � r �/usr/lib/python3.6/parallel.py�closing. s
r � )�func�iterable� chunksizer c C s
t | |�S )z�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.
)�map)r r r r r r �
_map_fallback; s r c C s$ t t� ��}|j| ||�S Q R X dS )z�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 �ProcessPool�imap_unordered)r r r r r r r �_map_multiprocessG s
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