| Current File : //lib/python3.9/site-packages/pip/_internal/utils/__pycache__/parallel.cpython-39.pyc |
a
[��f| � @ s\ d Z ddgZddlmZ ddlmZ ddlmZ ddlmZ ddl
m Z m Z m
Z
mZmZ ddlmZ eejej f Zed �Zed
�Zz dd lZW n ey� d ZY n0 d
ZdZeee
e d�dd��Zde egef e e ee
e d�dd�Zde egef e e ee
e d�dd�Zd e egef e e ee
e d�dd�Z e�rPe Z Z neZ e Z d S ) 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 c sB z"| V W | � � | �� | �� n| � � | �� | �� 0 dS )z>Return a context manager making sure the pool closes properly.N)�close�joinZ terminater � r �@/usr/lib/python3.9/site-packages/pip/_internal/utils/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� �� }|�| ||�W d � S 1 s.0 Y 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
r c C s> t tt��� }|�| ||�W d � S 1 s00 Y dS )z�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 �
ThreadPoolr
r r r r r �_map_multithreadU s
r! )r )r )r ) �__doc__�__all__�
contextlibr Zmultiprocessingr r r Zmultiprocessing.dummyr �typingr r r
r r Z pip._vendor.requests.adaptersr
r r Zmultiprocessing.synchronize� ImportErrorZ
LACK_SEM_OPENZTIMEOUTr �intr r r! r r r r r r �<module> sJ
��
�� ��