3
Ug|                 @   s^  d Z ddgZddlmZ ddlmZ ddlmZ ddlmZ	 dd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
ZyddlZW n ek
r   dZY nX dZdZeeee dddZdeegef ee eee dddZdeegef ee eee dddZdeegef ee eee dddZerRe ZZneZ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   s*   z
| V  W d| j   | j  | j  X dS )z>Return a context manager making sure the pool closes properly.N)closejoin	terminate)r    r   @/tmp/pip-unpacked-wheel-0ht26j5g/pip/_internal/utils/parallel.pyclosing.   s
    
r      )funciterable	chunksizer   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.
    )map)r   r   r   r   r   r   _map_fallback;   s    	r   c             C   s$   t t }|j| ||S Q R X dS )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   ProcessPoolimap_unordered)r   r   r   r   r   r   r   _map_multiprocessG   s    
r   c             C   s&   t tt}|j| ||S Q R X dS )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   
ThreadPoolr   r   )r   r   r   r   r   r   r   _map_multithreadU   s    
r    )r   )r   )r   )__doc____all__
contextlibr   multiprocessingr   r   r   Zmultiprocessing.dummyr   typingr   r   r	   r
   r   Zpip._vendor.requests.adaptersr   r   r   Zmultiprocessing.synchronizeImportErrorZLACK_SEM_OPENTIMEOUTr   intr   r   r    r   r   r   r   r   r   <module>   s8   

