class_docstr: Pool using MPI processes as workers.
docstr: Apply *func* to each element in *iterable*.
  
  Equivalent to ``list(map(func, iterable))``.
  
  Block until all results are ready and return them in a `list`.
  
  The *iterable* is choped into a number of chunks which are submitted as
  separate tasks. The (approximate) size of these chunks can be specified
  by setting *chunksize* to a positive integer.
  
  Consider using `imap()` or `imap_unordered()` with explicit *chunksize*
  for better efficiency.
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code: def map(self, func, iterable, chunksize=None):
      """Apply *func* to each element in *iterable*.
  
      Equivalent to ``list(map(func, iterable))``.
  
      Block until all results are ready and return them in a `list`.
  
      The *iterable* is choped into a number of chunks which are submitted as
      separate tasks. The (approximate) size of these chunks can be specified
      by setting *chunksize* to a positive integer.
  
      Consider using `imap()` or `imap_unordered()` with explicit *chunksize*
      for better efficiency.
  
      """
      iterable, chunksize = _chunksize(self, iterable, chunksize)
      return list(self.imap(func, iterable, chunksize=chunksize))
  
imports: from os import cpu_count
  import functools
  import operator
  import threading
  import warnings
  import weakref
  from ..None import futures
label_desc: Use image node_id 4 for calling the Pool obj's underlying member method code with example usage: obj.map(func, iterable, chunksize) and returns: list