Viewing file: parallel.py (3.32 KB) -rw-r--r-- Select action/file-type: (+) | (+) | (+) | Code (+) | Session (+) | (+) | SDB (+) | (+) | (+) | (+) | (+) | (+) |
"""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. """
__all__ = ['map_multiprocess', 'map_multithread']
from contextlib import contextmanager from multiprocessing import Pool as ProcessPool from multiprocessing.dummy import Pool as ThreadPool
from pip._vendor.requests.adapters import DEFAULT_POOLSIZE from pip._vendor.six import PY2 from pip._vendor.six.moves import map
from pip._internal.utils.typing import MYPY_CHECK_RUNNING
if MYPY_CHECK_RUNNING: from typing import Callable, Iterable, Iterator, Union, TypeVar from multiprocessing import pool
Pool = Union[pool.Pool, pool.ThreadPool] S = TypeVar('S') T = TypeVar('T')
# On platforms without sem_open, multiprocessing[.dummy] Pool # cannot be created. try: import multiprocessing.synchronize # noqa except ImportError: LACK_SEM_OPEN = True else: LACK_SEM_OPEN = False
# Incredibly large timeout to work around bpo-8296 on Python 2. TIMEOUT = 2000000
@contextmanager def closing(pool): # type: (Pool) -> Iterator[Pool] """Return a context manager making sure the pool closes properly.""" try: yield pool finally: # For Pool.imap*, close and join are needed # for the returned iterator to begin yielding. pool.close() pool.join() pool.terminate()
def _map_fallback(func, iterable, chunksize=1): # type: (Callable[[S], T], Iterable[S], int) -> Iterator[T] """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. """ return map(func, iterable)
def _map_multiprocess(func, iterable, chunksize=1): # type: (Callable[[S], T], Iterable[S], int) -> Iterator[T] """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. """ with closing(ProcessPool()) as pool: return pool.imap_unordered(func, iterable, chunksize)
def _map_multithread(func, iterable, chunksize=1): # type: (Callable[[S], T], Iterable[S], int) -> Iterator[T] """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. """ with closing(ThreadPool(DEFAULT_POOLSIZE)) as pool: return pool.imap_unordered(func, iterable, chunksize)
if LACK_SEM_OPEN or PY2: map_multiprocess = map_multithread = _map_fallback else: map_multiprocess = _map_multiprocess map_multithread = _map_multithread
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