1 files changed, 0 insertions, 101 deletions
diff --git a/src/pip/_internal/utils/parallel.py b/src/pip/_internal/utils/parallel.py
deleted file mode 100644
index de91dc8ab..000000000
--- a/src/pip/_internal/utils/parallel.py
+++ /dev/null
@@ -1,101 +0,0 @@
-"""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 import pool
-from multiprocessing.dummy import Pool as ThreadPool
-from typing import Callable, Iterable, Iterator, TypeVar, Union
-
-from pip._vendor.requests.adapters import DEFAULT_POOLSIZE
-
-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:
-    map_multiprocess = map_multithread = _map_fallback
-else:
-    map_multiprocess = _map_multiprocess
-    map_multithread = _map_multithread