lib-python.2.7.multiprocessing.__init__.py Maven / Gradle / Ivy
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Jython is an implementation of the high-level, dynamic, object-oriented
language Python written in 100% Pure Java, and seamlessly integrated with
the Java platform. It thus allows you to run Python on any Java platform.
#
# Package analogous to 'threading.py' but using processes
#
# multiprocessing/__init__.py
#
# This package is intended to duplicate the functionality (and much of
# the API) of threading.py but uses processes instead of threads. A
# subpackage 'multiprocessing.dummy' has the same API but is a simple
# wrapper for 'threading'.
#
# Try calling `multiprocessing.doc.main()` to read the html
# documentation in a webbrowser.
#
#
# Copyright (c) 2006-2008, R Oudkerk
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#
# 1. Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# 2. Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# 3. Neither the name of author nor the names of any contributors may be
# used to endorse or promote products derived from this software
# without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE AUTHOR AND CONTRIBUTORS "AS IS" AND
# ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR OR CONTRIBUTORS BE LIABLE
# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS
# OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
# HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY
# OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
# SUCH DAMAGE.
#
__version__ = '0.70a1'
__all__ = [
'Process', 'current_process', 'active_children', 'freeze_support',
'Manager', 'Pipe', 'cpu_count', 'log_to_stderr', 'get_logger',
'allow_connection_pickling', 'BufferTooShort', 'TimeoutError',
'Lock', 'RLock', 'Semaphore', 'BoundedSemaphore', 'Condition',
'Event', 'Queue', 'JoinableQueue', 'Pool', 'Value', 'Array',
'RawValue', 'RawArray', 'SUBDEBUG', 'SUBWARNING',
]
__author__ = 'R. Oudkerk ([email protected])'
#
# Imports
#
import os
import sys
from multiprocessing.process import Process, current_process, active_children
from multiprocessing.util import SUBDEBUG, SUBWARNING
#
# Exceptions
#
class ProcessError(Exception):
pass
class BufferTooShort(ProcessError):
pass
class TimeoutError(ProcessError):
pass
class AuthenticationError(ProcessError):
pass
# This is down here because _multiprocessing uses BufferTooShort
import _multiprocessing
#
# Definitions not depending on native semaphores
#
def Manager():
'''
Returns a manager associated with a running server process
The managers methods such as `Lock()`, `Condition()` and `Queue()`
can be used to create shared objects.
'''
from multiprocessing.managers import SyncManager
m = SyncManager()
m.start()
return m
def Pipe(duplex=True):
'''
Returns two connection object connected by a pipe
'''
from multiprocessing.connection import Pipe
return Pipe(duplex)
def cpu_count():
'''
Returns the number of CPUs in the system
'''
if sys.platform == 'win32':
try:
num = int(os.environ['NUMBER_OF_PROCESSORS'])
except (ValueError, KeyError):
num = 0
elif 'bsd' in sys.platform or sys.platform == 'darwin':
comm = '/sbin/sysctl -n hw.ncpu'
if sys.platform == 'darwin':
comm = '/usr' + comm
try:
with os.popen(comm) as p:
num = int(p.read())
except ValueError:
num = 0
else:
try:
num = os.sysconf('SC_NPROCESSORS_ONLN')
except (ValueError, OSError, AttributeError):
num = 0
if num >= 1:
return num
else:
raise NotImplementedError('cannot determine number of cpus')
def freeze_support():
'''
Check whether this is a fake forked process in a frozen executable.
If so then run code specified by commandline and exit.
'''
if sys.platform == 'win32' and getattr(sys, 'frozen', False):
from multiprocessing.forking import freeze_support
freeze_support()
def get_logger():
'''
Return package logger -- if it does not already exist then it is created
'''
from multiprocessing.util import get_logger
return get_logger()
def log_to_stderr(level=None):
'''
Turn on logging and add a handler which prints to stderr
'''
from multiprocessing.util import log_to_stderr
return log_to_stderr(level)
def allow_connection_pickling():
'''
Install support for sending connections and sockets between processes
'''
from multiprocessing import reduction
#
# Definitions depending on native semaphores
#
def Lock():
'''
Returns a non-recursive lock object
'''
from multiprocessing.synchronize import Lock
return Lock()
def RLock():
'''
Returns a recursive lock object
'''
from multiprocessing.synchronize import RLock
return RLock()
def Condition(lock=None):
'''
Returns a condition object
'''
from multiprocessing.synchronize import Condition
return Condition(lock)
def Semaphore(value=1):
'''
Returns a semaphore object
'''
from multiprocessing.synchronize import Semaphore
return Semaphore(value)
def BoundedSemaphore(value=1):
'''
Returns a bounded semaphore object
'''
from multiprocessing.synchronize import BoundedSemaphore
return BoundedSemaphore(value)
def Event():
'''
Returns an event object
'''
from multiprocessing.synchronize import Event
return Event()
def Queue(maxsize=0):
'''
Returns a queue object
'''
from multiprocessing.queues import Queue
return Queue(maxsize)
def JoinableQueue(maxsize=0):
'''
Returns a queue object
'''
from multiprocessing.queues import JoinableQueue
return JoinableQueue(maxsize)
def Pool(processes=None, initializer=None, initargs=(), maxtasksperchild=None):
'''
Returns a process pool object
'''
from multiprocessing.pool import Pool
return Pool(processes, initializer, initargs, maxtasksperchild)
def RawValue(typecode_or_type, *args):
'''
Returns a shared object
'''
from multiprocessing.sharedctypes import RawValue
return RawValue(typecode_or_type, *args)
def RawArray(typecode_or_type, size_or_initializer):
'''
Returns a shared array
'''
from multiprocessing.sharedctypes import RawArray
return RawArray(typecode_or_type, size_or_initializer)
def Value(typecode_or_type, *args, **kwds):
'''
Returns a synchronized shared object
'''
from multiprocessing.sharedctypes import Value
return Value(typecode_or_type, *args, **kwds)
def Array(typecode_or_type, size_or_initializer, **kwds):
'''
Returns a synchronized shared array
'''
from multiprocessing.sharedctypes import Array
return Array(typecode_or_type, size_or_initializer, **kwds)
#
#
#
if sys.platform == 'win32':
def set_executable(executable):
'''
Sets the path to a python.exe or pythonw.exe binary used to run
child processes on Windows instead of sys.executable.
Useful for people embedding Python.
'''
from multiprocessing.forking import set_executable
set_executable(executable)
__all__ += ['set_executable']