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0c4486ad-b6b2-4fba-bfe0-799c05c644b8
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for both objects because the system allows only a limited number of named semaphores, and shared memory segments occupy some space in the main memory.) To select a start method you use the :func:`set_start_method` in the ``if __name__ == '__main__'`` clause of the main module. For example::
trusted_official_docs
CPython Docs
for both objects because the system allows only a limited number of named semaphores, and shared memory segments occupy some space in the main memory.) To select a start method you use the :func:`set_start_method` in the ``if __name__ == '__main__'`` clause of the main module. For example::
for both objects because the system allows only a limited number of named semaphores, and shared memory segments occupy some space in the main memory.) To select a start method you use the :func:`set_start_method` in the ``if __name__ == '__main__'`` clause of the main module. For example::
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When a process exits, it attempts to terminate all of its daemonic child processes. Note that a daemonic process is not allowed to create child processes. Otherwise a daemonic process would leave its children orphaned if it gets terminated when its parent process exits. Additionally, these are **not** Unix daemons or...
trusted_official_docs
CPython Docs
When a process exits, it attempts to terminate all of its daemonic child processes. Note that a daemonic process is not allowed to create child processes. Otherwise a daemonic process would leave its children orphaned if it gets terminated when its parent process exits. Additionally, these are **not** Unix daemons or...
When a process exits, it attempts to terminate all of its daemonic child processes. Note that a daemonic process is not allowed to create child processes. Otherwise a daemonic process would leave its children orphaned if it gets terminated when its parent process exits. Additionally, these are **not** Unix daemons or...
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is possible to run a manager server on one machine and have clients use it from other machines (assuming that the firewalls involved allow it). Running the following commands creates a server for a single shared queue which remote clients can access::
trusted_official_docs
CPython Docs
is possible to run a manager server on one machine and have clients use it from other machines (assuming that the firewalls involved allow it). Running the following commands creates a server for a single shared queue which remote clients can access::
is possible to run a manager server on one machine and have clients use it from other machines (assuming that the firewalls involved allow it). Running the following commands creates a server for a single shared queue which remote clients can access::
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proxy object) does propagate through the manager and so to effectively modify such an item, one could re-assign the modified value to the container proxy:: # create a list proxy and append a mutable object (a dictionary) lproxy = manager.list() lproxy.append({}) # now mutate the dictionary d = lproxy[0] d['a'] = 1...
trusted_official_docs
CPython Docs
proxy object) does propagate through the manager and so to effectively modify such an item, one could re-assign the modified value to the container proxy:: # create a list proxy and append a mutable object (a dictionary) lproxy = manager.list() lproxy.append({}) # now mutate the dictionary d = lproxy[0] d['a'] = 1...
proxy object) does propagate through the manager and so to effectively modify such an item, one could re-assign the modified value to the container proxy:: # create a list proxy and append a mutable object (a dictionary) lproxy = manager.list() lproxy.append({}) # now mutate the dictionary d = lproxy[0] d['a'] = 1...
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Local_Trusted_Corpus
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.. class:: Lock() A non-recursive lock object: a close analog of :class:`threading.Lock`. Once a process or thread has acquired a lock, subsequent attempts to acquire it from any process or thread will block until it is released; any process or thread may release it. The concepts and behaviors of :class:`threading.L...
trusted_official_docs
CPython Docs
.. class:: Lock() A non-recursive lock object: a close analog of :class:`threading.Lock`. Once a process or thread has acquired a lock, subsequent attempts to acquire it from any process or thread will block until it is released; any process or thread may release it. The concepts and behaviors of :class:`threading.L...
.. class:: Lock() A non-recursive lock object: a close analog of :class:`threading.Lock`. Once a process or thread has acquired a lock, subsequent attempts to acquire it from any process or thread will block until it is released; any process or thread may release it. The concepts and behaviors of :class:`threading.L...
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CPython Docs
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default the return value is actually a synchronized wrapper for the object. The object itself can be accessed via the *value* attribute of a :class:`Value`. *typecode_or_type* determines the type of the returned object: it is either a ctypes type or a one character typecode of the kind used by the :mod:`array` module...
trusted_official_docs
CPython Docs
default the return value is actually a synchronized wrapper for the object. The object itself can be accessed via the *value* attribute of a :class:`Value`. *typecode_or_type* determines the type of the returned object: it is either a ctypes type or a one character typecode of the kind used by the :mod:`array` module...
default the return value is actually a synchronized wrapper for the object. The object itself can be accessed via the *value* attribute of a :class:`Value`. *typecode_or_type* determines the type of the returned object: it is either a ctypes type or a one character typecode of the kind used by the :mod:`array` module...
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CPython Docs
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shared object will be accessible. (Here a "public method" means any attribute which has a :meth:`~object.__call__` method and whose name does not begin with ``'_'``.) *method_to_typeid* is a mapping used to specify the return type of those exposed methods which should return a proxy. It maps method names to typeid st...
trusted_official_docs
CPython Docs
shared object will be accessible. (Here a "public method" means any attribute which has a :meth:`~object.__call__` method and whose name does not begin with ``'_'``.) *method_to_typeid* is a mapping used to specify the return type of those exposed methods which should return a proxy. It maps method names to typeid st...
shared object will be accessible. (Here a "public method" means any attribute which has a :meth:`~object.__call__` method and whose name does not begin with ``'_'``.) *method_to_typeid* is a mapping used to specify the return type of those exposed methods which should return a proxy. It maps method names to typeid st...
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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package does not use process shared locks so it is possible (depending on the handler type) for messages from different processes to get mixed up. .. currentmodule:: multiprocessing .. function:: get_logger()
trusted_official_docs
CPython Docs
package does not use process shared locks so it is possible (depending on the handler type) for messages from different processes to get mixed up. .. currentmodule:: multiprocessing .. function:: get_logger()
package does not use process shared locks so it is possible (depending on the handler type) for messages from different processes to get mixed up. .. currentmodule:: multiprocessing .. function:: get_logger()
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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dabaa007-4d48-4185-8c2f-de72cec02891
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the pool as a context manager or by calling :meth:`close` and :meth:`terminate` manually. Failure to do this can lead to the process hanging on finalization. Note that it is **not correct** to rely on the garbage collector to destroy the pool as CPython does not assure that the finalizer of the pool will be called (s...
trusted_official_docs
CPython Docs
the pool as a context manager or by calling :meth:`close` and :meth:`terminate` manually. Failure to do this can lead to the process hanging on finalization. Note that it is **not correct** to rely on the garbage collector to destroy the pool as CPython does not assure that the finalizer of the pool will be called (s...
the pool as a context manager or by calling :meth:`close` and :meth:`terminate` manually. Failure to do this can lead to the process hanging on finalization. Note that it is **not correct** to rely on the garbage collector to destroy the pool as CPython does not assure that the finalizer of the pool will be called (s...
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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of '0.0.0.0' is used, the address will not be a connectable end point on Windows. If you require a connectable end-point, you should use '127.0.0.1'. *family* is the type of socket (or named pipe) to use. This can be one of the strings ``'AF_INET'`` (for a TCP socket), ``'AF_UNIX'`` (for a Unix domain socket) or ``'A...
trusted_official_docs
CPython Docs
of '0.0.0.0' is used, the address will not be a connectable end point on Windows. If you require a connectable end-point, you should use '127.0.0.1'. *family* is the type of socket (or named pipe) to use. This can be one of the strings ``'AF_INET'`` (for a TCP socket), ``'AF_UNIX'`` (for a Unix domain socket) or ``'A...
of '0.0.0.0' is used, the address will not be a connectable end point on Windows. If you require a connectable end-point, you should use '127.0.0.1'. *family* is the type of socket (or named pipe) to use. This can be one of the strings ``'AF_INET'`` (for a TCP socket), ``'AF_UNIX'`` (for a Unix domain socket) or ``'A...
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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.. note:: When an object is put on a queue, the object is pickled and a background thread later flushes the pickled data to an underlying pipe. This has some consequences which are a little surprising, but should not cause any practical difficulties -- if they really bother you then you can instead use a queue crea...
trusted_official_docs
CPython Docs
.. note:: When an object is put on a queue, the object is pickled and a background thread later flushes the pickled data to an underlying pipe. This has some consequences which are a little surprising, but should not cause any practical difficulties -- if they really bother you then you can instead use a queue crea...
.. note:: When an object is put on a queue, the object is pickled and a background thread later flushes the pickled data to an underlying pipe. This has some consequences which are a little surprising, but should not cause any practical difficulties -- if they really bother you then you can instead use a queue crea...
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CPython Docs
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true if using the ``"fork"`` start method, as of Python ``3.14`` that is no longer the default on any platform. See :ref:`multiprocessing-start-methods`. See also :gh:`132898`. .. versionchanged:: 3.3 Added the *daemon* parameter.
trusted_official_docs
CPython Docs
true if using the ``"fork"`` start method, as of Python ``3.14`` that is no longer the default on any platform. See :ref:`multiprocessing-start-methods`. See also :gh:`132898`. .. versionchanged:: 3.3 Added the *daemon* parameter.
true if using the ``"fork"`` start method, as of Python ``3.14`` that is no longer the default on any platform. See :ref:`multiprocessing-start-methods`. See also :gh:`132898`. .. versionchanged:: 3.3 Added the *daemon* parameter.
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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dabaa007-4d48-4185-8c2f-de72cec02891
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If *lock* is ``False`` then access to the returned object will not be automatically protected by a lock, so it will not necessarily be "process-safe". Operations like ``+=`` which involve a read and write are not atomic. So if, for instance, you want to atomically increment a shared value it is insufficient to just d...
trusted_official_docs
CPython Docs
If *lock* is ``False`` then access to the returned object will not be automatically protected by a lock, so it will not necessarily be "process-safe". Operations like ``+=`` which involve a read and write are not atomic. So if, for instance, you want to atomically increment a shared value it is insufficient to just d...
If *lock* is ``False`` then access to the returned object will not be automatically protected by a lock, so it will not necessarily be "process-safe". Operations like ``+=`` which involve a read and write are not atomic. So if, for instance, you want to atomically increment a shared value it is insufficient to just d...
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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sure that the main module can be safely imported by a new Python interpreter without causing unintended side effects (such as starting a new process). For example, using the *spawn* or *forkserver* start method running the following module would fail with a :exc:`RuntimeError`::
trusted_official_docs
CPython Docs
sure that the main module can be safely imported by a new Python interpreter without causing unintended side effects (such as starting a new process). For example, using the *spawn* or *forkserver* start method running the following module would fail with a :exc:`RuntimeError`::
sure that the main module can be safely imported by a new Python interpreter without causing unintended side effects (such as starting a new process). For example, using the *spawn* or *forkserver* start method running the following module would fail with a :exc:`RuntimeError`::
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CPython Docs
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*processes* is the number of worker processes to use. If *processes* is ``None`` then the number returned by :func:`os.process_cpu_count` is used. If *initializer* is not ``None`` then each worker process will call ``initializer(*initargs)`` when it starts.
trusted_official_docs
CPython Docs
*processes* is the number of worker processes to use. If *processes* is ``None`` then the number returned by :func:`os.process_cpu_count` is used. If *initializer* is not ``None`` then each worker process will call ``initializer(*initargs)`` when it starts.
*processes* is the number of worker processes to use. If *processes* is ``None`` then the number returned by :func:`os.process_cpu_count` is used. If *initializer* is not ``None`` then each worker process will call ``initializer(*initargs)`` when it starts.
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CPython Docs
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consumed. Similarly, if the child process is non-daemonic then the parent process may hang on exit when it tries to join all its non-daemonic children. Note that a queue created using a manager does not have this issue. See :ref:`multiprocessing-programming`.
trusted_official_docs
CPython Docs
consumed. Similarly, if the child process is non-daemonic then the parent process may hang on exit when it tries to join all its non-daemonic children. Note that a queue created using a manager does not have this issue. See :ref:`multiprocessing-programming`.
consumed. Similarly, if the child process is non-daemonic then the parent process may hang on exit when it tries to join all its non-daemonic children. Note that a queue created using a manager does not have this issue. See :ref:`multiprocessing-programming`.
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garbage collector to destroy the pool as CPython does not assure that the finalizer of the pool will be called (see :meth:`object.__del__` for more information). .. versionchanged:: 3.2 Added the *maxtasksperchild* parameter.
trusted_official_docs
CPython Docs
garbage collector to destroy the pool as CPython does not assure that the finalizer of the pool will be called (see :meth:`object.__del__` for more information). .. versionchanged:: 3.2 Added the *maxtasksperchild* parameter.
garbage collector to destroy the pool as CPython does not assure that the finalizer of the pool will be called (see :meth:`object.__del__` for more information). .. versionchanged:: 3.2 Added the *maxtasksperchild* parameter.
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Release a lock. This can be called from any process or thread, not only the process or thread which originally acquired the lock. Behavior is the same as in :meth:`threading.Lock.release` except that when invoked on an unlocked lock, a :exc:`ValueError` is raised.
trusted_official_docs
CPython Docs
Release a lock. This can be called from any process or thread, not only the process or thread which originally acquired the lock. Behavior is the same as in :meth:`threading.Lock.release` except that when invoked on an unlocked lock, a :exc:`ValueError` is raised.
Release a lock. This can be called from any process or thread, not only the process or thread which originally acquired the lock. Behavior is the same as in :meth:`threading.Lock.release` except that when invoked on an unlocked lock, a :exc:`ValueError` is raised.
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same process or thread may acquire it again without blocking; that process or thread must release it once for each time it has been acquired. Note that :class:`RLock` is actually a factory function which returns an instance of ``multiprocessing.synchronize.RLock`` initialized with a default context.
trusted_official_docs
CPython Docs
same process or thread may acquire it again without blocking; that process or thread must release it once for each time it has been acquired. Note that :class:`RLock` is actually a factory function which returns an instance of ``multiprocessing.synchronize.RLock`` initialized with a default context.
same process or thread may acquire it again without blocking; that process or thread must release it once for each time it has been acquired. Note that :class:`RLock` is actually a factory function which returns an instance of ``multiprocessing.synchronize.RLock`` initialized with a default context.
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.. _multiprocessing-start-method-forkserver: *forkserver* When the program starts and selects the *forkserver* start method, a server process is spawned. From then on, whenever a new process is needed, the parent process connects to the server and requests that it fork a new process. The fork server process is sing...
trusted_official_docs
CPython Docs
.. _multiprocessing-start-method-forkserver: *forkserver* When the program starts and selects the *forkserver* start method, a server process is spawned. From then on, whenever a new process is needed, the parent process connects to the server and requests that it fork a new process. The fork server process is sing...
.. _multiprocessing-start-method-forkserver: *forkserver* When the program starts and selects the *forkserver* start method, a server process is spawned. From then on, whenever a new process is needed, the parent process connects to the server and requests that it fork a new process. The fork server process is sing...
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1 >>> d_first_inner['b'] = 2 >>> l_outer[1]['c'] = 3 >>> l_outer[1]['z'] = 26 >>> print(l_outer[0]) {'a': 1, 'b': 2} >>> print(l_outer[1]) {'c': 3, 'z': 26} If standard (non-proxy) :class:`list` or :class:`dict` objects are contained in a referent, modifications to those mutable values will not be propagated through th...
trusted_official_docs
CPython Docs
1 >>> d_first_inner['b'] = 2 >>> l_outer[1]['c'] = 3 >>> l_outer[1]['z'] = 26 >>> print(l_outer[0]) {'a': 1, 'b': 2} >>> print(l_outer[1]) {'c': 3, 'z': 26} If standard (non-proxy) :class:`list` or :class:`dict` objects are contained in a referent, modifications to those mutable values will not be propagated through th...
1 >>> d_first_inner['b'] = 2 >>> l_outer[1]['c'] = 3 >>> l_outer[1]['z'] = 26 >>> print(l_outer[0]) {'a': 1, 'b': 2} >>> print(l_outer[1]) {'c': 3, 'z': 26} If standard (non-proxy) :class:`list` or :class:`dict` objects are contained in a referent, modifications to those mutable values will not be propagated through th...
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.. versionadded:: 3.14 :class:`set` support was added. .. versionchanged:: 3.6 Shared objects are capable of being nested. For example, a shared container object such as a shared list can contain other shared objects which will all be managed and synchronized by the :class:`SyncManager`.
trusted_official_docs
CPython Docs
.. versionadded:: 3.14 :class:`set` support was added. .. versionchanged:: 3.6 Shared objects are capable of being nested. For example, a shared container object such as a shared list can contain other shared objects which will all be managed and synchronized by the :class:`SyncManager`.
.. versionadded:: 3.14 :class:`set` support was added. .. versionchanged:: 3.6 Shared objects are capable of being nested. For example, a shared container object such as a shared list can contain other shared objects which will all be managed and synchronized by the :class:`SyncManager`.
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file://datasets/cpython/Doc/library/multiprocessing.rst
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This # ensures that when p closes its handle for the writable end, # wait() will promptly report the readable end as being ready. w.close() while readers: for r in wait(readers): try: msg = r.recv() except EOFError: readers.remove(r) else: print(msg)
trusted_official_docs
CPython Docs
This # ensures that when p closes its handle for the writable end, # wait() will promptly report the readable end as being ready. w.close() while readers: for r in wait(readers): try: msg = r.recv() except EOFError: readers.remove(r) else: print(msg)
This # ensures that when p closes its handle for the writable end, # wait() will promptly report the readable end as being ready. w.close() while readers: for r in wait(readers): try: msg = r.recv() except EOFError: readers.remove(r) else: print(msg)
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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4 worker processes result = pool.apply_async(f, (10,)) # evaluate "f(10)" asynchronously in a single process print(result.get(timeout=1)) # prints "100" unless your computer is *very* slow print(pool.map(f, range(10))) # prints "[0, 1, 4,..., 81]"
trusted_official_docs
CPython Docs
4 worker processes result = pool.apply_async(f, (10,)) # evaluate "f(10)" asynchronously in a single process print(result.get(timeout=1)) # prints "100" unless your computer is *very* slow print(pool.map(f, range(10))) # prints "[0, 1, 4,..., 81]"
4 worker processes result = pool.apply_async(f, (10,)) # evaluate "f(10)" asynchronously in a single process print(result.get(timeout=1)) # prints "100" unless your computer is *very* slow print(pool.map(f, range(10))) # prints "[0, 1, 4,..., 81]"
python, official-docs, cpython, P0
Local_Trusted_Corpus
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CPython Docs
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1, 4, 9, 16, 25, 36, 49, 64, 81] >>> print(repr(l)) <ListProxy object, typeid 'list' at 0x...> >>> l[4] 16 >>> l[2:5] [4, 9, 16] Notice that applying :func:`str` to a proxy will return the representation of the referent, whereas applying :func:`repr` will return the representation of the proxy.
trusted_official_docs
CPython Docs
1, 4, 9, 16, 25, 36, 49, 64, 81] >>> print(repr(l)) <ListProxy object, typeid 'list' at 0x...> >>> l[4] 16 >>> l[2:5] [4, 9, 16] Notice that applying :func:`str` to a proxy will return the representation of the referent, whereas applying :func:`repr` will return the representation of the proxy.
1, 4, 9, 16, 25, 36, 49, 64, 81] >>> print(repr(l)) <ListProxy object, typeid 'list' at 0x...> >>> l[4] 16 >>> l[2:5] [4, 9, 16] Notice that applying :func:`str` to a proxy will return the representation of the referent, whereas applying :func:`repr` will return the representation of the proxy.
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CPython Docs
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or named pipe of the listener object. This is called automatically when the listener is garbage collected. However it is advisable to call it explicitly. Listener objects have the following read-only properties:
trusted_official_docs
CPython Docs
or named pipe of the listener object. This is called automatically when the listener is garbage collected. However it is advisable to call it explicitly. Listener objects have the following read-only properties:
or named pipe of the listener object. This is called automatically when the listener is garbage collected. However it is advisable to call it explicitly. Listener objects have the following read-only properties:
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Local_Trusted_Corpus
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it adds a handler which sends output to :data:`sys.stderr` using format ``'[%(levelname)s/%(processName)s] %(message)s'``. You can modify ``levelname`` of the logger by passing a ``level`` argument. Below is an example session with logging turned on::
trusted_official_docs
CPython Docs
it adds a handler which sends output to :data:`sys.stderr` using format ``'[%(levelname)s/%(processName)s] %(message)s'``. You can modify ``levelname`` of the logger by passing a ``level`` argument. Below is an example session with logging turned on::
it adds a handler which sends output to :data:`sys.stderr` using format ``'[%(levelname)s/%(processName)s] %(message)s'``. You can modify ``levelname`` of the logger by passing a ``level`` argument. Below is an example session with logging turned on::
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CPython Docs
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The address used by the manager. .. versionchanged:: 3.3 Manager objects support the context management protocol -- see :ref:`typecontextmanager`. :meth:`~contextmanager.__enter__` starts the server process (if it has not already started) and then returns the manager object. :meth:`~contextmanager.__exit__` calls :...
trusted_official_docs
CPython Docs
The address used by the manager. .. versionchanged:: 3.3 Manager objects support the context management protocol -- see :ref:`typecontextmanager`. :meth:`~contextmanager.__enter__` starts the server process (if it has not already started) and then returns the manager object. :meth:`~contextmanager.__exit__` calls :...
The address used by the manager. .. versionchanged:: 3.3 Manager objects support the context management protocol -- see :ref:`typecontextmanager`. :meth:`~contextmanager.__enter__` starts the server process (if it has not already started) and then returns the manager object. :meth:`~contextmanager.__exit__` calls :...
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CPython Docs
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One client can access the server as follows:: >>> from multiprocessing.managers import BaseManager >>> class QueueManager(BaseManager): pass >>> QueueManager.register('get_queue') >>> m = QueueManager(address=('foo.bar.org', 50000), authkey=b'abracadabra') >>> m.connect() >>> queue = m.get_queue() >>> queue.put('...
trusted_official_docs
CPython Docs
One client can access the server as follows:: >>> from multiprocessing.managers import BaseManager >>> class QueueManager(BaseManager): pass >>> QueueManager.register('get_queue') >>> m = QueueManager(address=('foo.bar.org', 50000), authkey=b'abracadabra') >>> m.connect() >>> queue = m.get_queue() >>> queue.put('...
One client can access the server as follows:: >>> from multiprocessing.managers import BaseManager >>> class QueueManager(BaseManager): pass >>> QueueManager.register('get_queue') >>> m = QueueManager(address=('foo.bar.org', 50000), authkey=b'abracadabra') >>> m.connect() >>> queue = m.get_queue() >>> queue.put('...
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Local_Trusted_Corpus
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CPython Docs
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.. doctest:: >>> mp_context = multiprocessing.get_context('spawn') >>> manager = mp_context.Manager() >>> Global = manager.Namespace() >>> Global.x = 10 >>> Global.y = 'hello' >>> Global._z = 12.3 # this is an attribute of the proxy >>> print(Global) Namespace(x=10, y='hello')
trusted_official_docs
CPython Docs
.. doctest:: >>> mp_context = multiprocessing.get_context('spawn') >>> manager = mp_context.Manager() >>> Global = manager.Namespace() >>> Global.x = 10 >>> Global.y = 'hello' >>> Global._z = 12.3 # this is an attribute of the proxy >>> print(Global) Namespace(x=10, y='hello')
.. doctest:: >>> mp_context = multiprocessing.get_context('spawn') >>> manager = mp_context.Manager() >>> Global = manager.Namespace() >>> Global.x = 10 >>> Global.y = 'hello' >>> Global._z = 12.3 # this is an attribute of the proxy >>> print(Global) Namespace(x=10, y='hello')
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CPython Docs
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pipe at the same time. Of course there is no risk of corruption from processes using different ends of the pipe at the same time. The :meth:`~Connection.send` method serializes the object and :meth:`~Connection.recv` re-creates the object.
trusted_official_docs
CPython Docs
pipe at the same time. Of course there is no risk of corruption from processes using different ends of the pipe at the same time. The :meth:`~Connection.send` method serializes the object and :meth:`~Connection.recv` re-creates the object.
pipe at the same time. Of course there is no risk of corruption from processes using different ends of the pipe at the same time. The :meth:`~Connection.send` method serializes the object and :meth:`~Connection.recv` re-creates the object.
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Instantiating this class may set the global start method. See :ref:`global-start-method` for more details. A solitary difference from its close analog exists: its ``acquire`` method's first argument is named *block*, as is consistent with :meth:`Lock.acquire`.
trusted_official_docs
CPython Docs
Instantiating this class may set the global start method. See :ref:`global-start-method` for more details. A solitary difference from its close analog exists: its ``acquire`` method's first argument is named *block*, as is consistent with :meth:`Lock.acquire`.
Instantiating this class may set the global start method. See :ref:`global-start-method` for more details. A solitary difference from its close analog exists: its ``acquire`` method's first argument is named *block*, as is consistent with :meth:`Lock.acquire`.
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CPython Docs
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Note that it may cause high memory usage for very long iterables. Consider using :meth:`imap` or :meth:`imap_unordered` with explicit *chunksize* option for better efficiency. .. method:: map_async(func, iterable[, chunksize[, callback[, error_callback]]])
trusted_official_docs
CPython Docs
Note that it may cause high memory usage for very long iterables. Consider using :meth:`imap` or :meth:`imap_unordered` with explicit *chunksize* option for better efficiency. .. method:: map_async(func, iterable[, chunksize[, callback[, error_callback]]])
Note that it may cause high memory usage for very long iterables. Consider using :meth:`imap` or :meth:`imap_unordered` with explicit *chunksize* option for better efficiency. .. method:: map_async(func, iterable[, chunksize[, callback[, error_callback]]])
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CPython Docs
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value it sees (if any) may not be the same as the value in the parent process at the time that :meth:`Process.start <multiprocessing.Process.start>` was called. However, global variables which are just module level constants cause no problems.
trusted_official_docs
CPython Docs
value it sees (if any) may not be the same as the value in the parent process at the time that :meth:`Process.start <multiprocessing.Process.start>` was called. However, global variables which are just module level constants cause no problems.
value it sees (if any) may not be the same as the value in the parent process at the time that :meth:`Process.start <multiprocessing.Process.start>` was called. However, global variables which are just module level constants cause no problems.
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CPython Docs
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As far as possible one should try to avoid shifting large amounts of data between processes. It is probably best to stick to using queues or pipes for communication between processes rather than using the lower level synchronization primitives.
trusted_official_docs
CPython Docs
As far as possible one should try to avoid shifting large amounts of data between processes. It is probably best to stick to using queues or pipes for communication between processes rather than using the lower level synchronization primitives.
As far as possible one should try to avoid shifting large amounts of data between processes. It is probably best to stick to using queues or pipes for communication between processes rather than using the lower level synchronization primitives.
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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Connection objects allow the sending and receiving of picklable objects or strings. They can be thought of as message oriented connected sockets. Connection objects are usually created using :func:`Pipe <multiprocessing.Pipe>` -- see also :ref:`multiprocessing-listeners-clients`.
trusted_official_docs
CPython Docs
Connection objects allow the sending and receiving of picklable objects or strings. They can be thought of as message oriented connected sockets. Connection objects are usually created using :func:`Pipe <multiprocessing.Pipe>` -- see also :ref:`multiprocessing-listeners-clients`.
Connection objects allow the sending and receiving of picklable objects or strings. They can be thought of as message oriented connected sockets. Connection objects are usually created using :func:`Pipe <multiprocessing.Pipe>` -- see also :ref:`multiprocessing-listeners-clients`.
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object passed to the object's constructor as the target argument, if any, with sequential and keyword arguments taken from the *args* and *kwargs* arguments, respectively. Using a list or tuple as the *args* argument passed to :class:`Process` achieves the same effect.
trusted_official_docs
CPython Docs
object passed to the object's constructor as the target argument, if any, with sequential and keyword arguments taken from the *args* and *kwargs* arguments, respectively. Using a list or tuple as the *args* argument passed to :class:`Process` achieves the same effect.
object passed to the object's constructor as the target argument, if any, with sequential and keyword arguments taken from the *args* and *kwargs* arguments, respectively. Using a list or tuple as the *args* argument passed to :class:`Process` achieves the same effect.
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it is worth pointing out here. This means that some examples, such as the :class:`multiprocessing.pool.Pool` examples will not work in the interactive interpreter. For example:: >>> from multiprocessing import Pool >>> p = Pool(5) >>> def f(x): ... return x*x ... >>> with p: ... p.map(f, [1,2,3]) Process PoolWork...
trusted_official_docs
CPython Docs
it is worth pointing out here. This means that some examples, such as the :class:`multiprocessing.pool.Pool` examples will not work in the interactive interpreter. For example:: >>> from multiprocessing import Pool >>> p = Pool(5) >>> def f(x): ... return x*x ... >>> with p: ... p.map(f, [1,2,3]) Process PoolWork...
it is worth pointing out here. This means that some examples, such as the :class:`multiprocessing.pool.Pool` examples will not work in the interactive interpreter. For example:: >>> from multiprocessing import Pool >>> p = Pool(5) >>> def f(x): ... return x*x ... >>> with p: ... p.map(f, [1,2,3]) Process PoolWork...
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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To use :func:`Client` to connect to a named pipe on a remote computer called *ServerName* one should use an address of the form :samp:`r'\\\\\\\\{ServerName}\\pipe\\\\{PipeName}'` instead. Note that any string beginning with two backslashes is assumed by default to be an ``'AF_PIPE'`` address rather than an ``'AF_UNIX'...
trusted_official_docs
CPython Docs
To use :func:`Client` to connect to a named pipe on a remote computer called *ServerName* one should use an address of the form :samp:`r'\\\\\\\\{ServerName}\\pipe\\\\{PipeName}'` instead. Note that any string beginning with two backslashes is assumed by default to be an ``'AF_PIPE'`` address rather than an ``'AF_UNIX'...
To use :func:`Client` to connect to a named pipe on a remote computer called *ServerName* one should use an address of the form :samp:`r'\\\\\\\\{ServerName}\\pipe\\\\{PipeName}'` instead. Note that any string beginning with two backslashes is assumed by default to be an ``'AF_PIPE'`` address rather than an ``'AF_UNIX'...
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Note that *lock* is a keyword only argument. Note that an array of :data:`ctypes.c_char` has *value* and *raw* attributes which allow one to use it to store and retrieve strings.
trusted_official_docs
CPython Docs
Note that *lock* is a keyword only argument. Note that an array of :data:`ctypes.c_char` has *value* and *raw* attributes which allow one to use it to store and retrieve strings.
Note that *lock* is a keyword only argument. Note that an array of :data:`ctypes.c_char` has *value* and *raw* attributes which allow one to use it to store and retrieve strings.
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CPython Docs
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locks/semaphores. When a process first puts an item on the queue a feeder thread is started which transfers objects from a buffer into the pipe. Instantiating this class may set the global start method. See :ref:`global-start-method` for more details.
trusted_official_docs
CPython Docs
locks/semaphores. When a process first puts an item on the queue a feeder thread is started which transfers objects from a buffer into the pipe. Instantiating this class may set the global start method. See :ref:`global-start-method` for more details.
locks/semaphores. When a process first puts an item on the queue a feeder thread is started which transfers objects from a buffer into the pipe. Instantiating this class may set the global start method. See :ref:`global-start-method` for more details.
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The usual :exc:`queue.Empty` and :exc:`queue.Full` exceptions from the standard library's :mod:`queue` module are raised to signal timeouts. :class:`Queue` implements all the methods of :class:`queue.Queue` except for :meth:`~queue.Queue.task_done`, :meth:`~queue.Queue.join`, and :meth:`~queue.Queue.shutdown`.
trusted_official_docs
CPython Docs
The usual :exc:`queue.Empty` and :exc:`queue.Full` exceptions from the standard library's :mod:`queue` module are raised to signal timeouts. :class:`Queue` implements all the methods of :class:`queue.Queue` except for :meth:`~queue.Queue.task_done`, :meth:`~queue.Queue.join`, and :meth:`~queue.Queue.shutdown`.
The usual :exc:`queue.Empty` and :exc:`queue.Full` exceptions from the standard library's :mod:`queue` module are raised to signal timeouts. :class:`Queue` implements all the methods of :class:`queue.Queue` except for :meth:`~queue.Queue.task_done`, :meth:`~queue.Queue.join`, and :meth:`~queue.Queue.shutdown`.
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Better to inherit than pickle/unpickle When using the *spawn* or *forkserver* start methods many types from :mod:`!multiprocessing` need to be picklable so that child processes can use them. However, one should generally avoid sending shared objects to other processes using pipes or queues. Instead you should arrang...
trusted_official_docs
CPython Docs
Better to inherit than pickle/unpickle When using the *spawn* or *forkserver* start methods many types from :mod:`!multiprocessing` need to be picklable so that child processes can use them. However, one should generally avoid sending shared objects to other processes using pipes or queues. Instead you should arrang...
Better to inherit than pickle/unpickle When using the *spawn* or *forkserver* start methods many types from :mod:`!multiprocessing` need to be picklable so that child processes can use them. However, one should generally avoid sending shared objects to other processes using pipes or queues. Instead you should arrang...
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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Python supports several ways to create and initialize a process. The global start method sets the default mechanism for creating a process. Several multiprocessing functions and methods that may also instantiate certain objects will implicitly set the global start method to the system's default, if it hasn’t been set a...
trusted_official_docs
CPython Docs
Python supports several ways to create and initialize a process. The global start method sets the default mechanism for creating a process. Several multiprocessing functions and methods that may also instantiate certain objects will implicitly set the global start method to the system's default, if it hasn’t been set a...
Python supports several ways to create and initialize a process. The global start method sets the default mechanism for creating a process. Several multiprocessing functions and methods that may also instantiate certain objects will implicitly set the global start method to the system's default, if it hasn’t been set a...
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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Usually message passing between processes is done using queues or by using :class:`~Connection` objects returned by :func:`~multiprocessing.Pipe`. However, the :mod:`!multiprocessing.connection` module allows some extra flexibility. It basically gives a high level message oriented API for dealing with sockets or Window...
trusted_official_docs
CPython Docs
Usually message passing between processes is done using queues or by using :class:`~Connection` objects returned by :func:`~multiprocessing.Pipe`. However, the :mod:`!multiprocessing.connection` module allows some extra flexibility. It basically gives a high level message oriented API for dealing with sockets or Window...
Usually message passing between processes is done using queues or by using :class:`~Connection` objects returned by :func:`~multiprocessing.Pipe`. However, the :mod:`!multiprocessing.connection` module allows some extra flexibility. It basically gives a high level message oriented API for dealing with sockets or Window...
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file://datasets/cpython/Doc/library/multiprocessing.rst
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.. function:: set_executable(executable) Set the path of the Python interpreter to use when starting a child process. (By default :data:`sys.executable` is used). Embedders will probably need to do something like ::
trusted_official_docs
CPython Docs
.. function:: set_executable(executable) Set the path of the Python interpreter to use when starting a child process. (By default :data:`sys.executable` is used). Embedders will probably need to do something like ::
.. function:: set_executable(executable) Set the path of the Python interpreter to use when starting a child process. (By default :data:`sys.executable` is used). Embedders will probably need to do something like ::
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import Queue >>> queue = Queue() >>> class QueueManager(BaseManager): pass >>> QueueManager.register('get_queue', callable=lambda:queue) >>> m = QueueManager(address=('', 50000), authkey=b'abracadabra') >>> s = m.get_server() >>> s.serve_forever() One client can access the server as follows::
trusted_official_docs
CPython Docs
import Queue >>> queue = Queue() >>> class QueueManager(BaseManager): pass >>> QueueManager.register('get_queue', callable=lambda:queue) >>> m = QueueManager(address=('', 50000), authkey=b'abracadabra') >>> s = m.get_server() >>> s.serve_forever() One client can access the server as follows::
import Queue >>> queue = Queue() >>> class QueueManager(BaseManager): pass >>> QueueManager.register('get_queue', callable=lambda:queue) >>> m = QueueManager(address=('', 50000), authkey=b'abracadabra') >>> s = m.get_server() >>> s.serve_forever() One client can access the server as follows::
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file://datasets/cpython/Doc/library/multiprocessing.rst
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that their already imported state is inherited by forked processes. This can be used as a performance enhancement to avoid repeated work in every process. For this to work, it must be called before the forkserver process has been launched (before creating a :class:`Pool` or starting a :class:`Process`).
trusted_official_docs
CPython Docs
that their already imported state is inherited by forked processes. This can be used as a performance enhancement to avoid repeated work in every process. For this to work, it must be called before the forkserver process has been launched (before creating a :class:`Pool` or starting a :class:`Process`).
that their already imported state is inherited by forked processes. This can be used as a performance enhancement to avoid repeated work in every process. For this to work, it must be called before the forkserver process has been launched (before creating a :class:`Pool` or starting a :class:`Process`).
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This allows the newly spawned Python interpreter to safely import the module and then run the module's ``foo()`` function. Similar restrictions apply if a pool or manager is created in the main module.
trusted_official_docs
CPython Docs
This allows the newly spawned Python interpreter to safely import the module and then run the module's ``foo()`` function. Similar restrictions apply if a pool or manager is created in the main module.
This allows the newly spawned Python interpreter to safely import the module and then run the module's ``foo()`` function. Similar restrictions apply if a pool or manager is created in the main module.
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file://datasets/cpython/Doc/library/multiprocessing.rst
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ctypes type or a one character typecode of the kind used by the :mod:`array` module. *\*args* is passed on to the constructor for the type. Note that setting and getting the value is potentially non-atomic -- use :func:`Value` instead to make sure that access is automatically synchronized using a lock.
trusted_official_docs
CPython Docs
ctypes type or a one character typecode of the kind used by the :mod:`array` module. *\*args* is passed on to the constructor for the type. Note that setting and getting the value is potentially non-atomic -- use :func:`Value` instead to make sure that access is automatically synchronized using a lock.
ctypes type or a one character typecode of the kind used by the :mod:`array` module. *\*args* is passed on to the constructor for the type. Note that setting and getting the value is potentially non-atomic -- use :func:`Value` instead to make sure that access is automatically synchronized using a lock.
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can be used to tell the server process to create a new shared object and return a proxy for it. By default it is ``True``. :class:`BaseManager` instances also have one read-only property:
trusted_official_docs
CPython Docs
can be used to tell the server process to create a new shared object and return a proxy for it. By default it is ``True``. :class:`BaseManager` instances also have one read-only property:
can be used to tell the server process to create a new shared object and return a proxy for it. By default it is ``True``. :class:`BaseManager` instances also have one read-only property:
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# evaluate "os.getpid()" asynchronously res = pool.apply_async(os.getpid, ()) # runs in *only* one process print(res.get(timeout=1)) # prints the PID of that process # launching multiple evaluations asynchronously *may* use more processes multiple_results = [pool.apply_async(os.getpid, ()) for i in range(4)] print([r...
trusted_official_docs
CPython Docs
# evaluate "os.getpid()" asynchronously res = pool.apply_async(os.getpid, ()) # runs in *only* one process print(res.get(timeout=1)) # prints the PID of that process # launching multiple evaluations asynchronously *may* use more processes multiple_results = [pool.apply_async(os.getpid, ()) for i in range(4)] print([r...
# evaluate "os.getpid()" asynchronously res = pool.apply_async(os.getpid, ()) # runs in *only* one process print(res.get(timeout=1)) # prints the PID of that process # launching multiple evaluations asynchronously *may* use more processes multiple_results = [pool.apply_async(os.getpid, ()) for i in range(4)] print([r...
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Local_Trusted_Corpus
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file://datasets/cpython/Doc/library/multiprocessing.rst
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from multiprocessing.managers import BaseManager >>> class QueueManager(BaseManager): pass >>> QueueManager.register('get_queue') >>> m = QueueManager(address=('foo.bar.org', 50000), authkey=b'abracadabra') >>> m.connect() >>> queue = m.get_queue() >>> queue.get() 'hello' Local processes can also access that queue, usi...
trusted_official_docs
CPython Docs
from multiprocessing.managers import BaseManager >>> class QueueManager(BaseManager): pass >>> QueueManager.register('get_queue') >>> m = QueueManager(address=('foo.bar.org', 50000), authkey=b'abracadabra') >>> m.connect() >>> queue = m.get_queue() >>> queue.get() 'hello' Local processes can also access that queue, usi...
from multiprocessing.managers import BaseManager >>> class QueueManager(BaseManager): pass >>> QueueManager.register('get_queue') >>> m = QueueManager(address=('foo.bar.org', 50000), authkey=b'abracadabra') >>> m.connect() >>> queue = m.get_queue() >>> queue.get() 'hello' Local processes can also access that queue, usi...
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CPython Docs
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Note that there are several differences in this first argument's behavior compared to the implementation of :meth:`threading.RLock.acquire`, starting with the name of the argument itself. When invoked with the *block* argument set to ``False``, do not block. If the lock has already been acquired (and thus is owned) by ...
trusted_official_docs
CPython Docs
Note that there are several differences in this first argument's behavior compared to the implementation of :meth:`threading.RLock.acquire`, starting with the name of the argument itself. When invoked with the *block* argument set to ``False``, do not block. If the lock has already been acquired (and thus is owned) by ...
Note that there are several differences in this first argument's behavior compared to the implementation of :meth:`threading.RLock.acquire`, starting with the name of the argument itself. When invoked with the *block* argument set to ``False``, do not block. If the lock has already been acquired (and thus is owned) by ...
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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(The ``freeze_support()`` line can be omitted if the program will be run normally instead of frozen.) This allows the newly spawned Python interpreter to safely import the module and then run the module's ``foo()`` function.
trusted_official_docs
CPython Docs
(The ``freeze_support()`` line can be omitted if the program will be run normally instead of frozen.) This allows the newly spawned Python interpreter to safely import the module and then run the module's ``foo()`` function.
(The ``freeze_support()`` line can be omitted if the program will be run normally instead of frozen.) This allows the newly spawned Python interpreter to safely import the module and then run the module's ``foo()`` function.
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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versionchanged:: 3.14 This is no longer the default start method on any platform. Code that requires *fork* must explicitly specify that via :func:`get_context` or :func:`set_start_method`. .. versionchanged:: 3.12 If Python is able to detect that your process has multiple threads, the :func:`os.fork` function that t...
trusted_official_docs
CPython Docs
versionchanged:: 3.14 This is no longer the default start method on any platform. Code that requires *fork* must explicitly specify that via :func:`get_context` or :func:`set_start_method`. .. versionchanged:: 3.12 If Python is able to detect that your process has multiple threads, the :func:`os.fork` function that t...
versionchanged:: 3.14 This is no longer the default start method on any platform. Code that requires *fork* must explicitly specify that via :func:`get_context` or :func:`set_start_method`. .. versionchanged:: 3.12 If Python is able to detect that your process has multiple threads, the :func:`os.fork` function that t...
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Local_Trusted_Corpus
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CPython Docs
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consumers. For each :meth:`~Queue.get` used to fetch a task, a subsequent call to :meth:`task_done` tells the queue that the processing on the task is complete. If a :meth:`~queue.Queue.join` is currently blocking, it will resume when all items have been processed (meaning that a :meth:`task_done` call was received f...
trusted_official_docs
CPython Docs
consumers. For each :meth:`~Queue.get` used to fetch a task, a subsequent call to :meth:`task_done` tells the queue that the processing on the task is complete. If a :meth:`~queue.Queue.join` is currently blocking, it will resume when all items have been processed (meaning that a :meth:`task_done` call was received f...
consumers. For each :meth:`~Queue.get` used to fetch a task, a subsequent call to :meth:`task_done` tells the queue that the processing on the task is complete. If a :meth:`~queue.Queue.join` is currently blocking, it will resume when all items have been processed (meaning that a :meth:`task_done` call was received f...
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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keyword-only *daemon* argument sets the process :attr:`daemon` flag to ``True`` or ``False``. If ``None`` (the default), this flag will be inherited from the creating process. By default, no arguments are passed to *target*. The *args* argument, which defaults to ``()``, can be used to specify a list or tuple of the a...
trusted_official_docs
CPython Docs
keyword-only *daemon* argument sets the process :attr:`daemon` flag to ``True`` or ``False``. If ``None`` (the default), this flag will be inherited from the creating process. By default, no arguments are passed to *target*. The *args* argument, which defaults to ``()``, can be used to specify a list or tuple of the a...
keyword-only *daemon* argument sets the process :attr:`daemon` flag to ``True`` or ``False``. If ``None`` (the default), this flag will be inherited from the creating process. By default, no arguments are passed to *target*. The *args* argument, which defaults to ``()``, can be used to specify a list or tuple of the a...
python, official-docs, cpython, P0
Local_Trusted_Corpus
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CPython Docs
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argument. When the result becomes ready *callback* is applied to it, that is unless the call failed, in which case the *error_callback* is applied instead. If *error_callback* is specified then it should be a callable which accepts a single argument. If the target function fails, then the *error_callback* is called w...
trusted_official_docs
CPython Docs
argument. When the result becomes ready *callback* is applied to it, that is unless the call failed, in which case the *error_callback* is applied instead. If *error_callback* is specified then it should be a callable which accepts a single argument. If the target function fails, then the *error_callback* is called w...
argument. When the result becomes ready *callback* is applied to it, that is unless the call failed, in which case the *error_callback* is applied instead. If *error_callback* is specified then it should be a callable which accepts a single argument. If the target function fails, then the *error_callback* is called w...
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a parent process using a global resource. However, it is better to pass the object as an argument to the constructor for the child process. Apart from making the code (potentially) compatible with Windows and the other start methods this also ensures that as long as the child process is still alive the object will no...
trusted_official_docs
CPython Docs
a parent process using a global resource. However, it is better to pass the object as an argument to the constructor for the child process. Apart from making the code (potentially) compatible with Windows and the other start methods this also ensures that as long as the child process is still alive the object will no...
a parent process using a global resource. However, it is better to pass the object as an argument to the constructor for the child process. Apart from making the code (potentially) compatible with Windows and the other start methods this also ensures that as long as the child process is still alive the object will no...
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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* An ``'AF_UNIX'`` address is a string representing a filename on the filesystem. * An ``'AF_PIPE'`` address is a string of the form :samp:`r'\\\\\\.\\pipe\\\\{PipeName}'`. To use :func:`Client` to connect to a named pipe on a remote computer called *ServerName* one should use an address of the form :samp:`r'\\\\\\\...
trusted_official_docs
CPython Docs
* An ``'AF_UNIX'`` address is a string representing a filename on the filesystem. * An ``'AF_PIPE'`` address is a string of the form :samp:`r'\\\\\\.\\pipe\\\\{PipeName}'`. To use :func:`Client` to connect to a named pipe on a remote computer called *ServerName* one should use an address of the form :samp:`r'\\\\\\\...
* An ``'AF_UNIX'`` address is a string representing a filename on the filesystem. * An ``'AF_PIPE'`` address is a string of the form :samp:`r'\\\\\\.\\pipe\\\\{PipeName}'`. To use :func:`Client` to connect to a named pipe on a remote computer called *ServerName* one should use an address of the form :samp:`r'\\\\\\\...
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two methods in addition to those of the object it wraps: :meth:`get_obj` returns the wrapped object and :meth:`get_lock` returns the lock object used for synchronization. Note that accessing the ctypes object through the wrapper can be a lot slower than accessing the raw ctypes object.
trusted_official_docs
CPython Docs
two methods in addition to those of the object it wraps: :meth:`get_obj` returns the wrapped object and :meth:`get_lock` returns the lock object used for synchronization. Note that accessing the ctypes object through the wrapper can be a lot slower than accessing the raw ctypes object.
two methods in addition to those of the object it wraps: :meth:`get_obj` returns the wrapped object and :meth:`get_lock` returns the lock object used for synchronization. Note that accessing the ctypes object through the wrapper can be a lot slower than accessing the raw ctypes object.
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.. function:: synchronized(obj, lock=None, ctx=None) Return a process-safe wrapper object for a ctypes object which uses *lock* to synchronize access. If *lock* is ``None`` (the default) then a :class:`multiprocessing.RLock` object is created automatically.
trusted_official_docs
CPython Docs
.. function:: synchronized(obj, lock=None, ctx=None) Return a process-safe wrapper object for a ctypes object which uses *lock* to synchronize access. If *lock* is ``None`` (the default) then a :class:`multiprocessing.RLock` object is created automatically.
.. function:: synchronized(obj, lock=None, ctx=None) Return a process-safe wrapper object for a ctypes object which uses *lock* to synchronize access. If *lock* is ``None`` (the default) then a :class:`multiprocessing.RLock` object is created automatically.
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>>> from multiprocessing.managers import BaseManager >>> class QueueManager(BaseManager): pass >>> QueueManager.register('get_queue') >>> m = QueueManager(address=('foo.bar.org', 50000), authkey=b'abracadabra') >>> m.connect() >>> queue = m.get_queue() >>> queue.put('hello') Another client can also use it::
trusted_official_docs
CPython Docs
>>> from multiprocessing.managers import BaseManager >>> class QueueManager(BaseManager): pass >>> QueueManager.register('get_queue') >>> m = QueueManager(address=('foo.bar.org', 50000), authkey=b'abracadabra') >>> m.connect() >>> queue = m.get_queue() >>> queue.put('hello') Another client can also use it::
>>> from multiprocessing.managers import BaseManager >>> class QueueManager(BaseManager): pass >>> QueueManager.register('get_queue') >>> m = QueueManager(address=('foo.bar.org', 50000), authkey=b'abracadabra') >>> m.connect() >>> queue = m.get_queue() >>> queue.put('hello') Another client can also use it::
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file://datasets/cpython/Doc/library/multiprocessing.rst
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POSIX this is done using the :py:const:`~signal.SIGTERM` signal; on Windows :c:func:`!TerminateProcess` is used. Note that exit handlers and finally clauses, etc., will not be executed. Note that descendant processes of the process will *not* be terminated -- they will simply become orphaned.
trusted_official_docs
CPython Docs
POSIX this is done using the :py:const:`~signal.SIGTERM` signal; on Windows :c:func:`!TerminateProcess` is used. Note that exit handlers and finally clauses, etc., will not be executed. Note that descendant processes of the process will *not* be terminated -- they will simply become orphaned.
POSIX this is done using the :py:const:`~signal.SIGTERM` signal; on Windows :c:func:`!TerminateProcess` is used. Note that exit handlers and finally clauses, etc., will not be executed. Note that descendant processes of the process will *not* be terminated -- they will simply become orphaned.
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A wrapper for a bound socket or Windows named pipe which is 'listening' for connections. *address* is the address to be used by the bound socket or named pipe of the listener object.
trusted_official_docs
CPython Docs
A wrapper for a bound socket or Windows named pipe which is 'listening' for connections. *address* is the address to be used by the bound socket or named pipe of the listener object.
A wrapper for a bound socket or Windows named pipe which is 'listening' for connections. *address* is the address to be used by the bound socket or named pipe of the listener object.
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Return the name of start method used for starting processes. If the global start method is not set and *allow_none* is ``False``, the global start method is set to the default, and its name is returned. See :ref:`global-start-method` for more details.
trusted_official_docs
CPython Docs
Return the name of start method used for starting processes. If the global start method is not set and *allow_none* is ``False``, the global start method is set to the default, and its name is returned. See :ref:`global-start-method` for more details.
Return the name of start method used for starting processes. If the global start method is not set and *allow_none* is ``False``, the global start method is set to the default, and its name is returned. See :ref:`global-start-method` for more details.
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.. doctest:: >>> a = manager.list() >>> b = manager.list() >>> a.append(b) # referent of a now contains referent of b >>> print(a, b) [<ListProxy object, typeid 'list' at ...>] [] >>> b.append('hello') >>> print(a[0], b) ['hello'] ['hello']
trusted_official_docs
CPython Docs
.. doctest:: >>> a = manager.list() >>> b = manager.list() >>> a.append(b) # referent of a now contains referent of b >>> print(a, b) [<ListProxy object, typeid 'list' at ...>] [] >>> b.append('hello') >>> print(a[0], b) ['hello'] ['hello']
.. doctest:: >>> a = manager.list() >>> b = manager.list() >>> a.append(b) # referent of a now contains referent of b >>> print(a, b) [<ListProxy object, typeid 'list' at ...>] [] >>> b.append('hello') >>> print(a[0], b) ['hello'] ['hello']
python, official-docs, cpython, P0
Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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supabase-export-v2
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them to proceed. If after the decrement the recursion level is still nonzero, the lock remains locked and owned by the calling process or thread. Only call this method when the calling process or thread owns the lock. An :exc:`AssertionError` is raised if this method is called by a process or thread other than the own...
trusted_official_docs
CPython Docs
them to proceed. If after the decrement the recursion level is still nonzero, the lock remains locked and owned by the calling process or thread. Only call this method when the calling process or thread owns the lock. An :exc:`AssertionError` is raised if this method is called by a process or thread other than the own...
them to proceed. If after the decrement the recursion level is still nonzero, the lock remains locked and owned by the calling process or thread. Only call this method when the calling process or thread owns the lock. An :exc:`AssertionError` is raised if this method is called by a process or thread other than the own...
python, official-docs, cpython, P0
Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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.. method:: apply(func[, args[, kwds]]) Call *func* with arguments *args* and keyword arguments *kwds*. It blocks until the result is ready. Given this blocks, :meth:`apply_async` is better suited for performing work in parallel. Additionally, *func* is only executed in one of the workers of the pool.
trusted_official_docs
CPython Docs
.. method:: apply(func[, args[, kwds]]) Call *func* with arguments *args* and keyword arguments *kwds*. It blocks until the result is ready. Given this blocks, :meth:`apply_async` is better suited for performing work in parallel. Additionally, *func* is only executed in one of the workers of the pool.
.. method:: apply(func[, args[, kwds]]) Call *func* with arguments *args* and keyword arguments *kwds*. It blocks until the result is ready. Given this blocks, :meth:`apply_async` is better suited for performing work in parallel. Additionally, *func* is only executed in one of the workers of the pool.
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
unknown
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6,263
supabase-export-v2
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.. note:: In general, all arguments to :class:`Process` must be picklable. This is frequently observed when trying to create a :class:`Process` or use a :class:`concurrent.futures.ProcessPoolExecutor` from a REPL with a locally defined *target* function.
trusted_official_docs
CPython Docs
.. note:: In general, all arguments to :class:`Process` must be picklable. This is frequently observed when trying to create a :class:`Process` or use a :class:`concurrent.futures.ProcessPoolExecutor` from a REPL with a locally defined *target* function.
.. note:: In general, all arguments to :class:`Process` must be picklable. This is frequently observed when trying to create a :class:`Process` or use a :class:`concurrent.futures.ProcessPoolExecutor` from a REPL with a locally defined *target* function.
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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dabaa007-4d48-4185-8c2f-de72cec02891
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supabase-export-v2
957781664d579640
and behaviors of :class:`threading.Lock` as it applies to threads are replicated here in :class:`multiprocessing.Lock` as it applies to either processes or threads, except as noted. Note that :class:`Lock` is actually a factory function which returns an instance of ``multiprocessing.synchronize.Lock`` initialized with...
trusted_official_docs
CPython Docs
and behaviors of :class:`threading.Lock` as it applies to threads are replicated here in :class:`multiprocessing.Lock` as it applies to either processes or threads, except as noted. Note that :class:`Lock` is actually a factory function which returns an instance of ``multiprocessing.synchronize.Lock`` initialized with...
and behaviors of :class:`threading.Lock` as it applies to threads are replicated here in :class:`multiprocessing.Lock` as it applies to either processes or threads, except as noted. Note that :class:`Lock` is actually a factory function which returns an instance of ``multiprocessing.synchronize.Lock`` initialized with...
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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.. function:: Value(typecode_or_type, *args, lock=True, ctx=None) The same as :func:`RawValue` except that depending on the value of *lock* a process-safe synchronization wrapper may be returned instead of a raw ctypes object.
trusted_official_docs
CPython Docs
.. function:: Value(typecode_or_type, *args, lock=True, ctx=None) The same as :func:`RawValue` except that depending on the value of *lock* a process-safe synchronization wrapper may be returned instead of a raw ctypes object.
.. function:: Value(typecode_or_type, *args, lock=True, ctx=None) The same as :func:`RawValue` except that depending on the value of *lock* a process-safe synchronization wrapper may be returned instead of a raw ctypes object.
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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dabaa007-4d48-4185-8c2f-de72cec02891
6,425
supabase-export-v2
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is not equivalent to the number of CPUs the current process can use. The number of usable CPUs can be obtained with :func:`os.process_cpu_count` (or ``len(os.sched_getaffinity(0))``). When the number of CPUs cannot be determined a :exc:`NotImplementedError` is raised.
trusted_official_docs
CPython Docs
is not equivalent to the number of CPUs the current process can use. The number of usable CPUs can be obtained with :func:`os.process_cpu_count` (or ``len(os.sched_getaffinity(0))``). When the number of CPUs cannot be determined a :exc:`NotImplementedError` is raised.
is not equivalent to the number of CPUs the current process can use. The number of usable CPUs can be obtained with :func:`os.process_cpu_count` (or ``len(os.sched_getaffinity(0))``). When the number of CPUs cannot be determined a :exc:`NotImplementedError` is raised.
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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supabase-export-v2
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wrapper object for a ctypes object which uses *lock* to synchronize access. If *lock* is ``None`` (the default) then a :class:`multiprocessing.RLock` object is created automatically. *ctx* is a context object, or ``None`` (use the current context). If ``None``, calling this may set the global start method. See :ref:`...
trusted_official_docs
CPython Docs
wrapper object for a ctypes object which uses *lock* to synchronize access. If *lock* is ``None`` (the default) then a :class:`multiprocessing.RLock` object is created automatically. *ctx* is a context object, or ``None`` (use the current context). If ``None``, calling this may set the global start method. See :ref:`...
wrapper object for a ctypes object which uses *lock* to synchronize access. If *lock* is ``None`` (the default) then a :class:`multiprocessing.RLock` object is created automatically. *ctx* is a context object, or ``None`` (use the current context). If ``None``, calling this may set the global start method. See :ref:`...
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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dabaa007-4d48-4185-8c2f-de72cec02891
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.. method:: accept() Accept a connection on the bound socket or named pipe of the listener object and return a :class:`~Connection` object. If authentication is attempted and fails, then :exc:`~multiprocessing.AuthenticationError` is raised.
trusted_official_docs
CPython Docs
.. method:: accept() Accept a connection on the bound socket or named pipe of the listener object and return a :class:`~Connection` object. If authentication is attempted and fails, then :exc:`~multiprocessing.AuthenticationError` is raised.
.. method:: accept() Accept a connection on the bound socket or named pipe of the listener object and return a :class:`~Connection` object. If authentication is attempted and fails, then :exc:`~multiprocessing.AuthenticationError` is raised.
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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supabase-export-v2
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management protocol -- see :ref:`typecontextmanager`. :meth:`~contextmanager.__enter__` starts the server process (if it has not already started) and then returns the manager object. :meth:`~contextmanager.__exit__` calls :meth:`shutdown`. In previous versions :meth:`~contextmanager.__enter__` did not start the manage...
trusted_official_docs
CPython Docs
management protocol -- see :ref:`typecontextmanager`. :meth:`~contextmanager.__enter__` starts the server process (if it has not already started) and then returns the manager object. :meth:`~contextmanager.__exit__` calls :meth:`shutdown`. In previous versions :meth:`~contextmanager.__enter__` did not start the manage...
management protocol -- see :ref:`typecontextmanager`. :meth:`~contextmanager.__enter__` starts the server process (if it has not already started) and then returns the manager object. :meth:`~contextmanager.__exit__` calls :meth:`shutdown`. In previous versions :meth:`~contextmanager.__enter__` did not start the manage...
python, official-docs, cpython, P0
Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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.. function:: wait(object_list, timeout=None) Wait till an object in *object_list* is ready. Returns the list of those objects in *object_list* which are ready. If *timeout* is a float then the call blocks for at most that many seconds. If *timeout* is ``None`` then it will block for an unlimited period. A negative ...
trusted_official_docs
CPython Docs
.. function:: wait(object_list, timeout=None) Wait till an object in *object_list* is ready. Returns the list of those objects in *object_list* which are ready. If *timeout* is a float then the call blocks for at most that many seconds. If *timeout* is ``None`` then it will block for an unlimited period. A negative ...
.. function:: wait(object_list, timeout=None) Wait till an object in *object_list* is ready. Returns the list of those objects in *object_list* which are ready. If *timeout* is a float then the call blocks for at most that many seconds. If *timeout* is ``None`` then it will block for an unlimited period. A negative ...
python, official-docs, cpython, P0
Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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dabaa007-4d48-4185-8c2f-de72cec02891
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supabase-export-v2
8c704510a70e7b74
to stderr, and ``"fail"`` causes the forkserver subprocess to exit with the exception traceback on stderr, making subsequent process creation fail with :exc:`EOFError` or :exc:`ConnectionError`. Only meaningful when using the ``'forkserver'`` start method. See :ref:`multiprocessing-start-methods`.
trusted_official_docs
CPython Docs
to stderr, and ``"fail"`` causes the forkserver subprocess to exit with the exception traceback on stderr, making subsequent process creation fail with :exc:`EOFError` or :exc:`ConnectionError`. Only meaningful when using the ``'forkserver'`` start method. See :ref:`multiprocessing-start-methods`.
to stderr, and ``"fail"`` causes the forkserver subprocess to exit with the exception traceback on stderr, making subsequent process creation fail with :exc:`EOFError` or :exc:`ConnectionError`. Only meaningful when using the ``'forkserver'`` start method. See :ref:`multiprocessing-start-methods`.
python, official-docs, cpython, P0
Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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.. doctest:: >>> import multiprocessing, time, signal >>> mp_context = multiprocessing.get_context('spawn') >>> p = mp_context.Process(target=time.sleep, args=(1000,)) >>> print(p, p.is_alive()) <...Process ... initial> False >>> p.start() >>> print(p, p.is_alive()) <...Process ... started> True >>> p.terminate...
trusted_official_docs
CPython Docs
.. doctest:: >>> import multiprocessing, time, signal >>> mp_context = multiprocessing.get_context('spawn') >>> p = mp_context.Process(target=time.sleep, args=(1000,)) >>> print(p, p.is_alive()) <...Process ... initial> False >>> p.start() >>> print(p, p.is_alive()) <...Process ... started> True >>> p.terminate...
.. doctest:: >>> import multiprocessing, time, signal >>> mp_context = multiprocessing.get_context('spawn') >>> p = mp_context.Process(target=time.sleep, args=(1000,)) >>> print(p, p.is_alive()) <...Process ... initial> False >>> p.start() >>> print(p, p.is_alive()) <...Process ... started> True >>> p.terminate...
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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Available on POSIX platforms which support passing file descriptors over Unix pipes such as Linux. The default on those. .. versionchanged:: 3.14 This became the default start method on POSIX platforms.
trusted_official_docs
CPython Docs
Available on POSIX platforms which support passing file descriptors over Unix pipes such as Linux. The default on those. .. versionchanged:: 3.14 This became the default start method on POSIX platforms.
Available on POSIX platforms which support passing file descriptors over Unix pipes such as Linux. The default on those. .. versionchanged:: 3.14 This became the default start method on POSIX platforms.
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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by :meth:`_callmethod`. If some other exception is raised in the manager's process then this is converted into a :exc:`RemoteError` exception and is raised by :meth:`_callmethod`. Note in particular that an exception will be raised if *methodname* has not been *exposed*.
trusted_official_docs
CPython Docs
by :meth:`_callmethod`. If some other exception is raised in the manager's process then this is converted into a :exc:`RemoteError` exception and is raised by :meth:`_callmethod`. Note in particular that an exception will be raised if *methodname* has not been *exposed*.
by :meth:`_callmethod`. If some other exception is raised in the manager's process then this is converted into a :exc:`RemoteError` exception and is raised by :meth:`_callmethod`. Note in particular that an exception will be raised if *methodname* has not been *exposed*.
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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supabase-export-v2
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Method representing the process's activity. You may override this method in a subclass. The standard :meth:`run` method invokes the callable object passed to the object's constructor as the target argument, if any, with sequential and keyword arguments taken from the *args* and *kwargs* arguments, respectively.
trusted_official_docs
CPython Docs
Method representing the process's activity. You may override this method in a subclass. The standard :meth:`run` method invokes the callable object passed to the object's constructor as the target argument, if any, with sequential and keyword arguments taken from the *args* and *kwargs* arguments, respectively.
Method representing the process's activity. You may override this method in a subclass. The standard :meth:`run` method invokes the callable object passed to the object's constructor as the target argument, if any, with sequential and keyword arguments taken from the *args* and *kwargs* arguments, respectively.
python, official-docs, cpython, P0
Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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on Windows child processes will only inherit the level of the parent process's logger -- any other customization of the logger will not be inherited. .. currentmodule:: multiprocessing .. function:: log_to_stderr(level=None)
trusted_official_docs
CPython Docs
on Windows child processes will only inherit the level of the parent process's logger -- any other customization of the logger will not be inherited. .. currentmodule:: multiprocessing .. function:: log_to_stderr(level=None)
on Windows child processes will only inherit the level of the parent process's logger -- any other customization of the logger will not be inherited. .. currentmodule:: multiprocessing .. function:: log_to_stderr(level=None)
python, official-docs, cpython, P0
Local_Trusted_Corpus
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CPython Docs
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.. function:: set_start_method(method, force=False) Set the method which should be used to start child processes. The *method* argument can be ``'fork'``, ``'spawn'`` or ``'forkserver'``. Raises :exc:`RuntimeError` if the start method has already been set and *force* is not ``True``. If *method* is ``None`` and *force...
trusted_official_docs
CPython Docs
.. function:: set_start_method(method, force=False) Set the method which should be used to start child processes. The *method* argument can be ``'fork'``, ``'spawn'`` or ``'forkserver'``. Raises :exc:`RuntimeError` if the start method has already been set and *force* is not ``True``. If *method* is ``None`` and *force...
.. function:: set_start_method(method, force=False) Set the method which should be used to start child processes. The *method* argument can be ``'fork'``, ``'spawn'`` or ``'forkserver'``. Raises :exc:`RuntimeError` if the start method has already been set and *force* is not ``True``. If *method* is ``None`` and *force...
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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.. method:: get([timeout]) Return the result when it arrives. If *timeout* is not ``None`` and the result does not arrive within *timeout* seconds then :exc:`multiprocessing.TimeoutError` is raised. If the remote call raised an exception then that exception will be reraised by :meth:`get`.
trusted_official_docs
CPython Docs
.. method:: get([timeout]) Return the result when it arrives. If *timeout* is not ``None`` and the result does not arrive within *timeout* seconds then :exc:`multiprocessing.TimeoutError` is raised. If the remote call raised an exception then that exception will be reraised by :meth:`get`.
.. method:: get([timeout]) Return the result when it arrives. If *timeout* is not ``None`` and the result does not arrive within *timeout* seconds then :exc:`multiprocessing.TimeoutError` is raised. If the remote call raised an exception then that exception will be reraised by :meth:`get`.
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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dabaa007-4d48-4185-8c2f-de72cec02891
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.. method:: recv() Return an object sent from the other end of the connection using :meth:`send`. Blocks until there is something to receive. Raises :exc:`EOFError` if there is nothing left to receive and the other end was closed.
trusted_official_docs
CPython Docs
.. method:: recv() Return an object sent from the other end of the connection using :meth:`send`. Blocks until there is something to receive. Raises :exc:`EOFError` if there is nothing left to receive and the other end was closed.
.. method:: recv() Return an object sent from the other end of the connection using :meth:`send`. Blocks until there is something to receive. Raises :exc:`EOFError` if there is nothing left to receive and the other end was closed.
python, official-docs, cpython, P0
Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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Like :meth:`~multiprocessing.pool.Pool.map` except that the elements of the *iterable* are expected to be iterables that are unpacked as arguments. Hence an *iterable* of ``[(1,2), (3, 4)]`` results in ``[func(1,2), func(3,4)]``.
trusted_official_docs
CPython Docs
Like :meth:`~multiprocessing.pool.Pool.map` except that the elements of the *iterable* are expected to be iterables that are unpacked as arguments. Hence an *iterable* of ``[(1,2), (3, 4)]`` results in ``[func(1,2), func(3,4)]``.
Like :meth:`~multiprocessing.pool.Pool.map` except that the elements of the *iterable* are expected to be iterables that are unpacked as arguments. Hence an *iterable* of ``[(1,2), (3, 4)]`` results in ``[func(1,2), func(3,4)]``.
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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.. module:: multiprocessing.managers :synopsis: Share data between process with shared objects. Manager processes will be shutdown as soon as they are garbage collected or their parent process exits. The manager classes are defined in the :mod:`multiprocessing.managers` module:
trusted_official_docs
CPython Docs
.. module:: multiprocessing.managers :synopsis: Share data between process with shared objects. Manager processes will be shutdown as soon as they are garbage collected or their parent process exits. The manager classes are defined in the :mod:`multiprocessing.managers` module:
.. module:: multiprocessing.managers :synopsis: Share data between process with shared objects. Manager processes will be shutdown as soon as they are garbage collected or their parent process exits. The manager classes are defined in the :mod:`multiprocessing.managers` module:
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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.. note:: Functionality within this package requires that the ``__main__`` module be importable by the children. This is covered in :ref:`multiprocessing-programming` however it is worth pointing out here. This means that some examples, such as the :class:`multiprocessing.pool.Pool` examples will not work in the in...
trusted_official_docs
CPython Docs
.. note:: Functionality within this package requires that the ``__main__`` module be importable by the children. This is covered in :ref:`multiprocessing-programming` however it is worth pointing out here. This means that some examples, such as the :class:`multiprocessing.pool.Pool` examples will not work in the in...
.. note:: Functionality within this package requires that the ``__main__`` module be importable by the children. This is covered in :ref:`multiprocessing-programming` however it is worth pointing out here. This means that some examples, such as the :class:`multiprocessing.pool.Pool` examples will not work in the in...
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Local_Trusted_Corpus
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CPython Docs
file://datasets/cpython/Doc/library/multiprocessing.rst
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def f(d, l, s): d[1] = '1' d['2'] = 2 d[0.25] = None l.reverse() s.add('a') s.add('b') if __name__ == '__main__': with Manager() as manager: d = manager.dict() l = manager.list(range(10)) s = manager.set()
trusted_official_docs
CPython Docs
def f(d, l, s): d[1] = '1' d['2'] = 2 d[0.25] = None l.reverse() s.add('a') s.add('b') if __name__ == '__main__': with Manager() as manager: d = manager.dict() l = manager.list(range(10)) s = manager.set()
def f(d, l, s): d[1] = '1' d['2'] = 2 d[0.25] = None l.reverse() s.add('a') s.add('b') if __name__ == '__main__': with Manager() as manager: d = manager.dict() l = manager.list(range(10)) s = manager.set()
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Send an object to the other end of the connection which should be read using :meth:`recv`. The object must be picklable. Very large pickles (approximately 32 MiB+, though it depends on the OS) may raise a :exc:`ValueError` exception.
trusted_official_docs
CPython Docs
Send an object to the other end of the connection which should be read using :meth:`recv`. The object must be picklable. Very large pickles (approximately 32 MiB+, though it depends on the OS) may raise a :exc:`ValueError` exception.
Send an object to the other end of the connection which should be read using :meth:`recv`. The object must be picklable. Very large pickles (approximately 32 MiB+, though it depends on the OS) may raise a :exc:`ValueError` exception.
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Local_Trusted_Corpus
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that the other knows the authentication key. (Demonstrating that both ends are using the same key does **not** involve sending the key over the connection.) If authentication is requested but no authentication key is specified then the return value of ``current_process().authkey`` is used (see :class:`~multiprocessing....
trusted_official_docs
CPython Docs
that the other knows the authentication key. (Demonstrating that both ends are using the same key does **not** involve sending the key over the connection.) If authentication is requested but no authentication key is specified then the return value of ``current_process().authkey`` is used (see :class:`~multiprocessing....
that the other knows the authentication key. (Demonstrating that both ends are using the same key does **not** involve sending the key over the connection.) If authentication is requested but no authentication key is specified then the return value of ``current_process().authkey`` is used (see :class:`~multiprocessing....
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multiple processes call :meth:`~io.IOBase.close` on this file-like object, it could result in the same data being flushed to the object multiple times, resulting in corruption. If you write a file-like object and implement your own caching, you can make it fork-safe by storing the pid whenever you append to the cache,...
trusted_official_docs
CPython Docs
multiple processes call :meth:`~io.IOBase.close` on this file-like object, it could result in the same data being flushed to the object multiple times, resulting in corruption. If you write a file-like object and implement your own caching, you can make it fork-safe by storing the pid whenever you append to the cache,...
multiple processes call :meth:`~io.IOBase.close` on this file-like object, it could result in the same data being flushed to the object multiple times, resulting in corruption. If you write a file-like object and implement your own caching, you can make it fork-safe by storing the pid whenever you append to the cache,...
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class Point(Structure): _fields_ = [('x', c_double), ('y', c_double)] def modify(n, x, s, A): n.value **= 2 x.value **= 2 s.value = s.value.upper() for a in A: a.x **= 2 a.y **= 2
trusted_official_docs
CPython Docs
class Point(Structure): _fields_ = [('x', c_double), ('y', c_double)] def modify(n, x, s, A): n.value **= 2 x.value **= 2 s.value = s.value.upper() for a in A: a.x **= 2 a.y **= 2
class Point(Structure): _fields_ = [('x', c_double), ('y', c_double)] def modify(n, x, s, A): n.value **= 2 x.value **= 2 s.value = s.value.upper() for a in A: a.x **= 2 a.y **= 2
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the message will be written into the buffer from that position. Offset must be a non-negative integer less than the length of *buf* (in bytes). If the buffer is too short then a :exc:`BufferTooShort` exception is raised and the complete message is available as ``e.args[0]`` where ``e`` is the exception instance.
trusted_official_docs
CPython Docs
the message will be written into the buffer from that position. Offset must be a non-negative integer less than the length of *buf* (in bytes). If the buffer is too short then a :exc:`BufferTooShort` exception is raised and the complete message is available as ``e.args[0]`` where ``e`` is the exception instance.
the message will be written into the buffer from that position. Offset must be a non-negative integer less than the length of *buf* (in bytes). If the buffer is too short then a :exc:`BufferTooShort` exception is raised and the complete message is available as ``e.args[0]`` where ``e`` is the exception instance.
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A variant of the :meth:`.map` method which returns a :class:`~multiprocessing.pool.AsyncResult` object. If *callback* is specified then it should be a callable which accepts a single argument. When the result becomes ready *callback* is applied to it, that is unless the call failed, in which case the *error_callback*...
trusted_official_docs
CPython Docs
A variant of the :meth:`.map` method which returns a :class:`~multiprocessing.pool.AsyncResult` object. If *callback* is specified then it should be a callable which accepts a single argument. When the result becomes ready *callback* is applied to it, that is unless the call failed, in which case the *error_callback*...
A variant of the :meth:`.map` method which returns a :class:`~multiprocessing.pool.AsyncResult` object. If *callback* is specified then it should be a callable which accepts a single argument. When the result becomes ready *callback* is applied to it, that is unless the call failed, in which case the *error_callback*...
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If *lock* is ``False`` then access to the returned object will not be automatically protected by a lock, so it will not necessarily be "process-safe". *ctx* is a context object, or ``None`` (use the current context). If ``None``, calling this may set the global start method. See :ref:`global-start-method` for more de...
trusted_official_docs
CPython Docs
If *lock* is ``False`` then access to the returned object will not be automatically protected by a lock, so it will not necessarily be "process-safe". *ctx* is a context object, or ``None`` (use the current context). If ``None``, calling this may set the global start method. See :ref:`global-start-method` for more de...
If *lock* is ``False`` then access to the returned object will not be automatically protected by a lock, so it will not necessarily be "process-safe". *ctx* is a context object, or ``None`` (use the current context). If ``None``, calling this may set the global start method. See :ref:`global-start-method` for more de...
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The process's name. The name is a string used for identification purposes only. It has no semantics. Multiple processes may be given the same name. The initial name is set by the constructor. If no explicit name is provided to the constructor, a name of the form 'Process-N\ :sub:`1`:N\ :sub:`2`:...:N\ :sub:`k`' is co...
trusted_official_docs
CPython Docs
The process's name. The name is a string used for identification purposes only. It has no semantics. Multiple processes may be given the same name. The initial name is set by the constructor. If no explicit name is provided to the constructor, a name of the form 'Process-N\ :sub:`1`:N\ :sub:`2`:...:N\ :sub:`k`' is co...
The process's name. The name is a string used for identification purposes only. It has no semantics. Multiple processes may be given the same name. The initial name is set by the constructor. If no explicit name is provided to the constructor, a name of the form 'Process-N\ :sub:`1`:N\ :sub:`2`:...:N\ :sub:`k`' is co...
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Proxy Objects ^^^^^^^^^^^^^ A proxy is an object which *refers* to a shared object which lives (presumably) in a different process. The shared object is said to be the *referent* of the proxy. Multiple proxy objects may have the same referent.
trusted_official_docs
CPython Docs
Proxy Objects ^^^^^^^^^^^^^ A proxy is an object which *refers* to a shared object which lives (presumably) in a different process. The shared object is said to be the *referent* of the proxy. Multiple proxy objects may have the same referent.
Proxy Objects ^^^^^^^^^^^^^ A proxy is an object which *refers* to a shared object which lives (presumably) in a different process. The shared object is said to be the *referent* of the proxy. Multiple proxy objects may have the same referent.
python, official-docs, cpython, P0
Local_Trusted_Corpus