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The multiprocessing package offers both local and remote concurrency, effectively side-stepping the Global Interpreter Lock by using subprocesses instead of threads. Due to this, the multiprocessing module allows the programmer to fully leverage multiple processors on a given machine. It runs on both Unix and Windows. The multiprocessing module also introduces APIs which do not have analogs in the threading module.
A prime example of this is the Pool object which offers a convenient means of parallelizing the execution of a function across multiple input values, distributing the input data across processes data parallelism.
The following example demonstrates the common practice of defining such functions in a module so that child processes can successfully import that module. This basic example of data parallelism using Pool ,. In multiprocessing , processes are spawned by creating a Process object and then calling its start method.
Process follows the API of threading. A trivial example of a multiprocess program is. Depending on the platform, multiprocessing supports three ways to start a process. These start methods are. The parent process starts a fresh python interpreter process.
In particular, unnecessary file descriptors and handles from the parent process will not be inherited. Starting a process using this method is rather slow compared to using fork or forkserver. The parent process uses os. The child process, when it begins, is effectively identical to the parent process. All resources of the parent are inherited by the child process.
Note that safely forking a multithreaded process is problematic. When the program starts and selects the forkserver start method, a server process is started. 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 single threaded so it is safe for it to use os. No unnecessary resources are inherited. Changed in version 3.
The fork start method should be considered unsafe as it can lead to crashes of the subprocess. See bpo Child processes no longer inherit all of the parents inheritable handles on Windows.
On Unix using the spawn or forkserver start methods will also start a resource tracker process which tracks the unlinked named system resources such as named semaphores or SharedMemory objects created by processes of the program.
When all processes have exited the resource tracker unlinks any remaining tracked object. Neither leaked semaphores nor shared memory segments will be automatically unlinked until the next reboot. This is problematic 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. For example:.
Context objects have the same API as the multiprocessing module, and allow one to use multiple start methods in the same program. Note that objects related to one context may not be compatible with processes for a different context. In particular, locks created using the fork Class 10 Maths Ch 2 Pdf 40 context cannot be passed to processes started using the spawn or forkserver start methods. The 'fork' start method does work. The Queue class is a near clone of queue.
The Pipe function returns a pair of connection objects connected by a pipe which by default is duplex two-way. The two connection objects returned by Pipe represent the two ends of the pipe. Each connection object has send and recv methods among others. Note that data in a pipe may become corrupted if two processes or threads try to read from or write to the same end of the 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. For instance one can use a lock to ensure that only one process prints to standard output at a time:.
As mentioned above, when doing concurrent programming it is usually best to avoid using shared state as far as possible. This is particularly true when using multiple processes. However, if you really do need to use some shared data then multiprocessing provides a couple of ways of doing so. Data can be stored in a shared memory map using Value or Array. For example, the following code.
The 'd' and 'i' arguments used when creating num and arr are typecodes of the kind used by the array module: 'd' indicates a double precision float and 'i' indicates a signed integer. These shared objects will be process and thread-safe. For more flexibility in using shared memory one can use the multiprocessing. A manager object returned by Manager controls a server process which holds Python objects and allows other processes to manipulate them using proxies. For example,. Server process managers are more flexible than using shared memory objects because they can be made to support arbitrary object types.
Also, a single manager can be shared by processes on different computers over a network. They are, however, slower than using shared memory. The Pool class represents a pool of worker processes. It has methods which allows tasks to be offloaded to the worker processes in a few different ways. This is covered in Programming guidelines however it is worth pointing out here. This means that some examples, such as the multiprocessing.
Pool examples will not work in the interactive interpreter. If you try this it will actually output three full tracebacks interleaved in a semi-random fashion, and then you may have to stop the parent process somehow. The multiprocessing package mostly replicates the API of the threading module. Process objects represent activity that is run in a separate process. The Process class has equivalents of all the methods of threading. The constructor should always be called with keyword arguments.
It defaults to None , meaning nothing is called. If provided, the keyword-only daemon argument sets the process daemon flag to True or False. If None the default , this flag will be inherited from the creating process. If a subclass overrides the constructor, it must make sure it invokes the base class constructor Process. You may override this method in a subclass.
This must be called at most once per process object. If the optional argument timeout is None the default , the method blocks until the process whose join method is called terminates. If timeout is a positive number, it blocks at most timeout seconds. Note that the method returns None if its process terminates or if the method times out. A process cannot join itself because this would cause a deadlock.
It is an error to attempt to join a process before it has been started. 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. Roughly, a process object is alive from the moment the start method returns until the child process terminates.
This must be set before start is called. 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 services, they are normal processes that will be terminated and not joined if non-daemonic processes have exited. In addition to the threading. Thread API, Process objects also support the following attributes and methods:.
Return the process ID. Before the process is spawned, this will be None. This will be None if the process has not yet terminated. A negative value -N indicates that the child was terminated by signal N. When multiprocessing is initialized the main process is assigned a random string using os. When a Process object is created, it will inherit the authentication key of its parent process, although this may be changed by setting authkey to another byte string.
See Authentication keys. You can use this value if you want to wait on several events at once using multiprocessing.
Otherwise calling join is simpler. On Unix, this is a file descriptor usable with primitives from the select module. Terminate the process.


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