queue — A synchronized queue class¶
The queue module implements multi-producer, multi-consumer queues. It is especially useful in threaded programming when information must be exchanged safely between multiple threads. The Queue class in this module implements all the required locking semantics.
The module implements three types of queue, which differ only in the order in which the entries are retrieved. In a FIFO queue, the first tasks added are the first retrieved. In a LIFO queue, the most recently added entry is the first retrieved (operating like a stack). With a priority queue, the entries are kept sorted (using the heapq module) and the lowest valued entry is retrieved first.
Internally, those three types of queues use locks to temporarily block competing threads; however, they are not designed to handle reentrancy within a thread.
In addition, the module implements a “simple” FIFO queue type, SimpleQueue , whose specific implementation provides additional guarantees in exchange for the smaller functionality.
The queue module defines the following classes and exceptions:
class queue. Queue ( maxsize = 0 ) ¶
Constructor for a FIFO queue. maxsize is an integer that sets the upperbound limit on the number of items that can be placed in the queue. Insertion will block once this size has been reached, until queue items are consumed. If maxsize is less than or equal to zero, the queue size is infinite.
class queue. LifoQueue ( maxsize = 0 ) ¶
Constructor for a LIFO queue. maxsize is an integer that sets the upperbound limit on the number of items that can be placed in the queue. Insertion will block once this size has been reached, until queue items are consumed. If maxsize is less than or equal to zero, the queue size is infinite.
class queue. PriorityQueue ( maxsize = 0 ) ¶
Constructor for a priority queue. maxsize is an integer that sets the upperbound limit on the number of items that can be placed in the queue. Insertion will block once this size has been reached, until queue items are consumed. If maxsize is less than or equal to zero, the queue size is infinite.
The lowest valued entries are retrieved first (the lowest valued entry is the one that would be returned by min(entries) ). A typical pattern for entries is a tuple in the form: (priority_number, data) .
If the data elements are not comparable, the data can be wrapped in a class that ignores the data item and only compares the priority number:
from dataclasses import dataclass, field from typing import Any @dataclass(order=True) class PrioritizedItem: priority: int item: Any=field(compare=False)
Constructor for an unbounded FIFO queue. Simple queues lack advanced functionality such as task tracking.
Exception raised when non-blocking get() (or get_nowait() ) is called on a Queue object which is empty.
Exception raised when non-blocking put() (or put_nowait() ) is called on a Queue object which is full.
Queue Objects¶
Queue objects ( Queue , LifoQueue , or PriorityQueue ) provide the public methods described below.
Return the approximate size of the queue. Note, qsize() > 0 doesn’t guarantee that a subsequent get() will not block, nor will qsize() < maxsize guarantee that put() will not block.
Return True if the queue is empty, False otherwise. If empty() returns True it doesn’t guarantee that a subsequent call to put() will not block. Similarly, if empty() returns False it doesn’t guarantee that a subsequent call to get() will not block.
Return True if the queue is full, False otherwise. If full() returns True it doesn’t guarantee that a subsequent call to get() will not block. Similarly, if full() returns False it doesn’t guarantee that a subsequent call to put() will not block.
Queue. put ( item , block = True , timeout = None ) ¶
Put item into the queue. If optional args block is true and timeout is None (the default), block if necessary until a free slot is available. If timeout is a positive number, it blocks at most timeout seconds and raises the Full exception if no free slot was available within that time. Otherwise (block is false), put an item on the queue if a free slot is immediately available, else raise the Full exception (timeout is ignored in that case).
Equivalent to put(item, block=False) .
Queue. get ( block = True , timeout = None ) ¶
Remove and return an item from the queue. If optional args block is true and timeout is None (the default), block if necessary until an item is available. If timeout is a positive number, it blocks at most timeout seconds and raises the Empty exception if no item was available within that time. Otherwise (block is false), return an item if one is immediately available, else raise the Empty exception (timeout is ignored in that case).
Prior to 3.0 on POSIX systems, and for all versions on Windows, if block is true and timeout is None , this operation goes into an uninterruptible wait on an underlying lock. This means that no exceptions can occur, and in particular a SIGINT will not trigger a KeyboardInterrupt .
Two methods are offered to support tracking whether enqueued tasks have been fully processed by daemon consumer threads.
Indicate that a formerly enqueued task is complete. Used by queue consumer threads. For each get() used to fetch a task, a subsequent call to task_done() tells the queue that the processing on the task is complete.
If a join() is currently blocking, it will resume when all items have been processed (meaning that a task_done() call was received for every item that had been put() into the queue).
Raises a ValueError if called more times than there were items placed in the queue.
Blocks until all items in the queue have been gotten and processed.
The count of unfinished tasks goes up whenever an item is added to the queue. The count goes down whenever a consumer thread calls task_done() to indicate that the item was retrieved and all work on it is complete. When the count of unfinished tasks drops to zero, join() unblocks.
Example of how to wait for enqueued tasks to be completed:
import threading import queue q = queue.Queue() def worker(): while True: item = q.get() print(f'Working on item>') print(f'Finished item>') q.task_done() # Turn-on the worker thread. threading.Thread(target=worker, daemon=True).start() # Send thirty task requests to the worker. for item in range(30): q.put(item) # Block until all tasks are done. q.join() print('All work completed')
SimpleQueue Objects¶
SimpleQueue objects provide the public methods described below.
Return the approximate size of the queue. Note, qsize() > 0 doesn’t guarantee that a subsequent get() will not block.
Return True if the queue is empty, False otherwise. If empty() returns False it doesn’t guarantee that a subsequent call to get() will not block.
SimpleQueue. put ( item , block = True , timeout = None ) ¶
Put item into the queue. The method never blocks and always succeeds (except for potential low-level errors such as failure to allocate memory). The optional args block and timeout are ignored and only provided for compatibility with Queue.put() .
CPython implementation detail: This method has a C implementation which is reentrant. That is, a put() or get() call can be interrupted by another put() call in the same thread without deadlocking or corrupting internal state inside the queue. This makes it appropriate for use in destructors such as __del__ methods or weakref callbacks.
Equivalent to put(item, block=False) , provided for compatibility with Queue.put_nowait() .
SimpleQueue. get ( block = True , timeout = None ) ¶
Remove and return an item from the queue. If optional args block is true and timeout is None (the default), block if necessary until an item is available. If timeout is a positive number, it blocks at most timeout seconds and raises the Empty exception if no item was available within that time. Otherwise (block is false), return an item if one is immediately available, else raise the Empty exception (timeout is ignored in that case).
A queue class for use in a multi-processing (rather than multi-threading) context.
collections.deque is an alternative implementation of unbounded queues with fast atomic append() and popleft() operations that do not require locking and also support indexing.
pqueue 0.1.7
A single process, persistent multi-producer, multi-consumer queue.
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Лицензия: BSD License (BSD)
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pqueue is a simple persistent (disk-based) FIFO queue for Python.
pqueue goals are speed and simplicity. The development was initially based on the Queuelib code.
Requirements
Installation
You can install pqueue either via Python Package Index (PyPI) or from source.
To install using easy_install:
If you have downloaded a source tarball you can install it by running the following (as root):
How to use
pqueue provides a single FIFO queue implementation.
Here is an example usage of the FIFO queue:
>>> from pqueue import Queue >>> q = Queue("tmpqueue") >>> q.put(b'a') >>> q.put(b'b') >>> q.put(b'c') >>> q.get() b'a' >>> del q >>> q = Queue("tmpqueue") >>> q.get() b'b' >>> q.get() b'c' >>> q.get_nowait() Traceback (most recent call last): File "", line 1, in File "/usr/lib/python2.7/Queue.py", line 190, in get_nowait return self.get(False) File "/usr/lib/python2.7/Queue.py", line 165, in get raise Empty Queue.Empty The Queue object is identical to Python’s ‘Queue’ module (or ‘queue’ in Python 3.x), with the difference that it requires a parameter ‘path’ indicating where to persist the queue data and ‘chunksize’ indicating how many enqueued items should be stored per file. The same ‘maxsize’ parameter available on the system wise ‘Queue’ has been maintained.
In other words, it works exactly as Python’s Queue, with the difference any abrupt interruption is ACID-guaranteed:
q = Queue() def worker(): while True: item = q.get() do_work(item) q.task_done() for i in range(num_worker_threads): t = Thread(target=worker) t.daemon = True t.start() for item in source(): q.put(item) q.join() # block until all tasks are done
Note that pqueue is not intended to used by multiple processes.
How it works?
Pushed data is serialized using pickle in sequence, on chunked files named as qNNNNN, with a maximum of ‘chunksize’ elements, all stored on the given ‘path’.
The queue is formed by a ‘head’ and a ‘tail’. Pushed data goes on ‘head’, pulled data goes on ‘tail’.
An ‘info’ file is pickled in the ‘path’, having the following ‘dict’:
- ‘head’: a list of three integers, an index of the ‘head’ file, the number of elements written, and the file position of the last write.
- ‘tail’: a list of three integers, an index of the ‘tail’ file, the number of elements read, and the file position of the last read.
- ‘size’: number of elements in the queue.
- ‘chunksize’: number of elements that should be stored in each disk queue file.
Both read and write operations depend on sequential transactions on disk. In order to accomplish ACID requirements, these modifications are protected by the Queue locks.
If, for any reason, the application stops working in the middle of a head write, a second execution will remove any inconsistency by truncating the partial head write.
On ‘get’, the ‘info’ file is not updated, only when you first call ‘task_done’, and only on the first time case you have to call it sequentially.
The ‘info’ file is updated in the following way: a temporary file (using ‘mkstemp’) is created with the new data and then moved over the previous ‘info’ file. This was designed this way as POSIX ‘rename’ is guaranteed to be atomic.
In case of abrupt interruptions, one of the following conditions may happen:
- A partial write of the last pushed element may occur and in this case only this last element pushed will be discarded.
- An element pulled from the queue may be processing, and in this case a second run will consume same element again.
Tests
Tests are located in pqueue/tests directory. They can be run using Python’s default unittest module with the following command:
The output should be something like the following:
./runtests.py test_GarbageOnHead (pqueue.tests.test_queue.PersistenceTest) Adds garbage to the queue head and let the internal integrity . ok test_MultiThreaded (pqueue.tests.test_queue.PersistenceTest) Create consumer and producer threads, check parallelism . ok test_OpenCloseOneHundred (pqueue.tests.test_queue.PersistenceTest) Write 1000 items, close, reopen checking if all items are there . ok test_OpenCloseSingle (pqueue.tests.test_queue.PersistenceTest) Write 1 item, close, reopen checking if same item is there . ok test_PartialWrite (pqueue.tests.test_queue.PersistenceTest) Test recovery from previous crash w/ partial write . ok test_RandomReadWrite (pqueue.tests.test_queue.PersistenceTest) Test random read/write . ok ---------------------------------------------------------------------- Ran 6 tests in 1.301s OK
License
This software is licensed under the BSD License. See the LICENSE file in the top distribution directory for the full license text.