A single process, persistent multi-producer, multi-consumer queue.

## Project description

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

• Python 2.7 or Python 3.3

• no external libraries requirements

## Installation

You can install pqueue either via Python Package Index (PyPI) or from source.

To install using pip:

$pip install pqueue To install using easy_install:$ easy_install pqueue

If you have downloaded a source tarball you can install it by running the following (as root):

# python setup.py install

## 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.pop()
b'a'
>>> del q
>>> q = Queue("tmpqueue")
>>> q.get()
b'b'
>>> q.get()
b'c'
>>> q.get_nowait()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
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:

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:

./runtests.py

The output should be something like the following:

./runtests.py
Create consumer and producer threads, check parallelism ... ok
test_OpenCloseOneHundred (pqueue.tests.test_queue.TestSuite_PersistenceTest)
Write 1000 items, close, reopen checking if all items are there ... ok
test_OpenCloseSingle (pqueue.tests.test_queue.TestSuite_PersistenceTest)
Write 1 item, close, reopen checking if same item is there ... ok
test_PartialWrite (pqueue.tests.test_queue.TestSuite_PersistenceTest)
Test recovery from previous crash w/ partial write ... ok

----------------------------------------------------------------------
Ran 5 tests in 4.615s

OK

## Versioning

This software follows Semantic Versioning