Queue.Queue vs. collections.deque

I need a queue which multiple threads can put stuff into, and multiple threads may read from.

Python has at least two queue classes, Queue.Queue and collections.deque, with the former seemingly using the latter internally. Both claim to be thread-safe in the documentation.

However, the Queue docs also state:

collections.deque is an alternative implementation of unbounded queues with fast atomic append() and popleft() operations that do not require locking.

Which I guess I don't quite unterstand: Does this mean deque isn't fully thread-safe after all?

If it is, I may not fully understand the difference between the two classes. I can see that Queue adds blocking functionality. On the other hand, it loses some deque features like support for the in-operator.

Accessing the internal deque object directly, is

x in Queue().deque

thread-safe?

Also, why does Queue employ a mutex for it's operations when deque is thread-safe already?

Queue.Queue and collections.deque serve different purposes. Queue.Queue is intended for allowing different threads to communicate using queued messages/data, whereas collections.deque is simply intended as a datastructure. That's why Queue.Queue has methods like put_nowait(), get_nowait(), and join(), whereas collections.deque doesn't. Queue.Queue isn't intended to be used as a collection, which is why it lacks the likes of the in operator.

It boils down to this: if you have multiple threads and you want them to be able to communicate without the need for locks, you're looking for Queue.Queue; if you just want a queue or a double-ended queue as a datastructure, use collections.deque.

Finally, accessing and manipulating the internal deque of a Queue.Queue is playing with fire - you really don't want to be doing that.

If all you're looking for is a thread-safe way to transfer objects between threads, then both would work (both for FIFO and LIFO). For FIFO:

• Queue.put() and Queue.get() are thread-safe
• deque.append() and deque.popleft() are thread-safe

Note:

• Other operations on deque might not be thread safe, I'm not sure.
• deque does not block on pop() or popleft() so you can't base your consumer thread flow on blocking till a new item arrives.

However, it seems that deque has a significant efficiency advantage. Here are some benchmark results in seconds using CPython 2.7.3 for inserting and removing 100k items

deque 0.0747888759791
Queue 1.60079066852

Here's the benchmark code:

import time
import Queue
import collections

q = collections.deque()
t0 = time.clock()
for i in xrange(100000):
    q.append(1)
for i in xrange(100000):
    q.popleft()
print 'deque', time.clock() - t0

q = Queue.Queue(200000)
t0 = time.clock()
for i in xrange(100000):
    q.put(1)
for i in xrange(100000):
    q.get()
print 'Queue', time.clock() - t0