Queue.Queue vs. collections.deque

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 0.0747888759791Queue 1.60079066852

Here's the benchmark code:

import timeimport Queueimport collectionsq = collections.deque()t0 = time.clock()for i in xrange(100000):    q.append(1)for i in xrange(100000):    q.popleft()print 'deque', time.clock() - t0q = 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

For information there is a Python ticket referenced for deque thread-safety (https://bugs.python.org/issue15329).Title "clarify which deque methods are thread-safe"

Bottom line here: https://bugs.python.org/issue15329#msg199368

The deque's append(), appendleft(), pop(), popleft(), and len(d) operations are thread-safe in CPython. The append methods have a DECREF at the end (for cases where maxlen has been set), but this happens after all of the structure updates have been made and the invariants have been restored, so it is okay to treat these operations as atomic.

Anyway, if you are not 100% sure and you prefer reliability over performance, just put a like Lock ;)