Using the built-in map function :

map(q.put, items)

It will apply q.put to all your items in your list. Useful one-liner.

For Python 3, you can use it as following :

list(map(q.put, items))

Or also :

from collections import deque
deque(map(q.put, items))

But at this point, the for loop is quite more readable.

Yes, use a tuple:

fruit = 'banana'
colour = 'yellow'
q.put((fruit, colour))

It will be automatically unpacked.

You can loop over a copy of the underlying data store:

for elem in list(q.queue)

Eventhough this bypasses the locks for Queue objects, the list copy is an atomic operation and it should work out fine.

If you want to keep the locks, why not pull all the tasks out of the queue, make your list copy, and then put them back.

mycopy = []
while True:
     try:
         elem = q.get(block=False)
     except Empty:
         break
     else:
         mycopy.append(elem)
for elem in mycopy:
    q.put(elem)
for elem in mycopy:
    # do something with the elements

If you're always pulling all available items off the queue, is there any real point in using a queue, rather than just a list with a lock? ie:

from __future__ import with_statement
import threading

class ItemStore(object):
    def __init__(self):
        self.lock = threading.Lock()
        self.items = []

    def add(self, item):
        with self.lock:
            self.items.append(item)

    def getAll(self):
        with self.lock:
            items, self.items = self.items, []
        return items

If you're also pulling them individually, and making use of the blocking behaviour for empty queues, then you should use Queue, but your use case looks much simpler, and might be better served by the above approach.

[Edit2] I'd missed the fact that you're polling the queue from an idle loop, and from your update, I see that the problem isn't related to contention, so the below approach isn't really relevant to your problem. I've left it in in case anyone finds a blocking variant of this useful:

For cases where you do want to block until you get at least one result, you can modify the above code to wait for data to become available through being signalled by the producer thread. Eg.

class ItemStore(object):
    def __init__(self):
        self.cond = threading.Condition()
        self.items = []

    def add(self, item):
        with self.cond:
            self.items.append(item)
            self.cond.notify() # Wake 1 thread waiting on cond (if any)

    def getAll(self, blocking=False):
        with self.cond:
            # If blocking is true, always return at least 1 item
            while blocking and len(self.items) == 0:
                self.cond.wait()
            items, self.items = self.items, []
        return items