QR helps you create and work with queue, capped collection (bounded queue), deque, and stack data structures for Redis. Redis is well-suited for implementations of these abstract data structures, and QR makes it even easier to work with the structures in Python.
You will need:
Redis is available in many package managers by default, or built from source.
redis-py is available via setuptools or pip:
sudo pip install redis
Then install qr:
python setup.py install
QR queues store serialized Python objects (using cPickle by default), but that can be changed by setting the serializer on a per-queue basis. This means "Python object in, and Python object out." There are a few constraints on what can be pickled, and thus put into queues:
None,True, andFalse- Integers, long integers, floating point numbers, complex numbers
- Normal and Unicode strings
- Tuples, lists, sets, and dictionaries containing only picklable objects
- Functions defined at the top level of a module
- Built-in functions defined at the top level of a module
- Classes that are defined at the top level of a module
- Instances of such classes whose
__dict__or__setstate__()is picklable (see section 'The pickle protocol' for details)
You probably know this already, but here's the 20-second overview of these data structures.
A queue:
- You push elements to the back of the queue and pop elements from the front.
- With respect to the elements, it's first in, first out (FIFO).
A capped collection:
- Another name for (what is essentially) a bounded queue.
- You push elements to the back, and once a maximum collection size is reached, the oldest element(s) is trimmed.
A deque, or double-ended queue:
- You can push values to the front or back of a deque, and pop elements from the front or back of the deque.
A stack, or, as they say in German, a 'Stapelspeicher':
- You can push elements to the back of the stack and pop elements from the back of the stack.
- It's last in, first out (LIFO).
A priority queue
- Push elements into a priority queue with scores, and then retrieve the elements in order of their respective scores.
- Values stored in the priority queue are unique.
QR contains a few small classes to represent each data structure. To get access to one of the data structures, you create an instance. You can pass custom options for the underlying Redis instance as keyword arguments. For example:
Queue('brand_new_queue_name', host='localhost', port=9000)- A first-position key argument is required for all objects. It's the string name of the Redis key you want to be associated with the new data structure.
Let's create a Beatles queue, circa 1962.
>> from qr import Queue
>> bqueue = Queue('Beatles')
You are now the owner of a Queue object (bqueue), associated with the underlying Redis key 'Beatles'.
>> bqueue.push('Pete')
>> bqueue.push('John')
>> bqueue.push('Paul')
>> bqueue.push('George')
Unfortunately, George Martin doesn't like Pete Best, so it's time to pop him. Since Pete was first in:
>> bqueue.pop()
'Pete'
Ringo joins:
>> bqueue.push('Ringo')
We can return the elements from the queue. Each class in QR includes two return-style methods: elements and elements_as_json.
-
Call elements(), and you'll get back a Python list.
-
Call elements_as_json(), and you'll get back the list as a JSON object.
For example:
>> bqueue.elements()
['Ringo', 'George', 'Paul', 'John']
>> bqueue.elements_as_json()
'['Ringo', 'George', 'Paul', 'John']'
Radiohead is adding a band member. Radiohead has a max of five members, so someone is going to have to get kicked out of the band. We'll do this with a Capped Collection.
>> from qr import CappedCollection
>> radiohead_cc = CappedCollection('Radiohead', 5)
>> radiohead_cc.push('Ed')
>> radiohead_cc.push('Colin')
>> radiohead_cc.push('Thom')
>> radiohead_cc.push('Jonny')
>> radiohead_cc.push('Phil')
>> radiohead_cc.elements()
['Phil', 'Jonny', 'Thom', 'Colin', 'Ed']
Now it's time for Donald to join the group.
>> radiohead_cc.push('Donald')
And our new Radiohead is :
>> radiohead_cc.elements()
['Donald', 'Phil', 'Jonny', 'Thom', 'Colin']
If you wanted a deque for the Rolling Stones:
>> from qr import Deque
>> stones_deque = Deque('Stones')
The deque has different methods:
- push_front()
- push_back()
- pop_front()
- pop_back()
The Kinks stack is:
>> from qr import Stack
>> kinks_stack = Stack('Kinks')
The stack has the same methods as the queue.
Suppose you want to process various tasks in an order other than you received them. Instead you can base this processing on a score associated with each task. Maybe you want to process bands in the order of how many fans they have:
>> from qr import PriorityQueue
>> pr = PriorityQueue('bands')
>> pr.push('The Beatles', 1e7)
>> pr.push('Some Small Band', 1)
>> pr.push('They Might Be Giants', 1e6)
>> pr.pop()
'Some Small Band'
>> pr.pop()
'They Might Be Giants'
>> pr.pop()
'The Beatles'
It's important to note that items in the queue are sorted by a score in ascending order, meaning that the items with the least score is popped off first. Additionally, values stored in the priority queue are unique. So, if you insert the same value twice with different scores, the value will only appear once in the queue, with the second score provided:
>> pr.push('The Beatles', 1e7)
>> pr.push('The Beatles', 1.1e7)
>> len(pr)
1
>> # There's still only one copy of 'The Beatles'
>> pr.peek(withscores=True)
('The Beatles', 11000000.0)
In addition to the values themselves, the pop and peek commands also support the argument
withscores, which returns a tuple of the value and its score when set to True.
All queues have certain additional features. For example, you can add multiple elements at once:
>> from qr import Queue
>> q = Queue('widgets')
>> q.extend(['foo', 'bar', 'sprockets'])
You can also get the number of elements in the queue like you would from any normal Python list:
>> len(q)
3
You can also look up a particular element from the queue (or range of elements). Note carefully: in Redis, lists are linked lists, and so index lookups are O(n) to lookup the n'th position. Although this functionality available in qr, you should be careful looking up large indices. Looking at the front or back of the queue is cheap, though:
>> q[0]
'foo'
>> q[1:2]
['bar', 'sprockets']
>> q[-1]
'sprockets'
>> q.peek()
'foo'
You can also put most Python objects into queues, and you get the same object back when you pop it.
>> from widgets import Widget
>> from sprockets import Sprocket
>> q = Queue('work')
# Put a sproket, widget and string in the queue
>> q.extend([Sproket('foo'), Widget('bar'), 'Frank Sinatra'])
>> q.pop()
<sprocket.Sproket object>
>> q.pop()
<widget.Widget object>
>> q.pop()
'Frank Sinatra'
Thanks to mafr for initial tests and dlecocq/seomoz for serialization work.
Author: Ted Nyman | @tnm
Copyright (c) Ted Nyman
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