Simple, distributed sorted sets with redis
Project description
You may not need heavyweights like Celery or RQ. Maintaing an AMQP server might be overkill. There’s a simpler, easier way to distribute work.
Redset provides simple, generic sorted sets backed by Redis that can be used to coordinate distributed systems and parcel out work. Unlike more common distribution libraries like Celery or RQ, redset avoids duplicate work for certain use-cases by maintaining a set of tasks instead of a list or queue. And it does so with a dead-simple interface that feels natural for Python.
Redset is currently used in the wild to do things like
maintain a high-throughput work queue of streaming updates to be processed
power a multi-producer, multi-consumer scraping architecture that won’t do the same work twice
maintain a simple, cross-process set of “seen” items that each have a TTL
schedule non-duplicate, periodic polling of analytics on social services
Features
No worker daemons to run, no heavy AMQP service to monitor
Safe for multiple producers and consumers
Seamless, simple use with Python objects using serializers
Zero dependencies: you provide an object that implements the redis.client.Redis interface, we don’t ask any questions.
Simple, easy-to-read implementation
Mimics Python’s native set interface
Battle-tested
Python 3 compatible
Simple example
import json
import redis
from redset import TimeSortedSet
r = redis.Redis()
ss = TimeSortedSet(r, 'important_json_biz', serializer=json)
ss.add({'foo': 'bar1'})
ss.add({'foo': 'bar2'})
ss.add({'foo': 'bar3'})
ss.add({'foo': 'bar3'})
len(ss)
# 3
# ...some other process A
ss.peek()
# {'foo': 'bar1'}
ss.pop()
# {'foo': 'bar1'}
# ...meanwhile in process B (at exactly same time as A's pop)
ss.take(2)
# [{'foo': 'bar2'}, {'foo': 'bar3'}]Docs
About
This software was developed at Percolate, where we use it for all sorts of things that involve maintaining synchronized sets of things across process boundaries. A common use-case is to use redset for coordinating time-sensitive tasks where duplicate requests may be generated.
Redset is unopinionated about how consumers look or behave. Want to have a plain ‘ol Python consumer managed by supervisor? Fine. Want to be able to pop off items from within a celery job? Great. Redset has no say in where or how it is used: mechanism, not policy.
Usage concepts
redset.SortedSet and its subclasses can be instantiated with a few paramters that are notable.
Specifying a serializer
Since Redis only stores primitive numbers and strings, handling serialization and deserialization is a key part of making redset set usage simple in Python.
A serializer instance can be passed (which adheres to the redset.interfaces.Serializer interface, though it need not subclass it) to automatically handle packing and unpacking items managed with redset.
Specifying a scorer
A callable that specifies how to generate a score for items being added can also be passed to SortedSet’s constructor as scorer. This callable takes one argument, which is the item object (i.e. the item before serialization) to be “scored.”
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