redset 0.5.1

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

Here

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.

Related projects

• redis-py

• celery

• RQ