Taxon is a package that provides storage and query capabilities to data organized by tags. It supports both in-process and Redis-backed storage options out of the box.
- Fully queryable. Supports expressions using
Notoperations as well as direct tag lookup.
- Versatile. Data sets can be kept in-process, or stored in Redis or any other engine through drop-in backends.
First install the taxon package with pip:
$ pip install -U redis-taxon
Then you can start tagging and querying your data:
import redis import taxon t = taxon.RedisTaxon()
To tag data, use the
tag method on any
The first argument is the tag to use, and the following variable arguments are the items to tag.
t.tag('feature', 'issue-312', 'issue-199', 'issue-321') t.tag('experimental', 'issue-199')
Taxon allows the dataset to be queried with arbitrary expressions and supports
The query syntax is a small DSL implemented directly in Python.
Most queries are issued with the
find method, which returns a set of items.
from taxon import RedisTaxon from taxon.query import And, Or, Not # get issue tracker items with no action required t = RedisTaxon() items = t.find(Or('invalid', 'closed', 'wontfix'))
Query expressions can also be arbitrarily complex.
Queries issued through the
query method return both the name of the Redis key and a list of items.
# get issue tracker items marked feature or bugfix, but not experimental _, items = t.query(And(Or('feature', 'bugfix'), Not('experimental')))
There is an alternate query syntax available using the
Tag member from
taxon.query which uses operators instead of classes.
The operators are
The above query in operator syntax looks like this:
from taxon.query import Tag items = t.find((Tag('feature') | Tag('bugfix')) & ~Tag('experimental'))
By implementing drop-in backends, there is greater flexibility in where data is stored.
Any object that implements the methods of
taxon.backends.Backend is a valid backend.
A backend is used by providing it as the first argument to a
from taxon import Taxon from taxon.backends import MemoryBackend t = Taxon(MemoryBackend())
from redis import Redis from taxon import Taxon from taxon.backends import RedisBackend t = Taxon(RedisBackend(Redis()), 'blog-posts')
You usually will not need to create Taxon instances like this though. There are convenience classes for using the memory and Redis backends:
from taxon import MemoryTaxon, RedisTaxon mt = MemoryTaxon() rt = RedisTaxon('redis://localhost:6379/0', 'blog-posts')
Copyright (c) 2012 Justin Poliey <firstname.lastname@example.org>
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