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
And,Or, andNotoperations 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 taxon.Taxon object.
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 And, Or, and Not operations.
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 & for And, | for Or, and ~ for Not.
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 Taxon constructor:
from taxon import Taxon from taxon.backends import MemoryBackend t = Taxon(MemoryBackend())
The MemoryBackend is the in-process storage option.
When your program ends, the data is lost.
The bundled persistence option is the Redis backend, which accepts Redis instances from redis-py:
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 <[email protected]>
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