Redis Tools
Project description
Redis Tools (retools)
retools is a package of Redis tools. It’s aim is to provide a variety of Redis backed Python tools that are always 100% unit tested, fast, efficient, and utilize the capabilities of Redis.
Current tools in retools:
Caching
Global Lock
On the horizon for future implementation:
A worker/job processing system similar to Celery but based on how Ruby’s Resque system works.
Caching
A high performance caching system that can act as a drop-in replacement for Beaker’s caching. Unlike Beaker’s caching, this utilizes Redis for distributed write-locking dogpile prevention. It also collects hit/miss cache statistics along with recording what regions are used by which functions and arguments.
Example:
from retools.cache import CacheRegion, cache_region, invalidate_function
CacheRegion.add_region('short_term', expires=3600)
@cache_region('short_term')
def slow_function(*search_terms):
# Do a bunch of work
return results
my_results = slow_function('bunny')
# Invalidate the cache for 'bunny'
invalidate_function(slow_function, [], 'bunny')
Differences from Beaker
Unlike Beaker’s caching system, this is built strictly for Redis. As such, it adds several features that Beaker doesn’t possess:
A distributed write-lock so that only one writer updates the cache at a time across a cluster.
Hit/Miss cache statistics to give you insight into what caches are less effectively utilized (and may need either higher expiration times, or just not very worthwhile to cache).
Very small, compact code-base with 100% unit test coverage.
Locking
A Redis based lock implemented as a Python context manager, based on Chris Lamb’s example.
Example:
from retools.lock import Lock
with Lock('a_key', expires=60, timeout=10):
# do something that should only be done one at a time
License
retools is offered under the MIT license.
retools
Next release
Job/Worker system based on Ruby’s Resque model.
0.1 (07/08/2011)
Features
Caching in a similar style to Beaker, with hit/miss statistics, backed by a Redis global write-lock with old values served to prevent the dogpile effect
Redis global lock
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