retools 0.1
Redis Tools
Latest Version:
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_functionCacheRegion.add_region('short_term', expires=3600)@cache_region('short_term')def slow_function(*search_terms): # Do a bunch of work return resultsmy_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 .
Example:
from retools.lock import Lockwith Lock('a_key', expires=60, timeout=10): # do something that should only be done one at a time