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:
- 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.
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.
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')
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.
A Redis based lock implemented as a Python context manager, based on Chris Lamb's 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
retools is offered under the MIT license.
retools is made available by Ben Bangert.