retools 0.1 : Python Package Index

retools 0.1

Redis Tools

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Latest Version:
0.2

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