faas-cache-dict 0.2.1

A Python dictionary implementation designed to act as an in-memory cache for FaaS environments

faas-cache-dict

A fast thread-safe Python dictionary implementation designed to act as an in-memory RAM constrained LRU TTL cache dict for FaaS environments. Though it has many valuable use cases outside FaaS.

If used in a serverless FaaS environment then this package works best by supporting an existing caching strategy, as there is no guarantee that any in-memory data will persist between calls.

This package uses only core Python stdlib + objsize. This is a Pythonic dict implementation with all the typical methods working .get .keys .values .items len etc.

Background

This was originally designed to be a performant in-memory cache for AWS Lambda, preventing repeated invocations making "slow" network calls to a connected ElastiCache Redis cluster.

In most FaaS environments, successive quick invocations of the function persists variables in the global scope. We can leverage this to cache data in global for future calls.

FaaS runtimes have limited RAM capacities so this library allows you to set a max byte size for the cache dict. It also allows setting an optional max items length, and a TTL for each item.

Items are kept in order with the LRU at the HEAD of the list.

Items are deleted if they expire, or from the head (LRU) if the cache is out of space.

Expiry Dimensions

Several dimensions exist to constrain the longevity of the data the cache object stores. These can all be combined as your use case demands. You can also use none, if you so wish.

Memory size

A max memory (RAM) size the cache can use before it starts deleting the LRU values. This can be expressed in bytes (1024) or "human" format 1K (kibibyte). Supported "human" expressions are K, M, G, T.

cache = FaaSCacheDict(max_size_bytes='128M')
cache.change_byte_size('64M')  # If data is too large, LRU will be trimmed until it fits

cache.get_byte_size()  # Returns actual memory size of data and cache structure (bytes)

TTL

The number of *seconds* to hold a data point before making it unavailable and then later purging it. This can be sub-second by using float values. This can be configured as a default across the cache, or on a per key basis.

cache = FaaSCacheDict(default_ttl=60)  # Setting it to None (default) means no expiry

cache['key'] = 'value'  # Will expire in 60 seconds
cache.set_ttl('key', 120)  # Will now expire in 120 seconds from now
cache.get_ttl('key')
>>> 120
cache.set_ttl('key', None)  # Will now never expire

from datetime import time
cache.expire_at('key', time.time()) # Expire now, or a chosen time (epoch) in future

cache.default_ttl = 30  # Now all *new* keys will expire in 30 seconds by default
cache['another_key'] = 'value'  # Expires in 30 seconds as per new default

<Wait 31 seconds>

cache['another_key']
>>> KeyError  # Expired

cache.is_expired('another_key')
>>> True

LRU

A max list length constraint which deletes the least recently accessed item once the max size is reached.

cache = FaaSCacheDict(max_items=10)  # Setting it to None (default) means sys.maxsize
cache.change_max_items(5)  # If data is too large, LRU will be trimmed until it fits

Usage

Simple usage guide:

from faas_cache_dict import FaaSCacheDict

cache = FaaSCacheDict(default_ttl=10, max_size_bytes='128M', max_items=10)

cache['foo'] = 'bar'
print(cache)
>>> <FaaSCacheDict@0x10a9daec0; default_ttl=10, max_memory=128M, max_items=10, current_memory_bytes=496, current_items=1>

print(cache['foo'])
>>> 'bar'

(wait 10 seconds TTL)

print(cache['foo'])
>>> KeyError

Known limitations

• The cache itself consumes a minor amount of memory in overheads, so eg. 1K of requested memory will yield slightly less than 1K of available internal storage. The memory constraint applies to the whole cache object not just its contents.
• Due to extra overheads performance does slowly degrade with size (item count), you will need to test this for your situation. In 99% of use cases this will still be orders of magintude faster than doing network calls to an external cache.

Support

CPython 3.8 or greater.

Contributions

This code is distributed under an open license. Feel free to fork it or preferably open a PR.

Inspirations

Thanks to mobilityhouse/ttldict for their implementation which served as a proof of concept, which has since been much extended.