pottery VS memoize

Compare pottery vs memoize and see what are their differences.

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pottery memoize
5 1
1,013 64
- -
7.2 6.2
about 1 month ago 6 days ago
Python Python
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

pottery

Posts with mentions or reviews of pottery. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-24.

memoize

Posts with mentions or reviews of memoize. We have used some of these posts to build our list of alternatives and similar projects.
  • Good and Bad Elixir
    1 project | news.ycombinator.com | 10 Jun 2021
    I totally agree, though I think those articles are a lot harder (eg requiring more skill) to write well because you need to quickly ramp your readers on all of whatever the context is that's necessary to actually appreciate the nuance of the design decisions under discussion. You're basically by definitely going to be out of the realm of "just follow best practice X" or "apply pattern Y or you're doing it wrong."

    As a small example, I've been working on a small asyncio-based web service (Python) which is oriented around an expensive process that generates a result, where the result is stashed in sqlite and returned. I knew upfront that I needed a way to track when a particular result was already being prepared so that if I got a second request for it, it would collapse it into the first one and only do the work once. I wrote this as a twenty line memoizing decorator, but it turns out this issue as a name— cache stampeding. Once I realized that, I discovered that there are existing (and much more complicated/tunable) solutions to this problem, such as https://github.com/DreamLab/memoize/, but the article pitching that solution spends quite a bit of time getting to it— enough so that if I'd discovered it before building my own, I'm not sure I would even have appreciated its applicability:

    https://tech.ringieraxelspringer.com/blog/open-source/cachin...

What are some alternatives?

When comparing pottery and memoize you can also consider the following projects:

fastapi-redis-cache - A simple and robust caching solution for FastAPI that interprets request header values and creates proper response header values (powered by Redis)

httpx-cache - Simple caching transport for httpx

aioredis - asyncio (PEP 3156) Redis support

Tornado-SQLAlchemy - SQLAlchemy support for Tornado

redsync - Distributed mutual exclusion lock using Redis for Go

webssh - :seedling: Web based ssh client

RPA-Python - Python package for doing RPA

turbo - A framework based on tornado for easier development, scaling up and maintenance

Redisson - Redisson - Easy Redis Java client and Real-Time Data Platform. Sync/Async/RxJava/Reactive API. Over 50 Redis based Java objects and services: Set, Multimap, SortedSet, Map, List, Queue, Deque, Semaphore, Lock, AtomicLong, Map Reduce, Bloom filter, Spring Cache, Tomcat, Scheduler, JCache API, Hibernate, RPC, local cache ...

fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production

reloadium - Hot Reloading and Profiling for Python

cacheme - Asyncio cache framework for Python