django-heroku-memcacheify
Automatic Django memcached configuration on Heroku. (by rdegges)
pylibmc
A Python wrapper around the libmemcached interface from TangentOrg. (by lericson)
| django-heroku-memcacheify | pylibmc | |
|---|---|---|
| 1 | 2 | |
| 100 | 477 | |
| - | - | |
| 0.0 | 4.6 | |
| over 2 years ago | 7 months ago | |
| Python | C | |
| The Unlicense | BSD 3-clause "New" or "Revised" License |
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.
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.
django-heroku-memcacheify
Posts with mentions or reviews of django-heroku-memcacheify.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-11.
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Memcached on Heroku w/ Django : can't install pylibmc / memcacheify
I've spent a lot of time on this and it's clearly beyond my newbie understanding/skills. I tried to install django-heroku-memcacheify with pip install, which throws errors. I tracked the problem down to pylibmc, which is causing all the problems. Here's one of the interesting parts of the error log:
pylibmc
Posts with mentions or reviews of pylibmc.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-11.
-
Improving distributed caching performance and efficiency at Pinterest
I do hope Pinterest would fund memcached development going forward, especially the language clients for memcached. I've been using pylibmc to access memcached fast, and that project seems to be almost dead (https://github.com/lericson/pylibmc/issues).
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Memcached on Heroku w/ Django : can't install pylibmc / memcacheify
I've spent a lot of time on this and it's clearly beyond my newbie understanding/skills. I tried to install django-heroku-memcacheify with pip install, which throws errors. I tracked the problem down to pylibmc, which is causing all the problems. Here's one of the interesting parts of the error log:
What are some alternatives?
When comparing django-heroku-memcacheify and pylibmc you can also consider the following projects:
django-haystack - Modular search for Django
DiskCache - Python disk-backed cache (Django-compatible). Faster than Redis and Memcached. Pure-Python.
Beaker - WSGI middleware for sessions and caching
johnny-cache - johnny cache django caching framework
HermesCache
django-cacheops - A slick ORM cache with automatic granular event-driven invalidation.
dogpile.cache
cashier - Persistent caching for python functions
django-cache-machine - Automatic caching and invalidation for Django models through the ORM.
django-viewlet - Render template parts with extended cache control.
Cachier - Persistent, stale-free, local and cross-machine caching for Python functions.
cachetools - Extensible memoizing collections and decorators
django-heroku-memcacheify vs django-haystack
pylibmc vs DiskCache
pylibmc vs Beaker
pylibmc vs johnny-cache
pylibmc vs HermesCache
pylibmc vs django-cacheops
pylibmc vs dogpile.cache
pylibmc vs cashier
pylibmc vs django-cache-machine
pylibmc vs django-viewlet
pylibmc vs Cachier
pylibmc vs cachetools