pylibmc VS django-cacheops

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).

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:

Here is an example of such thing https://github.com/Suor/django-cacheops/blob/8b3a79de29b2545...

django-cacheops is a great package https://github.com/Suor/django-cacheops

Nuts, I was hoping that this was an evolution of https://github.com/Suor/django-cacheops which uses Redis to cache and invalidate ORM result sets by an abstracted representation of filter values. It works, but has a lot of magic (as is the Django way) and takes some tending-to in production.

i came across this and this i am failing to understand what is the difference between the two and which is better.

The solution I recommend is setting up the caching backend using like redis then bringing in this awesome project django-cacheops! Takes 5 minutes to set up (literally) and you’re done!

We use django cacheops with redis and its incredible!