What is Graphene?
Who uses Graphene?
Why developers like Graphene?
Here are some stack decisions, common use cases and reviews by companies and developers who chose Graphene in their tech stack.
We recently switched from MongoDB and the Python library MongoEngine to PostgreSQL and Django in order to:
- Better leverage GraphQL (using the Graphene library)
- Allow us to use the autogenerated Django admin interface
- Allow better performance due to the way some of our pages present data
- Give us more a mature stack in the form of Django replacing MongoEngine, which we had some issues with in the past.
MongoDB was hosted on mlab, and we now host Postgres on Amazon RDS .
We recently implemented GraphQL because we needed to build dynamic reports based on the user preference and configuration, this was extremely complicated with our actual RESTful API, the code started to get harder to maintain but switching to GraphQL helped us to to build beautiful reports for our clients that truly help them make data-driven decisions.
Our goal is to implemented GraphQL in the whole platform eventually, we are using Graphene , a python library for Django .
I've been using Django for quite a long time and in my opinion I would never switch from it. My company is currently using Django with REST framework and a part in GraphQL using Graphene. On the frontend we use Next.js and so far everything has been running quite good. I've found limitations but manage to solve it.
As someone mentioned before, if you are comfortable with Django, don't switch. There's no need since with django you can basically achieve anything. Of course this will depend on the project you want to build, but the scalability and flexibility django can offer it's just out of this world. (Don't want to sound like a fan boy haha but it really is).
- Easy to use: Graphene helps you use GraphQL in Python without effort.
- Relay: Graphene has builtin support for Relay
- Django: Automatic Django model mapping to Graphene Types. Check a fully working Django implementation