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Flask vs Graphene: What are the differences?
Developers describe Flask as "a microframework for Python based on Werkzeug, Jinja 2 and good intentions". Flask is intended for getting started very quickly and was developed with best intentions in mind. On the other hand, Graphene is detailed as "GraphQL framework for Python". Graphene is a Python library for building GraphQL schemas/types fast and easily.
Flask belongs to "Microframeworks (Backend)" category of the tech stack, while Graphene can be primarily classified under "Query Languages".
Flask and Graphene are both open source tools. It seems that Flask with 44.8K GitHub stars and 12.6K forks on GitHub has more adoption than Graphene with 4.64K GitHub stars and 494 GitHub forks.
Netflix, AdRoll, and Keen are some of the popular companies that use Flask, whereas Graphene is used by A Color Bright, Advance.Careers, and flatfox. Flask has a broader approval, being mentioned in 502 company stacks & 509 developers stacks; compared to Graphene, which is listed in 11 company stacks and 5 developer stacks.
My journey to developing REST APIs started with Flask Restful, and I've found it to be enough for the needs of my project back then. Now that I've started investing more time on personal projects, I've yet to decide if I should move to use Django for writing REST APIs. I often see job posts looking for Python+Django developers, but it's usually for full-stack developers. I'm primarily interested in Data Engineering, so most of my web projects are back end.
Should I continue with what I know (Flask) or move on to Django?
If you want to be a Web developer with knowledge in another frontend and NoSql technology, maybe continue with Flask. However, if you want to create very fast solutions to grow up with a new business and merge these with data analysis and other tools, Django is the answer. Basically read more about the service architecture where you feel more comfortable, Microservice or Monolithic, but please will not married with any because they solve issues to different contexts.
Which is the best Python framework for microservices?
We are using Nameko for building microservices in Python. The things we really like are dependency injection and the ease with which one can expose endpoints via RPC over RabbitMQ. We are planning to try a tool that helps us write polyglot microservices and nameko is not super compatible with it. Also, we are a bit worried about the not so good community support from nameko and looking for a python alternate to write microservices.
Bottle is much less bloated and fast. Its built-in templating system is one of the fastest as it compiles the templates in bytecode. Also Bottle has no depenencies, preventing dependency bloat.
I have just started learning Python 3 weeks ago. I want to create a REST API using python. The API will be used to save form data in an Oracle database. The front end is using AngularJS 8 with Angular Material. In python, there are so many frameworks to develop REST APIs.
I am looking for some suggestions which REST framework to choose?
Here are some features I am looking for:
Easy integration and unit testing, like in Angular. We just want to run a command.
Code packaging, like in java maven project we can build and package. I am looking for something which I can push in as an artifact and deploy whole code as a package.
Support for swagger/ OpenAPI
Support for JSON Web Token
Support for test case coverage report
Framework can have features included or can be available by extension. Also, you can suggest a framework other than the ones I have mentioned.
For starters flask provides a beautiful and easy way to create REST APIs. Also its supported by excellent beginner docs as well as a very active community. Another good thing with Flask is its widely available list of plugins which allow you to build as you go. Its also good in performance and can scale to a quite decent level. However, if you are sure your project is going to be fairly big, it would be better to start with Django as it provides a lot of features out of the box and is extremely stable in performance. Both these frameworks have support for Swagger, JWT, Coverage Report although you have to install plugins for them. Deploying both of these are fairly simple and there is huge documentation available. Django has one of the best documentations I have come across. I hope I was able to answer your queries.
Pros of Flask
- Flexibilty14
- For it flexibility10
- Flexibilty and easy to use9
- Flask8
- User friendly7
- Secured6
- Unopinionated5
- Orm3
- Secure2
- Beautiful code1
- Easy to get started1
- Easy to develop and maintain applications1
- Not JS1
- Easy to use1
- Documentation1
- Python1
- Minimal1
- Lightweight1
- Easy to setup and get it going1
- Perfect for small to large projects with superb docs.1
- Easy to integrate1
- Speed1
- Get started quickly1
- Customizable1
- Simple to use1
- Powerful1
- Rapid development1
- Open source0
- Well designed0
- Productive0
- Awesome0
- Expressive0
- Love it0
Pros of Graphene
- Will replace RESTful interfaces0
- The future of API's0
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Cons of Flask
- Not JS10
- Context7
- Not fast5
- Don't has many module as in spring1
Cons of Graphene
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