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Advice on Flask and Streamlit
kristan-dev
Senior Solutions Analyst · | 8 upvotes · 155.8K views

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?

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Rafael Torres
Technical Lead at 4Agile · | 9 upvotes · 146.6K views

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.

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Girish Sharma
Software Engineer at FireVisor Systems · | 6 upvotes · 119.3K views
Needs advice
on
NamekoNamekoFlaskFlask
and
BottleBottle

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.

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Recommends
BottleBottle

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.

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Saurav Pandit
Application Devloper at Bny Mellon · | 5 upvotes · 118.9K views

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.

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Recommends
FlaskFlask
at

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.

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Pros of Flask
Pros of Streamlit
  • 313
    Lightweight
  • 269
    Python
  • 214
    Minimal
  • 145
    Open source
  • 98
    Documentation
  • 66
    Easy to use
  • 54
    Easy to setup and get it going
  • 53
    Well designed
  • 48
    Easy to develop and maintain applications
  • 45
    Easy to get started
  • 18
    Beautiful code
  • 16
    Rapid development
  • 14
    Powerful
  • 13
    Expressive
  • 12
    Awesome
  • 11
    Love it
  • 11
    Flexibilty
  • 11
    Speed
  • 10
    Get started quickly
  • 10
    Simple to use
  • 10
    Easy to integrate
  • 9
    Perfect for small to large projects with superb docs.
  • 9
    For it flexibility
  • 9
    Customizable
  • 8
    Productive
  • 8
    Flexibilty and easy to use
  • 7
    Flask
  • 6
    Not JS
  • 6
    User friendly
  • 5
    Secured
  • 4
    Unopinionated
  • 1
    Secure
  • 1
    Orm
  • 4
    Fast development

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Cons of Flask
Cons of Streamlit
  • 10
    Not JS
  • 7
    Context
  • 4
    Not fast
  • 1
    Don't has many module as in spring
    Be the first to leave a con

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    What is Flask?

    Flask is intended for getting started very quickly and was developed with best intentions in mind.

    What is Streamlit?

    It is the app framework specifically for Machine Learning and Data Science teams. You can rapidly build the tools you need. Build apps in a dozen lines of Python with a simple API.

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    What are some alternatives to Flask and Streamlit?
    Django
    Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design.
    Tornado
    By using non-blocking network I/O, Tornado can scale to tens of thousands of open connections, making it ideal for long polling, WebSockets, and other applications that require a long-lived connection to each user.
    ExpressJS
    Express is a minimal and flexible node.js web application framework, providing a robust set of features for building single and multi-page, and hybrid web applications.
    Node.js
    Node.js uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, perfect for data-intensive real-time applications that run across distributed devices.
    React
    Lots of people use React as the V in MVC. Since React makes no assumptions about the rest of your technology stack, it's easy to try it out on a small feature in an existing project.
    See all alternatives