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Flask vs Hug: What are the differences?
Key Differences between Flask and Hug
Flask and Hug are two popular frameworks used for building web applications in Python. While they both serve similar purposes, there are key differences that set them apart.
Routing: Flask uses a decorator-based approach for routing, where specific functions are mapped to specific URLs. On the other hand, Hug uses explicit syntax for routing, allowing developers to define routes using Pythonic syntax with more control and flexibility.
Performance: Hug is designed to be highly performant, with built-in optimizations that make it faster than Flask in certain scenarios. Hug achieves this by utilizing a compiled version of code and leveraging Cython for speed. Flask, on the other hand, does not have these performance optimizations by default.
API Generation: Hug's main focus is on building APIs, and it provides a straightforward way to generate API documentation automatically. It includes features like automatic serialization of responses and clean error handling. Flask, on the other hand, is a more general-purpose framework and does not have these built-in features specifically tailored for API development.
Scalability: Flask is a lightweight framework that allows developers to cherry-pick the components they need for their applications. This flexibility makes it easier to build small to medium-sized applications. Hug, on the other hand, is built with scalability in mind, making it suitable for larger applications that require high performance and extensive APIs.
Community and Ecosystem: Flask has a larger and more mature community and ecosystem compared to Hug. It has been around for a longer time and has a wider range of third-party libraries and extensions available. This means that Flask users have access to a larger pool of resources, tutorials, and community support. Hug, being a relatively newer framework, has a smaller community and ecosystem in comparison.
Learning Curve: Flask is known for its simplicity and ease of use, making it a great choice for beginners or those who prefer a minimalistic approach. Hug, on the other hand, has a steeper learning curve due to its more advanced features and explicit syntax. It may require more time and effort to grasp the full capabilities of Hug compared to Flask.
In summary, Flask and Hug are both capable frameworks for building web applications in Python, but they differ in terms of routing approach, performance, API generation features, scalability, community and ecosystem size, and learning curve. Choose Flask for simplicity and ease of use, or opt for Hug for high performance, advanced API features, and scalability.
Hey! So I am planning to make an e-commerce website with React Native as my frontend technology stack and MongoDB as my database. I was wondering what will be the best REST framework to use for my backend that will simply serve the frontend. Is Django rest framework a good option or should I go with Flask? I am currently leaning towards flask as the development team is well versed in it. Please help!
If the application is simple such as less endpoint or simple logic, I'd suggest Flask. But what you're building is quite a large system that contains many logics and a lot of models. So I'd suggest you with Django and Django REST framework. Django ORM is also one of the best ORM in the world as well.
FastAPI is modern microframework. If you haven't used any of them, I'd suggest FastAPI. Django REST is also good if you have previous experience with it.
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.
We decided to expose our small machine learning (ML) pipeline as a REST API. This allows us to nicely separate concerns from the rest of the codebase. There are two very popular choices in Python for building APIs: Flask and FastAPI. We have experience with both, but find that FastAPIs use of static type hints and validation with Pydantic allow us to build better APIs faster.
Pros of Flask
- For it flexibility10
- Flexibilty and easy to use9
- Flask8
- User friendly7
- Secured6
- Unopinionated5
- Secure2
- Customizable1
- Simple to use1
- Powerful1
- Rapid development1
- Beautiful code1
- Easy to develop and maintain applications1
- Easy to setup and get it going1
- Easy to use1
- Documentation1
- Python1
- Minimal1
- Lightweight1
- Easy to get started1
- Orm1
- Not JS1
- Perfect for small to large projects with superb docs.1
- Easy to integrate1
- Speed1
- Get started quickly1
- Open source0
- Well designed0
- Flexibilty0
- Productive0
- Awesome0
- Expressive0
- Love it0
Pros of Hug
- Simple4
- Self documenting2
- REST2
- Fast2
- Elegant2
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Cons of Flask
- Not JS10
- Context7
- Not fast5
- Don't has many module as in spring1
Cons of Hug
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