There’s no doubt about how Python has been dominating the world of web and application development. It has given us millions of applications on the platforms we use and has been one of the most demanded technologies over the years. One of the main reasons for this is a very progressive aspect of Python, Python frameworks, and its in-house libraries that level up the programming game.
Frameworks make the developers’ job effortless. They offer a prospected structure of the application, automate the solutions, reduce development time, and aid developers to focus more on the application logic. With this blog post, we will take you through some of the best Python frameworks. By the end of the article, you will know which framework would add laurels to your professional journey. If you want to get into data science, check out our data science programs from top institutions.
Before starting with frameworks, let’s discuss the categories under which the different frameworks have been classified.
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Python Framework Categories
There are three main classes of frameworks on which different frameworks are tabulated.
1. Full-Stack Framework
A full-stack framework, also called an enterprise framework, is an all-in-one solution with configured libraries working together seamlessly. These frameworks are called full-stack because they support the overall front-end and back-end interfaces and databases. They provide everything a developer needs to build an app. They are used for bigger applications because of the existence of MVC (model-view-controller) architecture.
A microframework is a web application framework that works without a web template engine, authentication function, input validation, and database abstraction, which areis present in a full-fledged framework. A microframework provides what is necessary for an application. It requires minimal coding. But some microframeworks can extend the database or template engines and scale to a full-stack solution.
3. Asynchronous Framework
An asynchronous framework is a form of microframework that provisions to handle large sets of concurrent connections. They use non-blocking sockets and work on the async io library of Python. The core concept that these frameworks follow is that – one task can start running before the previous task is complete, and the app doesn’t need to execute tasks consequently.
Now, let’s move on to the top ten most efficient Python frameworks prominent from a programmer’s and development point of view.
Also Read: Python Project Ideas & Topics
List of Python Frameworks
Django is an open-source framework categorized under the full-stack framework category. It is a fast, scalable, and versatile framework and encompasses the properties of authorization, routing, template engine, object-relational mapper, and database schema migration.
The Django ORM maps objects to database tables. Django works with popular databases such as MySQL, Oracle, SQLite, PostgreSQL, and third-party drivers as well. Its feature to work flexibly as a full-stack allows it to scale from small to complex web applications and create useful MVPs. This is the best Python framework used for machine learning.
Flask is classified under the microframework category of Python Frameworks. It has gained the BSD license inspired by the Sinatra Ruby framework. Flask helps in developing a strong web application base and relies upon the Werkzeug WSGI toolbox and Jinja2 template.
It was crafted for open-ended applications and preferred for small scale projects. It has an in-built server and debugger for development and RESTful request dispatching as well as support for Google App Engine and unit testing. Flask is used by organizations such as LinkedIn and Pinterest.
Pyramid is one of those web application frameworks that work with minimum complexity. This framework can accommodate applications of any size and can be used to create complex applications when scaling a small application. It specifies the location of a packaged asset and makes use of predicates as well as renderers.
It also allows URL generation. The templating engine or database of this framework can be mutually swapped out. It also has XHR views and decorators with which you can send Ajax requests easily. It supports the SQLAlchemy database.
Bottle is categorized under the microframework category, used for building APIs. It takes just one source file to implement the code. Its scope is small as its name signifies ‘bottle’ and is useful for creating an application with up to 500 lines of code. It offers unique features such as routing, templating, and abstraction over the WSGI standard.
It is a perfect framework for prototyping and building personal apps. Bottle users can become a part of the Bottle mailing list, blog, and twitter for its latest updates. They can also contribute to the Bottle community via GitHub.
CherryPy is a quick and stable open-source Python web development framework employing its multi-hung server. CherryPy facilitates developers to develop web applications similar to other object-oriented Python programs with small source code in less time. It has all the capabilities such as session handling, file uploading, static content, cookies, encoding, caching, authentication, etc.
It runs various HTTP servers on multiple ports at once. It runs on Python 2.7+, 3.5+, PyPy, Jython, and Android. It has a robust configuration system for profiling and testing for developers as well as deployers during support.
Web2py is a cross-platform full-stack Python framework for a web application developed by Massimo De Pierro that follows an MVC architecture. Web2py framework has a code editor, debugger, and deployment tool useful for developing and debugging code, testing, and maintaining applications.
It also has a unique ticketing system that issues a ticket when an error occurs and also helps to track the status of the error. The framework has built-in components for handling HTTP requests, responses, cookies, and sessions. It can read multiple protocols and has data security against cross-site scripting, injection flaws, and infected file execution.
For the projects requiring the coding and development of REST APIs, Falcon framework is the go-to lightweight framework option as it has REST- oriented resource classes and intuitive routing. With Falcon, you can build apps with a clean design, and you need not load a lot of dependencies for building HTTP APIs.
What makes it unique is the Cython support it has which allows the programmer to write an extensible and highly-optimized codebase. It also has the provision of upfront exception handling and idiomatic HTTP error responses and supports unit testing with WSGI helpers and mocks.
FastAPI is a new Python micro-framework. It is one of the fastest frameworks used for building APIs with Python version 3.6+ to date. FastAPI is very simple, similar to Flask. Built with Starlette ASGI, it offers extensive features such as templates, WebSockets, as well as GraphQL support.
It is gaining significance in most industries because it has enhanced the web development speed three-fold and has given 40% fewer errors. The debugging time required is less, and it also supports automatic interactive documentation and the databases you require.
Ben Darnell and Bret Taylor originally developed the Tornado framework. It was first developed by a company named FriendFeed, later overtaken by Facebook. Tornado is an open-source framework and known for the high performance it offers.
It can handle 10,000+ connections at a time. Some of the main reasons organizations use this framework are the high output quality it offers and supports user authentication. It allows developers to implement third-party authentication such as Google and Twitter OpenID/OAuth, Yahoo BBAuth, and Facebook Login.
Dash is an open-source framework categorized under asynchronous frameworks. It is useful in creating highly interactive analytical web applications. Dash applications interact with JSON packets over HTTP requests and run Flask.
Its frontend render is coupled with React.js language. Dash applications are created on the web browser and deployed to servers. The applications developed with Dash are cross-platform and mobile-friendly. Dash developers gain full access to Flask Plugins to extend the Dash applications capabilities.
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Which Python Framework is the Best Choice for you?
Python is one of the major programming languages. Each Python framework has its own set of features and properties. It depends on the developers what coding styles and preferences they wish to adapt to a particular framework.
You can definitely find the perfect framework from these leading open-source Python frameworks for web application development. For successful project execution, all you need is picking the right framework.
We hope you’ve found this list of frameworks interesting. Python still has much more to offer. Some other worth-mentioning popular Python frameworks are TurboGears, hug, Sanic, Pylon, Giotto, CubicWeb, Growler, Pycnic, AIOHTTP, and many more.
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