Top 8 Python Frameworks

Sakshi GuptaSakshi Gupta | 5 minute read | June 11, 2020

With the surging popularity of the Python programming language, many Python frameworks are being developed or upgraded to allow greater customisation and work efficiency. By providing a structure for app development and automating the implementation of common solutions, frameworks allow developers to concentrate more on the logic of the application. There are mainly three types of frameworks i.e. full-stack framework, microframework and asynchronous framework. Let’s have a look at some of the best frameworks from each of these types in no particular order.

Best Python Frameworks:

Take a look at this list to know more.

1. Python Frameworks: Django

Django is one of the most popular full-stack Python frameworks that is free and open-source. With the tagline “the web framework for perfectionists with deadlines”, Django lives up to its claims. Django follows an MVT (Model-View-Template) architecture and is loaded with impressive features that make it extremely fast and versatile. This ‘batteries included’ framework significantly simplifies the backend development process and allows you to build high-performing web applications in much less time. Features like URL routing, template engine, authentication, database schema migration and object-relational mapper (ORM) make Django highly flexible, incredibly fast and extremely scalable. Another major advantage of using Django is that it comes with many security features such as XSS protection, cross site request forgery (CSRF) prevention, SQL injection protection, clickjacking protection etc., which are applied automatically. With all these features, Django forms an excellent choice for building anything from small-scale web applications to complex websites as well as for emerging technologies such as AI and machine learning. You can read about Top 6 Python Libraries for AI and Machine Learning in this blog.

2. Flask

Unlike Django, Flask is a micro-framework that depends on the Jinja2 template and Werkzeug WSGI toolkit. Flask is a popular choice for developers who seek the freedom to choose the components of their choice. The lightweight and modular design of the web framework makes it easily adaptable to the developers’ requirements. It can be used to build a solid web application foundation, from where any extension can be used as per the need. Flask offers many noteworthy features such as built-in fast debugger and development server, RESTful request dispatching, integrated support for unit testing, ability to plug in any ORM, HTTP request handling, Unicode-enabled, WSGI 1.0 compliance, Jinja2 templating and secure cookies support to establish client-side sessions.

3. Python Frameworks: Bottle

Bottle is another popular micro-framework that was originally developed for building APIs. It is a simple, lightweight and fast WSGI framework for small web-applications and creates a single source file for every application developed using it. The framework has no dependencies other than Python Standard Library. With features such as built-in HTTP server, plugin support for different databases, adapter support for third-party template engines and WSGI/HTTP servers and simple access from data, cookies, file uploads and other HTTP-related metadata, Bottle is a good option for building simple apps and prototyping.

4. TurboGears

TurboGears is a full-stack web application framework and is open-source. This web framework is used for developing extensible data-driven web applications and is ideal for enterprise app development. It offers a combination of Ming (MongoDB Model) or SQLAlchemy (Model), Repoze, Kajiki (View) and ToscaWidgets2 which allow you to easily build apps requiring database connectivity. Another advantage of using this framework is that it has the ability to start as a single file app via its minimal mode setup or scale to a full stack solution for complex applications by using TurboGears devtools, giving you the flexibility to scale according to your needs. TurboGears uses a powerful ORM which is more capable than Django’s ORM and offers multi-database support. It comes with designer friendly templating and easy AJAX on the browser and server side. In nutshell, TurboGears is a mature and robust framework which is a great choice for developers.

Get To Know Other Data Science Students

Jonathan King

Jonathan King

Sr. Healthcare Analyst at IBM

Read Story

Garrick Chu

Garrick Chu

Contract Data Engineer at Meta

Read Story

Ginny Zhu

Ginny Zhu

Data Science Intern at Novartis

Read Story

5. Python Frameworks: Web2py

Another full-stack framework, Web2py was released in 2007 with the aim to make web development easy and accessible to all. As a result, it has no project-level configuration files, doesn’t require installation and can be run off a USB drive. Web2py comes with its own web-based IDE that includes code editor, debugger and one-click deployment. The framework has a built-in ticketing system for managing errors and a flexible authentication system (LDAP, janrain, MySQL etc.). Web2py has a pleasant and consistent API and includes libraries to handle RSS, HTML/XML, CSV, JSON, AJAX, RTF, ATOM, XMLRPC and WIKI Markup. In the end, this open-source framework is stable and secure for developing database-driven web apps, but it is not as preferred or recommended as other frameworks such as Django and flask.

6. Python Frameworks: Cherrypy

Cherrypy is a popular open-source micro framework that is minimalistic in approach. The framework allows developers to build web applications in similar way as they would build any other project-oriented Python program. Cherrypy has some distinctive features that are worth mentioning such as its built-in multi-threaded server, a powerful configuration system, built-in profiling, coverage and testing support and its ability to run on PyPy, Jython, Python 2.7+, 3.5+ and even Android. Cherrypy-powered web applications are standalone Python applications with their own embedded multi-threaded web server and are fit to run on any OS that supports Python.

7. Sanic

Unlike the other Python frameworks discussed so far, Sanic is an asynchronous framework built on uvloop with the goal to offer fast HTTP responses via asynchronous request handling. The framework is compatible with Python 3.5’s async/await functions which increases its speed and offers your code non-blocking capabilities. In a benchmark test with one process and 100 connections, Sanic was able to entertain 33,342 requests every second which demonstrates its incredible performance. Currently, Sanic runs on Python 3.6+ and is an excellent framework for easily building high-performing, fast and scalable applications.

8. Python Frameworks: Tornado

Tornado is another high-performing Python web framework and asynchronous networking library that was originally developed by FriendFeed and acquired by Facebook in 2009. It is an open-source scalable and non-blocking web server that is capable of solving C10k issues (meaning that it can handle 10,000+ concurrent connections if configured properly). With features like built-in support for user authentication, real-time services, non-blocking HTTP client, implementation of third-party authentication and authorisation schemes, support for translation and localisation and the like, Tornado is a promising tool for building apps that entertain thousands of concurrent users.

The above discussed Python tools can prove to be instrumental in cutting time, cost and effort for professional backend developers. In addition to these frameworks, Python enthusiasts must also check out the top Python libraries for data science that will be useful in the long run.

Related Read: Data Scientist Job Description

Since you’re here…Are you a future data scientist? Investigate with our free step-by-step guide to getting started in the industry. When you’re ready to build a CV that will make hiring managers melt, join our 4-week Data Science Prep Course or our Data Science Bootcamp—you’ll get a job in data science or we’ll refund your tuition.

Sakshi Gupta

About Sakshi Gupta

Sakshi is a Senior Associate Editor at Springboard. She is a technology enthusiast who loves to read and write about emerging tech. She is a content marketer and has experience working in the Indian and US markets.