25 Python Frameworks to Master

1

Flask

You’ll also have access to some extension packages like Flask-RESTful, which adds support for building powerful REST APIs, and Flask-SQLAlchemy, a convenient way to use SQLAlchemy in your flask app.

#Python Web Framework #Web Framework #Developer Tools 42 social mentions

2

Bottle

Want to create ridiculously light web applications with no other dependencies? Bottle is a lightweight Python microframework designed to easily build small- or medium-sized web applications. It doesn’t include any external dependencies aside from the Python standard library,

#Web Framework #Python Web Framework #Developer Tools 16 social mentions

3

CherryPy

The main task of CherryPy is to handle HTTP requests and match them with the adequate logic written by the developers. This means that by default, CherryPy doesn’t provide database access or HTML templating, leaving all the logic of the application to you.

#Python Web Framework #Web Framework #Developer Tools 2 social mentions

4

Django

You won’t go wrong by choosing Django for your next web project. It’s a powerful web framework that provides everything you need to build fast and reliable websites. And if you need any additional features — say, the ability to create a REST API to use with modern frontend frameworks like React or Angular — you can use extensions like Django REST framework.

#Python Web Framework #Python MVC Framework #Web Framework 14 social mentions

5

FastAPI

Since its release in 2018, it has rapidly gained popularity due to its great performance and simplicity. In fact, according to PyPi Stats, FastAPI has over 9 million monthly downloads, surpassing even full-stack frameworks like Django.

#Developer Tools #API Tools #Python Programming 232 social mentions

6

Pyramid

Pyramid is a flexible and extensible web framework that’s well-suited for both small and large applications. It’s the sweet spot between a microframework like Flask and a full-stack framework like Django.

#Web Framework #Python Web Framework #Developer Tools

7

Tornado

Tornado is an open-source asynchronous web framework and networking library for building web applications using Python. It was originally developed at FriendFeed, a social media aggregator that was later acquired by Facebook. It’s now widely used in a variety of applications, including web services, real-time analytics, and other high-concurrency applications.

#Web And Application Servers #Web Servers #Application Server

8

PyQt

PyQt is one of the most popular sets of Python bindings for the Qt cross-platform application framework. This framework perfectly combines the simplicity of Python as a general-purpose language and the powerful Qt application framework built in C++.

#Rapid Application Development #Development Tools #IDE 4 social mentions

9

Tkinter

It’s a great option for creating simple and easy-to-use graphical user interfaces in Python and allows you to add a GUI to your already working scripts pretty easily. PySimpleGUI wraps the power of 4 different GUI libraries, PySide, Tkinter, wxPython, and Remi.

#Development #Rapid Application Development #Development Tools 27 social mentions

10

Kivy

Unlike PyQt, Kivy is free and open-source, isn’t a wrapper around an external UI library, and is licensed under the MIT license, which means you can ship and monetize your Kivy apps.

#Developer Tools #Rapid Application Development #Python Tools 45 social mentions

11

PySide

It’s a great option for creating simple and easy-to-use graphical user interfaces in Python and allows you to add a GUI to your already working scripts pretty easily. PySimpleGUI wraps the power of 4 different GUI libraries, PySide, Tkinter, wxPython, and Remi.

#Rapid Application Development #Development Tools #IDE

12

PySimpleGUI

It’s a great option for creating simple and easy-to-use graphical user interfaces in Python and allows you to add a GUI to your already working scripts pretty easily. PySimpleGUI wraps the power of 4 different GUI libraries, PySide, Tkinter, wxPython, and Remi.

#Rapid Application Development #IDE #Game Engine

13

Scikit-learn

#Data Science And Machine Learning #Data Science Tools #Python Tools 27 social mentions

14

TensorFlow

Keras is a high-level deep-learning framework capable of running on top of TensorFlow, Theano, and CNTK. It was developed by François Chollet in 2015 and is designed to provide a simple and user-friendly interface for building and training deep learning models.

#Data Science And Machine Learning #AI #Machine Learning 7 social mentions

15

PyTorch

Along with TensorFlow, PyTorch (developed by Facebook’s AI research group) is one of the most used tools for building deep learning models. It can be used for a variety of tasks such as computer vision, natural language processing, and generative models.

#Data Science And Machine Learning #Data Science Tools #AI 100 social mentions

16

Keras

Keras is a high-level deep-learning framework capable of running on top of TensorFlow, Theano, and CNTK. It was developed by François Chollet in 2015 and is designed to provide a simple and user-friendly interface for building and training deep learning models.

#Data Science And Machine Learning #OCR #Data Science Tools 29 social mentions

17

NumPy

SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.

#Data Science And Machine Learning #Data Science Tools #Python Tools 105 social mentions

18

SciPy

SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.

#Data Science And Machine Learning #Python Tools #Software Libraries 15 social mentions

19

Pandas

Pandas is a powerful and flexible open-source library used to perform data analysis in Python. It provides high-performance data structures (i.e., the famous DataFrame) and data analysis tools that make it easy to work with structured data.

#Data Science And Machine Learning #Data Science Tools #Python Tools 195 social mentions

20

Matplotlib

Matplotlib is a widely used tool for data visualization in Python. It provides an object-oriented API for embedding plots into applications.

#Data Visualization #Technical Computing #Javascript UI Libraries 97 social mentions

21

pytest

Pytest is a widely adopted testing framework that is designed to be easy to use and extend. It helps you to write elegant tests in both small and complex Python codebases.

#Automated Testing #Testing #Online Services 5 social mentions

22

unittest

nose2 extends the built-in unittest library and provides a more powerful and flexible way to write and run tests. It’s an extensible tool, so you can use multiple built-in and third-party plugins to your advantage.

#Testing #Automated Testing #Browser Testing 59 social mentions

Aiohttp is an asynchronous HTTP client/server framework built on top of the asyncio package. It provides a simple and intuitive interface for handling HTTP requests and responses, as well as support for middleware, sessions, and other web development tools.

Aiohttp is an asynchronous HTTP client/server framework built on top of the asyncio package. It provides a simple and intuitive interface for handling HTTP requests and responses, as well as support for middleware, sessions, and other web development tools.

Aiohttp is an asynchronous HTTP client/server framework built on top of the asyncio package. It provides a simple and intuitive interface for handling HTTP requests and responses, as well as support for middleware, sessions, and other web development tools.