Python Development is on the rise. Be it machine learning or any other data science project, every full-stack developer needs frameworks to embed their back-end python code into client and server web technologies. For any full-stack developer or even a team of developers, it is a crucial step to choose a high-quality web framework for their projects to create an elegant application. Qualities of a good Python Web Application are its ease of access, security, optimization, usability as well as design. So it is highly coherent to choose the best web framework that suits your project. As python itself, a programming language has its fair share of involvement in Data Science, these frameworks can be applied to create Machine Learning and Data Analytics based full stack applications as well. The below-mentioned web frameworks are highly popular amongst the python developer community and are listed in no specific order of preference.
Reviews of Top Python Frameworks
Being a python developer, I will personally recommend it the most to all my fellow developers out there. Flask is a highly dynamic open-source framework that focuses on security and dynamic web application-building capabilities. Using Flask, backend files end code like python (.py files) can easily include the code from external front-end files like HTML, XML, and CSS. Flask is a great way to use both the backend and frontend code to its full extent as there is no restriction on the usage of both of their functionalities. For better understanding and learning refer to the book “Flask By Example by Gareth Dwyer ” and also check out GitHub repositories for more practice.
Py2Web is a framework that allows web developers to program dynamic web content using Python Programming. With easy designing and interfacing tools, it is easy to edit and save your projects. However it does not have enough coding capabilities as other web programming languages, but still suffices the needs of python developers to create a fully functional web application. The major plus points include server-side sessions, file handling, etc.
The pyramid was developed as a part of the Pylons Project to create faster python web framework applications. Pyramid has a huge number of functionalities and features that can be easily mastered to implement in your application. The pyramid is a broader platform with many tools like database integration, security, templates, and reliable testing methods. It is based on the WSG Interface and is developed on MVC architectural pattern.
The bottle is another full stack of python frameworks. The bottle is way simpler than Django and Flask when it comes down to prototyping project ideas due to its single source code style. It can be very useful for your personal projects. It contains many templates, WSGI/HTTP support, a built-in web server, and so on for better development of web applications. However, the Bottle framework is not recommended for larger projects. For reference, many open-source Bottle projects are available on GitHub that can be used for beginners to practice. It also contains plugins for REST API and database key-value pair connectivity as per its latest version.
Diesel is a great API for solving networking problems in python. Diesel Supports TCP/IP and UDP protocols which help in writing strong networking applications. It handles clients and servers. It is used for a connection-oriented approach to connect the backend and front-end code. It is a highly scalable framework. It can easily handle socket programming and contains tools that help in buffering, connection pools, seamless supervision, and thread integration. It can also be bundled with client libraries like MongoDB and Redis.
By using CherryPy the developers can create and host full-stack python and other machine-learning applications just like any other tool for Object-Oriented Programming applications. We can deploy a standalone python application with the help of CherryPy. It is fast and we can run multiple servers with a flexible plugin system. Some awesome features of CherryPy include a WSGI web server, Multiple server connectivity, caching tools, a configuration system, and session authentication
Django is a perfect is truly for perfectionists out there who need quick solutions for creating python applications on the web. It is free, scalable, fast, and best for full-stack python development. Detailed resources and practice sessions are readily available on the web along with its full official documentation. It follows model view architecture which focuses to reduce the complexities of data-driven websites as well as web applications.
Web Technologies are being implemented in many Python and Data Science applications to provide the best front-end interfacing and communication to the user. It is important for a full stack developer to create a user-friendly application so that the user can easily comprehend the desired role of the application and also is able to use it properly.