Frameworks make the coders life simpler by offering them a structure for application advancement. They mechanize the usage of regular solutions, minimizing the development time and permitting designers to concentrate on application rationale rather than routine components.

There are various splendid frameworks that may be used directly rather than re-building the wheel all around. Therefore, in this article, you will get to know about the distinctive Python frameworks that can be put to use. This will be helpful in your next Python Development.

One of the most common and inclining programming languages used by far most of the developers is Python. Python is the spine mechanical assembly for the Machine Learning Engineers and Data Scientists as well. In any case, this omnipresence isn’t simply confined to a particular region like ML, Data Science, and AI.


Various Types of Python Frameworks


Top python Framework

Full-Stack Framework:

A full-stack framework is a one-stop answer for all the development requirements. These frameworks comprise libraries that are designed to work consistently together.
These frameworks provide extended support to database systems, front and back end interfaces.

Micro Framework:

Micro frameworks are designed lightweight, moderate web application frameworks that have constrained functionalities and features. Generally, these frameworks offer just those parts that are required for building an application. They need numerous extra functionalities and features like database reflection layer, web format motor, input approval, and information sanitation.

Non-Synchronous Framework:

The non-synchronous framework is the most recent to join the Python framework fleeting trend. It is one of a kind micro-framework that allows developers to deal with and oversee huge arrangements of simultaneous associations. These systems feed on Python’s Asyncio library.


Points that should be considered while making a selection for the Python framework:

Python has thus positioned as the main programming language adored by data scientists and developers the same. There are numerous reasons which make Python the best programming language for data scientists. However, Python frameworks may likewise get overpowering while at the same time picking the correct framework for your application.

  • First of all, assess the size and multifaceted nature of the project. On the off chance that you need to build up a huge framework stuffed with various features and prerequisites, a full-stack framework will be the correct decision. On the other hand, if the current project is limited in functionalities and clear, you can pick a micro framework.
  • The second angle to consider is whether the framework permits the degree for scaling both vertically and evenly. This is especially vital when fabricating an undertaking that will run on numerous servers, handle a colossal traffic burden, and bolster the expansion of new features for usefulness streamlining.

Top Popular Python Frameworks


Official Website | GitHub | PyPI | Awesome

GitHub Stars: 44,077 | GitHub Forks: 18,949


Django is a full-stack Python framework which is available over the open platform. It follows the methodology of Don’t repeat yourself. Django comes furnished with a huge line of prepared to-utilize libraries. A portion of its most remarkable highlights is confirmation, URL steering, and database patterns. Together, these make Django profoundly adaptable, quick, and flexible.

Django is perfect with a large group of databases including PostgreSQL, MySQL, SQLite, and Oracle. Since it utilizes ORM to outline to database tables, a similar code works with various databases. You can even move to start with one database then onto the next with no trouble. Django permits you to build up any sort of application you want – from huge web applications to various small projects.



Official Website | GitHub | PyPI | Awesome

GitHub Stars: 3,215 | GitHub Forks: 866

Pyramid development

Pyramid is the Python’s another open-source framework. It runs on Python 3 and intends to achieve however much as could reasonably be expected with negligible complications. Moreover, the best component of the Pyramid is its capacity to run well with both little and huge applications. A portion of the key features of this system incorporates Routes, generation of HTML forms and validating them content based templating, URL mapping dependent on Routes arrangement. Pyramid brags of a functioning network that is consistently adding to improve the structure.


Turbo Gears

Official Website | GitHub | PyPI

GitHub Stars: 654 | GitHub Forks: 65




Turbo Gears is an information-driven, full-stack python framework. It consolidates the absolute best parts of other Python systems and accompanies numerous valuable libraries. It permits engineers to fabricate information-driven web applications quickly.



Official Website | GitHub | PyPI

GitHub Stars: 1,794 | GitHub Forks: 818


Web2py is an exceptionally adaptable, open-source full-stack Python framework. It accompanies its individual online IDE that incorporates a code supervisor, debugger, and a single tick stationing feature.

Web2py is an intense information handling tool. In spite of the fact that it permits developers to draft and construct dynamic web content in Python. In any case, it can run flawlessly on any web facilitating platform that offers help either for Python or Java. Additionally, it has worked in information security for forestalling regular vulnerabilities like cross-site scripting, infusion blemishes, and vindictive record execution.



Official Website | GitHub | PyPI

GitHub Stars: 1,057 | GitHub Forks: 259


Cherrypy is an object-oriented Python micro framework which follows the minimalistic approach. Following a moderate methodology, CherryPy is intended for extensibility. It incorporates components for snare focuses and augmentations. Also, the “cherry” on top is that any CherryPy-based web application is an independent Python application having its special implanted multi-strung web server.

In spite of being a microframework, CherryPy isn’t very constraining in usefulness. It lets you work with any innovation of your decision for templating, information get to, and so forth. Furthermore, it can deal with sessions, statistics, record transfers, and everything else that a web structure can.



Official Website | GitHub | PyPI | Awesome

Github Stars: 46,475 | GitHub Forks: 12,921


Python’s framework which is available under the BSD permit is flask. It gets motivation from the Sinatra Ruby system. Flask requires Jinja2 layout and Werkzeug WSGI toolbox to run. It has a lightweight and secluded design that makes it effectively versatile to a wide scope of improvement needs.

With Flask, you can fabricate a strong web application establishment that can scale to utilize any sort of expansions. It incorporates an inherent improvement server and quick debugger has coordinated help for unit testing and takes into consideration restful solicitation dispatching. Flask is good with Google App Engine.



Official Website | GitHub | PyPI

GitHub Stars: 12,780 | GitHub Forks: 1,203


Sanic is a non-synchronous framework based over uvloop. It is a basic Python structure developed unequivocally for offering quick HTTP responses. Since Sanic underpins non-concurrent demand handlers, it is perfect with Python 3.5’s ‘Async’ and ‘Anticipate’ capacities. This assists with improving its speed further.

Sanic is one of the most favoured non-synchronous frameworks by engineers since it can peruse and compose treats; permits various kinds of logging, has module backing, and supports outlines for sub-steering inside an application.



As discussed, every python framework accompanies its own unmistakable features and capacities to take into account changing application development needs. The key is to recognize which structure will best fit for the project, and that shouldn’t be extreme. Not to forget, if you are to hire a Python development company for your project then look for only the top Python development companies in India.

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