The Top 12 Python Frameworks

It is very common to ask questions regarding the different frameworks available in the programming language Python. PyCharm is an integrated development environment (IDE) and not a framework. Anaconda is a Python data science platform, which includes a wide range of pre-built packages and libraries. NumPy is a library used for scientific computing, but not a framework. Django is an open-source web framework written in Python, which provides full-stack development. Ultimately, the best Python framework to use depends on the project you are working on and your specific needs. It is important to research the different frameworks available and their respective features to determine the best fit for your particular project.

Are you looking for the answers to these questions? Continue reading to discover out.

Hire The Top 12 Python Frameworks

Python has become one of the most widely used programming languages, due to its dynamic, interpreted, and object-oriented nature. It allows developers to logically structure their code, making it both easier to read and write. Python is also renowned for its ability to reduce the amount of code needed to achieve a desired outcome, which helps to save time and effort while still providing a high level of accuracy and precision.

Despite Python’s ability to communicate with servers, its capability in this regard is somewhat limited. Consequently, Python developers often rely on frameworks to build applications. Frameworks offer a range of advantages, such as improved security, organisation, accessibility, and comprehensive documentation.

Python offers frameworks for almost every technological sector, but before we go into the many sorts of frameworks, let’s define a Python framework.

What exactly is a Python framework?

A Python framework is a toolbox of packages and modules that provides developers with the capability to quickly and effortlessly generate online applications and services. The framework eliminates the need for developers to tackle more intricate issues, such as protocols, sockets, and thread management, allowing them to focus on the development of the application.

Python frameworks, on the other hand, minimise development time by offering a prebuilt implementation of duplicate operations.

Python frameworks are used by developers for a variety of reasons.

Python frameworks are employed by developers as a means of reusing code for similar HTTP operations, as well as providing an organised structure for applications and a range of pre-defined functionality.

Additionally, many developers prefer utilising frameworks instead of libraries due to their greater conformity to common programming conventions, their dependability, and the ease with which their capabilities can be expanded using the provided tools.

What are the different kinds of Python frameworks?

Python frameworks can be categorised into three distinct types: full-stack frameworks, micro-frameworks, and asynchronous frameworks. Below is a brief overview of each of these types of frameworks: Full-stack frameworks provide comprehensive web development solutions, offering functions and features like web template systems, authentication, and databases. Popular full-stack frameworks include Django, Flask, and Pyramid. Micro-frameworks are designed to provide a minimalistic approach to web development, giving developers the ability to build more focused and lightweight applications. Popular micro-frameworks include Bottle and Flask. Asynchronous frameworks are designed to make applications more responsive by allowing them to process multiple requests in parallel. Popular asynchronous frameworks include Sanic and Tornado.

  1. Full-stack frameworks:

    Full-stack frameworks offer a comprehensive web development solution, encompassing everything from form generators and form validation to template layouts. Such frameworks offer a wealth of applications, though they may present a challenge to use effectively.

    Here are a few examples of full-stack Python frameworks:

    a. CubicWeb
    b. Django
    c. Giotto
    d. Pylons
  2. Micro frameworks:

    Micro frameworks are ideal for medium-sized applications that do not require a significant amount of additional features, such as a data abstraction layer or form validation. These frameworks are minimalistic and lightweight, providing the bare essentials needed to create a functioning application without bogging it down with unnecessary features.

    Here are a few examples of Micro Python frameworks:

    a. Bottle
    b. CherryPy
    c. Dash
    d. Falcon
  3. Asynchronous frameworks:

    Recent developments in software and applications have led to the increased popularity of frameworks that are compatible with the Asyncio library. These frameworks are highly effective in managing high numbers of concurrent connections, making them a popular choice for software and application developers.

    Here are a few examples of Asynchronous Python frameworks:

    a. AIOHTTP
    b. Growler
    c. Sanic
    d. Tornado

Full-Stack Python frameworks

  1. CubicWeb

    CubicWeb is a free and open-source Python framework that facilitates the rapid development of web applications. By leveraging the concept of cubes – reusable components – developers are able to construct robust, efficient, and high-quality semantic web applications with ease.

    CubicWeb Python framework highlights include:

    a. Security processes are available.
    b. There is a function for component reusability.
    c. It is compatible with the Resource Description Framework (RDF) and the Web Ontology Language (WOL) (OWL).
    d. Relational Query Language simplifies data-related queries (RQL).
    e. Multiple databases are supported.
  2. Django

    Django is a popular, high-level web application development framework that allows developers to efficiently create Python-based programs. This framework has an efficient design and is based on the Don’t Repeat Yourself (DRY) principle, which emphasises the importance of writing, debugging and maintaining code that is not duplicated. By embracing this principle, developers can ensure that their code is efficient and avoids unnecessary repetition.

    In comparison to other Python frameworks, Django is equipped with a wide range of features that are already present rather than needing to be acquired from separate libraries. Additionally, Django’s Object-Relational Mapping (ORM) layer facilitates the connection between objects and database tables. Furthermore, Django offers built-in support for a plethora of databases, including Oracle, MySQL, and numerous others.

    The following are the highlights of the Django Python framework:

    a. URL Routing
    b. Improved web server support
    c. Improved authentication support
    d. Framework that is very fast
    e. Libraries that are ready to use
    f. Simple to personalise
  3. Giotto

    Giotto is a Model View Controller (MVC) framework which provides a free RESTful interface to its users. This interface is capable of automating URL routing, and it also features Jinja2 for HTML template rendering with an easy-to-use Application Programming Interface (API).

    Giotto’s controller module provides users with the ability to develop and execute programs across multiple platforms, such as the command line, web, and Internet Relay Chat (IRC). This allows for efficient and powerful programming, allowing users to create complex applications and scripts that can be used across a variety of platforms.

    Giotto Python framework highlights:

    a. Common perspectives and models
    b. URL routing is automated and built-in.
    c. Several plug-in controllers are available.
    d. SQLAlchemy database persistence
    e. CRUD patterns that work
    f. There are several RESTful APIs accessible.
  4. Pylons

    Pylons is an open-source web development framework that emphasises the rapid creation of applications. It incorporates the best features of many popular programming languages, such as Ruby, Perl, and Python. Pylons brings these capabilities together in a single platform to provide developers with an efficient and effective toolset for creating web applications.

    Key Features of the Pylons Python Framework:

    a. URL distribution
    b. Templating using text
    c. URL mapping based on WebHelpers route setup
    d. Validation and creation of HTML forms

Micro Python frameworks

  1. Bottle

    Bottle is a widely-used micro web framework for creating Python-based applications. It is completely independent and comes as a single-file module that includes only one Python standard library.

    One of the most advantageous features of the Bottle framework is that it provides developers with the ability to interact directly with hardware. This makes it an ideal choice for creating simple applications for personal use.

    Bottle Python framework highlights include:

    a. HTTP server built-in
    b. Support for many databases through plugins
    c. Adapters provide support for third-party HTTP/WSGI servers and template engines.
    d. File uploads, headers, and cookies are all supported.
    e. There are no external dependencies.
  2. CherryPy

    CherryPy is an open source web application framework that enables developers to rapidly create object-oriented web applications. It is designed to provide a straightforward, easy-to-use API, allowing developers to create complex applications quickly. CherryPy programs are self-contained and run on their own multi-threaded web server, providing a lightweight, yet powerful platform for web development.

    CherryPy Python Framework Highlights:

    a. Android compatible
    b. Runs on many HTTP servers at the same time
    c. Provides a versatile built-in plugin system
    d. It has a sophisticated setup system.
  3. Dash

    Dash is an outstanding open source microframework ideal for data scientists who lack experience in web development. By creating web-based analytical applications, Dash is akin to web servers as it facilitates the exchange of JSON packets through HTTP requests.

    Dash has leveraged the power of Flask plugins to develop its own features, which can be rendered and served on web servers. As an added bonus, Dash programs are fully mobile-friendly and optimised for compatibility with all platforms. This flexibility ensures that users can access Dash programs no matter their device or operating system.

    Dash Python framework highlights include:

    a. Improved plugin support
    b. An efficient error-handling technique
    c. Routing functionality for URLs
    d. LDAP integration capability
    e. Simple user interface
    f. There are several customising options.
  4. Falcon

    The Falcon framework is a powerful tool used by developers to rapidly design and develop web APIs. This comprehensive suite of tools allows developers to create aesthetically pleasing online applications with ease. Furthermore, Falcon provides the necessary functionality to enhance and modify prevalent HTTP and Representational State Transfer (REST) architectural styles.

    Falcon Python framework highlights include:

    a. An incredibly efficient and extensible codebase.
    b. HTTP error response time is precise and efficient.
    c. Mocks and WSGI helpers enable unit testing.
    d. Request and response classes make it simple to manage and access bodies and headers.
    e. DRY requests are handled by hooks and middleware components.
    f. Developers may speed up their apps even further with Falcon’s assistance.

Asynchronous Python frameworks


    AIOHTTP is a widely renowned asynchronous Python framework that is built on the latest Python 3.5+ features such as Async and Awaits. The Asyncio library has been implemented by AIOHTTP, a client-side framework.

    One of the most noteworthy advantages of AIOHTTP is that it offers support for both server and client WebSockets without needing to implement a callback. Additionally, it comes with a router and request object that can be used to seamlessly direct incoming requests to the appropriate functions.

    The following are the key features of the AIOHTTP Python framework:

    a. HTTP servers are supported.
    b. Provides web servers with pluggable routing and middleware.
    c. Provide efficient view construction
  2. Growler

    Growler is built on the express framework of Node.js, Object Relational Mapping (ORM), and Templating. It is comparable to AIOHTTP.

    Rather than dealing with queries directly, Growler employs middleware technology to route them, making it one of the premier Python framework choices for streamlining the development of complex applications.

    Growler Python Framework Highlights:

    a. More decorators should be used to develop reusable and effective code.
    b. The Ziapp concept is available to bundle the whole program into a single executable file.
    c. A large number of open-source software are supported.
  3. Sanic

    Sanic is an open-source Python web framework that leverages the uvloop framework to provide asynchronous request processing, delivering faster HTTP responses. This powerful feature is one of Sanic’s key advantages and enables users to create applications that are highly responsive and performant.

    Sanic is capable of supporting request handlers which are analogous to Python 3.5’s Await or Async routines, leading to non-blocking capabilities and improved performance in applications. This compatibility is one of the major advantages of using Sanic for software and app development.

    The following are the highlights of the Sanic Python framework:

    a. Support for plugins
    b. Class-based perspectives
    c. Capable of writing and reading cookies
    d. Allows for a variety of error reports and access logs.
    e. Handlers with simple decorator support are available.
  4. Tornado

    Tornado has long been recognised as one of the most powerful and comprehensive Python frameworks available. It offers support for databases, URL routing, HTML templates and other essential components needed for the development of a wide range of applications. As such, it is a highly sought-after choice for developers looking to create complex and robust applications.

    The Tornado web framework simplifies web server development by focusing on non-blocking operations, allowing for the efficient handling of a large number of open connections.

    Tornado Python framework highlights include:

    a. Extensive localization and translation assistance
    b. Techniques for web templating are available.
    c. Services in real time
    d. Provides effective outcome
    e. Allows the use of third-party authorisation and authentication.

So, which Python framework is best for you?

In spite of the fact that there are a number of well-known and sought-after Python frameworks available, each of them have their own advantages and disadvantages. Selecting the correct Python framework for a project is heavily dependent on the requirements of the project and the familiarity of the developer with the framework.

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  1. What exactly is a Python framework?

    The Python Online framework is an extensive collection of packages and modules that provide developers with the capacity to build web applications and services with ease. This framework relieves developers from having to manage mundane, low-level elements such as protocols, sockets, and process/thread management, enabling them to focus on the higher-level aspects of development.
  2. Which framework is the most often used in Python?

    Django is widely regarded as the leading full-stack framework for Python due to its remarkable speed and reliability when building complex web applications. The popularity of this framework speaks to its strength as a development tool.
  3. Is PyCharm considered a framework?

    Absolutely not! PyCharm is an integrated development environment (IDE) that provides all the necessary components for programming. By taking advantage of the features of IntelliJ IDEA, such as JavaScript support, PyCharm enables efficient development of web applications.
  4. Anaconda is it a framework?

    Anaconda is an open-source distribution of the Python and R programming languages designed to simplify package management and deployment for scientific computing. Anaconda facilitates the installation of packages and their dependencies, as well as the seamless sharing of packages between users. Additionally, Anaconda provides the ability to create isolated Python and R environments, allowing users to tailor their computing environment to the project at hand. With these features, Anaconda makes scientific computing easier and more efficient.
  5. Is NumPy considered a framework?

    NumPy is a Python programming language library.

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