Python has gained a lot of popularity in recent years and it doesn't seem to be losing momentum anytime soon. According to current trends, Python is currently ranked as the second most popular programming language, with a significant increase in usage over the past year. And we anticipate another 50 percent increase in its ranking by the end of 2024.
One of the surveys conducted by Annual Stack Overflow Survey also revealed that Python is the top pick for web development, with 43.51% of professional developers choosing it over other options like Java, C#, and PHP.
Python VS Major Programming Languages
But here's the thing – Python isn't just about building web applications. Its versatility is a big part of why developers worldwide are turning to it for all sorts of tasks. From data analysis and DevOps to software testing, web scraping, security, and statistics, Python's got your back across a wide range of fields.
In addition to being widely used for web development, Python is one of the most powerful programming languages when it comes to machine learning and artificial intelligence. Thanks to its easy-to-understand syntax, dynamic concepts, and a plethora of reliable Python frameworks and libraries like TensorFlow, Pandas, and NumPy, Python makes it easy to leverage the power of AI and ML.
The growth of this high-level programming language can also be estimated from the fact that over 122,864 websites online are built using Python, with 93,197 unique domains. Major tech companies such as Google, Amazon, Spotify, Netflix, and Quora leverage Python's frontend framework and backend framework. So, it's no wonder Python commands such attention!
With Python gaining so much traction amongst the developers’ community, it is obvious to find many Python frameworks to ease the web application development process. So, if you want to learn more about Python frameworks, you're in the right place. We'll cover the basics and discuss the most popular frameworks.
But before we delve into that, let's lay down some foundational knowledge.
Python Libraries vs. Python Frameworks
There's often confusion surrounding Python libraries and frameworks, despite their shared purpose of providing functionality to developers. While both offer similar levels of detail and complexity, they serve distinct roles.
Python libraries consist of collections of functions tailored for specific tasks, with relatively low complexity. Essentially, they represent individual pieces of a larger puzzle, each serving a simple purpose. For example, some kind of mathematical operations, data manipulation, web scraping, or interacting with databases. Leveraging a web scraper API can simplify the process of extracting and structuring web data in Python-based applications.
When using a library, you have more control over your application's architecture and flow, as you decide when and how to utilize the functions provided by the library.
Frameworks, on the other hand, operate on a deeper level, enforcing a specific architecture or design pattern, such as Model-View-Controller (MVC) or Model-View-View-Model (MVVM), to build application development.
Unlike libraries, frameworks dictate the flow of control in your application. They provide a skeleton where you fill in the details by extending or overriding predefined components. Basically, frameworks outline the entire puzzle, including its internal components.
Frameworks often follow the principle of "don't call us, we'll call you," meaning that your code interacts with the framework rather than the other way around.
In essence, the complexity of a Python framework correlates with the level of detail it provides, offering developers a structured blueprint for their applications.
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3 Major Types of Python Frameworks for Web Application Development
Python frameworks come in various forms, each catering to different development needs. Factors like scalability, efficiency, specific business requirements, and compatibility with current technologies play a role in choosing the right framework.
Types of Python Frameworks
1) Full-Stack Framework – Also known as enterprise frameworks, full-stack frameworks offer comprehensive solutions for development tasks. They seamlessly integrate various components and come with pre-built libraries, facilitating the creation of both backend services and frontend interfaces. Additionally, they can serve as Python database frameworks for database development and management.
- CubicWeb
- Django
- Giotto
- Pyramid
- TurboGears
- Web2Py
2) Microframework – Microframeworks are lightweight Python web application frameworks with minimal features and functionalities. They provide only essential elements necessary for application development, lacking advanced features like form validation, web template engines, authorization, input sanitation, database abstraction layers, authentication capabilities, and input validation.
- Bottle
- CherryPy
- Dash
- Falcon
- Flask
- Hug
- Growler
3) Asynchronous Framework – Asynchronous frameworks represent the latest addition to Python's web development landscape. They enable developers to handle large volumes of concurrent connections efficiently. These frameworks leverage Python's Asyncio library to manage asynchronous operations effectively.
- AIOHTTP
- Tornado
Let's now delve into the top 20 Python frameworks, enabling developers to do more with fewer lines of code.
1. Django
Django is an open-source, Python framework that is known for building complex data-driven websites. The framework has templates, libraries, and APIs that help in building scalable web-development projects. Django is the most popular Python framework and is the basis for various popular websites, including Instagram, Pinterest, Bitbucket, Nextdoor, The Washington Times, etc.
2. TurboGears
TurboGears is a web application development framework, consisting of Web Server Gateway Interface (WSGI) components such as SQLAlchemy, Repoze, WebOb, etc. Similar to Ruby on Rails (RoR) or Apache Struts, TurboGears is built around MVC architecture that helps in rapid web application development. It aims to address the limitations found in many commonly used frameworks for web and mobile app development. By offering a simplified setup process, TurboGears enables software developers to quickly initiate web application projects.
With TurboGears, web developers and Python development firms can expedite the development of Python-based websites by leveraging various JavaScript development tools. This framework facilitates the rapid development of web applications by providing efficient elements such as SQLAlchemy, Repoze, WebOb, and Genshi. It offers compatibility with different databases and web servers, including Pylons.
Operating on an MVC (Model-View-Controller) architecture, TurboGears integrates robust templates, a powerful Object Relational Mapper (ORM), and support for Ajax on both the server and browser sides. Notable organizations utilizing TurboGears include Bisque, ShowMeDo, and SourceForge.
3. Hug
The Hug framework is crafted to empower Python developers to create an API once and deploy it across various platforms effortlessly. This Python framework streamlines API development by providing multiple interfaces and is recognized as the fastest web framework for Python 3.
Whether you're engaged in local development, HTTP interactions, or working via the command-line interface (CLI), Hug accelerates application development with ease and efficiency. To enhance performance, Hug optimizes resource usage by activating them only when necessary and leverages Cython for compilation. Additionally, It adheres to the "write once, use anywhere" principle and has automatic documentation support.
4. Pyramid
The Pyramid is another popular Python framework that is used by leading technology companies such as Mozilla, Yelp, Dropbox, and SurveyMonkey. One of the best things about the Pyramid is its flexibility and simplicity. It works well for both small projects and big ones. Plus, there are plenty of resources available to make it even better.
It is lightweight and adaptable. Developers can seamlessly integrate it with third-party libraries and plugins. It has comprehensive templating and asset management capabilities plus provides extensive support for testing and thorough documentation. Moreover, it offers flexible authentication and authorization mechanisms.
5. Tornado
A framework is essentially a set of tools that help organize and manage code, allowing for the creation of more complex systems. While simple websites can be built using basic languages like HTML, CSS, and Python, larger projects often require more robust solutions to meet deadlines efficiently. This is where web frameworks like Tornado come into play.
Tornado, an open-source web framework and networking library, facilitates the development of web applications using Python. Originally created at FriendFeed and later acquired by Facebook, Tornado is now widely used across various applications including web services, real-time analytics, and high-concurrency applications.
What sets Tornado apart is its ability to efficiently handle a large number of simultaneous connections, making it ideal for applications requiring persistent connections with users, such as chat apps, bots, and web scrapers. It addresses the C10k issue, enabling it to handle over 10,000 simultaneous connections when configured correctly.
Key features of Tornado include support for 3rd-party authentication and authorization, high-quality real-time services, non-blocking HTTP clients, customizable web templates, and capabilities for WebSockets and long-polling.
6. Numpy
Numpy- Numeric Python is a library that helps in performing mathematical and logical operations on arrays. The library consists of a multidimensional array of objects and a collection of routines for processing the arrays.
7. Pandas
Pandas is a BSD-licensed, open-source Python library that provides easy to use data structures and data analytics tools for Python programmers. The framework is primarily used in academic and commercial domains, such as finance, economics, analytics, statistics, etc.
8. Matplotlib
Matplotlib is a plotting library that allows the creation of 2D graphs and plots by using Python scripts. It supports a variety of graphs and plots, which includes bar charts, histograms, error charts, power spectra, etc. The library has a module named Pyplot that makes plotting easy with features such as color line styles, formatting axes, font properties, and more.
9. Flask
Flask is a micro web framework that’s built-in with a development server and support for unit testing. This Unicode-based Python framework supports RESTFUL request dispatching and is extensively documented for programmers to get started.
10. Web2py
Web2py is a cross-platform framework for web development, written in Python. Introduced in 2007, the framework comes with a code editor, debugger, and deployment tools.
11. Bottle
The bottle is a WSGI micro web framework, which is distributed as a single file module with no dependencies other than the Python Standard Library. It has support for request dispatching with URL support, key/value databases and templates, and a built-in HTTP server.
12. CherryPy
CherryPy provides the CRUD (Create, Retrieve, Update, and Delete) functionalities for applications and helps in managing the project from anywhere using the user’s browser. The framework can run on multiple HTTP servers, has a flexible plugin system, and has built-in profiling, coverage, and testing support.
13. Falcon
Falcon is a micro-framework for developing small-scale applications and backends. The Falcon web framework encourages the REST architectural style and is available with several add-ons, templates, and complementary packages to ease development.
14. AIOHTTP
Asynchronous framework AIOHTTP is a Python framework that relies heavily on Python 3.5+ features, such as async & awaits. The Python framework makes use of Python’s asyncio library and is hence called an asynchronous framework. In addition to being a server web framework, AIOHTTP can also serve as a client framework. It provides a request object and router to enable the redirection of queries to functions developed to handle the same.
15. CubicWeb
It is a full-stack framework developed and curated by Logilab, CubicWeb is a free-to-use, semantic, open-source, Python-based web framework. Based on the data model, CubicWeb requires the same definition in order to develop a functional application.
Unlike other popular Python frameworks that use separate views and models, CubicWeb makes use of a cube. Multiple cubes are then joined together for creating an instance with the help of a database, a web server, and some configuration files.
16. Dash
Microframework Dash is an open-source Python-based framework for building analytical web applications. It is an ideal Python framework for data scientists who aren’t much into the mechanics of web development.
Applications designed with Dash are web servers that run Flask and communicate with JSON packets via HTTP requests. Their frontend renders components using ReactJS. Flask plugins can be used to extend the capabilities of Dash.
17. Giotto
Full-stack framework Based on the Model View Controller pattern, Giotto is an application framework for Python. In order to allow web designers, web developers, and system admins to work independently, Giotto separates Model, View, and Controller elements in order.
Giotto includes controller modules that enable users to create apps on top of the web, IRC (Internet Relay Chat), and command line.
18. Growler
Asynchronous framework Inspired by the NodeJS and the Express/Connect frameworks, Growler is a micro web framework written atop Python’s asyncio library.
Unlike other conventional Python frameworks, requests in Growler aren’t handled in the framework but by passing through middleware technology.
Choosing the Right Python Framework for Your Project
Python and its frameworks are opening ways for building robust and scalable applications with fewer lines of code. Wondering which framework to choose for your next web application development project? Request a free consultation with our experts. As a leading web application development company, we specialize in harnessing the power of Python and its frameworks to create robust and scalable applications.
