Introduction

Python is often labelled as a versatile and beginner-friendly programming language. In addition to this, it comes with various prepacked libraries which can help developers by saving development time & effort. As pointed out earlier, python has a sea of libraries available. This is one of the biggest reasons why Python is popular among the developer community.

But as it is said there is another side of the story as well, as helpful as it is to have hundreds and thousands of libraries at your disposal, it can also become a tedious task to select the best Python framework & libraries as per your project requirements.  In this blog, you will get insight into an overview of Python web framework & libraries, factors to keep in mind while selecting the web framework for python, and much more.

So, without further ado, Let’s dive in!

Stats related to Python

So before diving into the world of Python frameworks & libraries, look at the stats which will justify the popularity of Python.

According to Statista,

• Various Python libraries are included in the most used libraries and frameworks among developers, worldwide, as of 2022.

• With respect to deployment type, python has scored 3^rd rank in programming languages used by software developers worldwide as of 2022

According to the Stack overflow developer survey 2022,

• In 2022, Python scored 43.51% for professional developers using Python, whereas for people learning to code, it scored a whopping 58.38%.

• In the section on other frameworks and libraries, there are Python libraries everywhere as well.

Best Python Frameworks & Libraries to Use in 2023

Python has a vast ecosystem of frameworks & libraries which greatly enhance the development process and empower developers to build robust and efficient applications.

From web development to scientific computing and machine learning, Python has a solution for nearly every domain making it the popular choice in the code learning community along with experienced professionals. The top Python web development frameworks & software libraries that we have utilized in projects for our clients are shown in the list below. Let’s take a look.

Django

Stars: 70.4K |Forks:  29.2K |Contributors: 2,390

Type: Framework

Mainly used for: Fast & simplified website development

Install: pip install Django==4.2.1

License: BSD-3-Clause

You cannot start any python framework list without adding Django in it. Django is a high-level web framework that simplifies web application development. Django emphasizes on DRY (Don’t Repeat Yourself), and comes with ready-to-use features like a login system, database connection, and CRUD operations. It follows MVT (Model-View-Template) architecture. It also provides tools that manage database management, URL routing, template rendering, user authentication, and more. With a focus on reusability and maintainability, Django framework in python is popular for building robust and scalable web applications.

Key features

• Django provides an Object Relational Mapping (ORM) that simplifies database interaction by using Python Objects
• It follows MVT (Model View Template) architecture, promoting code organization and reusability
• It includes a robust URL routing system for mapping URLs to views
• Django’s template engine separates the presentation logic from the business logic
• Built-in form handling in Django provides features like form validation and error handling
• Django emphasizes security with built-in measures to protect against several web vulnerabilities
• Django supports Internationalization and Localization, allowing the development of global applications
• Django is designed to handle high-traffic loads efficiently, making it scalable and performant

Use Cases

Pros and Cons

Pyramid

Stars: 3.8K |Forks:  895 |Contributors: 278

Type: Framework

Mainly used for: Web development

Install: pip install pyramid==2.0.1

License: Zope Public License (ZPL)

Pyramid is a lightweight & flexible Python web framework that prioritizes simplicity and customization. With the minimalistic approach, it gives developers complete control over the application’s structure and components. Designed for scalability and performance along with various features including different URL patterns, supports multiple templating engines, and built-in features for authentication and authorization. In addition to all this, it also has comprehensive documentation and an active community making it a popular choice for developers who are looking for customizable python web dev frameworks.

Key features

• Pyramid emphasizes simplicity and minimalism, allowing developers to selectively add necessary components
• URL dispatching in Pyramid provides a powerful mechanism for handling diverse URL patterns and HTTP methods
• Pyramid supports multiple templating engines, enabling the separation of presentation and application logic
• Built-in features in Pyramid facilitate authentication and authorization for secure user access control
• Pyramid offers flexibility in configuration through Python code or files, catering to project-specific needs
• Testing and debugging are made efficient in Pyramid with robust utilities and a debugger
• Pyramid supports middleware, enabling integration of additional functionality and customization of request/response processing
• Pyramid is compatible with various deployment options, including servers, WSGI containers, and cloud platforms
• Pyramid benefits from an active community and comprehensive documentation, providing valuable support and resources

Use Cases

Pros and Cons

Note: Although the points are listed in cons they don’t need to be drawbacks for all projects which use a pyramid. They can be pros as well for certain projects. Ultimately, the suitability or usefulness of a pyramid boils down to your project requirements.

Also Read: – Python Optimization: Performance, Tips & Tricks

Bottle

Stars: 8K |Forks:  1.5K |Contributors: 190+

Type: Framework

Mainly used for: Developing small to medium-sized web applications, APIs, mock-up

Install: conda install -c conda-forge bottle

License: MIT

Key Features

• Bottle’s lightweight & simple design offers a minimalistic approach to web development
• Built-in URL routing capabilities for easy request mapping
• Convenient handling of HTTP requests and responses
• Support for various templating engines
• Built-in user session management
• Simplified handling of client file uploads
• Easy processing and validation of form data
• Features for building RESTful APIs
• Plugin support for added functionality
• Easy integration with no complex setup or installation

Use Cases

Pros and Cons

Tornado

Stars: 21.1K |Forks: 5.5K |Contributors: 360+

Type: Framework

Mainly used for: Developing high-performance web applications and APIs.

Install: pip install tornado==6.2

License: Apache-2.0

Tornado is a high-performance Python web framework and asynchronous networking library. This best python framework for web development is known for its ability to handle thousands of simultaneous connections with low latency. Tornado is popular for building scalable, real-time web applications and APIs, thanks to its asynchronous I/O capabilities, request handlers, templating engine, and integration flexibility with existing applications. Apart from all this, it includes its web server, supports WebSockets, and employs an event-driven architecture for efficient handling of concurrent requests.

Key Features

• Asynchronous I/O for efficient handling of concurrent requests & non-blocking operations
• Built-in web server eliminating the need for additional servers like Nginx or Apache
• WebSocket’s support real-time bidirectional communication
• Request handler model for routing and handling different types of HTTP requests
• Templating engine for generating dynamic web pages
• Security features include secure cookies, input validation, and XSS protection
• Scalability with the ability to handle large numbers of concurrent connections
• Integration flexibility with existing applications or frameworks
• Active community & comprehensive documentation providing resources and support for developers

Use Cases

Pros and Cons

Flask

Stars: 63K |Forks: 15.6K |Contributors: 700

Type: Framework

Mainly used for: Developing async applications & HTTP/RESTful APIs

Install: $ pip install -U Flask

License: BSD-3-Clause license

Flask is a lightweight and flexible Python web framework used for building web applications and APIs. It emphasizes simplicity and minimalism, providing the essential tools for web development. With a built-in routing system, a templating engine for dynamic content, and extensibility through various plugins, flask framework python enables developers to create small to medium-sized web applications, prototypes, and RESTful APIs efficiently. It is highly regarded for its simplicity, ease of use, and flexibility, making it one of the most popular python frameworks.

Key Features

• Flask is a lightweight framework that enables quick & efficient development of web development
• Flask provides a flexible and intuitive routing system for different types of HTTP requests
• The powerful templating engine in Flask allows for dynamic content generation & seamless integration with HTML templates
• Flask’s extensibility allows for easy integration of additional functionality through a wide range of plugins & extensions
• It is highly compatible & versatile making Flask a seamless integration with other Python libraries
• Python Flask web framework facilitates easy testing and debugging due to the in-built development server
• Flask-WTF extension simplifies integration with forms, form validation, and security features for user input handling
• Flask has a vibrant community and comprehensive documentation, providing valuable resources and support to developers
• Flask’s modular design enables scalability, allowing for easy expansion and management as projects grow

Use Cases

Pros and Cons

Also Read: – Ruby vs Python

aiohttp

Stars: 13.5K |Forks: 1.9K |Contributors: 610

Type: Framework

Mainly used for: Developing web applications and APIs

Install: pip install aiohttp==3.8.3

License: Apache-2.0

aiohttp is a Python library mainly used for building asynchronous HTTP-based client and server applications. It leverages Python’s asyncio library for the efficient handling of concurrent requests, making it ideal for developing high-performance and scalable web applications, APIs, and web scraping tools. aiohttp supports various HTTP features like Web Sockets, cookies, sessions, and SSL/TLS encryption. It provides an easy-to-use API for making HTTP requests and handling responses asynchronously, enabling developers to build efficient and responsive applications that can handle many concurrent connections.

Key Features

• aiohttp is designed for handling asynchronous HTTP requests, allowing for efficient concurrency & responsiveness
• Using aiohttp allows developers to build a complete web application as it provides both client & server-side functionalities
• aiohttp allows real-time bidirectional communication between servers & clients using built-in WebSocket communication support
• aiohttp supports various HTTP features such as cookies, sessions, SSL/TLS encryption, content compression, and authentication
• It allows the use of middleware components to customize & extend the functionality of the application
• It also provides flexibility in deployment options as it can help in integrating with different asyncio, Gunicorn, and uWSGI
• aiohttp allows efficient content streaming, which enables the processing of large files or streaming responses to clients
• aiohttp provides a routing system for mapping URLs to specific handlers, making it easy to define and handle different routes in an application
• aiohttp provides tools and methods for testing applications, making it easier to write test cases for various functionalities

Use Cases

Pros and Cons

Pre-commit

Stars: 10.4K |Forks: 722K |Contributors: 122

Type: Framework

Mainly used for: managing and maintaining multi-language pre-commit hooks.

Install: pip install pre-commit==3.0.2

License: MIT

Last but not the least in our list of python frameworks is pre-commit. Pre-commit is a Popular Python framework and command-line tool used to maintain code quality by running configurable checks and fixes before committing changes. It integrates with the version control systems like Git, executing pre-commit hooks on each commit. With pre-configured and custom hooks, it enforces code formatting and style guidelines. Enforcing quality standards, ensures clean and compliant code, improving overall codebase quality and reducing potential issues.

Key Features

• Pre-commit allows developers to configure a set of hooks, specifying the tools and checks to be run before committing code
• It seamlessly integrates with popular version control systems like Git automatically triggering pre-commit hooks on each commit
• Pre-commit provides a wide range of pre-configured hooks for common tasks such as code formatting, linting, and more
• Developers can define their custom hooks to run specific checks or perform additional tasks based on project requirements
• Certain hooks in pre-commit can automatically fix issues, saving time by applying fixes before committing changes
• pre-commit optimizes performance by running only the necessary hooks on modified files, reducing unnecessary checks on unchanged code
• It can be seamlessly integrated into existing development workflows, allowing for smooth adoption and integration with CI/CD pipelines
• pre-commit works across different operating systems, making it suitable for projects with diverse development environments
• It provides an easy-to-use configuration file format, allowing developers to define hooks and their configurations clearly and concisely

Use Cases

Pros and Cons

Requests

Stars: 49.5K |Forks: 9.1K |Contributors: 620

Type:  Library

Mainly used for: making HTTP requests

Install: python -m pip install requests

License: Apache-2.0 license

The Requests library is a popular Python library used for making HTTP requests. It provides a simplified and intuitive API for sending HTTP requests and handling responses. With Requests, developers can easily perform common HTTP operations such as GET, POST, PUT, DELETE, and more. The library supports various authentication methods, cookies, sessions, and SSL/TLS encryption. It also offers convenient features like automatic content decoding, JSON parsing, and file uploads. Requests are widely used for web scraping, interacting with RESTful APIs, testing web services, and building web applications that rely on making HTTP requests.

Key Features

• The requests library offers a user-friendly and intuitive API for simplifying the process of sending HTTP requests & handling responses
• It supports common HTTP verbs such as GET, POST, PUT, DELETE, and OPTIONS making it easy to interact with web services
• Requests support various authentication methods like Basic, Digest, and OAuth, ensuring secure communication with authenticated APIs
• The library provides support for sessions and cookies, allowing for efficient and stateful interactions with web applications
• Requests seamlessly handle SSL/TLS encryption, ensuring secure communication with servers that require it
• It provides convenient methods to access response headers, content, and status codes, simplifying the extraction of relevant information
• Requests automatically decode content based on response headers, making it easy to handle compressed or encoded responses
• The library includes built-in JSON parsing, simplifying the handling of JSON data returned from APIs
• Requests support file uploads as part of HTTP requests, making it useful for transferring files or making multipart/form-data requests
• Developers can easily set custom headers and query parameters in requests, allowing for flexibility in specifying request details
• Requests provide support for making HTTP requests through proxies, enabling communication with services behind firewalls or within restricted networks

Use Cases

Pros and Cons

NumPy

Stars: 23.5K |Forks: 8.1K |Contributors: 1479

Type:  Library

Mainly used for: Scientific Computing

Install: pip install numpy==1.24.1

License: BSD-3-Clause

NumPy is a Python library used for numeric computing. It provides efficient multidimensional array objects and functions for mathematical operations. With its powerful array manipulation capabilities, NumPy is widely employed in data analysis, scientific research, and machine learning. It serves as the footing for developing various other scientific and data-oriented Python libraries. NumPy has become essential for performing advanced numerical computations in Python with the functionalities like array indexing, slicing, and linear algebra operations.

Key Features

• NumPy provides efficient multidimensional array objects for numerical computing
• It offers a wide range of mathematical functions and operators for element-wise operations on arrays
• NumPy supports broadcasting, enabling operations between arrays of different shapes
• It provides flexible indexing and slicing capabilities for accessing and manipulating array elements
• NumPy includes comprehensive linear algebra functions for matrix operations and solving equations
• It seamlessly integrates with other scientific Python libraries for data analysis and computation
• NumPy’s array operations are implemented in optimized C code, ensuring fast and efficient computation

Use Cases

Pros and Cons

Pandas

Stars: 38.4K |Forks: 16.3K |Contributors: 2926

Type:  Library

Mainly used for: Analyzing data

Install: pip install pandas

License: BSD-3-Clause

Pandas is a Python library used for data manipulation and analysis. It offers high-performance data structures like Data Frames and Series, along with functions for data visualization and transformation. It provides powerful data indexing and slicing, handles missing data efficiently, and seamlessly integrates with other Python libraries like NumPy and Matplotlib, making it a valuable tool for data-centric workflows.

Key Features

• Data Frames for efficient manipulation and analysis of structured data
• Data cleaning and handling of missing data
• Data transformation operations like filtering, sorting, grouping, and reshaping
• Flexible indexing and slicing for extracting subsets of data
• Time series analysis with date/time indexing and operations
• Integration with other libraries like NumPy and Matplotlib
• Data visualization capabilities
• Input/output support for various file formats
• Flexible data structures beyond Data frames, such as Series, Panel, and MultiIndex

Use Cases

Pros and Cons

Pillow

Stars: 10.8K |Forks: 2K |Contributors: 378

Type:  Library

Mainly used for: Python Imaging Library

Install: pip install Pillow==9.4.0

License: HPND

The Pillow is a popular Python library for image processing and manipulation. It provides a wide range of functions and methods for opening, editing, enhancing, and saving images in various formats. The pillow supports basic image operations like cropping, resizing, rotating, and flipping. It also offers advanced image processing capabilities such as filtering, blending, and color adjustments. With Pillow, you can handle image metadata, apply text and graphic overlays, and perform image format conversions.

Key Features

• The pillow provides functions for image manipulation, including resizing, cropping, rotating, flipping, and adjusting image attributes
• It offers tools for image enhancement, such as brightness, contrast, sharpness adjustments, and color correction
• The pillow supports image filtering operations like blurring, sharpening, edge detection, and noise reduction
• It can read, save, and convert images in various formats such as JPEG, PNG, GIF, BMP, TIFF, and more
• The pillow allows access and modification of image metadata, including EXIF data
• You can add text and graphic overlays like watermarks or annotations to images using Pillow
• Pillow facilitates conversion between different image formats

Use Cases