Types of Python Frameworks
1. Micro Frameworks
Micro frameworks, for example, Flask, Bottle, and CherryPy, are designed specifically to be simple and lightweight. They have limited dependencies and prioritize essential features for web development.
2. Full-Stack Frameworks
Full-stack frameworks provide a comprehensive web development solution. They feature form generators, form validation, and template layouts. Some of the examples of full-stack frameworks include Django, Giotto, and CubicWeb
3. GUI Frameworks
Python GUI frameworks like Tkinter, PyQt, Kivy, wxPython, and PySimpleGUI allow creating graphical user interfaces (GUIs) for apps, making them appealing and user-friendly. They provide tools to simplify the development of interfaces with widgets, such as buttons, menus, and windows.
4. Asynchronous Frameworks
Asynchronous frameworks like Tornado, Sanic, and AIOHTTP make use of the asyncio library, aiming to handle concurrent operations. It makes them suitable for real-time applications and high-performance tasks.
5. Testing Frameworks
Python testing frameworks like Pytest, Unittest (PyUnit), Robot Framework, Behave, and Lettuce automate the software process of software solutions, ensuring errors are detected early in the development cycle and optimizing code quality.
Popular Python Frameworks and Libraries
Most popular Python frameworks include Django, Falcon, Flask, FastAPI, and more—each well-suited for different web development needs. If you’re deciding between API-focused frameworks, understanding the differences in FastAPI vs Flask can help determine which is the right fit for your project.
Python libraries like NumPy, Pandas, and SciPy play a significant role in data science and scientific computing. Furthermore, frameworks like Streamlit and Anvil help create web applications with minimal code. Mentioned below are the top Python frameworks and libraries you need to know:
. Django
This is an open-source web development framework built using Python to create complex code for web apps’ backends. It follows the model-template-views architectural pattern and is maintained by the Django software foundation. The framework is known as one of the simplest, and most flexible frameworks that is less time-consuming, too.
Features of Django
- Makes use of MVC (Model-View-Controller) architecture
- Easy to understand, use, and extend
- Modular approach, allowing additional features to be included in the framework
- Built-in security features include user authentication and protection against common attacks like SQL injection
2. Flask
Flask tends to be a microweb framework developed based on Python. Since it doesn’t require specific tools and libraries, Flask is classified as a microframework. However, it supports extensions to add features as if they were integrated into Flask itself. Inspired by the Sinatra Ruby framework, the framework needs the Werkzeug WSGI toolkit and Jinja2 template. Because of its lightweight and modular construction, Flask is conveniently adjustable.
Features of Flask
- Development server and debugger
- Integrated support for unit testing
- Supports secure cookies
- RESTful request dispatching
- HTTP request handling
- Extensions for extended functionality
3. Falcon
Falcon tends to be a minimalist ASGI/WSGI framework used to build mission-critical REST APIs and microservices, focussing on correctness, reliability, and performance at scale.
Features of Falcon
- ASGI, WSGI, and WebSocket support
- Native asyncio support
- Strict adherence to RFCs
- Python 3.5+ and PyPy 3.5+ support
- Simple API modeling through centralized RESTful routing
- Highly optimized and extensible codebase
- Stable interfaces with an emphasis on backward compatibility
4. CherryPy
Built using Python, CherryPy is an object-oriented web application framework. It is designed for the rapid development of web applications. The framework is lightweight and fast that’s easy to install. Besides, CherryPy provides support for sockets, threads, and protocols.
Features of CherryPy
- HTTP/1.1-compliant, WSGI thread-pooled webserver
- Easy to run multiple HTTP servers
- Support for multiple WSGI servers
- Runs on Python 2.7+, 3.5+, PyPy, Jython, and Android
- Built-in profiling, coverage, and testing support
- Minimalistic syntax to write reusable code
- Comprehensive access to low-level modules
- Logging handler to handle errors in any part of the application
- Very minimal syntax to write reusable code
- Automatic process management in the background
5. Dash
Built using Python, Dash is a framework used to build web applications. It offers a next-level development environment for web applications. Dash can be used as a standalone library or integrated with Apache, Nginx, or any large-scale server. Consider relying on Dash if you’re looking for a framework for web development using Python.
Features of Dash
- Easy-to-use interface with excellent control structure and enhanced support for custom objects.
- Comprehensive access to low-level modules, including external libraries such as XML, and JSON.
6. Web2py
Written in the Python programming language, Web2py is an open-source framework for web application development. It allows developers to program dynamic web content making use of Python.
Features of Web2py
- Built-in components
- Database Abstraction Layer (DAL)
- jQuery for Ajax and UI effects
- Caching
- Robust security
7. Tornado
Tornado is a scalable framework for real-time web application development. Its non-blocking network I/O enables Python to manage hundreds and thousands of open connections, while its synchronous programming model is developed aiming at handling long-lasting network connections. For example, it helps to solve the “C10k problem.
Features of Tornado
- High-performance
- Non-blocking Network I/O
- Asynchronous I/O Library
- WebSocket support
- Enhanced flexibility and scalability
- Robust security
8. Bottle
The Bottle is a simple, fast, and lightweight WSGI microweb framework built based on Python programming language. It makes use of the WSGI application call interface; that’s one of the excellent ways to run a web server. The framework is distributed as a single file module with no dependency except the Python Standard Library. The Bottle is considerably easy but needs some knowledge of WSGI execution.
Feature of Bottle
- Built-in template engine and supports Jinja2, mako, and cheetah templates
- Built-in development server that works with a variety of WSGI-capable HTTP servers
- REST framework support
- Ease of extension by using plugins
- Ajax support
- Complete support of WSGI-based server frameworks
- Reliable schematics with configuration management features
9. CubicWeb
Last but not least, CubicWeb is one of the lightweight web frameworks developed in Python. It’s easy to install, provides support for many protocols, and can easily handle any processing size.
Features of CubicWeb
- Supports sockets, threads, and a wide variety of programming languages, including Ruby, PHP, etc.
- Supports various protocols, like HTTP, on one application.
- Complete access to low-level modules such as external libraries, including XML, and JSON.
- Pre-built modules like Nginx or Apache Web Server.
- Automated process management with in-process cache management facilities.
10. Pandas
Pandas is a powerful Python library for data analysis and manipulation that offers data structures like DataFrames and Series. It provides efficient data structures, specifically the DataFrame, to work with tabular data, and a rich set of functions aiming for data analysis, cleaning, and visualization
Features of Pandas
- Provides Dataframe, a two-dimensional labeled data structure embedded with columns of different types, similar to a spreadsheet or SQL table.
- It imports data from different sources like CSV, Excel, databases, etc., and exports to various formats.
- Handles missing data, removes duplicates, and transforms data types.
- Performs reshaping, sorting, filtering, and grouping data.
- Pandas is well-supported with a large and active community.
11. Numpy
Last but not least, NumPy is a foundational Python library aimed at scientific computing. It offers efficient numerical operations and tools for data analysis. Numpy’s core feature is the ndarray, which is a powerful multidimensional array object, providing versatile and fast manipulation of numerical data.
Features of Numpy
- Multidimensional Arrays (ndarrays) for efficient storage and manipulation of homogeneous data in multiple dimensions.
- Efficient Mathematical Operations for a vast collection of pre-built functions to perform mathematical operations on arrays, like arithmetic, statistical, and trigonometric functions.
- Broadcasting, a robust feature for element-wise operations on arrays of different shapes, automatically expands the smaller array to match the shape of the larger array.
How to Develop Software Using Python?
Similar to other software development, building software using Python involves many stages. These stages include outlining your goals, hiring the right Python development partner, planning the tech stack, developing the software, testing, launching, and scaling. Here’s how each stage contributes to the software development with Python:
1. Outline Your Python Software Goals
This phase includes clearly defining the need, identifying the purpose, target audience, and key features of prospective software. Be it a web app, a data processing tool, or an automation tool, a well-articulated goal assists developers in shaping the development direction while ensuring everyone is aligned from the very beginning.
Key Tasks:
- Conducting market/user research
- Drafting feature list and use cases
- Defining software objectives and KPIs
2. Hire the Right Development Team
In this stage, businesses hire Python developers familiar with Python’s tools, libraries, and ecosystem relevant to the project. It might be Django for web development, Flask for APIs, or TensorFlow for AI development services.
Key Tasks:
- Evaluating technical expertise and project experience
- Considering freelancers, agencies, or an in-house team
- Assessing project management, communication, and cultural fit
3. Plan the Tech Stack and Frameworks
This stage of Python software development deals with selecting the right tools and technologies to support your software’s goals. Since Python has a vast ecosystem, opting for the appropriate frameworks, databases, and integrations is crucial to ensure enhanced performance, scalability, and development speed.
Key Considerations for Technology Selection:
- Web frameworks like Django, Flask
- Front-end technologies like React, Vue.js
- Databases, for example, PostgreSQL, MongoDB
- Hosting/Cloud platforms involve AWS, Heroku
4. Development and Testing
This phase includes writing clean, maintainable code and testing the software. Python provides support for test-driven development (TDD) and tools for unit, integration, and functional testing. It helps ensure the software remains robust and bug-free.
Key Practices:
- Agile development with sprints and iterations
- Version control like Git
- Automated testing and continuous integration
- Code reviews and quality assurance
5. Launch and Scale
In this stage, the product gets deployed to the intended environment. Once it’s deployed, the developers keep monitoring its performance and gather user feedback. As user demand grows, they make adjustments to scale the infrastructure, optimize features, and ensure security and uptime.
Key Actions:
- Using CI/CD pipelines for deployment
- Setting up monitoring and analytics tools
- Preparing for scalability (load balancing, caching, database optimization)
- Rolling out updates and gathering user feedback
Real-Life Examples of Applications Built Using Python
Some prominent examples of the software built using Python include YouTube, Instagram, Netflix, Amazon, Pinterest, Dropbox, and many more. Here’s all about the real-life application of Python:
- Facebook: It uses Python for several aspects, including backend services, automation and scripting, prototyping, APIs and microservices, testing and quality assurance, and so on.
- Instagram: Python is used in Instagram’s backend infrastructure, and it plays a significant role when it comes to handling requests, managing databases, and ensuring an enhanced user experience.
- Netflix: Netflix chose Python for its various attributes, such as Python’s several modules, its excellence in video processing and data science as well as animated and VFX content creation.
- YouTube: The platform employs Python for multiple aspects like website templates, backend operations, video controls, and many more.
- Amazon: Backend web development, data processing, server-side code, and many others that Python can do, but the main reason Amazon mostly prefers Python is its ability to handle big data.
- Pinterest: Pinterest, an image-based social media platform, employs Python primarily for its ease of use and extensive libraries. It leverages Python for many aspects like backend development, machine learning, data processing, automation and scripting, etc.
- Spotify: Spotify makes use of Python for the backend and data analysis because of its exceptional speed and the benefits of machine learning.
- Uber: Uber chose Python for backend and frontend functions. The platform needs to make many calculations; hence, Uber’s backend is built using Python, which anticipates booking and services, traffic, arrival times, approximate reaching time to the destination, and more.
- Quora: The very platform makes use of Python for its robust ecosystem, excellent development speed, enhanced flexibility, wider community support, and the like.
Choosing MindInventory: A Smart Move for Premier Python Development
Working for more than a decade, MindInventory is a trendsetter when it comes to providing robust, and high-end software development services to businesses worldwide. We have built various high-end tailored solutions using Python, including CodeDog, Sidepocket, Zammans, and Bipedai that glimpse our dexterity and accomplishment in software development with Python.
CodeDog is an open-source project that automates speech-to-text, and text-to-speech conversion. It has become a reliable platform, making communication more accessible and efficient to people from a diverse background and use cases.
Sidepocket tends to be a tactical asset allocation robo-advising app, designed to decrease the drawdown and risk while increasing the diversification and profits to help individuals with transformative approaches to investment. Sidepocket experienced a 95% accuracy rate, 70%
increase in app performance, and a 15% increase in revenue.
Zammans is a holiday home booking platform, revolutionizing the way travelers find and manage their accommodations. We helped Zammans establish a dedicated support system and enhance user experience. The client received a 21% hike in revenues, 10K+ user inquiries monthly, and 4.2* rating online.
Last but not least, we built BipedAI, a smart navigation harness wearable over the shoulders and tailored for blind/visually impaired people as well as hemispatial neglect patients. The product delivered a 75% improvement in obstacle avoidance efficiency, a 60% reduction in navigation-related stress, and a 50% enhancement in user satisfaction relating to GPS instructions.
Do you have an innovative software development idea? If yes, hire Python developers, build your own team, and get your unique software development idea turned into a reality that meets your expectations!
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