Are you a software developer working on a web application? Yes? You must have heard or used Python at least once in the development project. Why do we claim so? Python is the most used programming language due to its simple, versatile, and extensive ecosystem. You can integrate modern Python frameworks for creating APIs, data-driven projects, or a complete automation tool.
However, for the proper implementation, it is very important to choose the correct Python framework that suits your requirements and also the preferences. Confused about choosing the right Python framework? Don’t worry! We are here for you.
Our article will help you go through some of the most popular Python frameworks that are currently available in the market. During our discussion, we’ll also analyze these frameworks depending on various requirements so that you can choose the best one for your project.
What Are Python Frameworks
Before we start analyzing all the popular Python frameworks, we must go to its basics in case you are not familiar with what is a Python framework. In the current stage, you can classify these frameworks into three of the following categories:
- The full-stack frameworks will provide built-in functionalities for database integration, form validation, and template rendering. In simple terms, these are independent frameworks that can work on their own without depending on any other third-party module or library.
- On the other hand, micro frameworks are lightweight frameworks which will still require additional components to properly extend their functionalities. Moreover, you also need to add various other libraries and modules with these frameworks so that you can implement them in your testing environment.
- And lastly, asynchronous frameworks are designed for handling asynchronous tasks and high performance applications. These frameworks are best suited for a complex testing environment that will be handling multiple elements like front end and back end for a massive application.
How To Choose Python Frameworks
Before choosing the perfect Python framework depending on the needs of your application development project, you must have a clear understanding of what you are looking for in the market. To help you further with the decision-making process, we have mentioned some of the major factors that you must consider for the same:
- The first thing is to consider the project requirements based on its complexity. For example, whether it is a web development project, data processing action, or a simple automation requirement. This will have a very important role in choosing the perfect framework for the purpose.
- You must choose a framework that supports future growth and changing business needs. This will become even more important when you’re working on certain applications that undergo frequent updates to add or remove features.
- You must consider the learning curve that comes almost every time with any new tool, platform, or framework integration. It is also important to go through the available documentation so that you have enough resources for the beginners and also for the veteran testers to get started with this framework.
- You must choose a well-supported framework which will provide faster troubleshooting and updates. If your chosen framework is open-source, there is a high chance that it will have a community of enthusiastic developers who will assist you at every stage of the implementation process.
- It is a common idea that there will be certain frameworks which are better optimized for high-performance applications. So, depending on the requirements of the project, you must choose these frameworks accordingly.
- Finally, you must look for all the built-in security features available with the Python frameworks. This will be one of the most important requirements for applications that will be handling sensitive user information. Some of the major apps in this category include health apps, banking apps, and shopping apps.
Popular Python Frameworks and Their Use Cases
A quick glance of the current application development market will easily reveal that there are multiple popular Python frameworks out there. However, it is very important to align your development requirements and personal preferences to choose the perfect one from this huge list.
To help you with the understanding process, we have mentioned some of the most common names in the market depending on the multiple use cases:
Django
Django is the best option for a full-stack Python framework that is suited for large applications, enterprise solutions, and apps that require rapid development.
This framework follows the model view template platform and is also available with built-in authentication and multiple other security features. Since this framework comes with an object relational mapping, you can use it to implement better data management.
Django also provides scalable solutions and supports high-traffic use cases to properly ensure the functioning of the application when exposed to various real world use cases.
Flask
Flask, on the other hand, is a minimal Python micro framework that is suitable for small to medium applications, APIs, and application development projects which require flexibility.
It is a lightweight and easy-to-get-started framework which does not enforce a particular structure to allow more flexibility. Flask also supports extensions for additional functionality while being well-suited for microservices and rest API.
FastAPI
FastAPI, on the other hand, is a high-performance API development tool that can help build high-performance APIs with asynchronous support.
It implements the asynchronous capabilities using ‘async’ and ‘await’ methods. It can also help you to auto-generate interactive API documentations using Swagger and Redoc. This framework is optimized for performance and it’s nearly as fast and responsive as node.js.
Tornado
Tornado is a real-time asynchronous processing tool that is best for applications which require WebSockets, real-time interactions, and high concurrency.
This framework also supports asynchronous networking and WebSockets so that it can handle thousands of simultaneous connections very easily. Therefore, it is the ideal option for chat applications and real-time analytics.
Pyramid
Pyramid is a flexible and scalable Python framework which is designed for developers who want flexibility without imposing heavy constraints on the implementation process.
This framework works well for both small and large organizations as it supports authentication and authorization. It also comes with an extensible and modular architecture so that you can constantly add or remove the test cases depending on the changing requirements of the application.
CherryPy
CherryPy is yet another minimalist wave framework that is targeted for developers who are looking for an object-oriented web framework. It has the capability to run as a standalone web server and is also available with built-in support for multiple HTTP servers. It is also easy for newcomers and beginners as it comes with minimal dependencies and also supports easy deployment.
Bottle
Bottle is a micro framework which targets simplicity as one of its major selling points. Therefore, it is the best option if you’re working on small applications, prototyping projects, or embedded systems.
It is also very simple and easy to set up as it comes with single file deployment that does not have any form of dependency restrictions. It is also idle for fast API development as it comes with a built-in template engine.
Sanic
Finally, Sanic is an asynchronous web framework which is developed for speedy application deployment. Therefore, it will be your best option for high-performance web apps that require non-blocking operations.
Since this framework is built on ‘asyncio,’ it provides better speed and performance. It also supports HTTP/2 and WebSockets while being lightweight and fast.
Also Read:Soujiyi.com: Your Ultimate Tool for Smarter Email Marketing
Comparing Python Frameworks
Based on all the factors that we have mentioned about each of the most popular Python frameworks, we have created a comparison table so that you can easily grasp the main differentiating factors to make an informed decision:
| Framework | Type | Performance | Ease of Use | Scalability | Best For |
| Django | Full-stack | Moderate | Easy | High | Large web apps |
| Flask | Micro | Moderate | Very Easy | Moderate | Small web apps, APIs |
| FastAPI | Micro | High | Easy | High | APIs, async apps |
| Tornado | Async | High | Moderate | High | Real-time apps |
| Pyramid | Full-stack | Moderate | Moderate | High | Enterprise apps |
| CherryPy | Micro | Moderate | Moderate | Moderate | Lightweight apps |
| Bottle | Micro | Moderate | Very Easy | Low | Prototyping |
| Sanic | Async | High | Moderate | High | High-performance apps |
Integrating Python Frameworks With Cloud Platforms
You can also consider executing your chosen Python framework with cloud platforms like LambdaTest for executing the test cases over remote servers. To shed more light over this segment, let us consider the example of integrating FastAPI with LambdaTest and Selenium.
LambdaTest is an AI-native test orchestration and execution platform that lets you perform manual and automation testing at scale with over 3000+ browsers, OS combinations and 5000+ real devices.
If you don’t know what is Selenium, it is one of the most popular browser automation test suites that you can integrate with your testing environment to execute automated cross-browser testing.
- The first step in the integration process is to ensure that Selenium is installed on your system. You can easily perform this process by executing the following code snippet in the terminal window:
pip install selenium
- The next step is to configure the Selenium WebDriver, a component of the Selenium test suite, to run the test cases using the LambdaTest cloud grid.
- Now you can integrate FastAPI with this configuration to build APIs and also verify the functioning of the endpoints in different servers, using the capabilities of LambdaTest. The following code snippet will help you install fast API and its requests:
pip install fastapi requests selenium
- You have to use the code that we mentioned below to create a FastAPI application that can run in the selenium background:
- Finally, you can use Selenium to automate testing of your FastAPI endpoints on different browsers. To put more light over this segment, we have mentioned a sample code for the same:
The Bottom Line
Based on all the factors that we have put forward in this article, we can easily say that the right Python framework will depend on your project’s needs, performance requirements, and scalability preferences. Based on the general requirements, Django and Flask will remain your top preferences for web development.
If you’re looking for Python frameworks for modern API development, you should consider FastAPI. It is very important to evaluate the features and align them with your requirements to make an informed decision for the efficiency and success of your overall application development project.
Still unsure about the perfect Python framework? Build a small project with different frameworks and see how each one fits depending on your development style and project needs. This will help you filter out the best option for you.
