Using Python to create your application testing environments? Well, you are not the only one! The simplicity, readability, and a huge community of this programming language has helped it to become probably the most popular framework in the market. This popularity has also given rise to a massive challenge. What’s that you ask? You will find there are thousands of Python frameworks that are available in the market.
So, how do you choose the perfect framework that suits all your requirements? Don’t worry! We are here for you! Our article will help you understand the fundamentals of Python frameworks and go through some of the major options that are currently available. We’ll also understand these frameworks so that they can suit your technical and business needs.
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What Are Python Frameworks?
Are you a new tester trying to implement Python frameworks? Then let’s begin our discussion with what are Python frameworks. A framework, in general, is a collection of packages, modules, and tools that help the application development process. In most cases they aim to set a convention for how to organize the code and all its related components.
You will see that modern frameworks come with a huge list of built-in features like URL routing, form handling, database connectivity, and user authentication. All these features help you handle the routine and other tedious tasks that are often related to the development cycle.
Now coming to Python frameworks, these are web hooks which consist of toolkits and libraries to help you build your modern web applications. However, you must remember that Python frameworks exist for other domains like data science, artificial intelligence, and desktop apps as well.
To help you with the understanding process, in this article, we are going to discuss only the context of Python frameworks for web app level development.
Why Use A Python Framework
Now, you might ask that instead of implementing the programming language directly, why should you even bother about using a web framework in the first place. To justify the inclusion of this process, let us go through the following parameters:
- With frameworks, you will have a set of predefined libraries, structures, and modules to massively reduce the amount of boilerplate code that you need to create. This inclusion will also help you reuse a huge section of the existing test code.
- Most Python frameworks usually come with built-in mechanisms against security issues. These can include issues like SQL injection, cross-site scripting, and cross-site request forgery. The advantage? No need to manually implement different security mechanisms for your web applications.
- By implementing a Python framework, you can have a consistent organization of files and code to improve the maintainability of the application in the long run. They also come with multiple style guides and best practices so that you can learn the good coding standards by following all these implementations.
- Finally, open-source frameworks like Python framework have a huge community of developers and testers who are always working to improve the testing experience with this intuition. Moreover, you can always refer to this community whenever you are stuck with any feature during the initial transition.
Most Popular Python Frameworks
To help you choose the perfect Python framework depending on your testing requirements, we have mentioned some of the most popular options that are currently available. While creating this list, we have ensured that we are extending all the general use cases of modern testers and developers:
1. Django
It is a full-stack Python framework that helps you implement rapid development while following the “batteries included” philosophy. This means that it will provide everything that you need out-of-the-box, like an ORM for database operations, an authentication system, and an administration back end.
By using this framework, you can perform everything, like handling forms, administering the back-end processes, and implementing security features.
So, who should choose Django? If you are a tester who needs comprehensive documentation, building admin interface, and a well-structured MVC, this should be a perfect option for you.
2. Flask
Flask is a very simple framework that comes under the micro-framework category as it provides basic routing and request-handling processes. To improve the capabilities of this framework, you can integrate libraries, database integrations, form handlings, and other requirements of the project. Out-of-the-box, it also comes with a large ecosystem of extensions like Flask-Login and Flask-SQLAlchemy.
So, who should choose Flask? If you’re looking for a straightforward and beginner-friendly Python framework with a large ecosystem of extensions for customizations, this should be your perfect option.
3. FastAPI
FastAPI is a new Python framework compared to all the other options that we have given in this list. It is built on top of Starlette for web routing and Pydantic for data handling. Using “asyncio” capabilities of Python, it will allow you to build highly performant APIs and services. Its execution speed is so fast, it is often compared to Node.js and Go.
So, who should choose FastAPI? If you are working on microservices or applications that need real-time features while maintaining its high performance, this should be a perfect option for you.
4. Tornado
Tornado is yet another comprehensive Python web framework and asynchronous networking library. While using this framework, you can implement long-lived connectors, WebSockets, and large numbers of concurrent requests. This will also be the perfect option for implementing high scalability due to its non-blocking I/O.
So who should choose Tornado? If you’re working on real-time applications like chat servers, streaming services, or event-driven backends that require frequent updates, this would be a perfect option for you.
5. Pyramid
A rather unique Python framework as it aims to be flexible enough for small apps while trying to be powerful enough for big complex applications. Out-of-the-box, it comes with a small set of code features and can extend its capabilities through multiple add-ons that are very easily available. It also aims to implement flexibility in templating, database usage, and the security of your applications.
So who should choose Pyramid? If you are working on projects which might start small but could scale in complexity over the execution time, you must seriously consider this option.
6. Web2py
Web2py Is the second full-stack framework on our list which has a strong synthesis on simplifying the entire test execution process for the testers. It has its own web-based IDE, a database abstraction layer, a powerful form builder, and an administrative interface. Why? To simplify the entire test management process for new developers and testers.
So who should choose Web2py? If you are working on educational projects, quick prototypes, and internal tools which can benefit from the integrated web-based IDE, this will be a perfect option for you.
Confused with so many options that we have mentioned? Don’t panic! The following table will help you summarize the advantages and disadvantages of all the options so that you can take a quick decision.
| Framework | Category | Pros | Cons |
| Django | Full-Stack | Batteries included, large community, admin interface, secure by default | Can be heavy for small apps, steeper learning curve |
| Flask | Microframework | Lightweight, flexible, large extensions ecosystem, easy to learn | Requires more configuration, potential fragmentation in large projects |
| FastAPI | Asynchronous | High performance, modern design, automatic API docs, data validation | Relatively new, ecosystem is still growing |
| Tornado | Asynchronous | Excellent for real-time apps (WebSockets), non-blocking I/O | Smaller community, less straightforward for traditional CRUD apps |
| Pyramid | General-Purpose | Flexible, good scalability, stable releases | Fewer out-of-the-box features, smaller ecosystem |
| Web2py | Full-Stack | Integrated web-based IDE, simple for rapid dev, minimal config | Highly opinionated, smaller community |
Best Practices for Framework Adoption
Apart from choosing the correct Python framework depending on your requirements, it is equally important to have some of the best practices in mind so that you can utilize the full potential of your entire testing workflow. To shed more light over this segment, we have mentioned some of the major best practices that we recommend you to integrate:
Version Control Everything
We strongly recommend you to keep all your application code, including the configuration files, in a version control system like Git. Using this approach, you can make the collaboration, rollbacks, and DevOps practices even smoother during the test implementation process.
Cloud Testing With Python Frameworks
We also suggest you to integrate your chosen Python frameworks with cloud platforms like LambdaTest. This will help you run all the test scripts over remote servers. To shed more light over this segment, let us consider the example of integrating LambdaTest with 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.
Don’t know what is Selenium? Don’t worry! It is a very popular automation test suite to execute automated web app testing. For the integration process, you will have to use the Selenium Grid, a component of the suite, along with FastAPI. It will also help you build APIs and verify the functioning of the endpoints in different servers.
To help you further understand the implementation process, we have given a sample code snippet below that aims to achieve this goal on different browsers:
Read The Documentation
Whenever you’re adopting any new tool or framework, like a Python framework, it is very important to go through the official documentation of your chosen option. This will provide you with multiple conventions and best practices to ensure a smooth test execution process. This practice will be very important to avoid common errors and confusions in the test cycle.
Use Virtual Test Environments
We would strongly recommend you to use tools like Virtualenv or Conda to isolate the dependencies in the testing environment. This approach will be very important to ensure that the local development environment is matching the production environment as closely as possible. The advantage? Ensuring the smooth execution of frameworks which rely on specific versions of certain libraries.
The Bottom Line
Based on all the areas that we have discovered in this article, we can easily say that having knowledge about Python frameworks to choose the correct one is very important so that you can massively improve your development speed, scalability, and, the long-term maintainability of your application infrastructure.
We’d also suggest the testers to consider that in most of the complex scenarios, you will find that there isn’t a single best framework but multiple frameworks that will be suitable for different areas of the application development and testing cycle.
Finally, by also implementing the right Python framework with all the best practices that we have mentioned in this article, you can ensure proper version control, security, and testing practices throughout the environment.
