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Python Frameworks for API Development
Aug 10, 2022by, Vaisali Sairam
API Development is a crucial sector of the IT industry that has undergone a lot of revolutionary changes in the last decade. With the emergence of new technologies, building these technological bridges and gateways has become much simpler and more efficient over time.
The technology we choose, its features, advantages, disadvantages, everything matters in the development process. APIs are usually simple bridges that connect different platforms, server ends, or applications. A lot of advancements in languages and technology have made API development simpler and more efficient. And a key player in the journey is the Python framework.
Python gained popularity in coding due to its platform-agnostic nature and requires no modification to run on any of the primary operating systems. It uses a simplified syntax with an emphasis on natural language, making it much easier for beginners. Python is also free to use and is supported by an extremely large system of libraries and packages, which makes it a popular choice for working with.
When it comes to building REST APIs, Python frameworks can provide various facilities to organise and monitor the application development processes across the client and server-side sub-systems of the application. Let us discuss the different Python Frameworks that do the magic in API Development. Some of the popular frameworks are Django, Fast API, Flask, Falcon, Hug, Cornice, Tornado, Bottle, TurboGears, Pylon, etc.
There are different ways to choose the right framework. The 3 main factors to be considered are,
- The application’s role and the end goal for which it works
- Scope, features provided, and the components of the framework
- The ability of the framework to handle a specific load.
Let us discuss 4 major Python frameworks that have brought remarkable changes in API Development.
Django is the most commonly used Python framework for API development. It is mostly used in cases where the API has to integrate multiple databases, handle complex schema migration benefits, and require high-level functionalities. It is a full-stack framework with multiple built-in authentication policies and higher usability. One of the main features of Django is the Object Relational Mapper (ORM), which facilitates the interaction and manipulation of data from a database. The other features such as URL routing, and database schema migration, also make Django a suitable option for API Development.
The Flask API is a lightweight and simple framework with minimal dependencies. It has fewer features. Yet it works almost as well as any full-stack framework. Flask is a micro-framework that can be used to access multiple HTTP methods. It is faster, supports easy NoSQL integration, and has extensive documentation.
Pylon is also a full-stack flexible Python framework that helps in making the development process fast and flexible. It is strongly influenced by the technology of many other Python frameworks and also uses SQLAlchemy, which is the most powerful database toolkit in Python, and SQLObject. Moreover, Pylon also works with many other Python projects to develop standard APIs that are reusable and interoperable.
Fast API is perhaps the most commonly used API development framework, as it is the fastest and most performant framework that is built for asynchronous programming. It uses the method of the Flask API for defining interfaces. It is a microframework that helps to reduce up to 40% of bugs generated due to the developer’s errors in the code. Moreover, the Fast API supports SQL, NoSQL databases, and GraphQL. All these features make it one of the most popular frameworks for API development.
There are several other popular Python Frameworks and there will be more to come in the future. Technologies get better and more efficient over time, and this will pave the way for more advancements in the future. The above-discussed Python frameworks have made API development more futuristic, efficient, simpler, and cost-effective. But it is not the final word yet. If you would like to know more about python frameworks and our services, click here.
Disclaimer: The opinions expressed in this article are those of the author(s) and do not necessarily reflect the positions of Dexlock.