Django vs Flask vs FastAPI &#8211; A Comparative Guide to Python Web Frameworks
There are many frameworks used in web application development, each of them has its own advantages and limitations. To develop a python based web application, there are three frameworks used very popularly – Django, Flask and FastAPI. Here in the article, we will discuss these three frameworks used for python-based web application development. Along with understanding these frameworks, we will also try to understand their advantages and disadvantages. Finally, we will do a comparative analysis of these frameworks based on several important parameters. The following major points we will cover in this article. Also read: Complete Hands-On Guide To FastAPI With Machine Learning DeploymentFastAPI vs Flask: Comparison Guide for Data Science EnthusiastsHere’s What You Can Expect From The Django 3.0 ReleaseDjango vs Flask: A Look At The Two Popular Python Web FrameworksComplete Guide To Model Deployment Using Flask in Google Cloud Platform Let’s begin by discussing the Django framework. Django What is Django framework? Django is a web framework based on python which is free and open source. The architecture pattern which it follows is the model-template-views architecture pattern. It was created by Adrian Holovaty and Simon Willison in 2003. Nowadays it is one of the most popular frameworks in the world because of its robust behaviour. One of the primary goals of Django is to make it easy to develop complex database-driven websites. It is used by some of the giant websites like Instagram, Mozilla, Nextdoor, and clubhouse. The reasons for being famous are less code, low coupling and reusability, and pluggability of components in the time of development. Also, these features help in the rapid development. Advantages of Django Despite having its own nomenclature it generates the HTTP responses and also the core of the framework can be considered as the MVC( model-view-controller) architecture. Where the architecture is commonly used for developing user interfaces consisting of three main components. The basic structure and components of the MVC architecture are represented in the following image. Where the model manages the data of the application, the view renders the user interface of the model, and the controller controls the input and the interaction between user and model. The framework consists of the ORM( object-relational mapper), relational database, web templating system, and URL dispatchers. Where the ORM links between the models, HTTP requests handled by the relational database and. URL dispatcher is the controller based on regular expressions.The contib package of the Django framework is used for bundling a number of applications. We can allow the thyroid party code into a running project using Django’s configuration system. It follows the reusable app convention.In the framework, we have more than 2500 packages with the solution of the problem on which this does not work. This can be helpful in extending the behaviour of the framework.The framework automatically enables security against most of the typical web attacks like cross-site request forgery, cross-site scripting, SQL injection, password cracking. Also, it can be considered as a tool for generating Google sitemaps and GIS applications. Django provides the rest framework with powerful API functionality. The rest framework has a built-in API browser for testing endpoints and Django with rest framework provides facility of authentication and permission rules with the framework. Disadvantages of Django Django frameworks have no conventions. Often when configuring “on-the-go” makes the components mismatched. Since everything has to be well defined in the process, this leads to a slower speed of development.   Sometimes Django is not appropriate for small projects with few features because the functionality of the framework can confuse the developer.A very small count of dependencies of the framework makes the Django monolithic wherein development we need to consider the framework as a single package. The lower number of dependencies makes the development be completed with a large amount of code.Django comes up with a lot of features and configurations which is the reason it cannot be learned fast by the user.The request for every individual process makes the Django development process slower. Flask What is Flask framework? Flask is a web framework developed in python. flask is a microframework because of no requirement of any particular library or tools in the web development with it. Common functionality provided by pre-existing third-party libraries. With the help of flask, we can build web apps with the python programming language. The primary goal of this framework is to develop lightweight applications with lower features in an easy and fast way. Flask is based on werkzeug, jinja, MarkupSafe, ItsDangerous. Which all are part of the pallet projects. Advantages of Flask We can alter most of the parts safely and easily of flask because of its simplicity and minimalism.We can create multiple applications or servers using modular codes of flasks which can be distributed across the large network each with specific tasks. This makes the applications more efficient and better performing.With a better understanding of python, it becomes easy to develop flask applications. The Flask developed application is more scalable than the monolithic application. Because according to new methods the application runs in the containers with auto-scaling. Monolith applications do not scale themselves. Disadvantages of Flask Flask is not standardized in most of the organization. The knowledge about any framework we get using flask doesn’t help in the other frameworks like Django. So it becomes difficult sometimes to switch from flask to any other framework.Less no of tools makes a developer develop more things on his own or we require to search a lot for libraries and extensions to complete the deployment.Most of the time networks of applications have a single source that needs to handle the request one after another regardless of multiple requests at a time which makes the application more time taking. FastAPI What is FastAPI? FastAPI is a modern, fast and robust framework that helps in building APIs with python 3.6+ versions. It is considered to be one of the fastest python frameworks. It is a framework that is fast to code with fewer bugs induced by the developers. The primary focus of the FastAPI are, in Fast developmentFewer bugsHigh and fast performance. Companies like Netflix and Uber are using this framework which fully supports asynchronous programming and can run with WSGI(Web Server Gateway interface) and ASGI(Asynchronous Server Gateway Interface).FastAPI is a crucial element that brings Starlette, Pydantic, OpenAPI, and JSON Schema together. Advantages of FastAPI FastAPI helps in validating the datatype from the developer even in nested JSON requests. It gives the autocomplete feature which helps in producing applications with less amount of effort and also less time in debugging. It is based and also compatible with the OpenAPI(An open API  is a publicly available application programming interface that provides developers with programmatic access to a proprietary software application or web service), JSON Schema(JSON Schema is a vocabulary that allows you to annotate and validate JSON documents).FastAPI makes it easy to build a GraphQL API with a Python library called graphene-python.FastAPI integrates well with OAuth 2.0 and external providers. Disadvantages of FastAPI FastAPI is a relatively new framework so the guideline community is small. We have lower external educational information like books, courses, or tutorials.Since in the development of the applications we need to tie everything together in the FastAPI application which causes the main file to become very long or crowded. Comparing Django vs Flask vs FastAPI As we have discussed earlier in the article that every framework has its own advantages and disadvantages, let’s compare them based on the following parameters: Packages: As we have seen, Django has more than 2500 packages in its library which can be considered as the full-stack web development framework. Flask is a microframework and FastAPI also has lower packages than Django. Community: Since there are a variety of uses of the Django framework, it has been released earlier than flask and FastAPI so It has the most significant community among all of these frameworks. We have a large number of tutorials for the Django framework after that we have many tutorials for Flask. Since FastAPI is a modern framework it has a low number of external information. Performance: Since the FastAPI has its main focus on high performance we can say it is the fastest framework among all of them, Flask is also a high-performance API because of its micro-framework feature and gives higher performance than Django. Flexibility: While developing an application the focus of any developer comes on the flexibility of the framework so that it can alter parts of the application in the future if further updates require changes. In the case of flexibility, flask supports changes in almost every part of the applications so we can say here it is the most flexible Final Words Through this article, we came to know about the three most globally famous web frameworks based on python. They all have something best about themselves like if we need high performance in the application we can choose the FastAPI, or in case of flexibility, nothing is more flexible than Flask among all these frameworks. When we talk about Django we can use this framework as a full-stack development framework because it provides various facilities which can be very helpful in developing a large number of functionalities in one application because of its robust behaviour.
goals of Django is to make it easy to develop complex database-driven websites, flask is a microframework because of no requirement of any particular library or tools, fastAPI is considered to be one of the fastest python frameworks.
In this article, we will do a comparative analysis of these frameworks based on several important parameters.
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Yugesh is a graduate in automobile engineering and worked as a data analyst intern. He completed several Data Science projects. He has a strong interest in Deep Learning and writing blogs on data science and machine learning.