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Though the names are different, these three frameworks FastAPI, Flask, and Django have a common similarity in that is they are web frameworks written using the Python language. These three frameworks have been used by developers for a variety of purposes. The three frameworks have distinct features that serve the best in development. Let us look at how these frameworks differ from each other in this article.

FastAPI

Fast API is a Python-based web framework that enables us to use the REST interface in development. It is a fast and high-performance framework to build APIs with the latest Python 3.6+, created by Sebastian Ramirez. Some of the popular features of the FastAPI include:

• Fast: As the name indicates, Fast API is the very fastest framework in Python with higher performance similar to NodeJS and GO.
• Faster Coding: Development speed has been increased from 200% to 300%
• Fewer Bugs: Human-made errors are reduced by 40%. Debugging time is less.
• Easy and Short: The framework is easy to use and it has less code duplication. So each parameter has multiple features and very few bugs.
• Robust: It provides automatic interactive documentation along with production-ready code.
• Standards: The framework is based on the OpenAPI and JSON Schema.
• Editor support: FastAPI is intuitive to use and the feature “Autocompletion” remains a favorite for all.

Pros:

• FastAPI offers validation of the developer’s data types and the deeply nested JSON requests.
• FastAPI has been developed using standards such as OAuth 2.0, JSON Schema, and OpenAPI.
• Building GraphQLAPI with graphene-python, a python library is easy using FastAPI.

Cons:

• It has a small community and lesser educational resources, as it newly emerges.

Read our article on – Python Basics: Data types

Flask

Flask is a Python-based micro web framework for developing web applications. It was created by Armin Ronacher. Since it is a microframework, it doesn’t have particular tools, libraries, or ORM (Object Relational Manager). Flask is a WSGI (webServer Gateway Interface) web application framework and doesn’t have features like template engine, routing, and more. The framework is based on WSGI and the Jinja2 template engine. Some of the notable features of flask include:

• Pythonic: Flask is entirely based on Python and very easy to get started with.
• Simple: Since Flask is a micro-framework, it is very simple and also extensible.
• Updated: Flask is a modern framework and its features are up-to-date.
• Readability: The framework is very explicit and it has better readability.
• Less complexity: You can save your program on multiple files, reducing the complexity.

Pros:

• Flask is more comfortable and flexible for the developers to use.
• Unit testing is possible with Flask. It enables you to tweak extensions and transit to a web framework.
• Flask is very simple and beginner-friendly.
• It lets you create apps faster and with minimal effort.

Cons:

• Security is a concern here as it uses modules that cause third-party involvement.
• Flask has a single source and multiple requests take time as it processes them one after the other.

Django

Django is also a python based web framework that uses the MTV (Model Template View) architectural pattern. It is an open-source framework developed by Adrian Holovaty and Simon Willison in 2005. The top features of Django include:

• Well documented: It is a well-established framework for the developers as it provides excellent documentation.
• Python-based: Since it is python based, Django is simple and easy to use.
• SEO Optimized: Django helps in maintaining the website through URLs which makes it efficient and easy for SEO engineers.
• Scalability: The level of implementation using Django is high. It helps in creating applications with greater precision and error-free.
• Security: Django provides security with expertise level of code.

Pros:

• The code structure of Django is efficient and using this, it is very easy to infuse more functionalities into the websites for the developers.
• Django is more flexible as it uses the Rest framework called Django Rest Framework (DRF).
• With Django, it is easy to build web APIs since it has a customizable and modular architecture.
• Django ensures security by protecting against joint SQL injection and forgery attacks from cross-site requests.

Cons:

• With Django, the speed is limited because of more reusable modules.

Read our article on – Python Basics: Functions and Variable Scopes

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We have seen the three frameworks separately and let’s compare them with each other now.

Features

• FastAPI
  • Packages – Minimalistic framework that doesn’t have reusability enabling packages.
  • Community – Has small community
  • Performance – High performant and faster
  • Job Openings – Fewer opportunities
  • Education – Easiest to learn but has very few online resources

• Flask
  • Packages – Minimalistic framework that doesn’t have reusability enabling packages.
  • Community – Has a moderate, thriving community
  • Performance – Moderate in speed
  • Job Openings – Moderate
  • Education – Easy to learn and has many online materials.

• Django
  • Packages – Full-stack web development framework that has reusability enabling packages.
  • Community – Has the most significant community.
  • Performance – Not so fast
  • Job Openings – More opportunities for job
  • Education – Learning Django is a bit harder but has many online resources available.

Conclusion

All three frameworks are effective for developing web applications as all the three are python based web frameworks. However, choosing the right one for you is in your hand. If you are looking to develop a full-stack website with high performance and functionalities, you can opt for Django. If you are aiming on developing a prototype for a web application and APIs or someone interested in machine learning, then Flask is ideal for you. FastAPI is suitable for someone who wants to focus on speed and scalability. Otherwise, all the three are good and suit you according to your requirements.

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Python helps in doing a number of things nowadays. Likewise, it establishes its importance in web scrapping. Web scrapping deals with extracting data from the web, manipulating and cleaning the data. This article will help you in learning about Web scrapping and how it is done using Python libraries.

What is Web Scraping?

An automated method that extracts an enormous amount of data from websites called Web Scraping. The data available on the websites are usually in the form of unstructured data. The web scraping method collects them and stores them as structured data. There are many ways to perform web scraping. One of the most popular ways is by using Python.

Read our article on Fast API vs Flask vs Django

Why Web Scraping?

We have seen that collecting a large amount of data from websites is called web scraping. However, why do we have to collect them? What is the purpose of web scraping? Let’s answer these questions below. Here are some of the applications of web scraping:

• Social media analysis: Social media like Facebook, Twitter, and Instagram handle loads and loads of trending data every day. Web scraping these social media websites reveals data about the latest information such as trending topics, sentiments, and more.
• Price Comparison on eCommerce: eCommerce sellers usually have different prices at different marketplaces. Using web scraping they can compare pricing on multiple platforms and analyze the places for getting higher profit.
• Real Estate Investment: Web scraping helps real estate investors to analyze different marketplaces by getting valuable information from websites such as high-rated areas, attractive renting options, and more.
• Machine Learning: Machine Learning needs enormous data to learn and improve. Web scraping helps in collecting many texts, images, and data points quickly and that can be used in improving reliability and accuracy in machine learning.
• Email address collection: Email marketing is one of the most used forms of marketing by many companies. Using scraping, they collect a large number of email addresses and use them for sending bulk emails for marketing purposes.
• Job listings: Job update information such as job openings, interviews, and dates are collected from various websites and listed in a single place. Users can easily browse all information about job updates in one place.