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1. Python Web frameworks.md

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Python Web Frameworks

  • A Web framework is a collection of packages or modules which allow developers to write Web applications or services without having to handle low-level details (protocols, sockets or process/thread management) .

  • The majority of Web frameworks are exclusively server-side technology.

    With the increased prevalence of AJAX, some Web frameworks are beginning to include AJAX code that helps developers with the particularly tricky task of programming (client-side) the user's browser.

  • As a developer using a framework, you typically write code which conforms to some kind of conventions that lets you plug in to the framework.

    • The communications, infrastructure and low-level stuff of the web application is taken care of by the framework.

    • The logic of the application is taken care of in your own code.

  • Frameworks provide support for a number of activities such as

    • interpreting requests (getting form parameters handling cookies and sessions),
    • producing responses (presenting data as HTML or in other formats),
    • storing data persistently

  • A web application may use a combination of

    • a base HTTP application server,
    • a database,
    • a template engine,
    • a request dispatcher,
    • an authentication module,
    • an AJAX toolkit.

  • Flask and FastAPI are some Non Full Stack Frameworks whereas Django is a popular Full Stack Framework.

Flask

Flask is a micro web framework written in Python.

Components of Flask are :

  • Werkzeug
  • Jinja 2

Werkzeug:

It is a WSGI(Web Server Gateway Interface) toolkit, which implements requests, response objects, and other utility functions.

Jinga:

Jinja is a fast, expressive, extensible templating engine. Special placeholders in the template allow writing code similar to Python syntax.

PROS:

  • Flexible: You can manipulate most aspects of Flask.
  • Intuitive: Flask is great for beginners because of its simplicity.
  • Built-in development server: This built-in functionality, along with its integrated support, allows for seamless unit testing.

CONS:

  • No data validation: With Flask, you can pass any data type. This can cause programs to crash often.
  • Time: It has a single source that handles requests in turns, meaning that it can take some time for requests to be addressed.

Use cases:

Flask is commonly used for projects such as:

  • E-commerce systems
  • Social media bots
  • Social networks
  • Static websites

FastAPI

FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints.

It is used for developing RESTful APIs in Python.

FastAPI is based on Pydantic and type hints to validate, serialize, and deserialize data, and automatically auto-generate OpenAPI documents.

It fully supports asynchronous programming and can run with Uvicorn and Gunicorn.

PROS:

  • Data validation: It validates your data type even in nested JSON requests.
  • Exception handling: With FastAPI, it’s easy to do exception handling.
  • Asynchronous code support: It supports async code using the async/await Python keywords.

CONS:

  • Request validation: FastAPI uses Pydantic for request validation. This process isn’t always very intuitive, and it sometimes requires you to write your own custom validator.
  • Smaller community: Since the framework is still pretty new, the community is smaller in comparison to other frameworks.

Use cases:

FastAPI is commonly used for projects such as:

  • Internal crisis management
  • Deploying machine learning models
  • Create accounts, logins, and authentication for web applications