Python is an interpreted, dynamically-typed, and high-level language. Due to its simple syntax, extensive libraries, capacities for development, and testing automation, Python is the choice of many programmers and tech companies. It is suitable for developing all kinds of projects. It can take your project from zero to a hundred in terms of complexity, whether it’s a simple website with limited functionality, an API, or a complex solution incorporating machine-learning algorithms. And there are numerous frameworks to facilitate this task. There are chiefly three types of Python frameworks, namely full-stack, microframework, and asynchronous. Let’s take a brief look into the various types of Python frameworks!
Types of Python Frameworks
1. Full-stack framework
Full-stack frameworks are generally focused on building larger, full-featured applications and offer a lot of common functionality out of the box.
Full-stack frameworks come pre-packaged with everything you need to build an app. Things like the MVC (model-view-controller) architecture, ORM (object-relational mapping) technique, a templating engine, and routers. Full-stack frameworks can be used to develop any kind of application, but it’s more common to use them for bigger projects.
Django
Official website | PyPI | GitHub
Django is a high-level framework with a focus on making the development process more efficient and quick. More precisely, Django’s design philosophy saves you time and money, and a number of its principles – like DRY and rapid development – encourage developers to minimize code and reduce redundancies.
Unlike others, the free-to-use and open-source full-stack Python framework includes a grand number of built-in features rather than offering them as individual libraries. Django makes use of its ORM for mapping objects to database tables.
This results in allowing the code to work across different databases as well as making it easier to migrate from one database to the other. Though Django has inherent support for MySQL, PostgreSQL, SQLite, and Oracle Database, it can support other databases via third-party drivers.
Key features:
- A plethora of ready-to-use libraries
- Authentication support
- Database schema migrations
- Object-relational mapper (ORM)
- Support for web servers
- Template engine
- URL routing
Project examples: Spotify, Instagram,…
Learn more. 3 things need-to-know to efficiently use Django.
TurboGear
Official website | PyPI | GitHub
TurboGears is a data-driven, open-source, full-stack web application framework for Python. The framework allows developers to rapidly develop extensible data-driven web apps.
In addition to supporting a flexible and powerful ORM, TurboGears come with intelligible templating. The full-stack framework makes use of components such as Genshi, Repoze, SQLAlchemy, and WebOb to easily and quickly develop apps requiring database connectivity.
Key features:
- All features are implemented as function decorators
- Available command-line tools
- MochiKit JavaScript library integration
- Multi-database support
- MVC-style architecture
- PasteScript templates
- ToscaWidgets for simplifying coordination of frontend design and server deployment
- Uses Pylons as a web server
- Validation support with FormEncode
Project examples. Apache Allura, Kamisons,…
Web2py
Official website | PyPI | GitHub
For Python developers looking for a scalable full-stack framework, Web2py might be the answer. The open-source Python framework comes with its own web-based IDE, which includes a code editor, debugger, and one-click deployment.
Though Web2Py allows users to create dynamic web content in Python, it doesn’t provide support for Python 3. The ticketing system is one of the most important features of the Python framework. The system issues a ticket to the user whenever an error occurs.
Key features:
- Ability to run on any web hosting platform that provides support for either Python or Java and Python
- Backward compatibility
- Built-in data security for preventing several common vulnerabilities, including cross-site scripting, injection flaws, and malicious file execution
- Devoid of installation and configuration requirements
- Follows MVC-pattern
- Provides support for internationalization
- Readability of multiple protocols
- Role-based access control
Project examples. IMSA, iTel Networks,…
2. Microframework
Microframeworks are generally focused on providing a small core of functionality and invite the developer to make their own choices about which libraries and technologies to add in for other functionality.
This has the advantage of allowing for much more control over application design and can result in better application performance. They typically require the developer to pick their own database abstraction layer and other libraries. Microframeworks can be a great choice for smaller, more narrowly focused applications, API development, or applications where performance is more important. Some microframeworks can easily scale to a full-stack solution.
Flask
Official website | PyPI | GitHub
Flask is another popular Python framework. Inspired by the Sinatra Ruby framework, the microframework requires Jinja2 template and Werkzeug WSGI toolkit. Thanks to its lightweight and modular design, Flask is readily adaptable.
Flask allows the developers to build a solid web application foundation from where it is possible to use any kind of extensions required. The microframework is compatible with Google App Engine.
Key features:
- Built-in fast debugger
- HTTP request handling
- Inbuilt development server
- Jinja2 templating
- RESTful request dispatching
- Support for plugging in any ORM
- Supports secure cookies to establish client-side sessions
- Unicode-based
- Unit testing support
- WSGI 1.0 compliance
Project examples. Lyft, Netflix,…
Bottle
Official website | PyPI | GitHub
Bottle creates a single source file for every application developed using it. The microframework for Python was originally developed for building APIs. Other than the Python Standard Library, Bottle has no dependencies required for crafting small web applications. One of the most important advantages of using Bottle is that it allows developers to work closer to the hardware. In addition to building simplistic personal-use apps, Bottle is an apt fit for learning the organization of web frameworks and prototyping.
Key features:
- Adapter support for 3rd-party template engines and WSGI/HTTP servers
- Allows simple access from cookies, data, file uploads, and other HTTP-related metadata
- Built-in HTTP server
- Plugin support for different databases
- Provides request-dispatching routes having URL-parameter support
Project examples. Total recall VR, CleverClicks,…
CherryPy
Official website | PyPI | GitHub
CherryPy is a popular open-source, object-oriented Python framework that follows a minimalistic approach. The microframework is one of the oldest Python frameworks, debuting in June of 2002.
Any CherryPy-powered web application is a standalone Python application with its own embedded multi-threaded web server and runs on any OS with support for Python. Such an app can be deployed anywhere an ordinary Python app is able to run.
There is no need for an Apache server for running apps developed using CherryPy. The microframework allows the developers to make use of any type of technology for data access, templating,…
Key features:
- A number of out-of-the-box tools for authentication, caching, encoding, sessions, static content, and much more
- A flexible built-in plugin system
- HTTP/1.1-compliant WSGI thread-pooled web server
- Inbuilt support for coverage, profiling, and testing
- Offers simplicity for running multiple HTTP servers simultaneously
- Powerful configuration system
- Runs on Android
Project examples. Aktion Mensch, Juju,…
3. Asynchronous framework
Asynchronous frameworks, which are focused on delivering high levels of performance by allowing a very large number of concurrent connections, are great when you need to provide a specific functionality at a very high volume.
Asynchronous framework is a microframework that allows for handling a large set of concurrent connections. Typically, an asynchronous framework built for Python uses the programming language’s asyncio library. Following this concept, an app doesn’t need to execute tasks consequently: one task can start running before the previous one is complete. Python asynchronous frameworks use the asyncio library and can handle huge sets of concurrent connections. Generally, asynchronous frameworks require more rigor in programming style and have a more limited set of plugins.
Tornado
Official website | PyPI | GitHub
Tornado is an open-source Python framework and an asynchronous networking library. In addition to solving the C10k issue (which simply means to handle 10k connections at any given time), the asynchronous framework uses a non-blocking network I/O.
The Python framework was originally developed for a company called FriendFeed, which was acquired by Facebook in 2009. The Tornado is an ideal tool for building apps asking for high performance and several thousand concurrent users.
Key features:
- Allows implementation of 3rd-party authentication and authorization schemes
- Offers high-quality output
- Real-time services
- Supports translation and localization
- User authentication support
- Web templating
Project examples. Facebook, Quora,…
Sanic
Official website | PyPI | GitHub
Built on top of the uvloop, Sanic is a simple and open-source Python framework developed especially for offering fast HTTP responses via asynchronous request handling. Hence, it is an asynchronous framework for Python.
Sanic supports asynchronous request handlers, making it compatible with Python 3.5’s async/await functions. It results in enhancing speed as well as offering non-blocking capabilities.
During a benchmark test with one process and 100 connections, Sanic was able to handle as much as 33,342 requests in a single second.
Key features:
- Able to read and write cookies
- Allows different types of logging, such as access log and error log
- Class-based views
- Handlers with easy to apply decorators support
- Plugin support
- Supports blueprints for sub-routing within an application
- The configuration object can be modified either by using dot-notation or like a dictionary
Project examples. Oh BiBi, Joblift,…
FastAPI
Official website | PyPI | GitHub
FastAPI is newer than Sanic (first release in early 2019) but gaining momentum fast. It excels at building REST or GraphQL APIs, and can handle synchronous requests, asynchronous requests, streaming and websockets. It also has built-in support for authentication and authorization, data validation, JSON serialization and features automatic API documentation following the OpenAPI standard.
FastAPI is a web framework for building APIs with Python 3.6+ based on standard Python type hints. A framework on the rise, FastAPI is worth exploring for your next async project.
Key features:
- Very high performance, on a par with NodeJS and Go. One of the fastest Python frameworks available.
- Increase the speed to develop features by about 200% to 300%.
- Reduce about 40% of human (developer) induced errors.
- Great editor support. Completion everywhere. Less time debugging.
- Designed to be easy to use and learn. Less time reading docs.
- Minimize code duplication. Multiple features from each parameter declaration. Fewer bugs.
- Get production-ready code. With automatic interactive documentation.
- Based on (and fully compatible with) the open standards for APIs: OpenAPI (previously known as Swagger) and JSON Schema.
Project examples. Netflix, Uber,…
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*Reference:
- https://djangostars.com/blog/python-frameworks-for-web-development/
- https://steelkiwi.com/blog/top-10-python-web-frameworks-to-learn/
- https://medium.com/better-programming/python-frameworks-comparison-how-to-choose-the-best-for-web-development-9603107ec905
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