Inquiring about the various frameworks in Python is a common practice. While PyCharm is an integrated development environment (IDE) rather than a framework, Anaconda provides pre-built libraries and packages for Python data science. NumPy is a library devoted to scientific computing, as opposed to a framework. Django is a freely available, open-source web framework that facilitates full-stack development in Python. Choosing the optimal Python framework hinges on respective project requirements and specific needs, thus conducting thorough research of the various frameworks and their features is critical for informed decisions.
Do you seek answers to these questions? Keep reading to find out.
Engage The Finest 12 Python Frameworks
With its dynamically interpreted and object-oriented attributes, Python has emerged as one of the most prevalent programming languages. Python enables developers to systematically organize their code, thereby simplifying both its comprehension and creation. Python is further recognized for its exceptional ability to minimize the volume of code required to achieve desired results. This proficiency not only conserves time and effort but also furnishes accuracy and precision for optimal performance.
Although Python can communicate with servers, its potential in this domain is relatively restricted. Therefore, Python developers frequently resort to frameworks for application development. Frameworks confer several benefits, such as enhanced security, organization, accessibility, and thorough documentation.
Python provides frameworks for nearly every technology sector. However, prior to exploring the diverse array of frameworks, let us elucidate the concept of a Python framework.
What is a Python Framework Exactly?
A Python framework can be viewed as a toolkit of packages and modules that empowers developers to efficiently build online applications and services. By relieving developers of handling complex issues like sockets, protocols, and thread management, frameworks enable them to channel their energy towards application development.
Python frameworks, conversely, curtail development time by furnishing a pre-existing implementation of repetitive operations.
Developers Utilize Python Frameworks for Diverse Objectives.
Developers utilize Python frameworks to repurpose code for identical HTTP operations, as well as establish an orderly structure for applications and a variety of pre-defined functionality.
Furthermore, several developers opt for frameworks over libraries citing their greater adherence to typical programming conventions, reliability, and the simplicity with which their functionality can be amplified via the provided tools.
Which Types of Python Frameworks Exist?
Python frameworks can be classified into three distinct types: full-stack frameworks, micro-frameworks, and asynchronous frameworks. Below is a brief summary of these categories: Full-stack frameworks furnish all-embracing web development solutions, encompassing functionalities such as web templates systems, authentication, and databases. Popular full-stack frameworks include Django, Flask, and Pyramid. Micro-frameworks, in contrast, provide a minimalist approach to web development, enabling developers to construct more focused and lightweight applications. Popular micro-frameworks include Bottle and Flask. Asynchronous frameworks aim to heighten application responsiveness by permitting simultaneous processing of multiple requests. Popular asynchronous frameworks include Sanic and Tornado.
Full-stack frameworks:Full-stack frameworks provide an extensive web development solution encompassing everything from form generation and validation to template layouts. While such frameworks offer a plethora of applications, they may pose a challenge to use effectively.
Here are some examples of full-stack Python frameworks:
Micro frameworks:Micro frameworks are ideal for medium-sized applications that do not necessitate a significant amount of additional features, such as a data abstraction layer or form validation. These frameworks are minimalistic and lightweight, providing only the essential components needed to develop a functioning application without overburdening it with superfluous features.
Here are a few examples of Micro Python frameworks:
Asynchronous frameworks:Recent software and application developments have elevated the utilisation of frameworks compatible with the Asyncio library. These frameworks are exceptionally competent in managing significant numbers of concurrent connections, making them a popular choice for software and application developers.
Here are a few examples of Asynchronous Python frameworks:
Python Frameworks for Full-Stack Development
CubicWebCubicWeb is a free and open-source Python framework that expedites the development of web applications. By utilising the concept of cubes – reusable components – developers can fabricate robust, efficient, and high-quality semantic web applications with ease.
Features of CubicWeb Python framework include:
a. Availability of security processes.
b. Capability for component reusability.
c. Compatibility with the Resource Description Framework (RDF) and the Web Ontology Language (WOL) (OWL).
d. Simplified data-related queries with Relational Query Language (RQL).
e. Support for multiple databases.
DjangoDjango is a popular, high-level framework for developing web applications that allows developers to efficiently create Python-based programmes. This framework’s architecture is designed for efficiency and is built around the Don’t Repeat Yourself (DRY) principle, which emphasizes writing, debugging, and maintaining code that is not duplicated. By following this principle, developers can ensure that their code is efficient and avoids unnecessary repetition.
Compared to other Python frameworks, Django is equipped with an extensive range of features that are included by default rather than requiring separate library installation. Moreover, Django’s Object-Relational Mapping (ORM) layer streamlines the linking of objects and database tables. Additionally, Django offers built-in support for numerous databases, including Oracle, MySQL, among others.
Highlights of the Django Python framework include:
a. URL Routing
b. Improved web server support
c. Enhanced authentication support
d. Extremely fast framework
e. Ready-to-use libraries
f. Ease of customisation
GiottoGiotto is a Model View Controller (MVC) framework that provides a free RESTful interface to its users. This interface is capable of automating URL routing, and it also utilises Jinja2 for HTML template rendering with an easy-to-use Application Programming Interface (API).
Giotto’s controller module furnishes users with the capability to build and execute programs across multiple platforms, including the command line, web, and Internet Relay Chat (IRC). This allows for efficient and powerful programming, enabling users to produce complex applications and scripts that can be utilised across a variety of platforms.
Features of Giotto Python framework include:
a. Consistent views and models
b. Automated and built-in URL routing
c. Various plug-in controllers are available
d. SQLAlchemy database persistence
e. Functional CRUD patterns
f. Access to several RESTful APIs.
PylonsPylons is an open-source web development framework that prioritises the swift creation of applications. It integrates the best features of several popular programming languages such as Ruby, Perl, and Python. Pylons combines these capabilities into a single platform, providing developers with an efficient and effective toolset for creating web applications.
Important Features of the Pylons Python Framework:
a. URL routing
b. Text-based templating
c. URL mapping based on WebHelpers route setup
d. Validation and creation of HTML forms.
Python Frameworks for Micro Development
BottleBottle is a widely-utilised micro web framework for building Python-based applications. It is entirely self-contained and is provided as a single-file module that contains just one Python standard library.
One of the most advantageous features of the Bottle framework is its capability to directly interact with hardware, making it an ideal choice for developing straightforward applications for personal use.
Features of the Bottle Python framework include:
a. Built-in HTTP server
b. Support for multiple databases through plugins
c. Adapters that provide support for third-party HTTP/WSGI servers and template engines.
d. Support for file uploads, headers, and cookies.
e. Absence of external dependencies.
CherryPyCherryPy is an open-source web application framework that facilitates the rapid development of object-oriented web applications. It’s designed to provide a simple, user-friendly API which enables developers to create complex applications quickly. CherryPy programs are self-contained and run on their own multi-threaded web server, providing a lightweight yet powerful platform for web development.
Key features of the CherryPy Python Framework include:
a. Compatible with Android
b. Can run on multiple HTTP servers simultaneously
c. Offers a versatile built-in plugin system
d. Incorporates a sophisticated setup system.
DashDash is an exceptional open-source microframework that is ideal for data scientists without expertise in web development. It generates web-based analytical applications that function similar to web servers by enabling the exchange of JSON packets through HTTP requests.
Dash has utilised Flask plugins to develop its own features, which can be optimally rendered and served on web servers. Moreover, Dash programs are mobile-friendly and adaptable to compatibility with all platforms. This adaptability guarantees that users can access Dash programs irrespective of their device or operating system.
Dash Python framework highlights are:
a. Enhanced plugin support
b. An efficient error-handling technique
c. URL routing functionality
d. Capability to integrate with LDAP
e. User-friendly interface
f. Customisation options.
FalconThe Falcon framework is a powerful resource utilised by developers to quickly design and develop web APIs. This comprehensive toolkit enables developers to fabricate visually appealing online applications effortlessly. Additionally, Falcon provides the necessary functionality to enhance and modify the prevalent HTTP and Representational State Transfer (REST) architectural styles.
Features of the Falcon Python Framework include:
a. An exceedingly efficient and scalable codebase.
b. Precise and effective HTTP error response time.
Python Frameworks for Asynchronous Development
AIOHTTPAIOHTTP is a widely recognised asynchronous Python framework that utilises the latest Python
GrowlerGrowler is built on the Node.js express framework, Object Relational Mapping (ORM) and Templating. It is similar to AIOHTTP.
Growler utilises middleware technology to route queries instead of dealing with them directly, making it one of the best options for streamlining the development of complex applications within the Python framework.
Features of the Growler Python Framework include:
a. Enhanced use of decorators to create reusable and efficient code.
b. Availability of the Ziapp concept to bundle the entire program into a single executable file.
c. Support for a wide range of open-source software.
SanicSanic is an open-source Python web framework that utilises the uvloop framework to provide asynchronous request processing, resulting in faster HTTP responses. This powerful functionality is one of Sanic’s major advantages, enabling users to build highly responsive and performant applications.
Sanic supports request handlers which are equivalent to Python 3.5’s Await or Async routines, resulting in non-blocking capabilities and improved performance in applications. This compatibility is one of the major benefits of using Sanic for software and app development.
The following are the key features of the Sanic Python framework:
a. Plugin support
b. Class-based views
c. Ability to write and read cookies
d. Capable of handling various error reports and access logs.
e. Supports handlers with simple decorators.
TornadoTornado has long been recognised as one of the most powerful and comprehensive Python frameworks available. It offers support for essential components such as databases, URL routing, and HTML templates that are required for developing a wide range of applications. As a result, it is a highly sought-after choice for developers seeking to develop professional and robust applications.
The Tornado web framework simplifies web server development by focusing on non-blocking operations, enabling the efficient handling of a large number of open connections. As a result, it is a highly efficient choice for handling complex and high-traffic applications.
The key features of the Tornado Python framework include:
a. Comprehensive support for localization and translation
b. Availability of web templating techniques.
c. Real-time services
d. Effective results
e. Support for third-party authorisation and authentication.
So, Which Python Framework is the Best Choice for You?
Although there is a wide variety of renowned and sought-after Python frameworks available, each framework has its own set of strengths and weaknesses. The selection of a Python framework for a project relies heavily on the project’s requirements and the developer’s familiarity with the framework.
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What is a Python framework?The Python online framework is a comprehensive and vast collection of packages and modules that enables developers to build web applications and services quickly and efficiently. This framework frees developers from the burdens of handling low-level elements such as protocols, sockets, and process/thread management, allowing them to concentrate on the higher-level aspects of development.
Which Python framework is the most commonly used?Django is widely regarded as the foremost full-stack framework for Python programming, thanks to its remarkable speed and reliability when developing complex web applications. The widespread adoption of this framework is a testament to its strength as a development tool.
Is Anaconda a framework?No, Anaconda is not a framework. Instead, it is an open-source distribution of the Python and R programming languages that simplifies package management and deployment for scientific computing. Anaconda streamlines package installation and their dependencies, allowing for easy sharing of packages between users. Additionally, Anaconda provides isolated Python and R environments, enabling users to customise their computing environment to their specific projects. With these features, Anaconda simplifies scientific computing and improves efficiency.
Is NumPy a framework?No, NumPy is not a framework. Instead, it is a library for the Python programming language that is used for scientific computing purposes. It provides numerous capabilities for performing mathematical and logical operations on arrays and matrices, making it a popular tool for data scientists and researchers.