TIOBE’s rankings for 2023 have placed Python at the top of the list for the most popular programming languages. To create a successful Python project, it is essential to employ the use of an appropriate Python framework.
Having a structured approach can be beneficial for developers, as it allows them to dedicate more time to designing and writing core code, rather than having to worry about other aspects of programming.
Java and C have been surpassed by the rapid growth of Python. Its ease of use and broad range of applications have made it a popular choice, and the development of several Python frameworks has enabled it to be used to address a variety of needs.
As Python continues to grow in popularity, there is now a range of frameworks available to developers. This article will provide an overview of the top 10 Python frameworks that developers should be familiar with in 2023. Whether you are just starting out in programming or looking to use Python, this guide will help you identify the most useful frameworks for the year ahead.
Explained: Python
Python is a popular programming language that is used for a variety of tasks, such as creating online and mobile applications, as well as in the fields of machine learning, data science and artificial intelligence.
It was designed by Guido Van Russom in 1991 to make authoring complicated code structures easier and to increase code readability.
If you are new to computer science but wish to explore the possibilities of technology, Python is an excellent choice as one of the easiest programming languages to learn.
Moreover, its syntax is uncomplicated and requires less code, both of which factors have contributed to the language’s growing popularity among experienced programmers and those starting out in the field.
To begin, let’s define Python frameworks.
The Software Development Life Cycle (SDLC) can be expedited by employing a framework, providing a platform with customization potential. This may include a selection of templating methods, a templating engine, code libraries, and Graphical User Interface components.
Generally speaking, Python frameworks comprise of reusable and adaptable components that help with the basic software development tasks such as creating websites, mobile applications, machine learning models and AI-based solutions.
By providing a standardized environment, these frameworks allow developers to focus on the conventions and logic of their projects, rather than the configuration aspects. This improves the system’s capacity to increase its reach and be used by a larger audience.
Python’s Top 10 Frameworks
Django
- Due to its comprehensive capabilities, Django is widely used in web development. It is highly flexible and provides a range of libraries, engines and UI components needed to create any type of website from basic to complex.
- Django is widely recognized as being one of the most powerful Python frameworks for the backend, due to its ability to deliver content in a range of formats, including XML, HTML, JSON, HTTP, and RSS feeds.
- Django’s built-in security provides developers with a secure method of protecting user accounts and passwords, helping to mitigate threats such as hash-based password storage and cookie-based session storage. Django employs a cryptographic hash algorithm to safeguard users’ passwords, thereby increasing their protection from potential risks on the web.
- Django’s component-based design, with its “Shared Nothing” approach, enables each component to be independent of the others and therefore easily interchangeable, making it highly scalable. This makes Django an ideal Python framework for large organisations and digital platforms to use when scaling their projects.
Features:-
- Amazingly quick.
- Included Object-Relational Mapping.
- Superior safety measures are in place.
- Incredibly expandable.
- URL redirection.
- Computes certificates of authenticity.
- Prepared-to-use library systems.
- Format-agnostic content distribution is being offered.
Bottle
- The Bottle micro-Python framework is a popular choice due to its requirement for only a single Python source file, regardless of the complexity of the application being developed. Furthermore, its main focus is on the development of APIs.
- Bottle is a popular choice for web development due to its compatibility with the base Python distribution. It has a great advantage in that developers can easily write code that fits the hardware specifications.
Features:-
- Support for URL parameters in the request dispatching route.
- With an in-built HTTP server.
- Numerous database plugins are supported.
- Allows the use of external template engines.
CherryPy
- CherryPy is one of the most popular open-source object-oriented Python frameworks. In the last decade, it has been a major contributor to the creation of websites that favor minimalism. As a Python framework for the backend, it offers a comprehensive range of features, such as data access, templating UI components, coverage, profiling, and testing.
- It sets itself apart from its competitors due to its in-built server, which is used to develop online applications, and its compatibility with all operating systems that run Python.
Features:-
- Ability to use many servers simultaneously.
- Separate from any platform.
- Incredible resources for protecting and delivering dynamic and static information, as well as authenticating and caching user data.
- A plugin architecture that’s already integrated.
- This web server is compatible with the HTTP/1.1 WSGI thread pool.
- Defensible set up.
- Uses the Android Operating System.
Flask
- Flask, a Python framework, is a highly sought-after lightweight solution for creating dependable web applications. Its straightforward nature makes it a great choice for those new to WSGI (Web Server Gateway Interface).
- Flask facilitates the development process by suggesting appropriate next steps. Moreover, due to its lack of requirements, developers are free to select any libraries and tools of their preference. It is highly versatile, even amongst Python frameworks.
Features:-
- The Jinja 2 templating engine is built right in.
- Built-in WSGI toolkit called Werkzeug.
- Constructed-in simulator for bugs.
- Ensure that client-side sessions have cookie support.
- Dispatch requests using the RESTful interface.
- Concurrent testing of many units.
Web2Py
- Web2Py is a fullstack Python framework which is characterized by its backwards compatibility, allowing for the integration of updated code libraries and user interface components into earlier versions. It also does not require installation or configuration prior to use, making it highly user-friendly.
- Web2Py is an open source, free-to-use Python framework, unlike some of its competitors which require their own platform to function. It is equipped with a range of integrated code development tools, including a debugger, code editor, and one-click deployment, providing users with all the modern IDE features.
Features:-
- Suitable for use with older equipment
- Separate from any platform.
- Compatible with all web hosts.
- Several protocols are available for use, which is convenient.
- Allows for an MVC structure.
- Secure.
Pyramid
- Pyramid is widely acknowledged as one of the leading Python frameworks for creating straightforward web applications. Developed using Python 3, it offers the capacity to create both basic and complex web apps. Furthermore, Pyramid has become increasingly popular among experienced developers due to its versatility with respect to templating languages, database back-ends and security measures.
- The Pyramid provides a range of supplementary functions designed to enhance web development. It is highly acclaimed amongst software engineers due to its open-source nature and high-quality capabilities.
Features:-
- Generates simple and sophisticated web applications.
- HTML-based structure checking and creation.
- Superior writing and record keeping.
- There is complete coverage in both the tests and the documentation.
- Superior efficiency.
- Optional features may be set up in a variety of ways.
- Large numbers of ancillary spaces.
Aiohttp
- Aiohttp is a popular asynchronous Python framework built on top of the asyncio module, which makes use of the await and async features introduced in Python 3.5. It is not only suitable for hosting websites but can also be used as a client.
- Aiohttp enables users to direct their requests to the relevant applications through its request object and router. Furthermore, it allows server and client WebSockets without any complicated callbacks.
Features:-
- Works with HTTP clients and servers.
- The WebSockets should function on the server and the client.
- Efficient framing of the scene.
- Helps out with the Middleware.
- Flexible plug-in routing is provided.
CubicWeb
- Logilab’s CubicWeb is a powerful, full-stack Python framework, drawing inspiration from the Semantic Web. With its open-source code freely available, anyone wishing to explore web development can take advantage of this resource.
- CubicWeb’s cube capability, allowing for its components to be reused, distinguishes it from other Python frameworks. It has been widely recognised as the leading Python framework for creating data-centric applications.
Features:-
- Help with RDF and OWL.
- Capabilities of a Cube (reusable components).
- Embeds RQL queries within database queries for resolution.
- Allows for use with a number of different data stores.
Giotto
- The Giotto full stack Python framework is a powerful tool for developing functional web applications. Built on the Model-View-Controller (MVC) architecture, like other popular Python frameworks, it encourages collaboration between web developers, designers and other professionals. Furthermore, its controller modules enable the creation of web applications, chat systems and command line interfaces.
Features:-
- Automatic URL redirection.
- Includes both Jinja2 and HTML design templates.
- Models and perspectives of a generic kind.
- Allows for simultaneous plugging of many controllers
Dash
- Dash is a highly regarded micro-Python framework for developing analytical web applications. Its ability to provide insightful data representation on the web makes it an ideal choice for data science developers. Dash enables the creation of dashboards through a user-friendly, mouse-driven interface connected with Python models. Furthermore, applications created using the Dash framework are cross-platform and mobile-compatible, as they can be rendered in any web browser and hosted on a web server.
Features:-
- Eases complicated code concerns.
- Superior adaptability.
- Correction of blunders.
- Connectivity to the LDAP directory service.
- Plenty of available add-ons are supported.
- An approachable and simple user interface.
Frameworks Written in Python for Use in Other Disciplines
Python’s robustness has been demonstrated in the development of online applications and there is no doubt that its future is secure due to the increasing number of frameworks dedicated to this field. Since its inception, Python has been used to develop a broad range of applications.
Python has been utilized for a while now in the flourishing fields of data science and machine learning. With the resurgence of interest in learning about and using Python-based data science and machine learning frameworks, we have compiled a list of the more popular and useful ones.
Python Data Science and Machine Learning Frameworks
- Numpy.
- Tensorflow
- Pandas.
- Matplotlib.
- How fascinating!
- SpaCy.
- Pytorch.
- H2O.
- Shogun.
Conclusion
When considering the development process, frameworks are undeniably integral as they handle tedious tasks such as setup, thus making the job of a developer much easier. Python’s extensive usage and adoption in a range of contexts is a testament to its versatility.
In order to further develop and innovate, the company has expanded its operations to include data science and machine learning. Any programmer looking to optimize their workflow should consider the advantages of the top Python frameworks outlined above.
