Category: Python

Top Python Frameworks for Web Development in 2022

Posted on by galaxy-admin

What does a Python programmer need to make their life a little bit easier for themselves? Using frameworks is the answer. This allows developers to focus on application logic rather than routine elements because frameworks automate the implementation of redundant tasks.

Python is one of the most popular programming languages, and there is no dearth of available frameworks. These Python frameworks have their own set of pros and cons and therefore, their selection must be based on project requirements as well as developer preferences.

When it comes to implementation, the Python programming language has a wide range of applications. In this blog, we will learn about the top Python frameworks. 

We will cover – 

  • Why Python for Web Development
  • Why Use A Framework?
  • What Are Popular Frameworks In Python?
  • Top Python Uses In The Real World
  • Conclusion
  • Useful Resources

Why Python for Web Development

Quicker prototyping: Python takes comparatively lesser time to finish your projects vis-a-vis other programming languages. Therefore, it takes lesser time to structure your ideas. This is the reason Python is the programming language of choice for startups.  

Large user base: Python is one of the most widely used languages in the world, with users from all over the globe. On account of its popularity, Python continues to add new features and libraries, as well as providing excellent documentation and community assistance. When it comes to support and framework for new developers, Python excels.

Libraries and ecosystem: Python offers a wide range of library tools and packages, which allows you to access much pre-written code, reducing the time it takes to develop applications. You can use Numpy and Pandas for mathematical analysis, Pygal for charting, and SQLALchemy for composing queries, for example. You can use web frameworks in Python such as Django and Flask, which we’ll talk about further down in this article.

Why Use a Framework?

A toolbox would be a good metaphor for what we are trying to achieve. It consists of pre-written, standardized packages and modules that make the development of web applications faster and easier, as well as more reliable and scalable. Instead of having to do all of the grunt work yourself, frameworks come with built-in components that “set up” your project from the ground up. 

As a server-side technology, Python web frameworks are primarily used to aid URL routing, HTTP requests and responses, accessing databases, and web security. When developing web applications, a web framework can help you develop complex applications in a fraction of the time.

What Are Popular Frameworks In Python?

In order to make their lives easier, Python programmers require frameworks. Frameworks reduce development time by automating the implementation of redundant tasks, allowing developers to focus on application logic rather than routine elements.

The fact that Python is one of the most popular programming languages means that there is no shortage of frameworks. There are advantages and disadvantages to using different frameworks. As a result, the selection should be based on the project’s requirements and developer preferences. Here is a list of some best python frameworks:

1. Bottle

Bottle generates a single source file for each application created with it. It is one of the most effective Python web frameworks. Python’s microframework was originally designed to help developers create APIs. One of the most significant benefits of using this framework is that it allows developers to work more closely with the hardware. 

The Bottle is an excellent choice for learning the organization of web frameworks and prototyping, in addition to creating simple personal-use apps.

 2. CubicWeb

This Full-Stack framework CubicWeb is a free, semantic, open-source, Python-based web framework developed and maintained by Logilab. CubicWeb requires a data model to be defined to develop a functional application.

Unlike other popular Python frameworks that use separate views and models, CubicWeb makes use of the cube. Then, using a database, a web server, and some configuration files, multiple cubes are joined together to form an instance.

3. AIOHTTP

This framework is asynchronous. AIOHTTP is a Python framework that heavily relies on Python 3.5+ features like async and await. The Python framework is asynchronous because it makes use of Python’s asyncio library. AIOHTTP, in addition to being a server web framework, can also be used as a client framework. It includes a request object and a router to allow queries to be routed to functions designed to handle them.

4. Django

This framework is a full-stack framework. Django is a popular web development framework for creating Python applications. It was named one of the top python frameworks to opt for.

Django is a free and open-source full-stack Python framework. It includes a range of built-in features, unlike the frameworks that use separate libraries. Django’s ORM is used to map objects to database tables.

Python Applications

1. Web Application Development

  • Web application development is without a doubt one of the most popular practical uses of Python. In the world of web applications, Python is the language of choice. Python is widely used in the real world for web development. Because of its scalability and ease of use, it makes applications safer and more convenient.
  • Python has numerous frameworks, including Django and Flask. This makes it possible to create apps very quickly. For web applications, Python has become more useful thanks to Django’s dynamic development capabilities. As a result of the framework’s inclusion of standard libraries, development time is reduced and the web application can be launched faster.

2. Internet of Things

  • Python can also be used in the internet of things, which is another real-world application. Using the Raspberry Pi and Python programming language, developers can turn any object into an electronic device.
  • Because Python can be used to create embedded software, it can be applied to smaller objects that can work with the programming language at high-performancelarge-scale levels.
  • With the Raspberry Pi, developers can use Python applications to perform high-level computations. A smart object can be created by embedding a microprocessor within a normal object.
  • Industrial IoT is widely used to track inventory, move machines and track order processing along with shipment status in large scale industries.

3. Enterprise Applications

  • Unlike regular web applications, enterprise apps have a unique set of features. As opposed to individual users, they are designed to meet the needs of an organization.
  • The use of Python in enterprise applications varies from company to company. They use it because of its scalability, readability, and ability to do a lot of different things.
  • Due to the need for a large amount of security and database handling capabilities, enterprise applications can be complex. As a robust language, Python can handle multiple database requests at the same time.

Improve your productivity with a top-notch enterprise Python application. Get a Free Consultation Here.

4. AI and Machine Learning

  • Artificial Intelligence and Machine Learning are probably the most interesting practical applications of Python. Developing Machine Learning models requires the use of Python, which is a stable and secure language capable of handling computations.
  • A large number of Machine Learning libraries are available in Python. Included in this are SciPy and Pandas as well as TensorFlow and NumPy.
  • There are a wide variety of ways that businesses can benefit from the use of Python language in AI solutions including advanced computing, data analytics, image recognition, and much more. 

Conclusion

Python can handle almost any type of request, making it extremely useful for all types of development tasks. Python is now used in a wide range of applications, from enterprise apps to gaming.

Python is quickly becoming a popular tool for developing a wide range of applications. At Galaxy, we have an expert team of Python developers who can assist you in developing a Python app. Talk To Us Today.

Useful Resources:

Blogs:

Node.js vs Python | Which Backend Framework to Choose?

Our Backend Development Technology Favorites in 2021

Choosing Django as Your Backend Framework in 2021

Choosing the best Software Architecture for your Enterprise App

Podcasts and videos:

Talk Python To Me Podcast

Python Bites

Test and Code

The Real Python Podcast

About Galaxy Weblinks

We specialize in delivering end-to-end web application design & development services and have hands-on experience with popular back-end languages and frameworks like Node.js, Python, etc. We have expertise in customizing websites for multiple business or web application development requirements, be it IoT, enterprise application, or a customized machine learning platform. Contact us for your project discussion today.

Node.js vs Python | Which Backend Framework to Choose?

Posted on by galaxy-admin

Choosing the right backend technology for your project is a decision that can have a long-term impact on your software. A favorable decision will be robust and easier to scale while a wrong one could send you down the path of rewriting the entire app, costing you time, money, and team morale in the process. 

Backend technologies are directly attributed to the stability, performance, and scalability of systems, hence thorough research is needed before making the decision. This blog will help you with that research. 

We’ll be comparing Node.js and Python on the following grounds:

  • Frameworks, libraries, and community
  • Use cases
  • Learning curve
  • Scalability
  • Performance

Backstory

Initially used in data sciences, Python has been ranking in web development as the most popular backend language since 2018-19.

Python is a programming language while Node.js, a runtime environment, on the other end boasts of a speedy V8 which makes it a popular choice for real-time server applications. 

So when you’re choosing either for your application take their respective ecosystems and how they fare for you into consideration.

Frameworks, Libraries, and Community

Python has Django and Flask as the most popular frameworks in its arsenal. Python also has support for rich libraries for various projects like:

  • Panda for data analysis
  • OpenCV for image processing 
  • matplotlib or Numpy for data visualization
  • TensorFlow/Scikit-Learn/PyTorch for machine learning
  • Raspberry Pi for robotic applications

When it comes to Node.js, NPM(Node Package Manager) is one of the richest libraries out there with about 1 million packages available. The most popular and dependable packages are:

  • express.js – a MEAN stack microframework
  • Nest.js – This framework is Node’s answer to Django
  • lodash for modular utilities
  • react for UI.

Takeaway

  • Both frameworks boast a rich ecosystem and libraries, which makes them a difficult choice. It comes down to your project and its inherent needs. If you think Python has the libraries that would make your life easier, then that’s the one you should go for. Same with Node.js!

Node.js vs Python use cases

Comparing Node.js and Python superficially is futile because both are robust and actively supported. To solve this mystery we have to dive into details. 

Python can be seen as a general-purpose language and hence is suitable for a vast range of applications. You can build web apps, machine learning projects, numerical computations, and even deep learning. The Banking and Insurance sector has a default inclination towards Python for the backend as it’s strong and natural at handling big data sets. 

When we talk about real-time and web-based projects that are data-intensive like chatting or streaming platforms, Node.js is the best option. Developers choose Node.js because of its asynchronous nature. It is ideal for projects that don’t require heavy processing and are good with I/O operations. Node.js is also preferred for memory-intensive applications like rendering 3D projects. 

Takeaway

  • Choose Node.js for small and extremely fast run-time apps.
  • Choose Python for large systems with huge datasets that require stability and consistency

Learning curve

Node.js is not a challenge to those who are adept at JavaScript. You can even utilize the same language to build the frontend as well as the backend of your application. Node, however, is natively asynchronous. The new developers find it hard to wrap their heads around in comparison to synchronous Python.

Python, on the other hand, is known as the easiest backend language to learn, as far as earlier phases are concerned. It is a compact and very well-documented language. 

Takeaway:

  • If your team is familiar with asynchronous code then it might be easier to go with Node.js. You’d still need to hire backend experts for complex problems. 
  • Even though introductory Python is dubbed as the easiest backend language to learn, the difficulty increases with the complexity of the problems.

Scalability

Node.js has an event-based asynchronous architecture and non-blocking I/O, which ultimately contributes to efficient scaling. As a default feature it’s great for smaller applications but not so much for the bigger systems. New developers or even intermediate ones will find it difficult to scale. 

Python is synchronous, however, it has additional tools that allow data migrations and data streaming. What works in its favor is how well it scales in code complexity.

Takeaway:

  • It’s a difficult call when it comes to scalability because both tackle scalability in their unique way, be it through architecture or tools. 

Node.js vs Python performance

We want fast apps and we want them now!  

Although it’s an unfair comparison, Node.js with its V8 engine and asynchronous architecture is one of the fastest server-side solutions among its peers. 

Python is not that far behind in terms of speed. With the latest release and speed optimizations, it has achieved up to 50% speed improvement in some cases. 

Takeaway:

  • Choose Node.js if building a real-time solution
  • In other cases where high-load is a concern, Python is recommended. 

Conclusion

When choosing the right software technology for your project, choosing between Node.js and Python can only add to your confusion as both are exceptional backend technologies. They can both be used to build robust, scalable, and performant software. 

We hope that this blog has helped you choose the appropriate backend framework for your project. If you’re still left with some unanswered questions, get in touch with our backend experts here.