Programmers often face a daunting decision when taking on a new project: which language to use. It is a difficult decision because every new project has a unique challenge. There is no such thing as a jack of all trades in the realm of programming. Experienced programmers agree that different programming languages have their strengths and weaknesses, making them suitable for some situations, but not all. In this article, we will compare Python and Node.js to see which works better in which case.
Python is a widely used, high-level multipurpose programming language created by Guido van Rossum. It can be used as a scripting language to compile byte code or create large applications. In terms of machine learning, Python is GitHub's second-most popular language. It is a universal, interpreted, interactive, object-oriented programming language at a high level. Python's design philosophy emphasizes the legibility of the code through its remarkable use of significant indentations. Furthermore, Python's convenient nature makes it a perfect choice for backend development, making it one of the most popular programming languages.
What is the difference between them?
Below are some of the criteria I will consider to differentiate between both Python and Node.js:
- Speed & Performance
- Error Handling
- Trending Technologies
- Apps it is best suited for
With that said, let's get started with it.
If we talk about architecture, Python does not have built-in support for asynchronous programming, and it requires special tools to run. Among these libraries is asyncio, which lets developers create asynchronous event-driven apps.
On the other hand, Node.js features a single-threaded event loop architecture, which, when combined with the non-blocking nature of Node.js, successfully handles thousands of concurrent connections without requiring thread context switching. As a result, Node.js is the best option for real-time web applications.
Result: Node.js wins this round and earns more points than Python due to its event-driven architecture.
2. Speed and Performance
Performance is considerably slower in Python because it runs requests in one flow, unlike Node.js, which allows for advanced multithreading. Even though Django can handle high loads in some cases, it still does not offer a viable option for mobile applications.
Result: Node.js takes this round.
3. Error Handling
Python allows developers to find and fix errors more easily thanks to its readable and compact syntax. Additionally, Python has a reputation for being easier to learn and better at handling exceptions, which gives it an edge over Node.js.
There are varying degrees of error handling in each programming language or runtime, as errors can occur at any point during the life cycle of an application. Furthermore, Node.js comes with excellent exception handling capabilities and can debug errors effectively.
Result: Both Python and Node.js excel here. Thus, we can say it is a draw.
Using Python syntax, you can achieve more with fewer lines of code. It is easier to understand and debug Python's code because it lacks curly brackets. Most people can read Python code simply with minimal technical knowledge, making it a beginner-friendly programming language.
Result: Python wins this one thanks to its user-friendly syntax.
Some reasons contribute to the lack of proper scalability support in Python. Python is a slower programming language due to its runtime interpretation. Additionally, Python does not support multithreading due to an internal lock mechanism that stops it from running several tasks simultaneously. Despite these limitations, these can be overcome by using Python implementations such as CPython or Jython, better architecture, and load balancing mechanisms.
Since it is built into the runtime environment, Node.js naturally offers scalability, and its cluster module can handle the full power of your machine. Through additional resources for vertical scaling and newer nodes for horizontal scaling, Node.js makes it easier to scale web applications vertically and horizontally. Additional strategies to manage scaling include:
Result: Thanks to its high scalability, Node.js beats Python.
Several frameworks, including Django, Flask, web2py, and others, can be used to extend Python for both full-stack and web-only development. Additionally, Python offers an API provided in the C source file for extending the features of C/C++. Using Python's implementation of Java, called Jython, you can perform scripting with ease and create applications quickly.
On the other hand, it is easy to customize, extend, and integrate Node.js with various tools. With built-in APIs, it can be extended to develop HTTP or DNS servers. We can integrate Babel (a JS compiler) with Node.js to facilitate frontend development with older versions of Node or the browser. Jasmine is useful for unit-testing, and Log.io is useful for project monitoring and troubleshooting. Moreover, you can use Migrat, PM2, and Webpack for data migration, process management, and module bundling.
Also, there are various frameworks for extending Node.js: Express, Hapi, Meteor, Koa, Fastify, Nest, Restify, and others.
Result: It is a draw as both are equally competent.
PIP (Pip installs Python), the default package installer for Python, handles Python packages and libraries. Python has over 220 thousand packages covering a wide range of categories, including data science, calculation, image processing, and more.
NPM (Node Package Manager) handles the packages in Node.js. NPM has 1.3 million packages surpassing Pip with a staggering figure, showing how extensible Node.js is with the right package. A simple search on NPM will bring up all the packages.
Result: Node.js wins this round thanks to the absolute number of packages.
8. Trending Technologies
Python has been the language of choice for trending technologies like Machine Learning, Data Science, and IoT in this era of cutting-edge technology. Several tools and libraries are available along with experts in the community for those needing assistance in ML. In IoT, there is a pocket Python variant called MicroPython that provides Python support for IoT devices.
Result: No contest. This result is dependent upon the programmer and the type of project.
Python is suitable for both frontend and backend cross-platform development, and it is built into macOS and Linux. Programming in Python is powerful for web and desktop development, but it is not practical for mobile development.
Result: Draw (Neither is incompetent)
Python has a large and helpful community for finding support and resources online. Using forums allows you to post your questions and get advice from fellow developers while opening up new opportunities for collaboration. Python and its packages are open to contributions from skilled developers. It's a great way to find the top developers for hire for businesses.
With its active community of friendly developers who are always willing to help you, Node.js is nothing short of amazing. Through the community, you can demonstrate your talent by contributing to the open-source nature of Node.js and its various packages, even finding better career opportunities.
Result: Both feature an active and friendly community. (Draw)
11. Apps it is best suited for
Python is ideal for both small and large-scale projects, but more importantly, it is a critical component of the Data Science industry where most tools rely on Python. Other than application development, Python is used in several domains, including:
- Machine Learning
- Data Visualization
- Neural Networks
- Image Processing
- Voice and Facial Recognition
As Node.js is event-based, it is the perfect tool for applications that must handle simultaneous requests in real-time, including data transmission from client to server. Real-time solutions using Node.js include:
- IoT implementations
- Collaboration systems
- Streaming platforms
- Complicated single-page apps
Result: Due to their distinct implementations, it results in a tie.
Python and Node.js are powerful programming languages for developing web applications. The choice of one of them depends on two main factors: the purpose of the project and the developer's skill. Each has specific advantages over the other, but they should never overshadow the project requirements as there is always a way around the shortcomings. In addition, it is always helpful to know how well your team works with either technology. Hopefully, this has answered some of your questions about Python and Node.js so you can make an educated decision on which option is good for you.
If you have made it this far, then certainly you are willing to learn more about Node.js and Python. Here are some more resources related to both Python and Node.js that we think will be useful to you.