Node.js and Python are two established solutions for server-side application development. With either platform, your team can develop and manage web apps of any complexity and functionality. As an app owner, you might be wondering which tool to choose for your next project. The choice will not be easy, and to make the final decision you should be aware of the advantages and limitations of Node and Python, and, more importantly, understand cases and types of applications where Node.js could be better than Python, and vice versa.
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Even though Node.js supports only one thread, its event-based architecture and non-blocking I/O allow for maximising the usage of a single CPU and computer memory, making servers faster and more productive. The event-driven architecture based on asynchronous calls allows Node.js servers process more concurrent requests than most conventional multi-threaded servers. In addition, Node.js’s non-blocking I/O, which does not block program execution under I/O-heavy workloads, is the first thing that improves the runtime performance of Node.js applications, making Node one of the fastest server-side solutions around.
Even though Node.js is a single-threaded solution, its standard library provides modules that support high scalability. Node clusters and workers are abstractions that can spawn additional Node.js processes depending on the workload of your web application. Limited only by the number of CPUs, you can easily scale your Node applications to fully functional enterprise solutions.
Node’s event-driven architecture comes with certain limitations as far as CPU-intensive operations are concerned. Although Node is great in handling multiple concurrent requests, it exhibits significant performance bottlenecks in such operations as generating graphics or resizing images. Luckily, a workaround in which you make a new task queue to manage CPU intensive requests exists, but it requires spawning additional workers and introducing new layers to your Node.js application.
Node.js philosophy leaves it too much freedom of choice for developers in what modules and tools to select. What follows is that developers can spend a considerable amount of time figuring out which module or library to choose for handling a development task. Developers need more planning, time, and involvement to find well-maintained modules and install and integrate them. Unfortunately, some of these modules might be buggy and introduce unexpected behaviour to your Node applications. If your application uses many modules built by different developers and having a different level of maintenance and bug fixing, it is crucial to have an experienced developer in your team.
Python has a concise and expressive syntax that helps think more clearly when writing programs and makes it easier for others to maintain and enhance your applications. Also, being dynamically typed and flexible, Python allows writing a code that is less verbose but more modular and extensible. Python’s readability facilitates the coordination of teams working on large projects and helps concentrate on completing real tasks rather than scaffolding and tweaking your code base. Python is also quite easy to learn, which allows experienced developers to quickly jump into your Python projects and bring their experience in other programming languages to the table.
Thanks to clean, concise and simple syntax, developing in Python is much faster than in Java or C. Although it’s always difficult to provide an accurate assessment of the development speed, most experts agree that developing a Python application is about 5 to 10 times faster than developing the same application in Java. The time savings are even greater if compared to C and C++. The speed advantages substantially outweigh performance downsides of Python that originate from its interpreted nature and dynamic typing. Due to the language’s extremely stable architecture, the availability of web development frameworks (e.g Django) and third-party modules, applications developed in Python are no less reliable than those written in any other framework.
Our brief overview demonstrates that neither Node nor Python is perfect. If so, how to make the right decision about which one to use? The answer is straightforward: both environments are good for different types of apps and tasks.
The event-driven architecture of Node.js, which allows multiple server requests and concurrent operations, is very good for chats and collaborative apps for video conferencing, document editing or drawing, collectively known as Real-Time Applications (RTAs). Node’s power in handling heavy I/O operations and shuffling of data between the front end and the back end also makes it a great choice for Single Page Applications (SPAs), which involve heavy client-side processing and rendering. Similarly, whenever performance and scalability of web applications are of concern, the lightweight and fast Node.js outperforms Python.
At the same time, you should opt for Python if you are building CPU-intensive applications. The thing is that Node’s single-threaded design is not suitable for CPU intensive operations with graphics and data. Making heavy computations in these types of tasks may simply block all incoming requests, leading to the slower performance of your web application.
Also, you should definitely choose Python when the speed of development is critical. With its rich standard library and modules available out of the box, Python solutions are very powerful in Rapid Application Development (RAD). With Python, you don’t need to search for many utility modules and packages for your application. Instead, you can immediately proceed with the design of a fully functional prototype, which could be supplemented with other features later. Python’s simple and concise syntax makes writing code very fast too.
Finally, many experts cite Python’s expressiveness and ease of use, along with its vibrant community, as one of the main reasons to use the language in the Internet of Things projects. On top of that, Python is the language of choice for one of the most popular micro-controllers for IoT devices in the market, the Raspberry Pi. Since much of the training literature for IoT and Raspberry Pi is written in Python, it’s natural to use this language for IoT programming.
When choosing between Python and Node.js, you should definitely consider the speed of development, the need for scalability, and your application’s type. If your requirement is fast development of CPU-heavy applications or the development of IoT back-end, go for Python. Conversely, choose Node.js if you are thinking about RTAs, SPAs, and other I/O heavy solutions. Hopefully, this overview will help you make the right choice of your web development environment for the next project.