‘What is the best tech stack’ is an all-time popular debate and experts have been comparing different languages and frameworks and sharing their views. They express their opinion after considering multiple metrics and the current and prospective state of developments in the subjects under discussion.
In this article, we are going to perform a very similar analysis on Node.JS and Python. Both of these languages have been around for quite a long time now. Node.JS however, got to experience the zeniths of fame in the last few years. On the contrary, Python, despite being a much older language, has recently arisen once again due to its rapid adoption in Artificial Intelligence (AI) and has begun to make its way into mainstream development.
Nonetheless, both Node.JS and Python are promising candidates for the future and your choice of either of the two can greatly influence the success of your products.
Let’s start with the basics and try to understand our contestants of the day, Node.JS and Python in their foundations.
Python was created by Guido van Rossum in 1991 (yes, it is pretty old school, but still equally competent). Like almost every other software of the time, Python was constructed around C and this very same aspect acts to its advantage even today.
The utility of every language depends upon two main aspects; its compatibility with the machine and its ease of usage for the developer. Python has a significant advantage in both of these aspects. Its construction around C makes it light on the machine while its syntax is one of the easiest syntax developers have ever seen. A developer with expertise in any language can get himself comfortable with Python in no time but also the same goes for a newbie who has just started programming and is learning Python as his/her first programming language.
Recently Python has emerged into the limelight once again because of its adoption in machine learning and artificial intelligence-based projects. It is also being considered in quantum computing as well, thanks to its easily understandable code and the aid of its mature libraries over the years.
As a developer or a software company, when you are deciding on the language or tech stack you should go for in a particular project, it is key to consider the capabilities of the language or framework and the technical requirements of your project.
Following are some important aspects that you should consider in your decision-making and so are we going to discuss them onwards:
iv.) Development tools
v.) Error handling
vi.) Data processing
Each of these aspects highlights certain requirements that a developer may have when building software and a foresighted decision considering these metrics can often save from a re-development of your software even up to 10 to 15 years down the road.
Architecture refers to the manner in which the lines of code are organized and stacked upon one another and how these commands are executed when the software is running.
A key quality to consider when studying architecture is whether the language being used is a ‘compiler’ or an ‘interpreter’. A compiler language has the ability to run multiple parts of code all at the same time. This allows for faster processing while utilizing the available hardware resources at their optimum capacity.
On the other hand, an interpreter’s language processes one command at a time. It takes part of the code, processes it, executes the commands, and once they are complete moves on to the next set of commands.
Node.JS, being a compiler, has a significant advantage over Python because it can process all inputs and outputs at the same time and indicate all errors in the code the very first time. On the other hand, Python code needs to be run over and over, again and again, to identify all errors till the point that your code runs exactly the way you want it to be.
However, it is important to argue here that if Python is slow in its processing to such an extent, why is it still being used in modern projects. It is because Python commands are converted into bytecode by the interpreter. Bytecode is the natural language of 0s and 1s for the computer is executed easily, thus, making Python a feasible option along with many other positives.
Scalability primarily means the extent of complexity to which you can push your app and still have a neatly performing code. It simply means the ability of a language to handle a structurally complex code that has multiple segments and sections, each of them performing a specific task.
Node.JS is often the preference in this regard because you can easily create multiple microservices and then construct multiple segments around those services. Consider the example of a large company that has a separate department that specializes in a specific function, you have a separate team for marketing and another one for HR.
On the other hand, Python lacks the functionality of building such a structural hierarchy. It is more like a one-man show company where everything is eventually looked after by the chief executive. While scalability might be a lot easier in Node.JS, efficient use of data containers in Python can help avoid the bottlenecks when it comes to growing your app.
Companies and developers are most concerned about performance because it is directly related to the user’s experience with the software. You simply can not make any compromises on user experience. Performance can be interpreted as a combination of different aspects such as processing time at the server, time period for the request to get back to the user, and frequency of bugs and glitches the user may encounter during their interaction.
Node.JS clearly gets the head start here, thanks to the multithread processing that it is capable of. Additionally, it has the capability to process code outside of the web browser putting less load on the browser itself and thus the client-side that is running entirely on the browser performs better.
While Python may try its best to deliver, it is not yet ready for real-time processing such as live streaming or online chatting because it needs to perform commands, again and again, many of them consecutively, which the Global Interpreter Lock does not permit.
A language itself being great makes a lot of work easier for the developer but the language alone is not enough. The concept of framework and libraries exists only to address the fact that each one of 10 developers who need one function in their app should not have to code it from scratch each and every time they try to use it.
Instead, the first developer should devise a library that contains all the backend code for the particular function and the rest can simply import the library and use it in their software. This collaboration gave rise to the extensive developer communities that we see today for each and every language and framework that has ever been developed.
Considering our contestants, Python has been around for a long time now and thus, it has a very strong community that is even supported by companies like Google and Facebook. Google and Facebook both use Python for developing different parts of their digital infrastructure. Python libraries such as NumPy are especially useful in processing data and help in effective analysis of information.
Similarly, Node.JS also has the strongest community support with 350,000 libraries, the largest number of libraries for any language and this eventually helps the developer to lessen his/her hard work by effectively using functions from these libraries.
Both Node.JS and Python are equally well-ranked in this aspect so your decision will ultimately depend on other factors in consideration.
Irrespective of the nature of your app or the language you have used to develop it, every piece of software processes data. The type of processing involved and the quantum of data in usage determine the software and hardware requirements and ultimately impact upon your choices.
Both Node.JS and Python are excellent with data. However, they may not be equally suited for the same kind of data being processed. Node.JS is the perfect choice for online systems such as video conferencing software, an online store, or a messaging app.
On the other hand, Python can be very handy when it comes to processing iterations of data over and over in order to extract insights from it such as in AI and machine learning.
Once you have coded the commands, the next step is to identify errors and resolve any bugs so that the software runs seamlessly and provides an excellent user experience. For this purpose, error handling is very important.
The interpreter nature has been playing to Python’s disadvantage in many comparisons but this is where it is extremely useful. It happens so that a segment of Python code runs and identifies an error. Now, instead of moving along with the rest of the code and identifying other errors all at the same time, the code stops and gives a single error. Once you have resolved the error, the code moves forward. This provides a step-by-step diagnosis of errors and makes error removal a lot easier.
Node.JS, on the contrary, identifies all errors in the code in one go. While it may seem convenient not having to run the code over and over, it is actually difficult for a developer to assess the reasons for multiple errors and their possible solution.
The facilities and drawbacks of individual languages make it difficult to recommend either of them as all problems, one solution language. Each of them has its separate usages:
a.) JS is efficient for online applications and web development. As mentioned earlier, chatbots, online stores, and proactive websites can benefit a lot from its offerings.
b.) Python has recently developed its own unique realm where it is being used and taught as the primary language of programming. Its abilities of numerical processing and data analytics have found applications in machine learning and neural networking and are on their way to change the world for good.