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Bridging the Cultural & Communication Gap

“Python is the future of programming.” 

                          “It seems impossible to develop a program without JavaScript.”

 “Python has become the lingua franca of coding.”

                        “JavaScript is the sine qua non of modern web development.”

These are the phrases that you hear more and more these days as both Python and JavaScript have consistently remained at the top of the most popular programming languages in the last few years.

Top Programming Languages Graph

Top Programming Languages (Source: GitHut 2.0)

So which of the two programming languages is going to rule in the coming years?

In this article, we focus on the top 5 comparisons between Python and JavaScript. In the end, you’ll come to know which service is best for you – Python Development Services or JavaScript Services.

Python Vs JavaScript Which Programming Language Will Rule the Future

When it comes to software development, there are only a handful of languages that can be used almost anywhere, be it web development, mobile application development, IoT software development, or AI & ML solution development.

Python and JavaScript (with the support of Node.js) are the ones that fall under this category.

According to Stack Overflow’s Developer Survey, JavaScript has retained its position at the top of the most commonly used programming languages.

However, the popularity of Python has risen by leaps and bounds, overtaking languages such as Java, C#, PHP, and C++. Its fast-growth clearly threatens to dethrone JavaScript.

Top programming, scripting and markup languages

However, the popularity of Python has risen by leaps and bounds, in a way that it has become the most wanted language among software developers – its rapid growth clearly threatens to dethrone JavaScript.

Most wanted languages

We can say that the battle is neck-to-neck.

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To understand which language will rule in the coming years, we need to go through several parameters of both the languages while comparing them.

So let’s dive into the comparisons –

Frontend Development

The tools present on the user’s device play an integral role when it comes to frontend development, particularly the web browser. Moreover, browsers can only process JavaScript code.

Talking about Python, there are ways to run its code in the browser which involves a Python interpreter written in JavaScript. For example, PyPy and CPython.

However, it is not wise to replace languages which are frontend by nature – even if you utilize Python interpreter, the interpretation of code makes the execution process slower.

Here, JavaScript wins the battle of Python vs JavaScript frontend development.

Backend Development

In 2009, a new technology made its debut the vast universe of backend development. Node.js was the first sincere attempt to pull JavaScript on the server-side, i.e. a runtime environment that executes JavaScript code on the server-side.

It has evolved to become an advanced backend technology which comes with fewer dependencies and is very simple to learn.

If we compare Python with Node.js, the latter one is best suited for smaller projects, runs faster, and offers scalability while the former is suited for a wide range of projects (from numerical computations, web development solutions, to network programming and AI & ML), is easy to learn, and is awesome at error handling (also takes less time to fix bugs).

We can say that both Python and JavaScript are winners when it comes to Python vs JavaScript backend development.

Data Science

Data science has quickly moved from experimental to applied technology, and the level of its adoption is growing rapidly.

While implementing a data science project, a few substantial factors come into play.

Let’s check out some of the best factors of JavaScript and Python that make them a preferable choice for a data science solution.

JavaScript for Data Science:

1) Data visualization: JavaScript stands out for it data visualization. Libraries like D3.js, Chart.js, Plotly.js and many more make it a powerful data visualization and dashboard development technology.

2) ML libraries: Libraries like Tensorflow.js, Brain.js, machinlearn.js, math.js, and more bring ML to JavaScript developers – these libraries help them carry out complex matrix manipulations and increase the speed and efficiency of project execution.

3) Product integration: Organizations are increasingly utilizing web technologies backed by Node-based stack to build their custom product. If data scientists have good grip over JavaScript, they can seamlessly communicate with product developers and build the product.

4) ETL processes: ETL stands for extract, transform, load which are the three fundamental functions of database management. Node.js, because of its asynchronous nature, is commonly used in ETL applications. Databases with hundreds of rows can be quickly processed with non-blocking calls over Node.js. This decreases waiting time and increases processing efficiency.

Python for Data Science:

1) Large set of libraries: A decent library ecosystem is one of the main reasons why Python is the most preferred language for data science projects. Python libraries offer developers with all the basic items so that they don’t have to code everything from the scratch. For e.g., Pandas, NumPy, SciPy, Keras, and PyBrain.

2) Data visualization: As mentioned above, Python supports a variety of pre-built libraries. Some of them act as visualization tools. With this, developers have the opportunity to represent data through histograms and charts. This is easily comprehensible to the non-technical people.

3) Code simplicity: Coding with Python is super easy to learn and implement. Building data science solutions involve complex algorithms and versatile workflows, where Python’s simplicity allows developers to write reliable codes.

4) Multi-threading: It is often helpful to process large data sets or run simulations in parallel. Python supports multi-threading which makes the data science job pretty easy.

If we closely observe the above factors, we can deduce that Python has the upper hand over JavaScript. Thus, Python wins the battle when it comes to Python vs JavaScript data science.

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Performance is the most critical element of any programming language. This is because it directly impacts the speed of the application which is dependent on how fast the code is getting executed.

Comparing Node.JS, a giant ecosystem of JavaScript, and Python performance wise, it’s clear that the former one is significantly faster. This is because it uses the Google V8 JavaScript and WebAssembly engine, which is a super-fast and dynamic engine.

Moreover, with its high performance and speed, Node.js is a perfect solution for applications featuring real-time messaging or chatting, as well as for heavy-weight applications, content management platforms, multi-vendor marketplaces, e-commerce solutions, and more largely depending on the speed of processing.

Here, JavaScript wins the battle of Python vs JavaScript performance.

User Friendliness

Python is a programming language that is mostly the beginner’s choice, especially for those who don’t have a programming background.

Several factors that make Python a user-friendly language are:

  • High readability of Python code
  • Fewer lines of code in comparison to languages like C and C++
  • Fewer structural rules & restrictions
  • Availability of numerous frameworks that contain pre-written code to speed up the project implementation

In comparison to Python, JavaScript is complicated and here’s why:

  • Difficult to debug
  • More structural rules & additional characters (such as curly brackets & semicolons)

No wonder why Python is the most loved and most wanted programming language among the two. Python beats JavaScript in user-friendliness.


So the score is 2 – 2!

We have gone through the 5 most crucial factors which will determine the future of any programming language – frontend, backend, data science, performance, and user-friendliness.

While Python beats JavaScript at data science and user-friendliness, JavaScript surpasses Python in frontend development and performance.

We can conclude that both of these languages will rule in the coming years, but in their respective fields – Python will dominate the machine learning, data science, and neural networks world, while JavaScript will take over the web development world featuring real-time applications.


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