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Python vs JavaScript: why not both?

The first thing we should take into consideration is that JavaScript is a scripting language, and each command or line is interpreted (not compiled) one by one by the web browser throughout the runtime. Hence, JavaScript follows a client-side implementation.

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However, it also has engines that provide server-side implementations. In fact, the popularity of Node.js resulted in the consequent growth of JavaScript as a server-side technology. Nevertheless, it is often considered not ideal for large and complex applications since it becomes harder to maintain and reuse code as it grows.

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In comparison, as a general-purpose programming language, Python can be used as a scripting language. In other words, Python is not necessarily just a scripting language but rather a general-purpose programming language that can also work well as a scripting language.

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Moreover, Python is an object-oriented programming language, mainly used as a server-side language. Its commands are compiled to bytecode during runtime, and afterward, an interpreter executes the byte code. It can also be used as a front-end language, although it is less common.

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Therefore, before moving on to the key differences between Python vs JavaScript, it is important to highlight how one language does not necessarily replace the other.

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In fact, Python and JavaScript can complement each other and make the most out of their strengths by perhaps using Python to work on the server-side and JavaScript on the client-side. For instance, Instagram uses Python (and Django) for the back-end; and native programming languages and JavaScript for the interface.

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According to The 2020 State of the Octoverse, JavaScript has been the most popular programming language for many years, having an undeniably high-grade reputation among developers. However, Python is definitely challenging the throne. It has had an impressive popularity growth over the years (especially since 2018), mainly due to creating great web development frameworks (such as Django) and being the go-to language for machine learning and data science.

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Currently, according to Stack Overflow Developer Survey 2020, JavaScript (67.7%) has maintained its position as the number one most commonly used language, and Python is still a bit behind (44.1%). Nonetheless, if we look at the TIOBE Index for July 2021, Python is in third place regarding programming language popularity, and JavaScript comes in seventh. Last but not least, let's also consider Github's PYPL - Popularity of Programming Language, which indicates that Python is the most searched popular language, and JavaScript the third.

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One of JavaScript's main purposes was to be fast on the web. Compared with Python, Node.js has a faster performance thanks to its advanced multithreading ability. Unlike Python, which has to process requests in a single flow.

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On the one hand, applications that require dynamic and real-time interactions are often built on JavaScript to avoid making users wait. On the other hand, to process vast amounts of data and to solve a specific issue regarding machine learning, Python is the most suitable option. It stands out for its readability and easiness of use, even when handling CPU-intensive situations or complex computation using GPUs.

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Moreover, even though Python might take longer to respond, there are a couple of ways to improve its performance by benefiting from the C programming language with NumPy and by using Cython. Cython is a compiler that allows developers to create fast C modules, speeding up Python's code execution.

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Python uses Global Interpreter Lock (GIL), which consequently makes concurrent programming more difficult. GIL ensures that only one thread runs at a time, making it harder (not to say impossible) to use multiple processors with threads. To overcome this issue, Python enables developers to use the multiprocessing library, which offers functionality for distributing work between multiple processes by using multiple CPU cores.

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Multithreading is the most suitable solution for an application to be scalable, and Node.js - which is implemented on JavaScript - has it. Thanks to multithreading, it is possible to improve scalability by increasing the number of threads.

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A mutable item is able to modify its states or content. Contrarily, immutable items cannot.

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In Python, everything is treated as an object. Therefore, once an object is initiated, a unique object ID is attributed, and the object's type is defined at runtime. When the type is set, it cannot change. However, the object's state can be changed if it is mutable.

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Python supports both mutable and immutable concepts. Usually, custom classes are mutable, as well as the following objects: list, set, byte array, and dict. However, Python also has immutable objects, such as tuple, string, int, and float.

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The data specified to a JavaScript variable can be:

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• Reference type: objects constituted by multiple properties, which are stored as a reference. When a reference has attributed a value from one variable to another, then the value stored in the variable is likewise copied into the new variable.
• Primitive type: data that is neither an object nor has methods, including string, numbers, boolean, symbol, null, and undefined.

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All primitive values in JS are immutable. However, objects and arrays are mutable.

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Inheritance is one of the four core principles of object-oriented  programming languages. This concept consists of one class inheriting the attributes and methods from another class, the parent class.

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As mentioned, JS is not considered a pure object-oriented language because even though it introduced the concept of classes, this language only supports inheritance by relying on a prototype-based inheritance model. Contrarily, as an OOP language, Python uses a class-based inheritance model.

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With Python, developers automatically have REPL (Read-Eval-Print-Loop) installed on the system; it is a built-in technique. In comparison, JavaScript does not come with REPL since its code mainly runs on the browser. However, it is possible to have this technique in JavaScript if developers install Node.js.

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On the one hand, Python is strongly typed, hence no implicit conversions between types. On the other hand, JavaScript is weakly typed, meaning that conversions between unrelated types are made implicitly.

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Both Python and JavaScript support various programming paradigms. The first supports object-oriented programming, functional programming, imperative programming, and procedural programming. In turn, JavaScript supports exactly the same paradigms, except for procedural programming.

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If a function is called with incorrect parameters, Python establishes an exception. Plus, the programming language also admits some additional parameter passing syntax.

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If functions are called with incorrect parameters in JavaScript, then their value is automatically considered "undefined". Hence, JS is not as worried as Python about the exact parameters. Further, in case of any additional arguments, these will be treated by JS as special arguments.

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Python is a "batteries-included" programming language. It comes with many included modules and libraries, allowing developers to easily perform various tasks for scientific computing, data analytics, machine learning, etc.

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JavaScript does not have as many ready-to-use modules as Python, but it does include date, math, JSON, and regexp. Moreover, additional functionality is available for JavaScript through the host environment.

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