JavaScript and Python are the two most popular programming languages among software developers.
Due to the stark differences in the two technologies (and use cases they pertain to) simply comparing them head-to-head is not conclusive in determining which language is “better”. Indeed, Python performs certain tasks a lot better than JavaScript, and JavaScript does certain things that Python cannot do, too.
Therefore, it will be the underlying use cases of JS and Python that this article will focus on, and what makes the language ideal for that particular use case, whether that be web development, artificial intelligence tasks, and more.
That being said, there are also tasks that both JavaScript and Python can perform well. These scenarios, where the programming language of choice is not so clear-cut, will also be discussed, with reasons for choosing one over the other.
If you’re wondering which of the two languages to learn today, the answer will become clear by the end of this article.
Both JavaScript and Python have been around for quite a while (initial releases in 1995 and 1991 respectively), and have evolved over time to maintain their positions as modern, industry standard languages.
So what does JavaScript vs Python look like in 2021? Let’s briefly run down where the languages are today before delving into their common use cases.
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JavaScript and Python in 2021
Both JavaScript and Python are scripting languages – E.g. They both execute programs via a runtime environment to automate some task or logic. They are the most popular programming languages period, and dominate the job market in terms of the amount of jobs on offer.
Both are interpreted (as opposed to compiled) whereby code is translated into machine-readable instructions as the program is being executed.
This brings advantages like a rapid test-feedback loop as you are developing, but often comes at the cost of speed – a common trade-off versus compiled programming languages.
JS and Python are also both multi-paradigm languages, each supporting multiple “styles” of programming.
The State of JavaScript
JavaScript is a high level programming language that is mostly known for its presence in web browsers for enabling interactivity in web apps.
In the last decade JavaScript’s role has dramatically expanded from just the web browser, now also widely used server-side via the Node.js runtime, offering a full stack solution for web applications. It is also used for native mobile app development (for iOS and Android).
JavaScript is also quite a forgiving programming language; it is dynamically typed and allows scenarios that stricter programming languages would treat as syntax errors – such as missing function arguments, or undefined and null variables.
JavaScript is a multi-paradigm scripting language
Historically speaking, programming languages often conform to one or more “types”, whether that be:
- Object-oriented: The popular paradigm of modelling data and logic around objects. (C++, Java, Python, etc.)
- Functional: Entire applications consisting of function definitions and function applications. (Haskell, OCaml, etc.)
- Imperative: Applications as a series of statements (Fortran, Pascal, etc.),
- Event-driven: Applications that respond to events, such as I/O, web APIs, etc (C++, Java, etc.)
What makes JavaScript impressive is that it can be treated as any of the above paradigms, offering support for each style of programming. JavaScript acts as an object oriented programming language via its prototype-based inheritance model – and this is how the language is primarily used.
The State of Python
Python is a general-purpose, object oriented programming language with a focus on readability from its simplified and expressive syntax.
The Python programming language is used in a variety of fields ranging from web development (with execution on the server-side), web scraping, machine learning and data processing tasks. Python is also used heavily in academia for research efforts, and is adopted in niche fields like casual game development.
Python is an object oriented programming language primarily, also multi paradigm
Although Python has a strong focus on objects, it is also a multi paradigm language supporting imperative and functional paradigms, as JavaScript does, but also a couple of others:
- Reflective: The ability of an application to examine, introspect, and modify its own structure and behaviour.
- Structured: A goal of improving clarity of a program by making extensive use of structured control flow constructs of selection and repetition, block structures, and subroutines.
Python has recently risen to prominence with its dominance in Machine Learning and fields that ML encompasses, including Deep Learning, Natural Language Processing and computer vision. It is also heavily used in Reinforcement Learning.
Python vs JavaScript Salaries
According to Stack Overflow, a Python developer can expect an average salary of $59,454, whereas a JavaScript developer can expect $54.049.
These figures are by no means the highest paying in the industry, but the job market for JavaScript and Python skills is vast, making up the majority of software development requirements.
Developer salaries in the US tend to be a lot higher than the global market. Referring to US based salaries alone will skew the salary ranges considerably to the upside.
As of October 2021, the average annual pay for a Python Programmer in the United States is $115,066 a year, and $107,529 for JavaScript.
The numbers tell us that the Python programming language has a small edge for salaries, and this gap may continue to widen in the future as the market demand for expert data science roles continue to rise.
JS vs Python by Use Case
The following sections will discuss how Python and JavaScript fare in a range of common use cases.
Python vs JavaScript in Web Development
Both Python and JavaScript are used for the web, but where Python solely lives on the server, JavaScript is present both on the server and in the web browser.
It is on the server where JavaScript and Python cross paths the most. JavaScript developers rely on the Node.js runtime environment for server-side applications; a cross-platform, fast and efficient JavaScript runtime engine.
The Node.js ecosystem is huge, with a wealth of packages developers rely on being available on NPMJS, the largest and most widely used public repository for JavaScript code.
Web Application Frameworks
For REST APIs, the Express framework has been relied upon for a number of years and is still the go-to package to quickly spin up a REST API service. GraphQL has recently been experiencing more widespread adoption as a modern web server offering a more modular API service, again with the flagship implementation being in JavaScript.
With JavaScript, it is common to develop both a back-end service and a front-end application that pertain to two different workspaces (or environments). With Python however, it is more common to handle a web app under a unified project.
Python also offers capable and popular web frameworks too, notably Django, Flask, Web2Py and Pyramid, among others. Both Django and Flask offer good salaries for Python engineers, in a similar range to JavaScript frameworks.
Standalone Execution
Developers need not only rely on these frameworks though – standalone Python or Node.js scripts can be executed on the server and managed via a process manager (the most notable of which being PM2).
This makes Python and JavaScript very capable of carrying out many ad-hoc tasks on the server:
- File system management. Both Python and JavaScript have filesystem support built into their standard libraries.
- Data management. Although Python is capable of connecting to major databases (SQLite, MariaDB, MongoDB, etc), it is Node.js that offers more comprehensive and seamless support for databases.
- Web crawlers and scrapers: Python is typically used for web crawling with packages like BeautifulSoup., winning against JavaScript in this department.
Full Stack with JavaScript
Perhaps JavaScripts biggest advantage in web development is that developers can simply learn one programming language (JavaScript) and write an entire web app using only JavaScript.
Doing so offers some clear advantages to a developer team, needing only to rely on one core technology, and not having to maintain separate codebases. While Node.js services can run on the server, the front-end application can be built using a JavaScript library such as React, Vue, Angular, or even the newcomer Svelte.
JavaScript frameworks offer performance enhancing features: optimised static bundles, ability to cache large portions of the application, efficient rendering with state management and a component-based system, and more.
Such front-end libraries simply do not exist with Python. On the contrary, WebAssembly is seen as the technology that will eventually replace at least some JavaScript in the browser, and is already used heavily in blockchain protocols server-side.
Python vs JavaScript in Data Science
Although JavaScript does have its place in data science as a data visualisation tool, it is Python that dominates the field in terms of data-crunching applications.
Python’s dominance in Machine Learning
Before Python’s rapid adoption by the data science community, the R programming language was the leader in scientific computing. Even with competition from languages like Julia and MatLab, Python is easily dominating the field in both academia and in the industry.
To read more about the field of data science, take a look at Iglu’s accompanying piece dedicated to exploring this topic in depth: Best Data Science Programming Languages
Machine Learning is perhaps the fastest growing field that Python is benefitting from. Python frameworks specifically for ML include Tensorflow, PyTorch and Keras that are now the most popular choices for data scientists.
It is with these tools that engineers can explore Computer Vision, Natural Language Processing, Reinforcement Learning and the many variants of these core competencies in the field of AI.
JavaScript support for data science
JavaScript does have some support for ML though, the most credible of which being Tensorflow.js, a JavaScript implementation of the framework. This makes it possible for Tensorflow based applications to run on the server via a Node.js environment, maintaining the full stack JavaScript solution we discussed above – even though it is not as fully-featured as its Python counterpart.
What further props up Python as the go-to programming language for data science is the surrounding ecosystem of software, with tools like Jupyter Notebook and Google Colab making it easier to build and run GPU-intensive programs.
Where Python does the heavy lifting of data processing tasks, JavaScript delivers analytics to the browser; they work hand-in-hand in this scenario.
Python vs JavaScript in Native App Development
Both JavaScript and Python are used for native app development, albeit for different use cases and platforms – that has been somewhat of a trend throughout this article.
Python has a number of GUI frameworks, the most popular of which being TkInter, the go-to GUI framework for Python developers. Other notable frameworks include PyQT5, built around the Qt framework, and Kivy, a cross-platform framework focused on multi-touch interfaces.
Modern hallmarks of a good GUI tool (or any library for that matter) first and foremost require cross-platform compatibility, open source licensing, and a dedicated community that maintains that library. With Python itself having all these characteristics, it is natural to develop such libraries with the programming language.
Where JavaScript shines on the other hand is the ecosystem of tools for developing mobile applications with React Native, the “learn once, write anywhere” framework.
React Native is now the industry standard for developing apps for both iOS and Android with one unified JavaScript codebase.
Some knowledge of Xcode and Android Studio is required, but the bulk of development, debugging and initial testing can all be done without having to build the app for a physical device – and this workflow has come a long way.
Python does not offer such an advanced and streamlined solution to mobile apps, but the aforementioned GUI frameworks are more suited for desktop app development.
There is a somewhat experimental library named React Native for Windows and macOS, that is very much in active development but worth keeping an eye on for the JavaScript developer.
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Python vs JavaScript: Head to Head
This section lists the key differences of Python and JavaScript. Let’s run them down.
Package Managers
NPMJS is the go-to public repository for JavaScript, while PyPi (Python Package Index) is Python’s, also offering a huge amount of packages.
Mutability
Python has mutable and immutable data types like mutable sets and immutable lists, whereas JavaScript has no concept of mutable and immutable (everything is mutable).
Syntax Encoding
Python source code is ASCII encoded by default, whereas JavaScript is UTF-16 encoded with no support for manipulating raw bytes.
Numbers
Python has support for int, float, fixed point, decimals, etc, whereas JavaScript only supports floating point numbers.
Hash Tables
Hash tables are built-in with Python in the form of dictionaries, sets, etc, whereas JavaScript has no support.
Inheritance
Python uses a class-based inheritance model whereas JavaScript uses prototype-based inheritance. JavaScript’s class syntax is just syntactic sugar, with everything being objects under the hood.
Code Blocks
Python relies on indentation whereas JavaScript relies upon curly braces.
Scope
Python is ideal for data intensive applications pertaining to data analytics, machine learning and mathematic-intensive processing. JavaScript’s scope primarily lies with web applications, but has successfully expanded into native mobile development in recent years, too.
The Best Scripting Language?
Ultimately, the best scripting language between Python and JavaScript depends on the requirements at hand. It should now be much clearer which you would choose for a prospective project or career path!
Summary
Even though JavaScript and Python share high level characteristics, their underlying implementations are very different, and are therefore suited to very different use cases – some of which have been discussed in this article.
Developers interested in the web and even mobile application development should consider learning JavaScript, not only for these use cases but also for critical skills for server-side development too.
For those interested in data analytics, neural networks and the Machine Learning space, or those looking for stricter syntax more suited for system programming, Python will be the programming language of choice.
With that being said, both JavaScript and Python are indeed the most used programming languages period, and that does not look like it will change for the foreseeable future. They are both object oriented programming languages (and are both multi-paradigm), so concepts learned from one can be carried over to the other.
The job market for both languages remains very strong with career prospects in either one.
As a final Python vs JavaScript note for those still on the fence, it is also a great idea to just start coding, whether in Python, JavaScript, or both! Get those vital perspectives via experience and really figure out which one is best suited for you.
