From the sleek lines of Python to the robust structures of C++ and the web-friendly syntax of JavaScript, the world of programming languages, the tools that translate human ideas into instructions for machines, is a vast and dynamic landscape, constantly shaped by innovation, necessity, and the pursuit of efficiency. As technology underpins every facet of our lives now, learning these languages has become an increasingly valuable skill. 

In this article, we will traverse the diverse terrains of programming languages, exploring their unique syntax, strengths, and applications and uncovering the stories behind their inception, the problems they aim to solve, and the communities that rally around them.

Whether you are a seasoned developer seeking to expand your linguistic repertoire or a newcomer curious about the foundational languages shaping the digital world, join us as we unravel the threads that connect the intricate web of programming languages.

Understanding Programming Languages

Put simply, programming languages are formal systems designed for instructing computers or other devices to perform specific tasks. These languages act as a bridge between human understanding and machine execution, allowing developers to write code that a computer can pretty much understand and execute. They also enable developers to express algorithms, data structures, and other computational concepts in a way that can be processed by a computer.

Low-Level Programming Languages

The very first programming language, or, to be more precise, the lowest-level programming instructions, is often called Machine Code or Native Code. Developed in the 1940s, Machine Code is inherently tied to the creation and evolution of early computers. That is why it consists of binary code—a sequence of 0s and 1s.

Programming Languages

Programmers had to write instructions in the form of binary numbers, which corresponded to specific operations understood by the computer.

As computers advanced, Assembly Languages were developed to provide a more human-readable and symbolic representation of machine code. They use mnemonics and symbols to represent the binary instructions of Machine Code, making it easier for programmers to write and understand.

As they provide a direct interface to the hardware, these low-level programming languages give programmers explicit control over memory management. This level of control enables efficient allocation and deallocation of memory, reducing the risk of memory leaks and optimising resource utilisation.

High-Level Programming Languages

It was not until 1957 that the first high-level programming language that was easier for humans to understand came into existence. Formula Translation, or Fortran, for short, was developed by IBM for scientific and engineering calculations. Its design was influenced by the need for a language that could facilitate numerical and scientific computing, and it quickly became the go-to language for such applications.

In 1958, John McCarthy, a famous American computer scientist and one of the founding fathers of artificial intelligence, developed the second high-level programming language, which he named LISP, a shortening of List Processing, mainly for symbolic reasoning—this is the process of manipulating symbols in the form of abstract representations to derive conclusions, solve problems, or perform logical operations. It is completely different from numerical computation.

LISP represents both code and data using symbolic expressions known as S-expressions. This flexibility allows the language to treat code as data and vice versa. LISP also pioneered automatic memory management through garbage collection. This feature automatically identifies and retrieves the memory that is no longer in use, reducing the burden on programmers to manage memory explicitly.

In the following years, more advanced high-level programming languages emerged, such as COBOL (1959), which was developed for business data processing, ALGOL (1960), which was designed for scientific computing and influenced the development of subsequent languages, and BASIC of 1964 which mainly aimed at making programming more accessible to non-experts. The latter played a significant role in popularising personal computing in the 1970s and 1980s.

Other more commonly known programming languages, such as C, Pascal, C++, Java, Python, and JavaScript, were developed between 1972 and 1995. We will look more into these later on.

Special-Purpose Languages

Special-purpose languages, also known as domain-specific languages (DSLs), are programming languages designed and optimised for a specific application domain or problem set. Unlike general-purpose programming languages that can be used across a wide range of applications, special-purpose languages are adapted to address the unique needs and challenges of a particular field and enhance productivity, readability, and expressiveness within a specific context.

For instance, Structured Query Language or SQL is a special-purpose programming language that is crafted for database management. Languages like HTML and CSS are mainly for web development, and MATLAB is for data analysis. Even applications such as Microsoft Word and Microsoft Excel have a special language built just for them called VBA or Visual Basic for Applications.

The Number of Programming Languages

It is quite challenging to provide an exact number of programming languages because the landscape is constantly evolving, with new languages emerging and existing ones being updated. Additionally, the definition of what constitutes a programming language can vary. Some languages may be specific to certain industries or domains, as we mentioned, and others may be experimental or have limited adoption.

So, there are various estimates of how many programming languages there are, each coming from a different source that uses its very own methodology.

SourceNumber of Programming Languages
TIOBE IndexApproximately 250
WikipediaApproximately 700
GitHubOver 500
DZoneApproximately 250

It is important to note that these numbers include both widely used languages, such as Python, Java and JavaScript, as well as less common ones. The number also includes esoteric programming languages, which are created as a test of the boundaries of computer programming language design, as a joke or a proof of concept.


The TIOBE Index is a monthly-updated tool that measures how popular programming languages are based on their search engine rankings and the number of people who know how to use them. However, it does not provide an exact count of the number of programming languages.

This means that some languages will definitely be left out of this list.

As of November 2023, Python is ranking first on the TIOBE Index, followed by C, C++, and Java. This measure is so helpful for many developers or anyone getting started in the field when choosing which language to learn next or what language is currently in high demand in the market.


Wikipedia is a great place to learn about the history and details of programming languages.

They have pages like List of Programming Languages or Comparison of Programming Languages that provide extensive data about these languages with different classifications, such as alphabetical, categorical, chronological, or generational.


GitHub is a website that offers hosting for version control using Git. It is broadly used for source code management and collaboration in software development as it allows developers to work on projects together, track changes to their code, and manage the development process.

In 2019, developers used over 370 main programming languages to do their work on GitHub. In 2022, the number of languages used on GitHub increased to almost 500, with JavaScript ranking first. Python came in second place with a growth of 22.5%, followed by Java, which has been in decline.


DZone is a website and online community that provides resources and content for software developers, architects, and IT professionals; it is basically a platform for sharing knowledge, insights, and best practices related to software development, programming languages, and various aspects of technology.

Based on the content regularly published and data from other resources, the platform once listed around 250 programming languages.

Types Programming Languages

The three categories we mentioned earlier, low-level, high-level, and special-purpose, can pretty much be the basic way to categorise programming languages that highlight their functionality. However, there are other various types and categories based on the features, use cases, and design principles of each programming language, which is what we are exploring next.

Procedural Languages

Procedural programming languages typically follow the procedural paradigm, organising code into procedures or routines, which are also known as functions or subroutines. In procedural programming, the emphasis is on specifying a series of steps or procedures for the computer to follow in order to accomplish a certain task. 

Examples of procedural languages include C, C++, BASIC, Pascal, Ada, and FORTRAN.

Procedural programming is a popular approach for developing large-scale software systems.

Object-Oriented Languages

Object-oriented programming (OOP) languages focus on code reusability and organisation. They revolve around the concept of objects which encapsulate data and behaviour, allowing for the creation of modular and reusable code. 

These languages use classes as blueprints for the code structure, which assists in managing and maintaining and also involves concepts like inheritance, polymorphism, and abstraction, which help create more flexible and scalable software solutions.

Some popular object-oriented languages include C++, Java, Python, C#, PHP, and Kotlin. 

Functional Languages

Functional languages are designed based on a programming paradigm that deals with computation as the evaluation of mathematical functions and avoids mutable data and changing states. They emphasise immutability and the use of higher-order functions, which make them well-suited for tasks like data transformation and manipulation.

There are two main groups of functional languages: pure functional languages and impure functional languages. Pure functional languages do not allow for mutable states or side effects, while impure functional languages do.

Some popular examples of functional languages include Haskell, Lisp, and Erlang.

Scripting Languages

Scripting languages are important types of programming languages that are used for automation and customisation purposes. They allow developers to manipulate and automate existing systems without the need for compilation.

Scripting languages like Python, Ruby, JavaScript, Perl, and PHP provide a convenient way to quickly modify or enhance software functionality. These languages can be executed directly by an interpreter or virtual machine, which means they do not require a separate compilation step before running.

One of the advantages of scripting languages is their ability to be embedded into HTML files, making them popular in web development for adding dynamic features to websites.

Compiled Languages

Compiled languages are a type of programming language that is translated from high-level source code into machine code before it can be executed.

These languages, such as C, C++, Java, and Scala, are known for their efficiency and fast execution speed. They are often used for system-level programming where performance is critical.

Unlike interpreted languages, which read the source code directly during runtime, compiled languages require a separate step for compilation to convert the source code into machine code before running it.

This compilation process helps improve the program’s overall performance.

Interpreted Languages

Interpreted languages are programming languages where the source code is not directly translated into machine code before runtime. Instead, an interpreter executes the code line by line at runtime. These languages offer certain advantages, such as platform independence and ease of debugging, but may be associated with a performance trade-off compared to compiled languages. 

Python, JavaScript, Ruby, and PHP, which are often used for web development, data analysis, and automation tasks, are examples of interpreted languages.

Esoteric Languages

Also referred to as esolangs, esoteric languages are unique programming languages. They are intentionally designed to be obscure, difficult to understand, and impractical for everyday programming tasks. They usually have unconventional syntax, strange semantics, and unusual features that challenge traditional concepts of programming.

These obscure languages were not created for experimentation purposes like modern esoteric languages but rather for serious purposes. One example of an early esoteric language is INTERCAL, which was designed in 1972.

Esoteric programming languages can be categorised in various ways based on their features and characteristics.

Most Popular Programming Languages

Determining the most popular programming languages can depend on various factors, including the context of use, for instance, web development, data science, or system programming, geographical location, and the specific metric used for measurement. 

In the following section, we are going to explore some of the widely used programming languages in modern computer science.


Since it was developed by James Gosling and his team at Sun Microsystems and released in 1995, Java has become one of the most commonly used and influential programming languages in the world, known for its reliability and ease of use. Many developers prefer Java because it allows them to build robust and complex applications.

Java is also versatile, as it can be used for various types of applications, such as web development. It is also a stable and scalable choice for businesses looking to develop software solutions. Its popularity created a strong community of developers who provide support and resources worldwide.


Python is another very popular programming language known for its readability and simplicity. It was developed by Guido van Rossum and was first released in 1991. Since then, Python has gained widespread popularity for its ease of learning, versatility, and a large and active community of developers. It supports several programming paradigms, including procedural, functional programming, and object-oriented.

Many startups and tech giants like Facebook, Google, and Cisco rely on Python due to its widespread adoption across various industries.


JavaScript is another widely-used programming language created by Brendan Eich while working at Netscape and was released in 1995. It is primarily known for its role in web development and is a core technology of the World Wide Web, along with both HTML and CSS.

JavaScript is designed to be compatible with different web browsers, enabling developers to write code that works consistently across various platforms. It is now one of the most popular programming languages to learn, with over 16.4 million developers using it worldwide.


C is one of the oldest and most used programming languages. It was created in the 1970s and continues to be influential in the programming world today. As a general-purpose language, C can be used for various purposes, such as system administration, network programming, and embedded software development.

Many developers around the world use C alongside other popular languages like Java, C#, and C++. Its versatility and huge range of applications make it an essential tool for businesses in different industries.


C++ is also a popular general-purpose programming language that supports both generic programming and low-level memory manipulation. C++ is commonly used for creating video games, developing embedded systems, and building IoT devices.

It is also important to note that C++ is a superset of the C language and has some similarities with Java. As of 2022, approximately four million programmers were estimated to use C++.


Developed by Apple, Swift is a powerful and popular programming language. It is built on top of LLVM, which is a framework used by other programming languages as well. Swift is widely used because it is easy to learn and use, making it accessible for beginners.

Many developers choose Swift because it combines well with other languages like Python, SQL, and HTML/CSS. So, if you are a business owner or marketing manager looking to develop new software or applications, Swift could be a great choice for your development team.

Programming languages make the backbone of the digital landscape, shaping the way we interact with technology and build innovative solutions. From the foundational assembly languages that communicate directly with hardware to high-level languages that power web applications, the diversity of programming languages reflects the diverse needs of developers and the applications they create.


1. How many programming languages are there?

It is hard to determine an exact number of programming languages, as new languages are continually being created, and some may fall out of use over time. So far, thousands of programming languages have been developed for various purposes and contexts, and many serve specific niches, industries, or research areas.

The most commonly used ones are usually in hundreds.

2. Which programming language is the best for beginners?

Python is most often recommended as a good programming language for beginners, as it 
has a simple and easy-to-understand syntax.

3. Can I learn several programming languages at the same time?

While it is possible to learn many programming languages at once, it can be overwhelming for beginners. It is generally advised to focus on one language first before moving on to others.

4. How long does it take to learn a new programming language?

The time it takes to learn a new programming language varies based on factors such as your previous coding experience and the complexity of the language itself. It can range from weeks to several months of consistent practice and study.

5. Are all programming languages used for the same purpose?

No, different programming languages have different purposes and strengths. Some are better suited for web development, while others are more commonly used in data analysis or mobile app development.

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