Introduction
So you’ve decided to learn data structures and algorithms but you don’t know the best language to learn them with? Well, it’s actually a more complex answer than you might think. There is no one best programming language to learn these topics. However, there are definitely some languages that are better suited than others. Below we are going to list the pros and cons of some of the best programming languages to learn data structures and algorithms. Then list a few that we highly recommend you don’t use, followed by our top picks. So if you want to learn what the best programming languages to learn DS and algorithms are, keep reading!
Best Programming Languages To Learn Data Structures and Algorithms
Python
High-level languages like Python, JavaScript, and Ruby are generally highly suggested due to their readability. They are also all very similar because they are dynamically typed and highly abstracted. If you are going to choose one of these languages, I highly recommend Python. If you only know and want to use JavaScript or Ruby, those could be good options to learn DS and algorithms as well.
Python is a great language to learn algorithms and data structures because it has a very clean, simplistic syntax that looks very similar to pseudocode. The simplicity of the language helps you to focus on writing the algorithm and less on the syntax necessary to do so. It is also generally much easier to understand how an algorithm works by looking at python code than looking at any other language.
A potential downside of Python is that it is dynamically typed, meaning you do not declare types in the syntax. Although this helps keep the syntax clean and readable, it can be more confusing for a beginner to understand what types are being used and for error-catching while writing code.
C
C is on the opposite end of Python and is a great choice for opposing reasons. The language is syntactically much more complex and you need to account for things like memory management (garbage collecting), pointers, and static typing. However, using C does bring the advantage of understanding algorithms and data structures from a lower-level perspective.
More importantly, C has no built-in functions or abstracted data types like lists, queues, etc. This means you will have to build it yourself. This can give you a much deeper appreciation and knowledge of these topics.
Why does this matter? Using Pythons built-in sort() method is not going to help you learn sorting algorithms and using Python lists won’t give you a deep appreciation for the data structure. C makes sure you do not have these shortcuts readily available without external libraries and allows you the freedom (and responsibility) to build from the ground up.
Java, C#
Java and C# are very similar languages, so we are going to combine them since they have the same advantages and disadvantages.
The main detractor from using Java or C# is that the syntax is very clunky and unnecessary. The languages are object-oriented and require that you write a lot more boilerplate code without having any benefit in understanding the data structures and algorithms you are using.
That being said, the languages are statically typed. This means that the types being used will be more apparent and bugs will be caught by your IDE. This could potentially make the process of writing code easier than C and even Python. They’re also high-level programming languages that are easier to learn than most. So you can get started quickly.
Worst Programming Languages To Learn Data Structures and Algorithms
C++
This is a difficult language to learn and its implementation of OOP makes it clunky and confusing. It also doesn’t have a common base class, which data structures like hash tables rely on. If you absolutely wanted to use this language, you can. However, it definitely isn’t one I recommend unless it’s a language you are already very comfortable with.
Lisp, Haskell, Clojure, Erlang, and Other Functional Languages
Writing algorithms in functional languages can look very different than in any of the languages mentioned above. I am a strong advocate of the power of functional programming and I think learning functional programming is a great idea. However, I think it is a terrible idea to learn algorithms and data structures with a functional language.
For starters, most examples of algorithms you find online will be written in one of the languages above. In technical interviews and on the job, you will also likely be expected to use those languages. Functional languages are much less commonly used in the industry. So the major takeaway is that you should learn functional programming, but learn it independently of data structures and algorithms!
Top Programming Languages To Learn Data Structures and Algorithms
So obviously, there is no best programming language to learn data structures and algorithms. However, I personally recommend learning data structures and algorithms with Python. When you want to learn algorithms, you want to understand the logical process happening and not get caught up in syntax. Pythons simplistic, easy to read and write style makes it easy to worry less about the syntax and more about the algorithm you are writing and the data structures you are using.
If you want to understand the lower-level details happening, then C is also a great option. Although realistically, you can always learn this later and it is not critical to understanding algorithms, just the data structures implemented in lower-level languages. C is also a much more challenging language to master, but will likely make you a better programmer. So take that into account when deciding on what language to choose.
If you have an upcoming job interview and need to learn data structures and algorithms as fast as possible, use whatever language you are most comfortable with. It will allow you to get started quickly and without the hassle of learning a new language.
Also, check out my reviews for HackerRank and Codewars. They can both be great resources to help you learn these topics quickly. In addition, if you want to become a web developer, check out my list of resources here.
Happy coding!
