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 we will list a few that we highly recommend you don’t use. So if you want to find out the best programming languages to learn DSA with, keep reading!
Best Programming Languages To Learn Data Structures and Algorithms
Python is a high-level language that is usually highly recommended by experienced programmers to learn data structures and algorithms. This is mainly because the language is highly abstract and readable. Python is also by far the easiest programming language to learn as a beginner.
Python is a great language to learn algorithms and data structures with 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 by 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. However, in my personal opinion, the benefits of Python outweigh this drawback.
C is on the opposite end of the spectrum from Python. The language is syntactically much more complex and you need to account for things like memory management (garbage collecting), pointers, and static typing. This makes C a much more difficult language to master than Python. However, the complexities also provide some benefit to learning DSA over higher-level languages like Python.
Primarily, C brings the advantage of understanding algorithms and data structures from a lower-level perspective. C has no built-in functions or abstracted data types like lists, queues, etc. This means you will have to build it yourself [or use a library to build it for you]. This can give you a much deeper appreciation and knowledge of these topics.
Why does this matter? Using the Python 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.
If you want a deep understanding of the algorithms you are building, build them in C!
Java and C# are very similar languages. So we are going to combine them together for this one 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 similarily to Python.
Which Programming Language Should You Learn Data Structures And Algorithms With?
Although the languages above will be most beneficial to learn data structures and algorithms with, ultimately, you should pick the language you’re most comfortable with. The important thing to do when learning DSA is to just get started. If there is a language above that you feel comfortable with, great! If you don’t know any languages get, pick one of those. If you are comfortable with a language outside of those above, then just use that one. Learning two languages will slow you down more than using a non-ideal language.
With that being said, I also want to point out some bad languages to learn DSA with and why. With that knowledge, you can understand why they are not an ideal option and why you may decide to use another language.
Worst Programming Languages To Learn Data Structures and Algorithms
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.
Functional Languages: Lisp, Haskell, Clojure, Erlang, etc.
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. If you already know a language really well, use that. However, I personally recommend learning data structures and algorithms with Python if not. When you want to learn algorithms, you want to understand the logical process happening and not get caught up in syntax. Python’s simplistic, easy-to-read, and writing style makes it easy to worry less about the syntax and more about the algorithm 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 how the data structures are 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!
Is C++ Best For Data Structures And Algorithms?
C++ is not the ideal language to learn DSA. Its implementation of object-oriented programming is both clunky and confusing. It also doesn’t have a base class that data structures like hashtable rely on. However, you can ultimately learn DSA with any language and C++ will give you a good lower-level look at how these data structures and algorithms are built. So if you know C++ well, go for it!
Should I Learn A Programming Language Before Learning Data Structures and Algorithms?
Yes, you should learn a programming language well before learning data structures and algorithms. DSA is one of the toughest aspects of programming to wrap your head around. If you are not comfortable with the tools you are using, you will likely get frustrated and give up. If you’re looking for a good language to learn, try Python!
Best Places To Learn Data Structures and Algorithms?
If you want to find good coding platforms to learn DSA, check out my reviews for HackerRank and Codewars. They are both 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.