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ProgrammingScienceEngineering

What are the best programming languages for science and engineering?

14

Options
Considered

18

User
Recs.

Jan 29, 2024

Last
Updated

13 Options Considered

Best programming languages for science and engineering	Price	Platforms	Current stable version
-- Nim	-	Windows, MacOS/iOS, Linux /Android/Termux, *BSD, Solaris/SmartOS, HaikuOS, lots of others	2.0.0
-- C	FREE	-	C'18
-- Julia	Free	Windows, Linux, Mac, FreeBSD	1.5.3
-- Go	Free	Windows, Linux, Mac etc.	1.21.0
-- Rust	-	Linux, MacOS X, Windows, BSD	1.71.1

Nim

Top Pro

Garbage-collected

You don't need to deal with all those manual memory allocations, Nim can take care of it. But also you can use another GC, or tweak it for your real-time application or a game. See More

Specs

Platforms:Windows, MacOS/iOS, Linux /Android/Termux, *BSD, Solaris/SmartOS, HaikuOS, lots of others

Current stable version:2.0.0

CPU:All CPU architectures that have an ANSI C compiler or JavaScript interpreter

Top Pro

Built-in Unicode support

You can use unicode names for variables, there is "unicode" module for operations with unicode. See More

Top Pro

Really cross-platform

The same code can be used for web, server, desktop and mobile. See More

Top Pro

Compile-time execution

Nim has a built-in VM, which executes macros and some other code at compile time. For example, you can check if you're on Windows, and Nim will generate code only for it. See More

Top Pro

Easy to integrate with another languages

You can use Nim with any language that can be interfaced with C. There's a tool which helps you to create new C and C++ bindings for Nim - c2nim. Also, you can use Nim with Objective C or even JavaScript (if you're compiling for these backends). See More

Top Pro

Type interferencing

You only need to specify types in your procedures and objects - you don't need to specify type when you're creating a new variable (unless you're creating it without initialization). See More

Top Pro

Easy to read

Nim has a lot of common with Python in terms of syntax. Indentation-based syntax, for/while loops. See More

Top Pro

Strict typing

Checks your code at compile time. See More

Top Pro

Great metaprogramming features

There are generics, templates, macros in Nim. They can allow you to write new DSL for your application, or avoid all boilerplate stuff. See More

Top Pro

Has built-in async support

Nim has "asyncdispatch" module, which allows you to write async applications. See More

Top Pro

Supports UFCS (Unified Function Call Syntax)

writeLine(stdout, "hello") can be written as stdout.writeLine("hello") proc add(a: int): int = a + 5 can be used like 6.add.echo or 6.add().echo() See More

Top Pro

Has built-in unittest module

With built-in "unittest" module you can create test with a very readable code. See More

Top Pro

Multi paradigm

Imperative, OOP, functional programming in one language. See More

C

Top Pro

Helps with learning other languages later

A lot of languages used in the industry have a C-like syntax (C++, Java, Javascript, C#, PHP) and starting with C will help new developers to be familiar with it's syntax and by extensions with the syntax of many popular languages. See More

DazzlingFionnuala's Experience

Great for low level applications. See More

Specs

Current stable version:C'18

Paradigm:imperative

Standard:ISO/IEC 9899:2011/Cor 1:2012 or C11

Typing discipline:static

Top Pro

Industry standard

C is the industry standard programming language, moreover, it is the most popular programming language to use. C is the language used for most Windows, UNIX and Mac operating systems. See More

Top Pro

Easy to drop down to assembly

Sometimes you really need to program directly in assembly. C’s ABI and common compiler extensions make this a piece of cake. See More

Top Pro

Low level of abstraction

While higher level languages languages like Java and Python provide possibilities to be "more expressive" per line of code, it's much more convenient to start with "less efficient" (get me right) language, in order to get initial concepts of how things behave at lower level. Actually C is a good starting point moving to both higher and lower levels of abstraction, the good example here would be learning C before Assembler, as for general use the Assembler quite hard to understand due to low level of its abstraction (like getting the understanding on how loops work in C before trying to implement them on Assembler). See More

Top Pro

Must-have

Capability to program in C is greatly appreciated in developers, creates an image of competency, and many programmers will learn it at some point in their careers. See More

Top Pro

Great for efficient and fluid data acquisition applications

Top Pro

More control over the code

Top Pro

C is simple with lesser rules than any other language

C is standardized and it is the go-to language when you have to speed things up. See More

Top Pro

If you can't grok C you should not be a professional programmer

It sets an early bar that if you can't hurdle you might as well do something other than programming and not waste any more of your time. See More

Top Pro

Low level langauge

Top Pro

Foundational, difficult but important

Learning C will teach valuable skills and transferrable understanding of computing. While learning a scripting language may be easier, students will not understand system constraints and performance problems, nor what features like garbage collection are actually doing in other languages. See More

Top Pro

Teaches good practices

Writing in C will require you to understand how things are done. C implies using and understanding the fundamentals. Learning a higher-level language after is much easier. See More

Top Pro

Basic concepts can be applied to accelerate learning any other language

You can easily pivot knowledge learned here and apply it to almost every other language. See More

Top Pro

Ubiquitous

There is a C compiler available for probably every computer system in existence today. See More

Top Pro

Portable between CPU architectures

C was designed to be independent of any particular machine architecture, and so with a little care, it is easy to write "portable" programs (see here). By design, C provides constructs that map efficiently to typical machine instructions, and therefore it has found lasting use in applications that had formerly been coded in assembly language like operating systems or small embedded systems. See More

Top Pro

The king of languages, imitated, extended but never equalled

Made of a small set of keywords and rules, only your imagination is the limit. Above all, when it comes to 'pro' programming, C is the only one to rely on. See More

Top Pro

Portable

C is portable between most hardware. Generally a C compiler is made for any new architecture, and already exists for existing architectures. C is portable between all operating systems (Windows, UNIX, Mac, etc.) and only needs a program to be recompiled to work. This allows anyone on any operating system to learn about the language and not be held back by intricacies of their operating system. With this said, C's portability these days is not quite what it used to be. Much of said portability relies on the POSIX standard in particular, and as time passes, the compliance of a given system with that standard is becoming less certain; especially in the case of Linux. Most things will still be portable (or at least emulatable) between Windows, Linux, and FreeBSD for example; but you will at times need to make use of platform-specific support libraries and APIs as well. See More

Top Pro

Understanding of computers

Learning C forces you to grapple with the low-level workings of your computer (memory management, pointers, etc.) in ways that the other languages abstract away. Without an understanding of these low-level aspects of computer programming you will be limited if you try to develop an application that needs to run in a memory or performance constrained environment. Other languages like Python can obscure a lot of details, so your foundation may be weaker. See More

Julia

Top Pro

Strong dynamic typing

Dynamic and high level, but does not isolate the user from properly thinking about types. Can do explicit type signatures which is great for teaching structured thinking. See More

DazzlingFionnuala's Experience

Speed, large scale efficiency, matrix use, highly useful and resourceful REPL. See More

Specs

Platforms:Windows, Linux, Mac, FreeBSD

Current stable version:1.5.3

Type Model:Dynamically Typed

Top Pro

Great standard REPL

Out of the box Julia has a very good Read-Eval-Print-Loop, which both completes functions and types, as well as completion based on history of previous statements. It integrates well with the shell and has an excellent online help system. See More

Top Pro

Nice regular syntax

Julia code is easy to read and avoid a lot of unnecessary special symbols and fluff. It uses newline to end statements and "end" to end blocks so there is no need for lots of semicolons and curly braces. It is regular in that unless it is a variable assignment, function name always comes first. No need to be confused about whether something is a method on an object or a free function. Unlike Python and Ruby, since you can annotate the types a function operates on, you can overload function names, so that you can use the same function name for many data types. So you can keep simple descriptive function names and not have to invent artificial function names to separate them from the type they operate on. See More

Top Pro

REPL-based

The Julia REPL allows quickly testing how some code behaves and gives access to documentation and package management immediately in the REPL. See More

Top Pro

Powerful n-dimensional arrays

Julia has built in n-dimensional arrays similar in functionality as Python's numpy. See More

Top Pro

Strong Metaprogramming

Julia allows you to edit Julia code in the language itself and write powerful macros. It is a great introduction to metaprogramming features . See More

Go

Top Pro

Syntax for exported code from a package is simplified to be less verbose than other languages

Any variable, type and function whose name begins with a capital letter will be exported by a project, while all other code remains private. There is no longer a need to signify that a piece of code is 'private' or 'public' manually. See More

Specs

Platforms:Windows, Linux, Mac etc.

Current stable version:1.21.0

Developer:Google with Ken Thompson, Robert Griesemer, Rob Pike

Top Pro

Performance is on the order of C and Java

Go is blazing fast, but easier to write than Python, JS, Ruby, or many other dynamic languages. See More

Top Pro

Supports splitting source code into multiple files

As long as every source code file in a directory has the same package name, the compiler will automatically concatenate all of the files together during the compilation process. See More

Top Pro

Provides tools for automatically formatting code for your entire software project

This helps keep every programmer on the same page in a project and eliminates arguments over formatting styles. See More

Top Pro

Demonstrates a unique, simple concept to object-oriented programming

All types are essentially objects, be they type aliases or structs. The compiler automatically associates types to their methods at compile time. Those methods are automatically associated to all interfaces that match. This allows you to gain the benefits of multiple inheritance without glue code. As a result of the design, classes are rendered obsolete and the resulting style is easy to comprehend. See More

Top Pro

Built-in unit testing

The idiomatic approach to writing a Go software project is to perform test-driven development with unit testing. Every source code file should have an associated *_test.go file which tests functions in the code. See More

Top Pro

Jobs available

You can find a Job knowing Go. Which is more than can be said with many other languages. See More

Top Pro

Exceptionally simple and scalable multithreaded and concurrent programming

Goroutines are "lightweight threads" that runs on OS threads. They provide a simple way for concurrent operations — prepending a function with go will execute it concurrently. It utilizes channels for communication between goroutines which aids to prevent races and makes synchronizing execution effortless across goroutines. The maximum number of OS threads goroutines can run on may be defined at compile time with the GOMAXPROCS variable. See More

Top Pro

Supports 'modules' in the form of packages

Every Go source file contains a package line that indicates which package a file belongs to. If the name of the package is 'main', it indicates that this is a program that will be compiled into a binary. Otherwise, it will recognize that it is a package. See More

Top Pro

Great language for building networking services

Go was started as a systems language but now it has fully committed in the niche of networking services. This has been a brilliant move by Go because it allows them to capitalize on the immense talent of the Go engineering team (who are in the most part network engineers). In a world dominated by Java EE and slow scripting language, Go was a breath of fresh air and it continues to be one of the most powerful languages if you want to build networking services. See More

Top Pro

Programmers don't have to argue over what 10% subet of the language to implement in their software project

The language promotes programming in a specific idiomatic style, which helps keep every programmer on the same page. See More

Top Pro

Easy to install and configure; simple to compile software

Go software can be immediately installed, regardless of your operating system, package manager, or processor architecture with the go get command. Software is compiled statically by default so there is no need to worry about software dependencies on the client system. Makefiles and headers are no longer necessary, as the package system automatically resolves dependencies, downloads source code and compiles via a single command: go build. See More

Top Pro

Great team working behind it

Go has a solid team of engineers working on it (some of the best networking engineers in the world are working on Go). Up until now, the great engineering of the language has compensated for its lack of power. See More

Top Pro

Simplified C-like syntax that is as easy to read and write as Python

The language is designed in a manner that seems logical. Syntax is simplified to reduce burden on the programmer and compiler developers. See More

Top Pro

Automatically generates API documentation for installed packages

Godoc is provided to automatically generate API documentation for Go projects. Godoc also hosts its own self-contained web server that will list documentation for all installed packages in your Go path. See More

Top Pro

Multiple variables may be assigned on a single line

This conveniently eliminates the need to create temporary variables. Fibonacci example: x, y = y, x+y See More

Top Pro

Supports functional programming techniques such as function literals

This naturally also supports first class and high order functions, so you may pass functions as variables to other functions. See More

Top Pro

API documentation is rich in content; easy to memorize

Only features deemed critical are added to the language to prevent cruft from working its way into the language. The language is small enough to fit inside one's head without having to repeatedly open documentation. Documentation is hosted on an official webpage in a manner that is simple to read and understand. See More

Top Pro

The go compiler compiles binaries instantly — as fast as a scripting language interpreter

Compiled binaries are fast — about as fast in C in most cases. Compiles on every OS without effort — truly cross-platform compiler. As a result of the fast compilation speed, you can use the gorun program to use go source code as if it was a scripting language. See More

Rust

Top Pro

Functional programming

Very easy to create functional with some additional from structure application. See More

Specs

Platforms:Linux, MacOS X, Windows, BSD

Current stable version:1.71.1

License:MIT/Apache

Top Pro

Big community

The biggest community contributing to language. See More

Top Pro

Easy to write understandable code

While not as verbose as Java, it still is much more verbose than languages like Go and Python. This means that the code is very explicit and easy to understand. See More

Top Pro

Official package manager and build tool

Cargo is the official package manager for Rust. It comes with the language and downloads dependencies, compiles packages, and makes and uploads distributable packages See More

Top Pro

Support for macros

When you identify a part of your code which gets repeated often, which you cannot abstract using functions or classes, you can use Rust's built-in Macros. See More

Top Pro

Supports cross compilation for different architectures

Since Rust 1.8 you can install additional versions of the standard library for different targets using rustup/multirust. For example: $ rustup target add x86_64-unknown-linux-musl Which then allows for: $ cargo build --target x86_64-unknown-linux-musl See More

Top Pro

Makes developers write optimal code

Rust is a modern programming language written around systems. It was designed from the ground up this way. It's language design makes developers write optimal code almost all the time, meaning you don't have to fully know and understand the compiler's source code in order to optimize your program. Furthermore, Rust does not copy from memory unnecessarily, to give an example: all types move by default and not copy. Even references to types do not copy by default. In other words, setting a reference to another reference destroys the original one unless it's stated otherwise. See More

Top Pro

Built-in concurrency

Rust has built-in support for concurrency. See More

Top Pro

Generics support

You don't have to write same array and dictionary classes hundreds and thousands times for strong type check by compiler. See More

Top Pro

Threads without data races

Unique ownership system guarantees a mutable data to be owned and mutated by only one thread at a time, so there's no data race, and this guarantee is checked at compile time statically. Which means easy multi-threading. Of course, immutable data can be shared among multiple threads freely. See More

Top Pro

Compiles to machine code allowing for extra efficiency

Rust uses LLVM as a backend, among other things this allows Rust code to compile down to machine languages. This allows developers to write programs that run as efficiently as possible. See More

Top Pro

Catch errors at compile-time

Since Rust is statically typed, you can catch multiple errors during compile time. This is extremely helpful with debugging, especially compared with dynamically typed languages that may fail silently during runtime. See More

C++

Top Pro

Huge language supports most everything

C++ is a large language with an even larger community and following. It has libraries for every kind of task that is possible to do with C++. See More

Top Con

Cost of third Party libraries.

Sometimes Science and Mathematics C++ Libraries (many times ported from Fortran) have a cost, that while not being so high it certainly could add to the overall cost of a project. See More

DazzlingFionnuala's Experience

Flexibility, disciplined structure, low and high level use for both hardware interface and data reduction, supports any industry. Worth the learning curve. See More

Top Pro

At the end top notch Industry solutions are implemented in C++.

Totally mandatory if you want to do something real in Engineering and Science in the real world. Mathematics are understood and researched with Wolfram Mathematica. Algortihms are developed in MATLAB. Solutions are implemented in C++, called from Python, and critical parts rewritten in niche specific languages if need be (read Fortran). See More

Top Con

Compiling times

Top Pro

Specific language features for many many Industry Fields

C++ is built for the Industry not for the Academia or for the Technology junkies. Real advantages in solving real Industry problems. See More

Top Con

Many love to hate on C++

It is not the first or second option. But real Industry usually ends up using C++. See More

Top Pro

Qt

You have the top notch Gui framework used in real machinery, and in real analysis tools. (although Qt also has python bindings, qt is a c++ framework predominantly) See More

Top Pro

Performance.

Common Lisp

Top Pro

Condition/restart system

It is easy to recover from errors. Error resolution can be determined by the user at the REPL. See More

Top Pro

Image based runtime

The state of the program may be saved and reloaded as an image, supporting safer modification of the running program. New code may be compiled into the image as the program runs, while late binding ensures that symbol redefinitions take effect throughout the program. See More

Top Pro

Very Powerful REPL with SLIME

SLIME (Superior Lisp Interaction Mode for Emacs). See More

Top Pro

Carefully designed for interactive use

Almost all aspects of the language are designed with interactive/repl use in mind. See More

Top Pro

Almost as fast as, or faster than, C

Some compilers such as SBCL can be faster than C or other low-level languages, and most compilers can generate fast native code. See More

Fortran

Top Pro

Maximum performance

Fortran was designed from the beginning for maximum performance, and as one of the oldest languages in continuous use, the compilers are now very mature. Even hand-optimized assembly is usually slower, because the compilers are that smart. See More

Top Con

Availability of programmers

Fortran Sufficiency is rare. See More

DazzlingFionnuala's Experience

Used since 1979 and it just keeps getting better. See More

Top Pro

Straight forward language for use with data analysis through report presentation

No quirky hoops to jump through to do what you need to do. Just code you work and move along. See More

Top Con

Pricing

Compilers. Libraries. Programmers. Everything costs a mini fortune or a real fortune in Fortran World. See More

Top Pro

Top CPU and GPU scientific computing is done in Fortran

Not only CPU but now also GPU is a field for Fortran Programming (albeit the fact that it is a binding to C++, C++ Libraries are ported from Fortran, so it is a full circle). See More

Top Con

It is a dead language, except that it isn't

60 years in the dying process. Could it be that this is the year that it finally dies? There is always the sensation that it is. See More

Top Pro

Scientific Libraries are done in Fortran

MATLAB Libraries are written in Fortran. Julia Libraries are written in Fortran. Some Python Libraries are written in Fortran. C++ Libraries are ported from Fortran. See More

Top Con

The top performing language for Computational Physics and Computational Biology

V

Top Pro

Safety

V is very safe. See More

Top Pro

Sum types

V has sum types. See More

Top Pro

GUI support

V comes with (simple) GUI support out of the box. See More

Top Pro

Cross-platform

Compile app to run on different OSes. See More

Top Pro

Lambdas

Supports using lambdas, which helps write more concise code without having to use so many lines. See More

Top Pro

Fast compile times

Compiles programs fast, less waiting around, so more productive and fun. See More

Top Pro

C Interop

Can import C libraries, structs, and headers. See More

Top Pro

Supports concurrency and channels

Can run functions concurrently that communicate over channels. See More

Top Pro

Generics

V has generics. See More

Top Pro

Closures

V has closures, which gives the user additional options and usefulness. See More

Top Pro

Fast like C

V is easier than C and fast like C. See More

Top Pro

Clear syntax

Highly understandable language. See More

Haskell

Top Pro

Mathematical consistency

As Haskell lends itself exceedingly well to abstraction, and borrows heavily from the culture of pure mathematics, it means that a lot more code conforms to very high-level abstractions. You can expect code from vastly different libraries to follow the same rules, and to be incredibly self-consistent. It's not uncommon to find that a parser library works the same way as a string library, which works the same way as a window manager library. This often means that getting familiar and productive with new libraries is often much easier than in other languages. See More

Top Con

Difficult learning curve

Haskell lends itself well to powerful abstractions - the result is that even basic, commonly used libraries, while easy to use, are implemented using a vocabulary that requires a lot of background in abstract mathematics to understand. Even a concept as simple as "combine A and B" is often, both in code and in tutorials, described in terms of confusing and discouraging terms like "monad", "magma", "monoid", "groupoid", and "ring". This also occasionally rears its ugly head in the form of complicated error messages from type inference. See More

PoisedZhangGuolao's Experience

Definitely not a de facto academic language for Natural Sciences. See More

Specs

Paradigm:functional

Site:https://www.haskell.org/

Type System:static

Top Pro

Functions curry automatically

Every function that expects more than one arguments is basically a function that returns a partially applied function. This is well-suited to function composition, elegance, and concision. See More

Top Con

Too academic, hard to find "real world" code examples

Top Pro

The de facto academic language for Natural Sciences

It could be well used for exact sciences if Wolfram Mathematica wasn't the preferred option there. It is functional and mathematical. See More

Top Pro

Easy syntax for people with a STEM degree

Since the basic syntax is very similar to mathematics, Haskell syntax should be easy for people who have taken higher math courses since they would be used to the symbols used in maths. See More

Top Pro

Referentially transparent

Haskell's Purely Functional approach means that code is referentially transparent. This means that to read a function, one only needs to know its arguments. Code works the same way that expressions work in Algebra class. There's no need to read the whole source code to determine if there's some subtle reference to some mutable state, and no worries about someone writing a "getter" that also mutates the object it's called on. Functions are all directly testable in the REPL, and there's no need to remember to call methods in a certain order to properly initialize an object. No breakage of encapsulation, and no leaky abstractions. See More

Top Pro

Very few language constructs

The base language relies primarily on function application, with a very small amount of special-case syntax. Once you know the rules for function application, you know most of the language. See More

Top Pro

Open source

All Haskell implementations are completely free and open source. See More

Top Pro

Hand-writeable concise syntax

Conciseness of Haskell lets us to write the expression on the whiteboard or paper and discuss with others easily. This is a strong benefit to learn FP over other languages. See More

Top Pro

Powerful categorical abstractions

Makes categorical higher order abstractions easy to use and natural to the language. See More

Top Pro

Quick feedback

It's often said that, in Haskell, if it compiles, it works. This short feedback loop can speed up learning process, by making it clear exactly when and where mistakes are made. See More

Top Pro

Highly transferable concepts

Haskell's referential transparency, consistency, mathematics-oriented culture, and heavy amount of abstraction encourage problem solving at a very high level. The fact that this is all built upon little other than function application means that not only is the thought process, but even concrete solutions are very transferable to any other language. In fact, in Haskell, it's quite common for a solution to simply be written as an interpreter that can then generate code in some other language. Many other languages employ language-specific features, or work around a lack of features with heavy-handed design patterns that discourage abstraction, meaning that a lot of what is learned, and a lot of code that is needed to solve a particular problem just isn't very applicable to any other language's ecosystem. See More

Top Pro

Easy to read

Haskell is a very terse language, particularly due to its type inference. This means there's nothing to distract from the intent of the code, making it very readable. This is in sharp contrast to languages like Java, where skimming code requires learning which details can be ignored. Haskell's terseness also lends itself to very clear inline examples in textbooks, and makes it a pleasure to read through code even on a cellphone screen. See More

Top Pro

Popular in teaching

Haskell is really popular in universities and academia as a tool to teach programming. A lot of books for people who don't know programming are written around Haskell. This means that there are a lot of resources for beginners in programming with which to learn Haskell and functional programming concepts. See More

Top Pro

Forces you to learn pure functional programming

It is pure and does not mix other programming paradigms into the language. This forces you to learn functional programming in its most pure form. You avoid falling back on old habits and learn an entirely new way to program. See More

Wolfram Mathematica

Top Pro

openModelica integration

Top Con

GUIs and sliders are not auto dimensioning

You tell it to put a graph with a slider, the thing looks by default small, you can make it bigger, but it just doesn't automatically resize or fit. Graphs always look either too small or to big. See More

Top Pro

Typesetting everywhere

Introduce equations in your code. Code with equations. You can read them, people that see your notebooks can read them. See More

Top Con

For documentation is not as straightforward as Mathcad/Mapple

Top Pro

Arguably more complete than a Basic MATLAB installation

Basic Mathematica is far more complete than basic MATLAB, which makes Mathematica cheaper in comparison. See More

Top Con

Strange programming

It is functional programming, not C based as MATLAB. Besides, the functions seem strange. See More

Top Pro

Supports units and can do much more than just maths

Other platforms severely lack this useful feature. See More

Top Con

Strange coloring of the typesetting

Top Pro

Built-in CPU Parallelization

Top Con

It does not have the depth and width of Functionality Extension that MATLAB has achieved

MATLAB has state of the art toolboxes that are industry standard in many fields. Mathematica has a few of them, here and there. Full Mathematica and OpenModelica cannot compete with Full MATLAB and Simulink in real industries. See More

MATLAB

Top Con

Too expensive

3k for MATLAB. 5k for Simulink. Toolboxes at 3k a pop, and you need at least a dozen of them. See More

Top Pro

The Industry standard, the Academy standard

This is what is taught in universities/colleges. This is what is used in top notch Industries. MATLAB is the standard. Just learn something else besides it, because nor your employer nor you will have the required resources to give you a full time full MATLAB license, it is expensive. See More

Specs

Platforms:Windows, Linux, macOS

Cross Platform:Yes

Top Con

No real Typesetting in programming

Despite being a mathematical package it lacks Typesetting (equation visualization) in *.m files. You can buy a notebook toolbox to visualize equations and do symbolic work, but equation input is in plain text. See More

Top Pro

Fully documented libraries

Top Pro

Parallel programming in GPUs

With a toolbox MATLAB can run GPUs, be it workstation, research node, or full data center (if you wanted to do such a thing). See More

Top Pro

Ready for production in data centers

If you had the money, you could run MATLAB in data centers. Some do have the money, as government funded weather prediction and analysis centers, or many other areas. See More

Top Pro

Built-in easy GUI generation with plots

Top Pro

Almost every Engineer knows at least a little MATLAB

While complete proficiency might be hard to find, training engineering and science personnel in a new functionality necessary for a research or development is not out of reach. See More

Top Pro

Professional Toolboxes for many industry fields

Industry developed Toolboxes that add real functionality for real professional engineers and scientists. See More

Python

Top Con

Too many dependents

Maple

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