If there was a reason to learn another programming language it would be now…
Not too long ago developers and research scientists came together and found a new programming language called Julia. Most liked to develop algorithms in python quickly, but hated porting the algorithm to faster languages like C because of all the overhead.
Julia in a nutshell… It runs like C, but reads like Python.
Right now Python is huge in the dev community and C has yet to die because its the fastest language still out there!
Why is this important?
Julia bridges a big gap from the following shortcomings of Python and C:
- Python is an interpreted, high-level programming language. C is a general-purpose, procedural programming language.
- Interpreted programs execute slower as compared to compiled programs.
- Python is easy to write, but C program syntax is harder than Python.
- Debugging is easier in Python because its interpeter error messages is mostly the same between different hardware architectures, but C is harder because some errors are compiler dependent.
- Memory is managed automatically in Python, but C has to be carefully managed by the programmer.
- Community written libraries in Python are enormous, but C not so much.
- Python is very general purpose, but C programming is well tailored to hardware applications.
- Python provides REPL (read–evaluate–print loop) an interactive text-based interface that takes the input, evaluates it and returns the results to the user. But in C the program must be compiled whole to return meaningful results.
Julia fixes most of the above problems. It enables developers to quickly prototype and ensure speed is not compromised.
As great as this sounds, it’s lacking the strong user base of Python and that maturity of C. This will change with time, but it’s good to know that development is accelerating with less overhead and fast results.
References:
Link: Julialang – The home of the Julia Programming Language
Link: Medium – Blog post