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Sep 1, 2010 · If you decide to learn C/C++ later, it'll become a bit easier. If you decide you want to learn functional programming later, you can switch to F# but still use existing code written in C#, because you stay within .NET framework. Python is not known to be a remarkably fast language.
But I think the primary reason I suggest learning C alongside python is because you can use C in python; the python interpreter is at its core a C program. Any bit of python code that is performance-critical you can extract out into whats called a C extension, and python can interface with your C code directly through the C/Python api.
Much later I learned Python. I like both languages and use a combination of them to do about 95% of my programming. I found Python easy to learn; and knowing much of the standard C libraries made many of the Python libraries trivial. Learn Python really well since that is what your university is setting you up with.
In my opinion, C is the best language to learn first. C's design pioneered the languages we have today. By studying C first you will understand the roots of object oriented programming and have a better appreciati i learned python first and dispute. If you just learn python and dont understand how it works and why, sure.
Nov 2, 2011 · Python syntax is nothing like that of C. So having prior knowledge of C really has nothing to do with how well you will learn python. Just because under the hood there is C code doesn't mean that you will learn python any quicker because you know C. As a python programmer you are dealing with the syntax of python not C.
May 23, 2024 · Cython allows writing C extensions for Python in a Python-like syntax, and PyPy can increase Python’s speed by approximately 4.2 times without altering the code. Integration with C : For scenarios where performance is critical, Python code can be integrated with C for computationally intensive functions.
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May 23, 2024 · Data Science and Machine Learning: Python is the go-to language for data scientists due to its simplicity and the powerful data processing capabilities provided by libraries like NumPy, Pandas, and Scikit-learn. This ease of use and comprehensive data handling make Python ideal for tasks ranging from automated trading systems to advanced artificial intelligence algorithms.
