A collection of IPython Notebooks.
“A language that doesn't affect the way you think about programming is not worth knowing.” ― Alan Perlis
All programming languages are equal but some are more equal. You could solve the same problem in C or Lisp or Fortran, but some would be more productive across most of the common avenues that programmers have to deal with. Programming languages are not mere descriptions, they are a means that dictate how one may think and hopefully approach and solve a given problem.
This repository is an invitation to the newcomers to the language to witness how the Python programming language could especially be a good choice for solving various kind of problems. Often, as it should be obvious from the notebooks, it's easier and sometimes even faster to program the solutions than to explain them in a natural language!
Considerations for the Notebooks
- Simple is better than complex.
- There is a deliberate attempt to stick (as much as possible) to stay within the Python Standard library (Py 3.7.x).
- Wherever appropriate, I have used a functional programming approach, and wherever using higher abstractions were apt, I preferred them. Often, they end up being common Python idioms.
- Each Notebook (and if possible, sections therein) should be independent and separabale units of code. Files, if present, sit at the folder root of the notebook.
- Vocabulary Analysis of the German Language. #NLP
- Project Euler with Python. #Competitive Programming, #Mathematical Methods