Scientific-Computing
Scientific Computing Grad Course
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Tools & Resources
The following is a list of tools, resources and readings for continuing and exploring Python.
Watch your code execute
Python Language
Official Python Resources:
Documentation:
https://docs.python.org/3.6/
Tutorial:
https://docs.python.org/3.6/tutorial/index.html
Codecademy:
https://www.codecademy.com
Python Practice Book:
https://anandology.com/python-practice-book/index.html
Google's Python Class:
https://developers.google.com/edu/python/
Think Python:
http://greenteapress.com/thinkpython/html/index.html
PythonTutor:
http://pythontutor.com
A Byte of Python:
https://python.swaroopch.com
Non-Programmers Tutorial Python3:
https://en.wikibooks.org/wiki/Non-Programmer%27s_Tutorial_for_Python_3
Jupyter Notebooks
Jupyter Notebooks, that we use in class, are an increasingly common tool for doing computation. If you're interested, see this article for some information on how they are being used in science:
https://www.nature.com/articles/d41586-018-07196-1
A list of interesting Jupyter notebooks
https://github.com/jupyter/jupyter/wiki/A-gallery-of-interesting-Jupyter-Notebooks
On Good Programming
Programming Sucks:
http://www.stilldrinking.org/programming-sucks
Python Constructs
Lists:
https://wiki.python.org/moin/BeginnersGuide/Programmers
https://www.biostars.org/p/219389/
https://www.codeconquest.com/blog/the-50-best-websites-to-learn-python/
https://hakin9.org/list-of-free-python-resources/
https://www.fullstackpython.com/best-python-resources.html