Python tutorials - ASU-CompMethodsPhysics-PHY494/PHY494-resources GitHub Wiki

If you want to do more Python exercises then you will find that the internet is full with them. Your instructors have not really comprehensively evaluated them (in fact, we learned Python mostly by having to solve problems and reading documentation, other people's code, and getting advice from kind Python gurus).

However, the following seem to be useful resources --- having them listed here is not a endorsement or guarantee of any kind. Have a look and decide for yourself (feeback is welcome!):

  1. The official Python Beginner's Guide gives various links, but no exercises.
  2. The official Python Tutorial is well worth working through, but if you feel that it already presupposes to much programming then start looking at the following resources, too.
  3. Software Carpentry's Programming with Python (a tutorial that is normally instructor-guided but can be easily done in self-study)
  4. How to Think Like a Computer Scientist is a nice introduction to programming (using Python 3). The goal of this book is to teach you to think like a computer scientist. This way of thinking combines some of the best features of mathematics, engineering, and natural science. Like mathematicians, computer scientists use formal languages to denote ideas (specifically computations). Like engineers, they design things, assembling components into systems and evaluating tradeoffs among alternatives. Like scientists, they observe the behavior of complex systems, form hypotheses, and test predictions.
  5. Swaroop CH's A Byte of Python (free online book) — note that you need to click the arrow on the right hand site to move through the pages...
  6. Code Academy's Learn Python (This is a Python 2 tutorial but Python 3 is the language that we learn because as of January 2020, Python 2 is not officially supported anymore. This is neverthless a professional step-by-step tutorial. Still worth checking out, especially if you like small steps and instant checks that tell you if you did it correctly; most of Python 2 is still applicable to Python 3.)
  7. Exercism: Python is quite good, but more suited for intermediate levels. But check it out, it's quite innovative (and free).