Difference between revisions of "Scientific Python Primer"
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== Textbook for the module == | == Textbook for the module == | ||
− | + | A Primer on Scientific Programming with Python by Hans Petter Langtangen (3rd Edition). Available online through the UO Library. To access it, follow this link: http://link.springer.com/book/10.1007%2F978-3-642-30293-0 | |
== Activities == | == Activities == | ||
− | + | Intro to Python, Definitions - Chapter 1 | |
+ | |||
+ | Loops, logic, and lists - Chapter 2 | ||
+ | |||
+ | Functions - Chapter 3 and NumPy | ||
+ | |||
+ | Input data and error handling - Chapter 4 and PANDAS | ||
+ | |||
+ | Functions on arrays and curve fitting - Chapter 5 | ||
+ | |||
+ | String handling, files, and dictionaries - Chapter 6 and PANDAS | ||
+ | |||
== Useful Links == | == Useful Links == |
Revision as of 14:39, 19 November 2015
This Python Primer utilizes an IPython notebook kernel running on a computer in the APL and a browser-based IPython notebook front end located on your computer. That is, you don't need any special software just a computer with a web-browser and a SSH client.
You will start your IPython session by establishing a SSH tunnel.
Step 1 SSH into the remote machine and run the IPython web-based environment and direct it to a specific port. The command for this should look something like:
ipython notebook --no-browser --port=70xx
Step 2 On the local machine you can access this remote port using an SSH tunnel with port forwarding. The command for that will look like:
ssh -N -f -L localhost:70xx:localhost:70xx username@remotemachine
Step 3 Now to use the session all you have to do is (from the local machine) run your preferred web browser with the URL:
Textbook for the module
A Primer on Scientific Programming with Python by Hans Petter Langtangen (3rd Edition). Available online through the UO Library. To access it, follow this link: http://link.springer.com/book/10.1007%2F978-3-642-30293-0
Activities
Intro to Python, Definitions - Chapter 1
Loops, logic, and lists - Chapter 2
Functions - Chapter 3 and NumPy
Input data and error handling - Chapter 4 and PANDAS
Functions on arrays and curve fitting - Chapter 5
String handling, files, and dictionaries - Chapter 6 and PANDAS
Useful Links
PANDAS - http://pandas.pydata.org/
NumPy - http://www.numpy.org
codecademy - https://www.codecademy.com/