Daniel Winklehner, Remi Lehe
The Python interpreter
Daniel Winklehner, Remi Lehe
US Particle Accelerator School (USPAS) Summer Session
Self-Consistent Simulations of Beam and Plasma Systems
S. M. Lund, J.-L. Vay, D. Bruhwiler, R. Lehe & D. Winklehner
Old Dominion U., Hampton, VA, 15-26 January, 2018
Python interpreter: Outline
1
Overview of the Python language
2
Python, numpy and matplotlib
3
Reusing code: functions, modules, classes
4
Faster computation: Forthon
Overview
Scientific Python
Reusing code
Forthon
Overview of the Python programming language
Interpreted language (i.e. not compiled)
¡ú Interactive, but not optimal for computational speed
Readable and non-verbose
No need to declare variables
Indentation is enforced
Free and open-source
+ Large community of open-souce packages
Well adapted for scientific and data analysis applications
Many excellent packages, esp. numerical computation (numpy),
scientific applications (scipy), plotting (matplotlib), data
analysis (pandas, scikit-learn)
3
Overview
Scientific Python
Reusing code
Forthon
Interfaces to the Python language
Scripting
Interactive shell
Code written in a file, with a
text editor (gedit, vi, emacs)
Obtained by typing python or
(better) ipython
Execution via command line
(python + filename)
Commands are typed in and
executed one by one
Convenient for long-term code
Convenient for exploratory work,
debugging, rapid feedback, etc...
4
Overview
Scientific Python
Reusing code
Forthon
Interfaces to the Python language
IPython (a.k.a Jupyter) notebook
Notebook interface, similar to
Mathematica.
Intermediate between scripting
and interactive shell, through
reusable cells
Obtained by typing jupyter
notebook, opens in your web
browser
Convenient for exploratory work,
scientific analysis and reports
5
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