Sherpa is an importable module for the dynamic, object-oriented Python programming language, which means you can write your own Python scripts for use in Sherpa. This easily allows for creating complex analysis and modeling functions, building batch-mode analysis, and extending the provided functionality to meet required needs. Below is a list of Python resources which you may find helpful as you conduct your scientific analysis in Sherpa. To learn about the key features of Python, refer to the official Python website.
- The Python Tutorial
Comprehensive documentation provided by the official Python website.
- Dive into Python
On-line version of the book Dive into Python, including many detailed examples of usage which prove helpful to both beginner and experienced Python users.
- Practical Python for Astronomers
A series of hands-on workshops to explore the Python language and the analysis tools it provides. The emphasis is on using Python to solve real-world problems that astronomers are likely to encounter in research.
A community Python library for Astronomy. See also the associated paper Astropy: A community Python package for astronomy by the AstroPy collaboration.
- AstroML: Machine Learning and Data Mining for Astronomy
The astroML project accompanies the book "Statistics, Data Mining, and Machine Learning in Astronomy".
- Ask SciPy
A site hosted on scipy.org which allows you to submit a question about Python and receive answers from other users of the site (questions are not limited to those about the scipy or numpy packages).
- Sherpa Blog
Includes useful tips and tricks on using Python in Sherpa.
- Python Perambulations
A wide-ranging look at data analysis with Python.
- Plumber Jack
Documents miscellaneous items relating to the Python logging package.
- Doug Hellmann
The "Python Module of the Week" series provides examples of usage of the various modules contained in the Python standard library.
- Beginning Python: From Novice to Professional, by Magnus Lie Hetland
- A Primer on Scientific Programming with Python, by Hans Petter Langtangen
- Python Scripting for Computational Science, Hans Petter Langtangen
- Beginning Python Visualization: Crafting Visual Transformation Scripts, by Shai Vaingast
- Statistics, Data Mining, and Machine Learning in Astronomy by Zeljko Ivezic, Andrew Connolly, Jacob VanderPlas, and Alex Gray