This page provides some general information regarding the email list for the AO&SS Python Interest Group. First, some key email addresses:
The list is set to archive old messages. You can view the archive by visiting https://lists.wisc.edu/read/?forum=aoss_python
New subscription requests must be approved. This is to ensure that the list remains primarily for users within (or at least somehow connected with) the Atmospheric, Oceanic, and Space Sciences building.
I created the list to facilitate the sharing of Python knowledge within our building but am otherwise leaving it to members to decide how best to use it. Possible uses that come to mind include
- emailing programming questions, tips, and other information to fellow members;
- organizing and publicizing brownbag-style seminars, mini-tutorials, Q&A sessions, and other activities;
- sharing other Python-related information or resources that are likely to be of interested to a significant number of list members.
A surprising range of Python programming questions can be most quickly answered by Googling an appropriate search phrase, including even error messages in some cases. Many such searches will land you on one or more of the following:
- documentation for Python 2.7 or Python 3
- documentation for one of its many modules/libraries (see the listings for Python 2.7 or Python 3)
Chances are, our email list will be most useful for getting answers to questions that are specific to the work being done in this building, such as working with scientific data sets.
Note that Python 2.7 continues to be used by a lot of scientific programmers, because some popular modules have not yet been updated to Python 3. Because it sometimes matters, consider mentioning in your emails whether your question and/or sample code assumes one version or the other.
Please feel free to use the list to propose one-time or recurring activities related to Python programming. If there is sufficient interest in weekly or monthly brownbag-style meetings, it would probably be a good idea to reserve room 811 or another seminar-type room for a regular time block.
Here are some random suggestions for future mini-tutorials, in case someone is inspired to put something together:
- Tips on making publication quality plots with matplotlib/pyplot
- Working with scientific data sets (NetCDF, HDF, GRIB, etc.)
- Plotting gridded data on maps
- Parallel processing with Python
- Creating Python wrappers for legacy Fortran or C routines
- Statistical analysis and regression
- Time series analysis, possibly using the Pandas module
- Image processing libraries
- GUI programming in Python
- Machine learning tools in Python
- Interpolation of spatial data
- Basics of object-oriented programming in Python
- Any of a million other potential topics of interest
If you do decide to present a mini-tutorial about some aspect of Python, consider using Jupyter Notebook rather than, say, PowerPoint for your presentation. You can then easily demonstrate live calculations and programming concepts; you can also share the notebook file in advance (along with any relevant data files) to other list members so that they can replicate your steps on their own laptop. Jupyter Notebook can be installed using the package manager for either the miniconda or (I think) the Enthought Python distributions.