On the mailing list today, Scott Collis shared this article on why Python is dominating scientific computing. The article also discusses some amazing new Python packages for scientific computing!
As most folks know, SciPy is the premiere conference on doing all things scientific with Python. This is really the place to be if you want to learn about the absolute cutting-edge in using Python for scientific computing. The SciPy 2013 talks are available online, a boon if you weren’t able to make the conference (like myself). Some tracks/mini-symposia of particular interest to PyAOS folks include one on GIS and one on Meteorology, Climatology, Atmospheric and Oceanic Science. The talks all look great; I’ll specifically mention Philip Elson’s talk on Iris and Cartopy which describes a set of really useful tools for PyAOS users. Hope folks can check them out!
Nikolay Koldunov is developing a site, earthpy.org, of examples of the use of Python in the geosciences, and is looking for contributors. Here’s more details from him:
We are trying to create a place that would collect small tutorials and tips and tricks related to use of Python in the Earth Sciences. Initial idea was that earth scientists are already have a lot of code written in Python but there is no place to share it. If you create a module, or after one week of struggle find interesting solution to a problem, there is no place to share this information, and you can be sure that after some time somebody will write similar module that do exactly the same, and spend the same amount of time to solve similar problem. We all write code that do the same things over and over again.
So in order to address this problem we create Earth.py. If you have some examples for your module, or want to share anything else you think would be useful for other Earth Scientist who write in Python, you can send IPython notebook with your post to me ([email protected]) and I will publish it on Earthpy. If not, I hope you will visit us from time to time to see what’s new
Nikolay Koldunov has a neat introduction to the use of Python in the geosciences as a set of nbviewer files (h/t from the author). In particular I appreciated the examples of how to use pandas, Iris, Cartopy, etc. for AOS applications. Check it out!
Packt has a new book out called Learning Geospatial Analysis with Python. Here’s more info.: http://www.packtpub.com/learning-geospatial-analysis-with-python/book.
(Hat tip to the author, Joel Lawhead.) Check it out!
The program for the 2014 AMS Python Symposium is now available here. As you can see in the schedule, besides oral sessions, we’ll also be having a Workshop discussing what tools are needed to build up the AOS Python community and grow projects, a Town Hall on learning and teaching Python, and a code sprint.
This year, we’re also offering three Python short courses. Here are the course titles and dates:
- A Beginner’s Course to Using Python in Climate and Meteorology: Saturday-Sunday, 1-2 February 2014.
- Intermediate Python: Data Visualization with Matplotlib, Sunday, 2 February 2014.
- Advanced Python for Climate Science: From Numpy to Parallel Computing, Saturday-Sunday, 1-2 February 2014.
Links to descriptions of the short courses are found here. The price for each short course is listed on the short course registration page.
Please let your colleagues know about the meeting! Look forward to seeing y’all in Atlanta!
At long last, thanks to Joel Lawhead, we have an image for the blog’s header that is more related to the atmospheric and oceanic sciences! It’s from an image taken on October 11, 2013, at 2200 UTC, from the buoy camera on the National Data Buoy Center’s Station 44013 buoy located 16 nm east of Boston, MA. Incidentally, Joel mentions that the folks at the NDBC mission control center do make use of Python in their work. Enjoy!
Felipe Fernandes let me know about a blog he’s put together, python4oceanographers, with tips and examples for using Python in oceanography. Here’s a funny post where CTDs meet the comic XKCD
Packt Publishing has a new book out: Python Geospatial Development, Second Edition, by Erik Westra.
Hat tip: Dyson D’Souza (Packt Publishing).