Software Carpentry: Python masterclass for weather, ocean and climate scientists
Python is rapidly emerging as the programming language of choice for data analysis in the weather, climate and ocean sciences. By consulting online tutorials and help pages, most researchers in this community are able to pick up the basic syntax and programming constructs (e.g. loops, lists and conditionals). This self-taught knowledge is sufficient to get work done, but it often involves spending hours to do things that should take minutes, reinventing a lot of wheels, and a nagging uncertainty at the end of it all regarding the reliability and reproducibility of the results. To help address these issues, this workshop will cover a suite of programming best practices that aren’t so easy to glean from a quick Google search:
- Using functions to write modular, reusable code
- Vectorisation of large array operations
- Testing and defensive programming
- Writing programs that can be executed from the command line
- Tools and strategies for profiling and debugging
- Version control
Along the way, participants will learn how to install and manage their Python environment using conda, interact with common development environments and the Jupyter notebook, and go on a tour of the most commonly used Python libraries in the weather, climate and ocean sciences.
To attend this workshop, participants must already be using Python for their data analysis. They don’t need to be highly proficient, but a strong familiarity with Python syntax and basic constructs such as loops, lists and conditionals (i.e. if statements) is required.
Convener: Damien Irving
Estimated attendance: 50 max. Participants should bring their own laptop (please contact us if you are not able to do so). Information has been sent to participants about software packages to be installed prior to the workshop. Contact us if you haven’t received information for this workshop. Please view the Software Carpentry website for further details.
Fee: $50. This includes morning and afternoon tea. Participants can bring or buy their own lunch.