A common instrument utilized in the atmospheric sciences is the disdrometer. This instrument gives a count of the numbers of different size drops that pass through it's sensor area. This talk will cover the development of a Python disdrometer and rain gauge library using open source tools focusing on the tooling, with the actual library as a motivating need.

Several important workflow tools will be addressed in this talk. We will start by showing how the algorithms were prototyped using the Ipython Notebook, a browser based system that empowers reproducible research methodologies and collaboration in Python. We utilize several different open source Python packages to enable electromagnetic scattering simulation, statistical inference, and visualization. The code is then transitioned into a library meant to be used by engineers and scientists to assist in their research. The goal is to demonstrate an efficient workflow for rapid prototyping of Python algorithms with real atmospheric science data using fully open source tools.