Pymicra is a Python package that was created to condense many of the knowledge of the micrometeorological community in one single fast-to-implement software that is freely available to anyone. Because of that, I made an effort to include a detailed docstring along with every function and class. By doing that I hope to have made every function, class etc. pretty self-explanatory, both within the auto-generated docs (thanks to Sphinx) and by importing the package and running help(pymicra.timeSeries), for example.

Since Pymicra is meant to be a community package, improvements, suggestions of improvement, and any kind of feedback are highly appreciated. The code is available at its Github page and any contact can be made through there (possibly creating an Github issue) or via email (tomaschor [at]

Quick notes

In order for the user to program fast and effectively (and to reduce the time it takes me to write its code), Pymicra was written on top of the Pandas package, so that it is faster to run the same code using Pymicra than it is running pure Python. As a consequence, Pymicra makes extensive use of Pandas’ DataFrame class, which is a very useful 2-D data structure optimized for performance and for timestamp-indexed data.

It is possible to use Pymicra without having to be familiar with Pandas, but because Pymicra depends on Pandas, I suggest at the very least that the user take a quick look at a Pandas tutorial this one for example so that one can be familiarized with the many functionalities that Pandas offers in order to take full advantage of Pymicra.


Currently, this project has only one part-time developer. This makes it hard to feed Pymicra with up-to-date information/routines as the state-of-the-art micrometeorology evolves quickly. The ideal scenario is one where micrometeorologists in the community not only use Pymicra, but also contribute to it, whether it’s by adding to the code, finding bugs, investing ideas and etc. Thus, I have made an effort to not only document the routines/functions in the docstring, but also detail them with comments throughout the code. This was done specially to make it easier for other people to contribute.

If you want to contribute with code you can either create a Github account and contact me via the Github page by creating an issue/pull request, or you can contact me directly by email (tomaschor [at] Furthermore, if you have some useful routines laying around (or even some routines with a procedure you recently created and published) but aren’t sure how to make them Pymicra-compatible, let me know by email and we’ll work together to adapt it.


Tomás Chor.