Editor's Note: This is part of a series of posts written by Unidata communications intern Larissa Gordon, highlighting new activities and interesting projects undertaken by software developers at the Unidata Program Center.
(Click to enlarge)
Unidata is pleased to announce the availability of the Python Data Access Framework (DAF). The DAF provides access to an AWIPS II Environmental Data EXchange (EDEX) server directly from Python code. Created by Unidata Program Center software engineer Michael James, the DAF strengthens Unidata's AWIPS II offerings by making it easier to retrieve data from the AWIPS II data storage system from outside the Common AWIPS Visualization Environment (CAVE).
Users have always been able to request real time NCEP/NWS weather data using AWIPS II, but now, with the addition of the Python DAF, users can request this data using only simple python commands.
The python DAF is very versatile because it is a client Python Module that requests data from a remote EDEX server. It does not depend on the CAVE client, or on any other AWIPS II technologies. Therefore, the Python DAF can be installed without the other packages that are a part of AWIPS II. This allows it to be used on any computer, even if that computer cannot run the AWIPS II software.
The Python DAF gives users the option of requesting data from the THREDDS catalog or the AWIPS II catalog. Similar to how Siphon requests data from THREDDS, the Python DAF allows users to query specific times, levels, and parameters from AWIPS II.
Users can easily render the retrieved data objects with any number of Python packages; MetPy, Matplotlib, and Cartopy to name a few. In addition, the Python DAF supports various data sets including gridded models, upper air profiles, METAR/Synoptic obs, NEXRAD Level 3 radar, and various text-based observations (ACARS, Profiler, Marine obs, AIREP/PIREP).
To introduce users to the new Python DAF, James has created and published a set of Jupyter/iPython notebooks on Github.com. Using the notebooks users are able to learn how to request and then render the various AWIPS II data sets.
The Python DAF example notebooks are available here.
Teaching Python with Jupyter notebooks is is well suited to the classroom because the notebooks are interactive scripts. Even better, using the new Python DAF, users no longer need to download and locally-store meteorological data sets. Users can simply request the real-time data sets they would like to explore from the remote EDEX data server whether it be in a classroom context or for research.
As Python becomes increasingly popular among the geoscience computing community, it is important for software engineers to tailor the software packages already in place to make Python more applicable. Michael James has allowed for this by making NCEP/ NWS weather data more available thanks to the new Python Data Access Framework.
