Welcome to pyku’s documentation!#
Comprehensive climate data handling with Xarray#
Pyku is an extension built on xarray for working with climate data. It provides tools to read, manipulate, validate, and analyze climate datasets while handling metadata and geospatial information in a consistent way.
Geospatial data handling
Define standardized geographic projections
Read metadata to build area definitions (PROJ, WKT, CF)
Convert between raster and vector formats
Create and apply masks from polygons or files
Climate metadata handling
Handle time bounds, units, coordinates, and variable metadata
Interpret CMOR-like metadata to infer variable names and convert units
Write standardized CMOR-like data paths and files
Validation and quality control
Detect inconsistencies in units, time bounds, and frequencies
Compare datasets to identify differences in coordinates and metadata
Climate analysis utilities
Resample time series while preserving climate metadata
Compute DWD-specific climate indices
Perform downscaling operations
Perform bias adjustement operations
Convenience utilities
Define ensembles
Provide dedicated colormaps for climate variables
Download standardized polygon datasets on demand
Provide test datasets for unit testing
Basic plotting and quantity visualization
Acknowledgments#
Special thanks to Seth Woodworth for his generosity in transferring the PyPI package name pyku. Seth originally established the name as an English portmanteau of “Python” and “Haiku.” It is now being repurposed for the py Klima und Umwelt project.
Contents
- Installation
- Changelog
- Starter pack
- Contribute
- Plugins
- Troubleshooting
- Crashes while processing NetCDF files
- Opening GRIB file with time and step
- Object has inconsistent chunks along dimension time
- Slicing is producing a large chunk
- Plots not rendering properly in a cronjob
- Plots do not show in ipython
- Plot is cut
- Empty plot in jupyter notebook
- Issues with UTF-8 characters
- API