Tools for harvesting earth observation data for use in flood forecasting.
Project description
Cosecha
Tools for harvesting earth observation data for use in flood forecasting.
Cosecha provides a flexible pipeline for collecting geospatial data from multiple sources and writing to various formats with optional transformations.
Features
- Time-series data collection (USGS NWIS streamflow, stage, precipitation)
- Gridded data support (HRRR, RRFS, RTMA via herbie; MRMS via S3)
- Multiple output formats: Parquet, NetCDF, Zarr, Iceberg, IceChunk
- Data transformations: unit conversion, spatial subsetting, variable selection/rename
- Cross-platform support (ecCodes C library required for GRIB2/MRMS)
Installation
pip install cosecha
With optional dependencies for NWP (HRRR, RRFS) support:
pip install 'cosecha[nwp]'
Note: Cosecha depends on the ecCodes C library for reading GRIB2 data (used by MRMS). When installing with pip, you must have ecCodes available on your system. The easiest cross-platform approach is to install it via conda-forge:
conda install -c conda-forge eccodes
pip install cosecha
Or use pixi which handles this automatically:
pixi add cosecha
Quick Start
from cosecha import USGSNWISReaper
# Fetch USGS streamflow data
reaper = USGSNWISReaper(
site_ids=["01650000"], start_date="2026-01-01", end_date="2026-01-31", parameter_code="00060"
)
# Execute
data = reaper.reap()
# Write to Parquet
path = reaper.sow_to_parquet(file_path="./data/streamflow.pq")
Documentation
Full documentation at https://dewberry.github.io/cosecha/
Contributing
Contributions are welcome! Please see CONTRIBUTING.md for details.
License
MIT License. See LICENSE for details.
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