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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