Skip to content

SWATGenX/swatgenx-python

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

1 Commit
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

swatgenx

Public API tests PyPI

Python client for SWATGenX — automated SWAT+ / MODFLOW 6 watershed models and open national water datasets for the conterminous United States.

pip install swatgenx

Public data — no account needed

import swatgenx as sg

# Example-model catalog: built SWAT+ models with calibration/validation metrics
models = sg.catalog(state="FL", calibrated_only=True)
sg.calibration("01451800")
# {'mode': 'engineer', 'cal_daily_nse': 0.642, 'val_daily_nse': 0.748, ...}

# National groundwater inventory: 28.8M lithology intervals, 7.9M wells, 46 states
sg.groundwater_at(42.73, -84.55)      # nearest well + lithology log
sg.groundwater_summary()

# National PFAS monitoring inventory (huc8 = 8-digit hydrologic unit code)
sg.pfas_stations(huc8="04050006")
sg.pfas_summary()

Order and download models — free account + API key

Sign in at swatgenx.com → dashboard → API keys, then:

c = sg.Client(api_key="...")                    # or env SWATGENX_API_KEY

order = c.order(usgs_station="04124500")        # any of 25,000+ USGS gauges
c.wait(order["order_id"])                       # typical build: 20 min – 2 h
c.download("04124500", vpuid="0406", dest="model.zip")   # ZIP straight to your disk

Builds run on SWATGenX cloud infrastructure from national data (NHDPlus HR, 3DEP, gSSURGO, NLCD, PRISM, USGS NWIS); delivery is pull-based — no email round-trip.

Access ladder

tier requires unlocks
guest nothing all public data functions
member free account + API key model orders (fair-use), downloads
extended request via info@swatgenx.com HUC8 whole-basin, SWAT+MODFLOW-6, HUC14 30 m site models
calibration account credit cloud calibration campaigns

sg.access_info() returns this ladder programmatically; quota/tier errors raise SwatGenXError with upgrade guidance.

AI agents

The same platform is agent-native via a public MCP server: https://www.swatgenx.com/mcp (see the site's llms.txt). This package and the MCP server expose the same surface, enforced by the same server-side quotas.

Data citations

MIT-licensed client; platform terms at swatgenx.com.

About

Python client for SWATGenX — order, monitor & download automated SWAT+ watershed models for any USGS gauge or HUC12 in CONUS. pip install swatgenx; REST + public MCP server for AI agents.

Topics

Resources

License

Stars

0 stars

Watchers

0 watching

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages