humanbaselines

Python client for the Human Crash Baselines API: typed access to human-driver crash-rate baselines by region, route, and filter. Created and maintained by Valgo.

It wraps the /v1 REST API behind the humanbaselines.com tool: construct a client with your key, call typed methods, and get typed results back, with no hand-built JSON and no need to remember the auth header.

pip install humanbaselines

from humanbaselines import HumanBaselines

hb = HumanBaselines(api_key="hbk_...")          # or set HUMANBASELINES_API_KEY

r = hb.compute(county="travis", outcome="police_reported",
               ego_vehicle=["cars", "light_trucks"])
print(r.rate, r.rate_low, r.rate_high)          # 4.05 4.0 4.1

Features

• Typed end to end. Request filters and results are Pydantic models generated from the API's OpenAPI schema, so the client can't drift from the server.
• Three compute modes. County-wide geofence rates, interstate route-segment rates, and full depot-to-depot trip rates, one method each.
• Filters three ways. Keyword args, a typed Selections model, or a plain dict; all validated locally before the request.
• Bound definitions. Bind a methodological definition (what counts as a crash, what you baseline against) to a client and reuse it; serialize it to JSON to version and share.
• Runtime discovery. filters() and regions() return the live catalog of valid values, defaults, and available regions.
• Typed errors. Non-2xx responses raise specific exceptions (auth vs. validation vs. warm-up) with the server's field-level detail.

Next steps

• Installation: install and authenticate.
• Quickstart: your first rate in a few lines.
• Reference: every method, argument, and model.

Learn more

For technical details, read the white paper, and reach out to humanbaselines@valgo.ai to submit feedback or request API access.

Outputs are derived statistics only (rates, counts, bounds). See methodology & licensing.