Skip to content

Getting started

provider files ──→ uv run windgram ──→ static profile JSON
npm package `windgram`
validate → derive → scene → SVG
└ analyze → compare
documentation + research ← committed teaching profiles
  1. Clone the repository and run uv sync --project pipeline with Python 3.12 or later.

  2. Create a versioned launch catalogue.

  3. Choose a catalogued model whose declared domain, cadence, levels, and capabilities fit the publication.

  4. Preflight one model without network access or writes:

    Terminal
    uv run --project pipeline windgram build --model hrrr-conus --sites ./club-sites.json --output ./public/data --max-steps 2 --dry-run
  5. Remove --dry-run and the temporary --max-steps cap only when ready for the provider’s full data volume. Then publish the static output on infrastructure you control.

Install the ESM package and begin at its contract boundary:

Terminal
npm install windgram

Render a first windgram covers the complete contract → scene → SVG path. The package is headless: the same scene and SVG code works in Node, workers, and browsers. Use windgram/transport when loading a manifest/profile pair from independently cached static storage.

Analyze a profile produces compact, auditable statements instead of chart geometry. The single-document API keeps the thresholds and source evidence behind each finding.

Compare model profiles reports agreement and divergence across those findings while preserving each model’s run, cadence, elevation, and availability.

Read Pipeline architecture before an internal module. Then follow Development setup and select tests by change class. Provider facts are verified and recorded in the living feed reference before a builder consumes them.

Start with Reading a windgram. The teaching-scenario guide explains how figures isolate one relationship. The research ledger records how derivations and visual conventions were established.