Climate Risk Commons Framework
CRC Framework provides a shared Rust computation core with official Python and JavaScript/WebAssembly bindings for climate-risk calculations. It turns hazard distributions into comparable impact microscores, scenario branches, and portfolio-level VaR/CVaR risk metrics.
| Interface | Package | Scope |
|---|---|---|
| Python | crc-framework on PyPI; import crc_framework |
Distributions, fitting, impacts, microscores, risk aggregation, and geography |
| JavaScript / WASM | @climateriskcommons/crc-framework on npm |
Canonical CRC curve consumption: quantile evaluation, batches, prepared handles, and TypeScript declarations |
| Rust | crates/core |
Shared algorithms and reference data used by both bindings |
The JavaScript binding consumes canonical curves, including PMTiles/MVT properties. Python also supports fitting, impacts, and portfolio risk. Application-specific workflows belong in packages built on this framework.
Installation · Quick start · Guides
Contributors
Thanks to the people who shape this project through code, reviews, research, and internal discussions and ideas.
 @ChrisHampu 💻 👀 |
 @woozyking 💻 👀 |
 @awiebe42 💻 👀 🔬 |
 @kylalangotsky 🔬 |
 @reshmasoman 🔬 |
 @rkodamana 🔬 👀 |
 @dilshank 🔬 |
Contribution types: 💻 code · 👀 review · 🔬 research. We recognize contributions both on and off GitHub using All Contributors.
Installation
Python
python -m pip install crc-framework
# To opt into prereleases:
python -m pip install --upgrade --pre crc-framework
Python 3.11 or later is required. Compatible prebuilt wheels need no Rust toolchain. Building from source requires Rust 1.85 or later and a C compiler suitable for Python extensions.
JavaScript / WebAssembly
npm install @climateriskcommons/crc-framework
Stable releases use npm's latest channel. Add @alpha to opt into
alpha prereleases. The package is ESM, requires WebAssembly, and includes TypeScript
declarations. See the JavaScript guide for browser, bundler, Node,
and SSR setup, canonical input rules, and prepared collection APIs.
Quick start
Python: evaluate a return-period curve
from crc_framework import TabulatedDistribution
exposure = TabulatedDistribution.from_return_periods(
periods=[10, 20, 50, 100, 200, 500],
values=[0.1, 0.2, 0.5, 0.9, 1.4, 2.0],
tail="upper",
)
print(exposure.ppf(0.99)) # 100-year return level: 0.9
JavaScript: consume a canonical curve
import init, { evaluateCurve } from '@climateriskcommons/crc-framework';
await init(); // initialize once at client startup
const properties = {
curve_kind: 'fitted',
curve_type: 'gumbel_r',
curve_location: 1,
curve_scale: 2,
};
const value = evaluateCurve(properties, 0.99);
Evaluation is synchronous after initialization. Imports are SSR-safe; initialize
in the client, or load WASM bytes explicitly for Node evaluation. For repeated
viewport or percentile queries, use prepareCurves to validate and transfer a
collection once, then call evaluate(q) and free the handle when finished.
Guides and next steps
| Task | Read next |
|---|---|
| Use distributions, fitting, impacts, microscores, or risk metrics | Python guide |
| Initialize WASM, prepare collections, or understand canonical inputs and errors | JavaScript guide |
| Pin schemas, validate identities, or record impact provenance | Impact contracts |
| Set up the repository, run checks, or update contributor credits | Development |
| Bump versions, migrate the npm scope, or publish a release | Releases |
Start with the documentation index for the reading order and repository boundaries. Historical implementation notes are linked there separately.
License
CRC Framework is licensed under the GNU Affero General Public License, version
3 or any later version (AGPL-3.0-or-later). See LICENSE.
Parts of the numerical distribution implementation are derived from or informed by SciPy and Cephes. Their applicable copyright notices and license terms are preserved in THIRD_PARTY_NOTICES.md.
1 maintainer
Metadata
1 maintainer
Release files for crc-framework 0.5.3
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