open-climate-data

Public climate and energy data is abundant and almost uniformly painful to consume: a dozen portals, a dozen schemas, units that disagree, and figures that get silently restated between vintages.

This library gives those sources one Python interface. Every value it returns carries its provenance (which source, which dataset version, retrieved when) because a number without a vintage cannot be defended six months later.

Two design commitments. Nothing is fabricated: if a source is unreachable, the call fails loudly rather than returning a plausible-looking figure. And every client works offline against recorded fixtures, so the test suite never depends on a third party being up, and neither does your CI.

Each tool lives in its own folder with its own README and its own tests, and leans on the Python standard library unless a dependency genuinely earns its place.

Layout

projects/
  NNN-project-name/
    README.md          what it does, how to run it, what it is not
    <package>/         the implementation
    tests/             python3 -m unittest discover -s tests -t .
    examples/          a working input file
    pyproject.toml     dependencies, if any

Projects

#	Project	What it does
001	provenance	The record every value is wrapped in (source, dataset, version, retrieval instant, licence and the exact query), carried through arithmetic so a derived figure still admits to everything that went into it.
002	units	Exact conversion between energy and mass units (GJ against MWh, kt against t) and a refusal rather than a guess when a mass unit's gas species is ambiguous, as with CO2 against everything but CO2e.

Roadmap

See BACKLOG.md.

Runs in the browser

Each project here is also a case study on the author's site, with the method, the assumptions and what it refuses to answer, and a version that runs in the page:

• Provenance

Licence

MIT, per project. See LICENSE.