Python SDK for quants, ML engineers, and AI agents — one interface to public data. Adapters ship weather + prediction-market settlements (Kalshi NHIGH/NLOW, Polymarket) today; SEC filings, Federal Reserve series, court filings, FDA approvals, and equities are next. Schema-versioned, leakage-free, local-first. Imports as `mostlyright`.
Project description
mostlyrightmd
The public-data SDK for quants, ML pipelines, and AI agents.
mostlyrightmd is the Python entry point: core types, schemas, validators, temporal-safety primitives, and the research() join that ties weather observations × climate into one row per settlement date — ready for prediction-market backtests (Kalshi NHIGH/NLOW, Polymarket), ML training pipelines, and AI-agent tool calls. Direct calls to public APIs (NOAA, NWS, IEM, GHCNh, Kalshi, Polymarket). No hosted backend, no API key.
Weather + prediction-markets adapters are live today. SEC filings (EDGAR), equities structured data, Federal Reserve series (FRED), court filings, and FDA approvals are next — and the architecture is built to ship an adapter for any public data source.
Install
pip install mostlyrightmd # core only (helpers + snapshot primitives)
pip install 'mostlyrightmd[research]' # core + weather; enables research()
pip install mostlyrightmd-weather # weather data sources only (brings core transitively)
mostlyrightmd and mostlyrightmd-weather share the mostlyright.* Python namespace but ship as separate PyPI distributions, so users who only need the helpers can skip the heavier weather deps. research() lazy-imports mostlyright.weather and raises a clear error if the weather package is not installed.
Quickstart
import mostlyright
df = mostlyright.research("KNYC", "2025-01-06", "2025-01-12")
print(df.head())
Documentation
Quickstart, concepts, and the full API reference live at https://mostlyright.md/docs/sdk/.
Project details
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