Mostly Right turns historical and live public data like weather, economic releases, financial reports, and satellite data into one consistent shape, with clear sources and timestamps.
1from mostlyright import weather 2 3live = await weather.live.latest("KNYC") 4historical = weather.observations( 5 "KNYC", "2025-01-15", "2025-01-15", 6 return_type="list", 7)[-1]
1import { weather } from "mostlyright"; 2 3const live = await weather.latest("KNYC"); 4const { rows } = await weather.observations( 5 "KNYC", "2025-01-15", "2025-01-15" 6); 7const historical = rows.at(-1);
1from datetime import date 2from mostlyright import weather 3from mostlyright.markets.catalog import kalshi_nhigh 4 5day = date(2025, 1, 15) 6contract = kalshi_nhigh.resolve("KHIGHNYC", day) 7table = weather.training_table( 8 contract.settlement_station, date(2025, 1, 12), day 9)
1import { trainingTable } from "mostlyright"; 2import { kalshiSettlementFor } from "@mostlyrightmd/markets"; 3 4const contract = kalshiSettlementFor("KHIGHNYC", "2025-01-15"); 5const { rows } = await trainingTable( 6 contract.settlementStation, "2025-01-12", "2025-01-15" 7);
Start with a Kalshi or Polymarket contract. Mostly Right resolves its official reference, keeps the cutoff visible, and puts the outcome beside data available by then.
Map the venue code to its official station, unit, and outcome source.
Place historical inputs beside the official outcome and keep the cutoff visible.
| Field | Type | Meaning |
|---|---|---|
| local_standard_date | local date | station-local standard day |
| station | string | canonical ICAO station |
| decision_time_utc | ISO datetime | research cutoff |
| daily_summary_temp_high_f | number · °F | official daily high label |
| observed_temp_high_f | number · °F | highest observation by the cutoff |
| observation_count | integer | reports included before the cutoff |
| knowable_at_utc | ISO datetime | latest input knowledge time |
station-local standard day
canonical ICAO station
research cutoff
official daily high label
highest observation by the cutoff
reports included before the cutoff
latest input knowledge time
Explore public datasets for prediction-market research and predictive modeling, with clear sources and timestamps.
Live observations, forecasts, climate records, and official daily outcomes from public weather sources.
Kalshi and Polymarket discovery, market history, contract research, and settlement data.
Earth observations mapped to weather stations for use as model inputs.
CPI, PPI, payrolls, GDP, jobless claims, and Fed decisions with first-print vintages preserved.
Earnings-call transcripts, point-in-time facts, and prediction-market mention resolution.
Election results, polling, and policy calendars are next, with source identity and release time kept explicit.
Historical and live methods return the same core fields and units. Every row states which source produced it.
Rows validate against versioned schemas and include source and timing fields, so you can inspect the exact inputs later.
Public APIs run from your runtime; hosted delivery stays explicit where required.
Rows validate against versioned JSON Schemas.
Pinned inputs stay reusable for repeatable research across Python and TypeScript.
Shared methods use matching snake_case fields and source tags in both SDKs.
Every frame names the feed that produced it, so you can detect a source change.
Arrival-time checks keep data published after your cutoff out of the backtest.
See live observations, past observations, and forecasts directly on supported Polymarket and Kalshi weather markets.