Open-Meteo Weather Scraper - Forecast & Historical Data

Fetch weather forecasts, historical weather data, and air quality data from Open-Meteo API. Supports multiple locations, hourly/daily granularity, temperature units. Free, no API key needed.

Use cases

• Add a weather-driven feature to an app without an API key
• Correlate daily sales or footfall with temperature and rain
• Plan logistics, events, or field work around forecasts
• Build agricultural or energy-demand models
• Backfill historical weather for a location

Input

Parameter	Type	Required	Default	Description
mode	string	Yes	"forecast"	Data type to fetch Allowed: forecast, historical, airQuality.
locations	array	Yes	[{"name":"Tokyo","latitude":35.6762,"longitude":139.6503}]	List of locations to fetch weather for. Each item must be an object with name, latitude, and longitude. Example: [{"name": "Tokyo", "latitude": 35.6762, "longitude": 139.6503}]
startDate	string	No	—	Start date for historical mode (YYYY-MM-DD)
endDate	string	No	—	End date for historical mode (YYYY-MM-DD)
forecastDays	integer	No	7	Number of forecast days (1-16)
granularity	string	No	"daily"	Data granularity Allowed: hourly, daily.
temperatureUnit	string	No	"celsius"	Temperature unit Allowed: celsius, fahrenheit.

Example input

{
  "mode": "forecast",
  "locations": [
    {
      "name": "Tokyo",
      "latitude": 35.6762,
      "longitude": 139.6503
    }
  ],
  "forecastDays": 7,
  "granularity": "daily",
  "temperatureUnit": "celsius"
}

Output

The exact fields depend on the mode you run. This is real output from an actual run of this Actor:

{
  "locationName": "Tokyo",
  "latitude": 35.6762,
  "longitude": 139.6503,
  "date": "2026-09-07",
  "temperatureMax": 26.8,
  "temperatureMin": 20.9,
  "precipitation": 195.3,
  "windSpeedMax": 11.7,
  "weatherCode": 65,
  "weatherDescription": "Heavy rain"
}

Field	Type
locationName	string
latitude	number
longitude	number
date	string
temperatureMax	number
temperatureMin	number
precipitation	number
windSpeedMax	number
weatherCode	number
weatherDescription	string

The dataset also ships a preset table view (Overview), so the key columns are readable straight away in Apify Console, and exportable to JSON, CSV, Excel, or XML.

How to run it

In Apify Console — open the Actor, fill in the input form, click Start, then download the results from the Dataset tab.

With the JavaScript client

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });

const run = await client.actor('cloud9_ai/open-meteo-scraper').call({
  "mode": "forecast",
  "locations": [
    {
      "name": "Tokyo",
      "latitude": 35.6762,
      "longitude": 139.6503
    }
  ],
  "forecastDays": 7,
  "granularity": "daily",
  "temperatureUnit": "celsius"
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

With the Python client

from apify_client import ApifyClient

client = ApifyClient('YOUR_APIFY_TOKEN')

run = client.actor('cloud9_ai/open-meteo-scraper').call(run_input={
  "mode": "forecast",
  "locations": [
    {
      "name": "Tokyo",
      "latitude": 35.6762,
      "longitude": 139.6503
    }
  ],
  "forecastDays": 7,
  "granularity": "daily",
  "temperatureUnit": "celsius"
})

for item in client.dataset(run['defaultDatasetId']).iterate_items():
    print(item)

With the API — POST https://api.apify.com/v2/acts/cloud9_ai~open-meteo-scraper/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN with the input JSON as the body.

Notes and limits

• No API key, account, or login is needed — just the input above.
• Requests to the source are paced to stay inside its rate limits.
• Only publicly available data is collected. How you use the output is your responsibility, including the source's terms of use and any applicable data-protection law.

Support

Found a bug, or need a field that isn't in the output? Open an issue on the Issues tab of this Actor in Apify Console. Issues there are read and answered.

License

Apache-2.0