🌤️ Weather Forecast API

Feed your applications, AI models, and forecasting dashboards with reliable meteorological metrics using this zero-configuration tool. By tapping directly into the Open-Meteo API, you can seamlessly extract granular weather data for any global coordinates without managing expensive subscriptions or complex authentication. Simply input a latitude and longitude to scrape highly accurate current conditions, detailed hourly shifts, or extended 16-day daily forecasts. Teams building predictive models for renewable energy, agricultural yield analysis, or smart city infrastructure can schedule routine extractions to build rich historical datasets. The scraped results yield critical environmental variables including surface temperature, relative humidity, wind speed and direction, precipitation accumulation, UV index, and total cloud cover. Designed to bypass the frustrating constraints of traditional commercial weather APIs, this fetcher enforces no strict rate limits and requires absolutely no API key. Run the tool to gather raw data from multiple geographic points simultaneously, then export the precise details as structured JSON or CSV files. Whether you are enriching a specialized website, extracting details for a travel app, optimizing delivery routes, or running automated checks for extreme weather alerts, this scraper delivers the exact environmental context your systems require.

Store Quickstart

Start with the Quickstart template (3 cities, daily forecast). For logistics planning, use 7-Day Hourly with hourly detail enabled.

Key Features

• 🌤️ Any location worldwide — Lat/lng coordinates with optional city name
• 📅 Up to 16 days forecast — Daily + hourly granularity
• ⚡ Open-Meteo free API — No API key, no rate limits, 100% free
• 📊 Current + hourly + daily — All three timescales in one response
• 🌡️ Full weather data — Temp, humidity, wind, precipitation, UV, cloud cover
• 🔑 No API key needed — Truly free commercial weather API

Use Cases

Who	Why
Logistics companies	Route planning with weather forecasts
Agricultural tech	Farm irrigation/harvest scheduling
Event planning	Outdoor venue weather risk assessment
Travel services	Destination weather for trip planners
Energy/utilities	Load forecasting from weather patterns

Input

Field	Type	Default	Description
locations	object[]	(required)	List of {lat, lng, name?}
forecastDays	integer	7	Forecast horizon (1-16)
hourly	boolean	false	Include hourly forecast
daily	boolean	true	Include daily forecast

Input Example

{
  "locations": [{"lat": 35.6762, "lng": 139.6503, "name": "Tokyo"}],
  "forecastDays": 7,
  "hourly": false,
  "daily": true
}

Output

Field	Type	Description
location	string	Location name
latitude	number	Latitude
longitude	number	Longitude
forecast	object[]	Daily forecast array
forecast[].date	string	ISO date
forecast[].tempMin	number	Min temperature (°C)
forecast[].tempMax	number	Max temperature (°C)
forecast[].precipitation	number	Precipitation (mm)
forecast[].weatherCode	integer	WMO weather code

Output Example

{
  "name": "Tokyo",
  "current": {"temperature": 18.5, "weatherCode": 1, "windSpeed": 12},
  "daily": [
    {"date": "2026-04-05", "tempMax": 22, "tempMin": 14, "precip": 0.2},
    {"date": "2026-04-06", "tempMax": 24, "tempMin": 15, "precip": 0.0}
  ]
}

API Usage

Run this actor programmatically using the Apify API. Replace YOUR_API_TOKEN with your token from Apify Console → Settings → Integrations.

cURL

curl -X POST "https://api.apify.com/v2/acts/taroyamada~weather-forecast-fetcher/run-sync-get-dataset-items?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{ "locations": [{"lat": 35.6762, "lng": 139.6503, "name": "Tokyo"}], "forecastDays": 7, "hourly": false, "daily": true }'

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("taroyamada/weather-forecast-fetcher").call(run_input={
  "locations": [{"lat": 35.6762, "lng": 139.6503, "name": "Tokyo"}],
  "forecastDays": 7,
  "hourly": false,
  "daily": true
})

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

JavaScript / Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });
const run = await client.actor('taroyamada/weather-forecast-fetcher').call({
  "locations": [{"lat": 35.6762, "lng": 139.6503, "name": "Tokyo"}],
  "forecastDays": 7,
  "hourly": false,
  "daily": true
});

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

Tips & Limitations

• Powered by Open-Meteo — completely free, no API key, no rate limits.
• Set hourly: true for hour-by-hour forecasts (24x more data).
• Use lat/lng for any location worldwide — no geocoding required.
• Schedule daily for travel apps, agriculture, or logistics planning.

FAQ

How accurate is Open-Meteo?

Very accurate — uses major global models (ECMWF, ICON, GFS). Comparable to OpenWeatherMap.

Rate limits?

No published limits for non-commercial use. Commercial users should self-limit to ~10,000 calls/day.

Historical data?

This actor focuses on forecasts. For historical weather, use Open-Meteo's archive endpoint separately.

What's weatherCode?

WMO standard weather codes (0=clear, 1-3=cloudy, 51-67=rain, 71-77=snow, etc.).

What's the forecast accuracy?

Open-Meteo uses ECMWF and DWD models. Reliable up to 7 days, useful up to 14.

Can I get historical weather data?

Not in this actor — it focuses on forecasts. Open-Meteo has a separate historical API.

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Cost

Pay Per Event:

• actor-start: $0.01 (flat fee per run)
• dataset-item: $0.001 per output item

Example: 1,000 items = $0.01 + (1,000 × $0.001) = $1.01

No subscription required — you only pay for what you use.

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