# Weather Forecast Scraper — Open-Meteo (`ponderable_hydrometer/open-meteo-scraper`) Actor Weather forecasts by city name or coordinates — current, daily & hourly temperature, precipitation, wind & more. Any location worldwide. Free keyless API. - **URL**: https://apify.com/ponderable\_hydrometer/open-meteo-scraper.md - **Developed by:** [Ponderable Hydrometer](https://apify.com/ponderable_hydrometer) (community) - **Categories:** Developer tools, Automation, SEO tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Weather Forecast Scraper — Open-Meteo **Weather forecasts for any location worldwide — by plain city name (auto-geocoded) or coordinates.** Current conditions plus daily and hourly temperature, precipitation, wind, weather code, sunrise/sunset and more. Free, keyless, no proxies. Built on the Open-Meteo API with **built-in geocoding**, so you can pass `"London"` instead of hunting for latitude/longitude — a real UX edge over raw-API scrapers. One clean result object per location. ### What you get One result per location, with the forecast nested inside: - **Location & geo** — resolved `location`, `country`, `admin1`, `latitude`, `longitude`, `timezone`, `elevation` - **Current weather** — `current` block (temperature, windspeed, wind direction, weather code, time) - **Daily forecast** — array of per-day objects; defaults to temp max/min, precipitation sum, weather code, max wind, sunrise/sunset. Add any Open-Meteo daily variable (e.g. `uv_index_max`, `windgusts_10m_max`) - **Hourly forecast** (optional) — array of per-hour objects for any hourly variables you request (`temperature_2m`, `relativehumidity_2m`, `precipitation`, `windspeed_10m`, …) - **Units metadata** — `dailyUnits` so every number is unambiguous - Configurable temperature unit, wind-speed unit, forecast horizon (up to 16 days) and past days (up to 92) ### Output sample ```json { "location": "Berlin", "country": "Germany", "admin1": "Berlin", "latitude": 52.52437, "longitude": 13.41053, "timezone": "Europe/Berlin", "elevation": 74.0, "current": { "time": "2026-07-12T14:00", "temperature": 23.4, "windspeed": 11.2, "winddirection": 210, "weathercode": 3 }, "dailyUnits": { "temperature_2m_max": "°C", "precipitation_sum": "mm" }, "daily": [ { "time": "2026-07-12", "temperature_2m_max": 25.1, "temperature_2m_min": 14.8, "precipitation_sum": 0.0, "weathercode": 3, "windspeed_10m_max": 18.5, "sunrise": "2026-07-12T04:52", "sunset": "2026-07-12T21:26" } ], "hourly": [] } ```` ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `locations` | array | `["Bucharest","Berlin"]` | Place names to geocode and forecast | | `coordinates` | array | — | Explicit `"lat,lon"` pairs | | `current` | boolean | `true` | Include current conditions | | `daily` | array | (defaults) | Daily variables (empty = sensible defaults) | | `hourly` | array | — | Hourly variables to include | | `forecastDays` | integer | `7` | Forecast days (1–16) | | `pastDays` | integer | `0` | Past days to include (0–92) | | `temperatureUnit` | string | `celsius` | `celsius` or `fahrenheit` | | `windspeedUnit` | string | `kmh` | `kmh`, `ms`, `mph`, `kn` | | `timezone` | string | `auto` | IANA timezone or `auto` | Provide at least one of `locations` or `coordinates`. ### Example input ```json { "locations": ["Bucharest", "Berlin", "Tokyo"], "forecastDays": 7, "current": true, "hourly": ["temperature_2m", "precipitation", "windspeed_10m"] } ``` ### Why this actor - **Plain city names work** — built-in geocoding means no coordinate lookup step. - **Keyless & reliable** — Open-Meteo's free API, no key to manage, auto-retry on rate limits. - **Flexible** — pick any daily/hourly variables, units, forecast horizon and past days. - **Batch-friendly** — many locations per run, one tidy result object each. ### Pricing Pay per result — **$1.00 per 1,000 results** (one location = one result, forecast nested). No subscription or platform fees. ### Related actors - **Marine Weather Forecast Scraper** — waves, swell and sea conditions for sailing. - **NOAA Tides & Currents Scraper** — tide predictions and water levels for US coasts. - **USGS Water Data Scraper** — river streamflow and water temperature. ### Notes - Data is Open-Meteo's free public API; the actor sets a descriptive User-Agent and retries on 429/5xx. - Geocoding returns the top match per name — pass explicit coordinates for ambiguous or precise locations. - This actor is an independent tool and is not affiliated with or endorsed by Open-Meteo. # Actor input Schema ## `locations` (type: `array`): Place names to geocode and forecast, e.g. \["Bucharest","Berlin","Tokyo"]. ## `coordinates` (type: `array`): Explicit "latitude,longitude" pairs, e.g. \["44.43,26.10","40.71,-74.00"]. ## `current` (type: `boolean`): Include current conditions (temperature, wind, weather code). ## `daily` (type: `array`): Daily fields. Empty = default (temp max/min, precipitation, weathercode, max wind, sunrise/sunset). Examples: temperature\_2m\_max, precipitation\_sum, uv\_index\_max, windgusts\_10m\_max. ## `hourly` (type: `array`): Optional hourly fields, e.g. temperature\_2m, relativehumidity\_2m, precipitation, windspeed\_10m. ## `forecastDays` (type: `integer`): Number of forecast days (1-16). ## `pastDays` (type: `integer`): Include this many past days as well (0-92). ## `temperatureUnit` (type: `string`): celsius or fahrenheit. ## `windspeedUnit` (type: `string`): kmh, ms, mph or kn. ## `timezone` (type: `string`): IANA timezone or "auto" (resolve from coordinates). ## Actor input object example ```json { "locations": [ "Bucharest", "Berlin" ], "current": true, "forecastDays": 7, "pastDays": 0, "temperatureUnit": "celsius", "windspeedUnit": "kmh", "timezone": "auto" } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "locations": [ "Bucharest", "Berlin" ] }; // Run the Actor and wait for it to finish const run = await client.actor("ponderable_hydrometer/open-meteo-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "locations": [ "Bucharest", "Berlin", ] } # Run the Actor and wait for it to finish run = client.actor("ponderable_hydrometer/open-meteo-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "locations": [ "Bucharest", "Berlin" ] }' | apify call ponderable_hydrometer/open-meteo-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ponderable_hydrometer/open-meteo-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Weather Forecast Scraper — Open-Meteo", "description": "Weather forecasts by city name or coordinates — current, daily & hourly temperature, precipitation, wind & more. Any location worldwide. Free keyless API.", "version": "0.1", "x-build-id": "blRhfxcZfnqTYTsqz" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ponderable_hydrometer~open-meteo-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ponderable_hydrometer-open-meteo-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ponderable_hydrometer~open-meteo-scraper/runs": { "post": { "operationId": "runs-sync-ponderable_hydrometer-open-meteo-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ponderable_hydrometer~open-meteo-scraper/run-sync": { "post": { "operationId": "run-sync-ponderable_hydrometer-open-meteo-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "locations": { "title": "Locations (city names)", "type": "array", "description": "Place names to geocode and forecast, e.g. [\"Bucharest\",\"Berlin\",\"Tokyo\"].", "items": { "type": "string" } }, "coordinates": { "title": "Coordinates (lat,lon)", "type": "array", "description": "Explicit \"latitude,longitude\" pairs, e.g. [\"44.43,26.10\",\"40.71,-74.00\"].", "items": { "type": "string" } }, "current": { "title": "Include current weather", "type": "boolean", "description": "Include current conditions (temperature, wind, weather code).", "default": true }, "daily": { "title": "Daily variables", "type": "array", "description": "Daily fields. Empty = default (temp max/min, precipitation, weathercode, max wind, sunrise/sunset). Examples: temperature_2m_max, precipitation_sum, uv_index_max, windgusts_10m_max.", "items": { "type": "string" } }, "hourly": { "title": "Hourly variables", "type": "array", "description": "Optional hourly fields, e.g. temperature_2m, relativehumidity_2m, precipitation, windspeed_10m.", "items": { "type": "string" } }, "forecastDays": { "title": "Forecast days", "minimum": 1, "maximum": 16, "type": "integer", "description": "Number of forecast days (1-16).", "default": 7 }, "pastDays": { "title": "Past days", "minimum": 0, "maximum": 92, "type": "integer", "description": "Include this many past days as well (0-92).", "default": 0 }, "temperatureUnit": { "title": "Temperature unit", "enum": [ "celsius", "fahrenheit" ], "type": "string", "description": "celsius or fahrenheit.", "default": "celsius" }, "windspeedUnit": { "title": "Wind speed unit", "enum": [ "kmh", "ms", "mph", "kn" ], "type": "string", "description": "kmh, ms, mph or kn.", "default": "kmh" }, "timezone": { "title": "Timezone", "type": "string", "description": "IANA timezone or \"auto\" (resolve from coordinates).", "default": "auto" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```