# 🔍 Google News Shopping Scholar Scraper (`ethereal_wool/google-news-shopping-scholar-scraper`) Actor Extract Google news shopping scholar data — title, source, link, and more. Scrape by keyword, URL or ID. Export to JSON, CSV & Excel, use the API, schedule runs and integrate. No code required. - **URL**: https://apify.com/ethereal\_wool/google-news-shopping-scholar-scraper.md - **Developed by:** [Jackie Chen](https://apify.com/ethereal_wool) (community) - **Categories:** News - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $4.00 / 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 ## Google News, Shopping & Scholar Scraper ![google-news-shopping-scholar-scraper](https://api.apify.com/v2/key-value-stores/48FFrfZnw5XqzUC1C/records/google-news-shopping-scholar-scraper__hero) Scrape **Google News, Shopping, Scholar, Patents, Places, Web and Images** results for any query — clean structured JSON, fast, with country/language and time filters. > **Unofficial.** Not affiliated with, authorized, or endorsed by Google. Independent tool > that retrieves search results via a third-party API. Use it in compliance with all > applicable terms and laws; you are responsible for how you use the retrieved data. ### What it does Pick a **search type** and pass one or more **queries**: - **News** — title, link, snippet, source, date, image. - **Shopping** — title, price, source, delivery, rating, offers, product ID, image. - **Scholar / Patents** — title, link, snippet, publication info, year, cited-by, PDF URL. - **Places (Maps)** — name, address, rating, category, phone, website, lat/long. - **Web search / Images** — organic results with snippets. Country (`gl`), language (`hl`), results-per-query, and a time filter (`tbs`, e.g. past day/week/month) are all configurable. ### Input | Field | Type | Default | Description | |---|---|---|---| | `queries` | string[] | `["artificial intelligence"]` | Search terms; each queried separately. | | `searchType` | enum | `news` | `news` / `shopping` / `scholar` / `patents` / `places` / `search` / `images`. | | `gl` | string | `us` | Country code. | | `hl` | string | `en` | Language code. | | `resultsPerQuery` | integer | `10` | Results per query (1–100). | | `tbs` | string | `""` | Optional time filter, e.g. `qdr:d`, `qdr:w`, `qdr:m`. | | `maxItems` | integer | `50` | Max total results. | #### Example input ```json { "queries": ["nvidia earnings", "openai"], "searchType": "news", "gl": "us", "tbs": "qdr:w", "maxItems": 100 } ```` ### Output One item per result, tagged with `searchType` and `query`. News example: ```json { "searchType": "news", "query": "nvidia earnings", "position": 1, "title": "Nvidia reports record quarterly revenue", "link": "https://...", "snippet": "...", "source": "Reuters", "date": "2 hours ago", "imageUrl": "https://..." } ``` ### Notes - Powered by the serper.dev Google API; transient rate-limits are retried with backoff. - News/Shopping/Places return a single page per query; Web/Scholar/Patents paginate. # Actor input Schema ## `queries` (type: `array`): Search terms. Each is queried separately for the selected search type. ## `searchType` (type: `string`): Which Google vertical to scrape. ## `gl` (type: `string`): Two-letter country code, e.g. us, gb, de. ## `hl` (type: `string`): Two-letter language code, e.g. en, es, zh-cn. ## `resultsPerQuery` (type: `integer`): How many results to request per query (serper num). 10–100. ## `tbs` (type: `string`): Optional serper time filter, e.g. qdr:d (past day), qdr:w (past week), qdr:m (past month). ## `maxItems` (type: `integer`): Maximum total results to scrape across all queries. ## Actor input object example ```json { "queries": [ "artificial intelligence" ], "searchType": "news", "gl": "us", "hl": "en", "resultsPerQuery": 10, "tbs": "", "maxItems": 50 } ``` # 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 = { "queries": [ "artificial intelligence" ] }; // Run the Actor and wait for it to finish const run = await client.actor("ethereal_wool/google-news-shopping-scholar-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 = { "queries": ["artificial intelligence"] } # Run the Actor and wait for it to finish run = client.actor("ethereal_wool/google-news-shopping-scholar-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 '{ "queries": [ "artificial intelligence" ] }' | apify call ethereal_wool/google-news-shopping-scholar-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ethereal_wool/google-news-shopping-scholar-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "🔍 Google News Shopping Scholar Scraper", "description": "Extract Google news shopping scholar data — title, source, link, and more. Scrape by keyword, URL or ID. Export to JSON, CSV & Excel, use the API, schedule runs and integrate. No code required.", "version": "0.1", "x-build-id": "1SI346toO6ch8ua1U" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ethereal_wool~google-news-shopping-scholar-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ethereal_wool-google-news-shopping-scholar-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ethereal_wool~google-news-shopping-scholar-scraper/runs": { "post": { "operationId": "runs-sync-ethereal_wool-google-news-shopping-scholar-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ethereal_wool~google-news-shopping-scholar-scraper/run-sync": { "post": { "operationId": "run-sync-ethereal_wool-google-news-shopping-scholar-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "queries": { "title": "Search queries", "type": "array", "description": "Search terms. Each is queried separately for the selected search type.", "default": [ "artificial intelligence" ], "items": { "type": "string" } }, "searchType": { "title": "Search type", "enum": [ "news", "shopping", "scholar", "patents", "places", "search", "images" ], "type": "string", "description": "Which Google vertical to scrape.", "default": "news" }, "gl": { "title": "Country (gl)", "type": "string", "description": "Two-letter country code, e.g. us, gb, de.", "default": "us" }, "hl": { "title": "Language (hl)", "type": "string", "description": "Two-letter language code, e.g. en, es, zh-cn.", "default": "en" }, "resultsPerQuery": { "title": "Results per query / page", "minimum": 1, "maximum": 100, "type": "integer", "description": "How many results to request per query (serper num). 10–100.", "default": 10 }, "tbs": { "title": "Time filter (tbs)", "type": "string", "description": "Optional serper time filter, e.g. qdr:d (past day), qdr:w (past week), qdr:m (past month).", "default": "" }, "maxItems": { "title": "Max results", "minimum": 1, "maximum": 100000, "type": "integer", "description": "Maximum total results to scrape across all queries.", "default": 50 } } }, "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 } } } } } } } } } } ```