# Google Trends API (`fingolfin/google-trends-api`) Actor Scrape Google Trends data without official API. Get interest over time, interest by region, related queries, related topics, trending searches, and keyword suggestions. Supports all filters: geo, timeframe, category, and search property (web/YouTube/news/images/Google Shopping). - **URL**: https://apify.com/fingolfin/google-trends-api.md - **Developed by:** [Mate Papava](https://apify.com/fingolfin) (community) - **Categories:** AI, Other, SEO tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $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.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 Trends Scraper — Apify Actor Scrape Google Trends data without using the official API. Uses `curl_cffi` for browser impersonation to bypass rate limits. ### Features - **Interest Over Time** — Weekly/daily/hourly interest scores (0–100) - **Interest by Region** — Breakdown by country or sub-region - **Related Queries** — Top and rising related searches - **Related Topics** — Top and rising related topics/entities - **Trending Now** — What's currently trending in a country - **Trending Daily** — Today's trending searches with traffic estimates - **Suggestions** — Topic autocomplete for finding precise terms ### Filters | Filter | Options | Description | |--------|---------|-------------| | `keywords` | Comma-separated (max 5) | Terms to analyze. Use comma for comparison | | `geo` | ISO country code | US, GB, IN, GE, DE. Empty = worldwide | | `timeframe` | 1h, 4h, 1d, 7d, 30d, 90d, 12m, 5y, all | Shorter = finer granularity | | `category` | all, finance, health, sports, news, etc. | 26 categories available | | `property` | web, youtube, news, images, froogle | Which Google product to search | ### Example Input #### Compare Python vs JavaScript interest worldwide (12 months) ```json { "action": "interest_over_time", "keywords": "python,javascript", "geo": "", "timeframe": "12m" } ```` #### ChatGPT interest on YouTube in the US (90 days) ```json { "action": "interest_over_time", "keywords": "chatgpt", "geo": "US", "timeframe": "90d", "property": "youtube" } ``` #### Interest by US state ```json { "action": "interest_by_region", "keywords": "python", "geo": "US", "timeframe": "12m" } ``` #### Trending searches in Georgia ```json { "action": "trending_now", "geo": "GE" } ``` #### Related queries for bitcoin in Finance category ```json { "action": "related_queries", "keywords": "bitcoin", "geo": "US", "category": "finance" } ``` ### Output Results are pushed to the dataset. Each result contains: - `data` — The actual data (array of points, regions, queries, etc.) - `status` — "success" or error status - `_action` — Which action was run - `_input` — Echo of the parsed input parameters ### Notes - Trending actions (`trending_now`, `trending_daily`) use Google's RSS feed which is reliable and never rate-limited. - Interest/related actions use the internal Trends API with session management via `curl_cffi` browser impersonation. - Not all keywords have related topics data — this is normal Google Trends behavior. - Hourly granularity is only available for timeframes of 1d or shorter. # Actor input Schema ## `action` (type: `string`): What data to fetch from Google Trends. ## `keywords` (type: `string`): One or more search terms, comma-separated (max 5 for comparison). Used by all actions except trending\_now and trending\_daily. Examples: • Single: python • Compare: python,javascript,rust • Phrase: machine learning ## `geo` (type: `string`): ISO 3166-1 alpha-2 country code. Leave empty for worldwide data. Examples: US, GB, IN, GE, DE, FR, JP, BR, AU For interest\_by\_region: empty = breakdown by country, set a country = breakdown by sub-region (e.g. US states). ## `timeframe` (type: `string`): Time range for the data. Shorter ranges give finer granularity (hourly for 1d, daily for 30d, weekly for 12m+). ## `category` (type: `string`): Filter results to a specific category. Only relevant for interest/related actions. ## `property` (type: `string`): Which Google property to search. Default is web search. ## Actor input object example ```json { "action": "interest_over_time", "keywords": "python", "geo": "", "timeframe": "12m", "category": "all", "property": "web" } ``` # Actor output Schema ## `results` (type: `string`): Google Trends data stored in the default dataset # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("fingolfin/google-trends-api").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 = {} # Run the Actor and wait for it to finish run = client.actor("fingolfin/google-trends-api").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 '{}' | apify call fingolfin/google-trends-api --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fingolfin/google-trends-api", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Trends API", "description": "Scrape Google Trends data without official API. Get interest over time, interest by region, related queries, related topics, trending searches, and keyword suggestions. Supports all filters: geo, timeframe, category, and search property (web/YouTube/news/images/Google Shopping).", "version": "1.0", "x-build-id": "EudgSgb4Rc7zVw08A" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fingolfin~google-trends-api/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fingolfin-google-trends-api", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/fingolfin~google-trends-api/runs": { "post": { "operationId": "runs-sync-fingolfin-google-trends-api", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/fingolfin~google-trends-api/run-sync": { "post": { "operationId": "run-sync-fingolfin-google-trends-api", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "action" ], "properties": { "action": { "title": "Action", "enum": [ "interest_over_time", "interest_by_region", "related_queries", "related_topics", "trending_now", "trending_daily", "suggestions" ], "type": "string", "description": "What data to fetch from Google Trends.", "default": "interest_over_time" }, "keywords": { "title": "Keywords", "type": "string", "description": "One or more search terms, comma-separated (max 5 for comparison). Used by all actions except trending_now and trending_daily.\n\nExamples:\n• Single: python\n• Compare: python,javascript,rust\n• Phrase: machine learning", "default": "python" }, "geo": { "title": "Country / Region", "type": "string", "description": "ISO 3166-1 alpha-2 country code. Leave empty for worldwide data.\n\nExamples: US, GB, IN, GE, DE, FR, JP, BR, AU\n\nFor interest_by_region: empty = breakdown by country, set a country = breakdown by sub-region (e.g. US states).", "default": "" }, "timeframe": { "title": "Timeframe", "enum": [ "1h", "4h", "1d", "7d", "30d", "90d", "12m", "5y", "all" ], "type": "string", "description": "Time range for the data. Shorter ranges give finer granularity (hourly for 1d, daily for 30d, weekly for 12m+).", "default": "12m" }, "category": { "title": "Category", "enum": [ "all", "arts_entertainment", "autos_vehicles", "beauty_fitness", "books_literature", "business_industrial", "computers_electronics", "finance", "food_drink", "games", "health", "hobbies_leisure", "home_garden", "internet_telecom", "jobs_education", "law_government", "news", "online_communities", "people_society", "pets_animals", "real_estate", "reference", "science", "shopping", "sports", "travel" ], "type": "string", "description": "Filter results to a specific category. Only relevant for interest/related actions.", "default": "all" }, "property": { "title": "Search Property", "enum": [ "web", "youtube", "news", "images", "froogle" ], "type": "string", "description": "Which Google property to search. Default is web search.", "default": "web" } } }, "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 } } } } } } } } } } ```