# Pinterest Search Scraper (`thescrappa/pinterest-search-scraper`) Actor Search Pinterest pins by keyword through Scrappa, with batch query input, pagination bookmark support, and one dataset item per pin. - **URL**: https://apify.com/thescrappa/pinterest-search-scraper.md - **Developed by:** [Scrappa](https://apify.com/thescrappa) (community) - **Categories:** Social media, Marketing, Developer tools - **Stats:** 2 total users, 1 monthly users, 93.3% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $0.20 / 1,000 pin 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 ## Pinterest Search Scraper Search Pinterest pins by keyword and export one dataset item per pin. This actor is a thin Scrappa-powered wrapper around Scrappa's `GET /api/pinterest/search` endpoint: Apify validates input, batches keyword searches in one run, calls Scrappa, and writes Pinterest pin results to the dataset. ### Use Cases - Find Pinterest pins for visual discovery, ecommerce research, and content trend monitoring. - Collect pin titles, descriptions, images, links, domains, pinner and board context, and social metrics by keyword. - Page through Pinterest keyword search using the returned `nextBookmark`. - Batch related Pinterest keyword searches in one Apify run instead of paying run overhead for each query. ### Input Use `queries` for batch searches. `query` is kept for compatibility with single-query integrations. ```json { "queries": ["home decor", "kitchen ideas"], "limit": 25 } ```` Pagination example: ```json { "query": "home decor", "limit": 25, "bookmark": "PASTE_NEXT_BOOKMARK_HERE" } ``` | Field | Type | Required | Description | |---|---:|---:|---| | `queries` | array | No | Preferred batch input. Up to 100 Pinterest keyword searches per run. | | `query` | string | No | Single-query compatibility input. | | `limit` | integer | No | Pins requested per query. Defaults to `50`, capped at `250`. Pinterest may return fewer results. | | `bookmark` | string | No | Optional pagination bookmark from `nextBookmark`. Applied to each query in the run. | Provide at least one value in `queries` or `query`. ### Output The actor writes one dataset item per Pinterest pin. Each item includes the original pin data plus normalized fields: ```json { "id": "123456789", "title": "Small apartment storage ideas", "description": "Storage ideas for small spaces", "image_url": "https://i.pinimg.com/originals/example.jpg", "link": "https://example.com/storage", "domain": "example.com", "pinner_username": "homeideas", "board_name": "Home Decor", "has_video": false, "repin_count": 42, "comment_count": 3, "request_query": "home decor", "request_limit": 25, "request_bookmark": null, "count": 25, "results_count": 25, "nextBookmark": "NEXT_PAGE_BOOKMARK" } ``` `count`, `results_count`, and `nextBookmark` are copied from Scrappa's Pinterest search response when available, so short pages and pagination state are visible in the dataset. ### Scale This actor is designed for high-intent Pinterest keyword search from Apify. For higher-volume visual discovery, ecommerce research, or direct API integration, use Scrappa's Pinterest Search API directly at `https://scrappa.co/api/pinterest/search`. # Actor input Schema ## `queries` (type: `array`): Pinterest keyword searches to run in one Apify Actor execution. ## `query` (type: `string`): Compatibility field for one Pinterest keyword search. Prefer Search Queries for batching. ## `limit` (type: `integer`): Maximum Pinterest pins to request from Scrappa for each query. Pinterest may return fewer pins than requested. ## `bookmark` (type: `string`): Optional Pinterest pagination bookmark returned as nextBookmark by a previous run. The same bookmark is applied to each query in this run. ## Actor input object example ```json { "queries": [ "home decor", "kitchen ideas" ], "query": "home decor", "limit": 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": [ "home decor", "kitchen ideas" ], "query": "home decor" }; // Run the Actor and wait for it to finish const run = await client.actor("thescrappa/pinterest-search-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": [ "home decor", "kitchen ideas", ], "query": "home decor", } # Run the Actor and wait for it to finish run = client.actor("thescrappa/pinterest-search-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": [ "home decor", "kitchen ideas" ], "query": "home decor" }' | apify call thescrappa/pinterest-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=thescrappa/pinterest-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Pinterest Search Scraper", "description": "Search Pinterest pins by keyword through Scrappa, with batch query input, pagination bookmark support, and one dataset item per pin.", "version": "1.0", "x-build-id": "LMfYWckarkOkzTe0d" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/thescrappa~pinterest-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-thescrappa-pinterest-search-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/thescrappa~pinterest-search-scraper/runs": { "post": { "operationId": "runs-sync-thescrappa-pinterest-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/thescrappa~pinterest-search-scraper/run-sync": { "post": { "operationId": "run-sync-thescrappa-pinterest-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "Pinterest keyword searches to run in one Apify Actor execution.", "items": { "type": "string", "minLength": 1, "maxLength": 200 } }, "query": { "title": "Single Search Query", "minLength": 1, "maxLength": 200, "type": "string", "description": "Compatibility field for one Pinterest keyword search. Prefer Search Queries for batching." }, "limit": { "title": "Limit", "minimum": 1, "maximum": 250, "type": "integer", "description": "Maximum Pinterest pins to request from Scrappa for each query. Pinterest may return fewer pins than requested.", "default": 50 }, "bookmark": { "title": "Pagination Bookmark", "maxLength": 2000, "type": "string", "description": "Optional Pinterest pagination bookmark returned as nextBookmark by a previous run. The same bookmark is applied to each query in this run." } } }, "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 } } } } } } } } } } ```