# Pinterest Scraper: Extract Pins, Search, Comments & Leads (`ahmed_jasarevic/pinterest-scraper`) Actor Professional Pinterest data extraction tool. Scrape pin details, high-res images, full comment lists, and creator contact info. Supports search keywords and direct URLs - **URL**: https://apify.com/ahmed\_jasarevic/pinterest-scraper.md - **Developed by:** [Ahmed Jasarevic](https://apify.com/ahmed_jasarevic) (community) - **Categories:** SEO tools, Social media, Lead generation - **Stats:** 4 total users, 2 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 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 --- #### README.md ## 📌 Pinterest Master Scraper: Search, Pins, Comments & Leads This is a professional-grade, high-performance **Pinterest Scraper** designed for marketing researchers, lead generation experts, and data analysts. It allows you to extract rich data from Pinterest without the need for an official API. ### 🚀 Key Features * **Search Keyword Support:** Scrape thousands of pins based on any search query. * **Direct URL Scraping:** Provide a list of specific Pin URLs to extract detailed data. * **Lead Generation Mode:** Specialized `Include User Info Only` flag to extract creators' data (usernames, follower counts, verified status). * **Deep Comment Extraction:** Fetch the latest comments for every pin, including user details of the commenters. * **Rich Media Mapping:** Get links to Original, HD, Medium, and Thumbnail image sizes. * **Video Support:** Detects and extracts video URLs where available. * **Business Insights:** Scrapes external links (e.g., Instagram, Shop links, Blogs) which are perfect for finding influencer contact info. ### 🛠 Usage & Input Options The scraper is highly flexible. Below are the main parameters you can configure: | Field | Type | Description | | --- | --- | --- | | **Search** | `String` | Any keyword (e.g., "fitness coach", "modern interior"). | | **Max Items** | `Integer` | Limit the number of pins collected. | | **Include Comments** | `Boolean` | Deep-scrapes the comment section for every pin. | | **Include User Info Only** | `Boolean` | Filters out pin data to give you a clean list of creators/leads. | | **Start URLs** | `Array` | List of direct Pin links to scrape specific items. | ### 📊 Output Data Structure The scraper provides a comprehensive JSON output. Example fields include: * `id` and `title` * `description` (including AI-generated alt text) * `stats` (saves, likes, comment count) * `author` (ID, username, full name, **follower count**, profile image, verified merchant status) * `board` (name, link, total pin count) * `images` (multiple resolutions) * `external_url` (the direct link to the creator's website or Instagram) ### 💡 Use Cases 1. **Influencer Outreach:** Search for niches like "fashion blogger" and extract their Pinterest profiles and Instagram links. 2. **Market Research:** Analyze trending styles by extracting descriptions and dominant colors. 3. **Content Aggregation:** Download high-quality images and descriptions for mood boards or AI training. 4. **Competitor Analysis:** Monitor boards and engagement (saves/likes) of specific brands. ### 🔒 Proxy Requirements For stable performance and to bypass Pinterest's rate limits, it is **highly recommended** to use **Residential Proxies**. # Actor input Schema ## `startUrls` (type: `array`): List of Pinterest URLs (Pin, Profile, Board or Search). ## `search` (type: `string`): Keyword for searching new pins. ## `maxItems` (type: `integer`): Maximum number of pins you want in the result. ## `includeComments` (type: `boolean`): If checked, extracts comments for each pin (uses more proxy resources). ## `includeUserInfoOnly` (type: `boolean`): Extracts only author data, without pin details. ## `proxy` (type: `object`): Recommended: Residential Proxy to avoid blocks. ## Actor input object example ```json { "startUrls": [ { "url": "https://www.pinterest.com/pin/1001839879614200593/" } ], "maxItems": 100, "includeComments": false, "includeUserInfoOnly": false, "proxy": { "useApifyProxy": true } } ```` # 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 = { "startUrls": [ { "url": "https://www.pinterest.com/pin/1001839879614200593/" } ], "proxy": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("ahmed_jasarevic/pinterest-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 = { "startUrls": [{ "url": "https://www.pinterest.com/pin/1001839879614200593/" }], "proxy": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("ahmed_jasarevic/pinterest-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 '{ "startUrls": [ { "url": "https://www.pinterest.com/pin/1001839879614200593/" } ], "proxy": { "useApifyProxy": true } }' | apify call ahmed_jasarevic/pinterest-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ahmed_jasarevic/pinterest-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Pinterest Scraper: Extract Pins, Search, Comments & Leads", "description": "Professional Pinterest data extraction tool. Scrape pin details, high-res images, full comment lists, and creator contact info. Supports search keywords and direct URLs", "version": "0.0", "x-build-id": "QJS8pbiVkpdHjJwqG" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ahmed_jasarevic~pinterest-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ahmed_jasarevic-pinterest-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ahmed_jasarevic~pinterest-scraper/runs": { "post": { "operationId": "runs-sync-ahmed_jasarevic-pinterest-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ahmed_jasarevic~pinterest-scraper/run-sync": { "post": { "operationId": "run-sync-ahmed_jasarevic-pinterest-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "proxy" ], "properties": { "startUrls": { "title": "Start URLs", "type": "array", "description": "List of Pinterest URLs (Pin, Profile, Board or Search).", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "search": { "title": "Search keyword", "type": "string", "description": "Keyword for searching new pins." }, "maxItems": { "title": "Maximum number of items", "minimum": 1, "type": "integer", "description": "Maximum number of pins you want in the result.", "default": 100 }, "includeComments": { "title": "Include comments", "type": "boolean", "description": "If checked, extracts comments for each pin (uses more proxy resources).", "default": false }, "includeUserInfoOnly": { "title": "Include only user info", "type": "boolean", "description": "Extracts only author data, without pin details.", "default": false }, "proxy": { "title": "Proxy configuration", "type": "object", "description": "Recommended: Residential Proxy to avoid blocks." } } }, "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 } } } } } } } } } } ```