# 🔴 Weibo Scraper (`ethereal_wool/weibo-scraper`) Actor Extract Weibo data — text, reposts, likes, 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/weibo-scraper.md - **Developed by:** [Jackie Chen](https://apify.com/ethereal_wool) (community) - **Categories:** Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $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 ## Weibo Scraper ![weibo-scraper](https://api.apify.com/v2/key-value-stores/48FFrfZnw5XqzUC1C/records/weibo-scraper__hero) Scrape **Weibo (微博)** in four modes — **keyword search**, **user timeline**, **post comments**, and **hot-search trends** — with zero configuration. Returns clean, structured data for each record: text, like / comment / repost counts, author info, timestamps, and the canonical URL. > **Unofficial.** This Actor is not affiliated with, authorized, or endorsed by > Weibo (Sina Weibo / 新浪微博) or Sina Corporation. It is an independent tool that > retrieves publicly available data via a third-party API. Use it in compliance with > Weibo's terms and all applicable laws; you are responsible for how you use the > retrieved data. ### What it does - **Keyword search** — give one or more keywords; the Actor paginates Weibo search results for each. Chinese keywords return the most results. - **User timeline** — give one or more numeric Weibo user IDs (uid) to scrape the posts they have published. - **Post comments** — give one or more numeric post IDs (mid); one dataset item is pushed per comment. - **Hot-search trends** — enable `includeHotSearch` to scrape the live Weibo hot-search ranking (top ~50 trending topics). You can combine any of the modes in a single run. ### Input | Field | Type | Default | Description | |---|---|---|---| | `searchKeywords` | string[] | `["美食"]` | Keywords to search. Each is paginated independently. | | `userIds` | string[] | `[]` | Numeric Weibo user IDs (uid) whose timeline to scrape. | | `postIds` | string[] | `[]` | Numeric post IDs (mid) to fetch comments for. | | `includeHotSearch` | boolean | `false` | Also scrape the current hot-search ranking. | | `maxItems` | integer | `50` | Max total items across all modes. | | `maxCommentsPerPost` | integer | `50` | Cap on comments per post ID. | #### Example input ```json { "searchKeywords": ["美食", "旅行"], "userIds": ["6048496695"], "postIds": ["5305452082759612"], "includeHotSearch": true, "maxItems": 200 } ```` ### Output One dataset item per record. Posts (search / user timeline): ```json { "id": "5305452082759612", "type": "post", "bid": "R2hPGbzTS", "text": "唯唯的吃喝plog🥬🍳🍇 ...", "createdAt": "Tue Jun 02 20:03:30 +0800 2026", "source": "美食博主 微博VLOG博主", "repostsCount": 91, "commentsCount": 114, "attitudesCount": 829, "picNum": 9, "url": "https://weibo.com/6048496695/5305452082759612", "author": { "userId": "6048496695", "screenName": "唯唯带你吃", "followersCount": 1251000, "verified": true }, "fetchedVia": "search:美食" } ``` Comments have `type: "comment"` with `postId`, `text`, `attitudesCount`, `author`. Trends have `type: "trend"` with `rank`, `keyword`, `heat`, `tag`, `url`. ### Notes - Data is sourced live; Weibo occasionally rate-limits, so the Actor retries transient blocks (Cloudflare 403 / 429 / 5xx) with exponential backoff. - Item IDs are de-duplicated within a run. # Actor input Schema ## `searchKeywords` (type: `array`): Keywords to search Weibo posts for. Each keyword is searched and paginated independently. Chinese keywords return the most results. ## `userIds` (type: `array`): Weibo user IDs (numeric uid, e.g. 6048496695) whose posted timeline you want to scrape. ## `postIds` (type: `array`): Weibo post IDs (numeric mid, e.g. 5305452082759612) to fetch comments for. One dataset item is pushed per comment. ## `includeHotSearch` (type: `boolean`): Also scrape the current Weibo hot-search ranking (top ~50 trending topics). One dataset item is pushed per trend. ## `maxItems` (type: `integer`): Maximum total number of items to scrape across all keywords, users, posts and trends. ## `maxCommentsPerPost` (type: `integer`): Maximum comments to fetch per post ID in comments mode. ## `proxyConfiguration` (type: `object`): Optional. Route the upstream API calls through an Apify Proxy to vary the source IP. Usually not needed. ## Actor input object example ```json { "searchKeywords": [ "美食" ], "userIds": [], "postIds": [], "includeHotSearch": false, "maxItems": 50, "maxCommentsPerPost": 50, "proxyConfiguration": { "useApifyProxy": false } } ``` # 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 = { "searchKeywords": [ "美食" ] }; // Run the Actor and wait for it to finish const run = await client.actor("ethereal_wool/weibo-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 = { "searchKeywords": ["美食"] } # Run the Actor and wait for it to finish run = client.actor("ethereal_wool/weibo-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 '{ "searchKeywords": [ "美食" ] }' | apify call ethereal_wool/weibo-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ethereal_wool/weibo-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "🔴 Weibo Scraper", "description": "Extract Weibo data — text, reposts, likes, 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": "kp7CfladASfueJG4h" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ethereal_wool~weibo-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ethereal_wool-weibo-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ethereal_wool~weibo-scraper/runs": { "post": { "operationId": "runs-sync-ethereal_wool-weibo-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ethereal_wool~weibo-scraper/run-sync": { "post": { "operationId": "run-sync-ethereal_wool-weibo-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchKeywords": { "title": "Search keywords", "type": "array", "description": "Keywords to search Weibo posts for. Each keyword is searched and paginated independently. Chinese keywords return the most results.", "default": [ "美食" ], "items": { "type": "string" } }, "userIds": { "title": "User IDs", "type": "array", "description": "Weibo user IDs (numeric uid, e.g. 6048496695) whose posted timeline you want to scrape.", "default": [], "items": { "type": "string" } }, "postIds": { "title": "Post IDs (for comments)", "type": "array", "description": "Weibo post IDs (numeric mid, e.g. 5305452082759612) to fetch comments for. One dataset item is pushed per comment.", "default": [], "items": { "type": "string" } }, "includeHotSearch": { "title": "Include hot-search trends", "type": "boolean", "description": "Also scrape the current Weibo hot-search ranking (top ~50 trending topics). One dataset item is pushed per trend.", "default": false }, "maxItems": { "title": "Max items", "minimum": 1, "maximum": 100000, "type": "integer", "description": "Maximum total number of items to scrape across all keywords, users, posts and trends.", "default": 50 }, "maxCommentsPerPost": { "title": "Max comments per post", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum comments to fetch per post ID in comments mode.", "default": 50 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Optional. Route the upstream API calls through an Apify Proxy to vary the source IP. Usually not needed.", "default": { "useApifyProxy": false } } } }, "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 } } } } } } } } } } ```