# 36Kr China Tech Startup News Feed Scraper (`jungle_synthesizer/36kr-china-tech-startup-news-feed-scraper`) Actor Scrape 36Kr (36氪), China's premier tech and startup news outlet. Extract articles, funding-round announcements, author metadata, section tags, and full body text across all verticals. - **URL**: https://apify.com/jungle\_synthesizer/36kr-china-tech-startup-news-feed-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** News, Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event 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 ## 36Kr China Tech & Startup News Scraper Scrapes 36Kr (36氪) — China's equivalent of TechCrunch — and extracts article metadata, funding-round announcements, and author data. Covers all major sections: 创投 (venture/startup), AI, 科技 (tech), 出海 (overseas expansion), 新经济 (new economy), and more. 36Kr is where Chinese funding rounds often break before Western press picks them up. If your workflow depends on early signals from China's startup ecosystem, this is the source. ### What You Get - Article ID, URL, title, and summary for each piece - Author name, publication timestamp (ISO-8601), and section label - Tags, hero image, read count, and comment count when available - Funding round label (Series A, B, etc.), amounts in CNY and USD — parsed from article leads when 36Kr surfaces them - Optional full body extraction (HTML + plain text) when you need the full text, not just the summary ### Features - **Section filtering** — target specific verticals (创投, AI, 科技, 出海) instead of crawling everything - **Date range filtering** — skip articles before a given date - **Full body mode** — fetches each article page to extract content and enriches funding data from the full text - **Residential proxy routing** — routes through DataImpulse residential proxies to avoid ByteDance's bot detection on listing pages ### How It Works 1. Seeds the requested section listing pages (`/information/web_/`) 2. Parses `window.initialState` embedded JSON — 30 articles per page 3. Normalises each item from 36Kr's internal data shape into the output schema 4. Paginates using `hasNextPage` signal until `maxItems` is reached 5. Optionally fetches each article page for full body HTML and investor details ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `maxItems` | integer | 10 | Maximum articles to scrape | | `sections` | array | `["web_news"]` | Section slugs to crawl. Available: `web_news`, `web_zhichuang`, `web_innovate`, `web_ai`, `web_tech`, `web_chuhai` | | `startDate` | string | — | ISO-8601 date. Skip articles published before this date | | `extractBody` | boolean | false | Fetch each article page for full body HTML/text | #### Input Example ```json { "maxItems": 50, "sections": ["web_zhichuang", "web_ai"], "startDate": "2025-01-01", "extractBody": false } ```` ### Output Each result is one article record. | Field | Type | Description | |-------|------|-------------| | `article_id` | string | 19-digit article ID from the URL | | `url` | string | Canonical article URL | | `title` | string | Article title (Chinese) | | `summary` | string | Lead paragraph | | `body_html` | string | Full article HTML (only when `extractBody: true`) | | `body_markdown` | string | Full article as plain text (only when `extractBody: true`) | | `author` | string | Author display name | | `publish_time` | string | ISO-8601 publication timestamp | | `section` | string | Section label (e.g., 创投, AI, 科技) | | `tags` | string | JSON array of subject tags | | `companies_mentioned` | string | JSON array of company entities (from widget data when `extractBody: true`) | | `funding_round` | string | Round label when article covers a funding event (e.g., "Series B") | | `funding_amount_cny` | number | Amount in CNY when surfaced in lead | | `funding_amount_usd` | number | Amount in USD when surfaced in lead | | `lead_investors` | string | JSON array of lead investor names (when `extractBody: true`) | | `hero_image` | string | Hero image URL | | `read_count` | integer | View count when available | | `comment_count` | integer | Comment count when available | #### Sample Output ```json { "article_id": "2492318105786505", "url": "https://36kr.com/p/2492318105786505", "title": "某AI公司完成10亿元A轮融资", "summary": "该公司专注于工业视觉检测，本轮融资由红杉领投。", "body_html": null, "body_markdown": null, "author": "36氪创投", "publish_time": "2025-05-30T03:14:00.000Z", "section": "创投", "tags": "[\"人工智能\",\"融资\",\"工业互联网\"]", "companies_mentioned": "[]", "funding_round": "Series A", "funding_amount_cny": 1000000000, "funding_amount_usd": null, "lead_investors": "[]", "hero_image": "https://img.36krcdn.com/hsossms/20250530/v2_image.jpg", "read_count": 4200, "comment_count": 12 } ``` ### 🔍 FAQ **Is this only for the news section?** No. Use the `sections` input to target specific verticals. 创投 (`web_zhichuang`) covers startup and funding news specifically, which is often the highest-signal content for VC and deal-flow use cases. **How fresh is the data?** The listing pages update continuously. A run against `web_news` with `maxItems: 30` captures the last hour or two of posts. **Does it extract full article text?** Set `extractBody: true`. The actor fetches each article page separately and returns `body_html` and `body_markdown`. Expect longer run times proportional to `maxItems`. **How are funding amounts parsed?** From Chinese-language patterns in article titles and summaries (e.g., "完成X亿元A轮融资"). When `extractBody: true`, the full article body is also scanned for more precise figures. This is heuristic — verify amounts for critical applications. **What sections are available?** `web_news` (all), `web_zhichuang` (创投/VC), `web_innovate` (新经济), `web_ai` (AI), `web_tech` (科技), `web_chuhai` (出海). The site has additional sections not listed here — their slugs follow the same `web_` pattern. **What about the gateway API at gateway.36kr.com?** It requires signed tokens and is not used. The SSR listing pages embed all article data needed to populate the schema. # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `maxItems` (type: `integer`): Maximum number of articles to scrape. Leave empty for no limit. ## `sections` (type: `array`): Filter by section slugs. Leave empty to crawl all sections. Available: web\_news, web\_zhichuang, web\_innovate, web\_ai, web\_tech, web\_chuhai ## `startDate` (type: `string`): Only include articles published on or after this date (e.g. 2025-01-01). Leave empty for no filter. ## `extractBody` (type: `boolean`): When enabled, fetch each article page to extract full body HTML and Markdown. Increases run time proportionally. ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "sections": [ "web_news" ], "extractBody": false } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "sections": [ "web_news" ], "extractBody": false }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/36kr-china-tech-startup-news-feed-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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "sections": ["web_news"], "extractBody": False, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/36kr-china-tech-startup-news-feed-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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "sections": [ "web_news" ], "extractBody": false }' | apify call jungle_synthesizer/36kr-china-tech-startup-news-feed-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/36kr-china-tech-startup-news-feed-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "36Kr China Tech Startup News Feed Scraper", "description": "Scrape 36Kr (36氪), China's premier tech and startup news outlet. Extract articles, funding-round announcements, author metadata, section tags, and full body text across all verticals.", "version": "0.1", "x-build-id": "C9t1vWDksC1sPGixP" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~36kr-china-tech-startup-news-feed-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-36kr-china-tech-startup-news-feed-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/jungle_synthesizer~36kr-china-tech-startup-news-feed-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-36kr-china-tech-startup-news-feed-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/jungle_synthesizer~36kr-china-tech-startup-news-feed-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-36kr-china-tech-startup-news-feed-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": [ "maxItems" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of articles to scrape. Leave empty for no limit.", "default": 10 }, "sections": { "title": "Sections", "type": "array", "description": "Filter by section slugs. Leave empty to crawl all sections. Available: web_news, web_zhichuang, web_innovate, web_ai, web_tech, web_chuhai", "default": [ "web_news" ], "items": { "type": "string" } }, "startDate": { "title": "Start Date (ISO-8601)", "type": "string", "description": "Only include articles published on or after this date (e.g. 2025-01-01). Leave empty for no filter." }, "extractBody": { "title": "Extract Full Body", "type": "boolean", "description": "When enabled, fetch each article page to extract full body HTML and Markdown. Increases run time proportionally.", "default": 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 } } } } } } } } } } ```