# Baidu Library Wenku Scraper - Low-cost ไฝๆๆฌ๐ฒ๐ฅ๐จ๐ณ๐ (`delectable_incubator/baidu-library-wenku-scraper---low-cost-di-cheng-ben`) Actor
Scrape Baidu Wenku document results easily ๐จ๐ณ๐ with a powerful SERP scraper.
Extract titles, document URLs, cover images, authors, page counts, ratings, and views for any keyword.
Ideal for document research, trend analysis, competitor intelligence, and Baidu Wenku tracking ๐๐
- **URL**: https://apify.com/delectable\_incubator/baidu-library-wenku-scraper---low-cost-di-cheng-ben.md
- **Developed by:** [Prime Scrape](https://apify.com/delectable_incubator) (community)
- **Categories:** Lead generation, Developer tools, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
from $0.00005 / actor start
This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.
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
---
### Baidu Wenku Scraper ๐จ๐ณ๐๐ ็พๅบฆๆๅบ็ฌ่ซ
The Baidu Wenku Scraper is a fast, scalable, and reliable Apify Actor designed to extract structured document search results directly from Baidu Wenku.
It is built for China market intelligence, academic research, document analysis, competitor benchmarking, industry reports collection, and SERP tracking of Baidu Wenku content.
---
### ็พๅบฆๆๅบ็ฌ่ซ ๐ง ๐๐
่ฏฅๅทฅๅ
ทๅฏ้่ฟๆน้ๅ
ณ้ฎ่ฏ่ชๅจๆๅ็พๅบฆๆๅบๆ็ดข็ปๆ๏ผๅนถ่ฟๅ็ปๆๅ็ๆๆกฃๆฐๆฎ๏ผๅ
ๆฌไฝ่
ใ้กตๆฐใ่ฏๅใๆต่ง้็ญไฟกๆฏใ
้ๅธธ้ๅ็ ็ฉถไบบๅใๆฐๆฎๅๆๅธใไผไธๆ
ๆฅๅข้ไปฅๅAIๆฐๆฎ้ๆๅปบไฝฟ็จใ
---
### ๐ฏ What This Scraper Does
Simply provide a list of keywords and a limit per keyword โ the scraper handles everything automatically.
โ
Scrapes Baidu Wenku search results at scale
โ
Supports bulk keyword input (multi-search mode)
โ
Extracts structured document metadata
โ
Handles scrolling & pagination automatically
โ
Stops at defined limits per keyword
โ
Moves seamlessly between keywords
โ
Clean, structured, analysis-ready output
---
### ๐ Data Extracted
๐งพ Document Fields
| Field | Description |
| ------------------- | --------------------------------------- |
| ๐ `keyword` | Search keyword used |
| ๐ข `position` | Ranking position in Baidu Wenku results |
| ๐ `title` | Document title |
| ๐ `url` | Direct document URL |
| ๐ผ `coverImage` | Document cover image |
| ๐ `fileType` | File format (PDF, DOC, PPT, etc.) |
| ๐งพ `content` | Preview text / description snippet |
| ๐ค `author` | Document author/uploader |
| ๐ผ๏ธ `authorAvatar` | Author profile image |
| โญ `rating` | Document rating (if available) |
| ๐ `pageCount` | Number of pages |
| ๐ `viewCount` | Total number of views |
| โฑ `searchTimestamp` | Time of extraction |
---
### ๐ How to Use
1๏ธโฃ Configure Input
Provide one or multiple keywords:
````
{
"keywords": \[
"AI",
"็ฝ็ป",
"ไบบๅทฅๆบ่ฝ"
],
"MAX\_ITEMS\_PER\_KEYWORD": 50
}
```
2๏ธโฃ Run the Actor
โข Performs Baidu Wenku document search
โข Extracts structured document results
โข Collects metadata per keyword
โข Stops automatically at limit
3๏ธโฃ Export the Dataset
Download your results in multiple formats:
โ
JSON
โ
CSV
โ
Excel
โ
XML
โ
HTML
---
### โ๏ธ Input Configuration
#### ๐ฅ Input Example
```
{
"keywords": \["ไบบๅทฅๆบ่ฝ"],
"MAX\_ITEMS\_PER\_KEYWORD": 50
}
```
#### Input Fields
| Field | Type | Description |
| ----------------------- | ------- | -------------------------------------------------- |
| `keywords` | array | List of search keywords (bulk mode supported) |
| `MAX_ITEMS_PER_KEYWORD` | integer | Maximum number of documents to extract per keyword |
---
### ๐ค Output Example
```
{
"keyword": "ไบบๅทฅๆบ่ฝ",
"position": 1,
"title": "ไบบๅทฅๆบ่ฝ่กไธๅๅฑ็ ็ฉถๆฅๅ",
"url": "https://example.com/document",
"coverImage": "https://example.com/cover.jpg",
"fileType": "PDF",
"content": "ๆฌๆฅๅๅๆไบไบบๅทฅๆบ่ฝ่กไธ็ๅๅฑ่ถๅฟ...",
"author": "่กไธ็ ็ฉถไธญๅฟ",
"authorAvatar": "https://example.com/avatar.jpg",
"rating": "4.8",
"pageCount": "32",
"viewCount": "12,530",
"searchTimestamp": "2026-02-15T10:21:34.000Z"
}
````
---
### ๐ Output explanation
| Field | Description |
| ----------------- | ------------------------ |
| `keyword` | Search term used |
| `position` | Ranking in Wenku results |
| `title` | Document title |
| `url` | Document URL |
| `coverImage` | Cover image |
| `fileType` | File type |
| `content` | Text preview |
| `author` | Uploader name |
| `rating` | Document rating |
| `pageCount` | Number of pages |
| `viewCount` | Total views |
| `searchTimestamp` | Scraping time |
---
### ๐ Why Use This Scraper?
๐ Academic Research โ collect papers, reports, and studies
๐ Market Intelligence โ analyze industry documents in China
๐ต๏ธ Competitor Analysis โ track competitor whitepapers
๐ท Brand Monitoring โ detect brand-related publications
๐ค AI Dataset Building โ structured document datasets for NLP
๐ Automation Ready โ schedule recurring extraction
---
### โ ๏ธ Disclaimer
This tool is an independent solution and is not affiliated with, endorsed by, or sponsored by Baidu or its subsidiaries or partners.
---
### ๐ธ Pricing
This scraper runs on a **pay per events subscription model**.
You only pay for **successful runs**.
๐ณ **Price:** $9.98 / 1000 results
---
### Related Actors
If you're interested in SEO scraping solutions, explore more tools:
(Coming soon)
---
### ๐ฌ Support
โญโญโญโญโญ Leave a 5-star rating if you like this tool
---
### ๐ PrimeScrape
Built for scalable web data extraction & automation
Contact for custom scraping solutions or enterprise requests via Apify or by email.
# Actor input Schema
## `keywords` (type: `array`):
List of keywords or topics to search for documents. Each keyword will be scraped separately.
็จไบๆ็ดขๆๆกฃ็ๅ
ณ้ฎ่ฏๆไธป้ขๅ่กจใๆฏไธชๅ
ณ้ฎ่ฏๅฐๅๅซ่ฟ่กๆๅใ
## `MAX_ITEMS_PER_KEYWORD` (type: `integer`):
Maximum number of documents to extract per keyword.
ๆฏไธชๅ
ณ้ฎ่ฏ่ฆๆๅ็ๆๆกฃๆๅคงๆฐ้ใ
## Actor input object example
```json
{
"keywords": [
"Web",
"็ฝ็ป"
],
"MAX_ITEMS_PER_KEYWORD": 20
}
````
# Actor output Schema
## `overview` (type: `string`):
No description
# API
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'apify-client';
// Initialize the ApifyClient with your Apify API token
// Replace the '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"keywords": [
"Web",
"็ฝ็ป"
],
"MAX_ITEMS_PER_KEYWORD": 20
};
// Run the Actor and wait for it to finish
const run = await client.actor("delectable_incubator/baidu-library-wenku-scraper---low-cost-di-cheng-ben").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`๐พ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
// ๐ Want to learn more ๐? Go to โ 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 = {
"keywords": [
"Web",
"็ฝ็ป",
],
"MAX_ITEMS_PER_KEYWORD": 20,
}
# Run the Actor and wait for it to finish
run = client.actor("delectable_incubator/baidu-library-wenku-scraper---low-cost-di-cheng-ben").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("๐พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# ๐ Want to learn more ๐? Go to โ https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"keywords": [
"Web",
"็ฝ็ป"
],
"MAX_ITEMS_PER_KEYWORD": 20
}' |
apify call delectable_incubator/baidu-library-wenku-scraper---low-cost-di-cheng-ben --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=delectable_incubator/baidu-library-wenku-scraper---low-cost-di-cheng-ben",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Baidu Library Wenku Scraper - Low-cost ไฝๆๆฌ๐ฒ๐ฅ๐จ๐ณ๐",
"description": "Scrape Baidu Wenku document results easily ๐จ๐ณ๐ with a powerful SERP scraper. \n\nExtract titles, document URLs, cover images, authors, page counts, ratings, and views for any keyword. \n\nIdeal for document research, trend analysis, competitor intelligence, and Baidu Wenku tracking ๐๐",
"version": "0.0",
"x-build-id": "nig5i6m00sXgV93EQ"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/delectable_incubator~baidu-library-wenku-scraper---low-cost-di-cheng-ben/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-delectable_incubator-baidu-library-wenku-scraper---low-cost-di-cheng-ben",
"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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/delectable_incubator~baidu-library-wenku-scraper---low-cost-di-cheng-ben/runs": {
"post": {
"operationId": "runs-sync-delectable_incubator-baidu-library-wenku-scraper---low-cost-di-cheng-ben",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/delectable_incubator~baidu-library-wenku-scraper---low-cost-di-cheng-ben/run-sync": {
"post": {
"operationId": "run-sync-delectable_incubator-baidu-library-wenku-scraper---low-cost-di-cheng-ben",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": [
"keywords",
"MAX_ITEMS_PER_KEYWORD"
],
"properties": {
"keywords": {
"title": "Keywords or topics ๐๐ | ๅ
ณ้ฎ่ฏๆไธป้ข ๐๐",
"type": "array",
"description": "List of keywords or topics to search for documents. Each keyword will be scraped separately.\n\n็จไบๆ็ดขๆๆกฃ็ๅ
ณ้ฎ่ฏๆไธป้ขๅ่กจใๆฏไธชๅ
ณ้ฎ่ฏๅฐๅๅซ่ฟ่กๆๅใ",
"items": {
"type": "string"
},
"default": [
"Web",
"็ฝ็ป"
]
},
"MAX_ITEMS_PER_KEYWORD": {
"title": "Max documents per keyword | ๆฏไธชๅ
ณ้ฎ่ฏ็ๆๅคงๆๆกฃๆฐ",
"type": "integer",
"description": "Maximum number of documents to extract per keyword.\n\nๆฏไธชๅ
ณ้ฎ่ฏ่ฆๆๅ็ๆๆกฃๆๅคงๆฐ้ใ",
"default": 20
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```