Chaoxing Document Downloader (超星文档下载)

Download PDFs from Chaoxing WPS viewer URLs using the

getYunFiles

API.

Core Principle

Every Chaoxing viewer URL contains an

objectid

(32-char hex). Call the

getYunFiles

API to get the direct PDF link — no cookies or auth tokens needed.

Arguments

$ARGUMENTS

contains the user's download request — typically one or more entries with page count, name, and viewer URL. Parse them to extract the data.

Download Method

Step 1: Extract objectid from each URL

Find the

objectid=([a-f0-9]{32})

parameter in each viewer URL.

Step 2: Call getYunFiles API

For each objectid, call:

https://contestyd.chaoxing.com/app/files/{objectid}/getYunFiles?key=allData

Response JSON contains:

• data.pdf

  — direct PDF URL on

  s3.cldisk.com

  or

  s3.ananas.chaoxing.com

  (preferred)

• data.download

  — alternative download URL with auth tokens (fallback)

• data.filename

  — original filename

• data.pagenum

  — page count

Step 3: Download the PDF

Use the

data.pdf

URL to download directly. No authentication headers needed.

Save to:

~/Downloads/chaoxing_pdfs/{用户给的名称}.pdf

Step 4: Validate page count

Compare

data.pagenum

with the user's expected page count. Report any mismatch.

Step 5: Convert PDF to TXT (with OCR fallback)

After downloading each PDF, automatically extract text to a plain text file. Use a two-stage approach: native text extraction first, then OCR fallback for image-based pages.

Prerequisites:

pip install pymupdf rapidocr-onnxruntime

Conversion method (Python):

import sys, os, fitz
from rapidocr_onnxruntime import RapidOCR

if sys.platform == "win32":
    sys.stdout.reconfigure(encoding="utf-8")

ocr = RapidOCR()
pdf_path = "~/Downloads/chaoxing_pdfs/{name}.pdf"
doc = fitz.open(pdf_path)
all_text = []

for i, page in enumerate(doc):
    # Stage 1: Try native text extraction
    native = page.get_text().strip()
    if len(native) > 50:
        all_text.append(f"--- 第{i+1}页 ---\n{native}")
        continue
    # Stage 2: OCR fallback for image-based pages
    pix = page.get_pixmap(dpi=200)
    img_bytes = pix.tobytes("png")
    result, _ = ocr(img_bytes)
    ocr_text = "\n".join([item[1] for item in result]) if result else ""
    label = "OCR" if len(ocr_text) > 0 else "(empty)"
    all_text.append(f"--- 第{i+1}页 [{label}] ---\n{ocr_text}")

doc.close()
full_text = "\n".join(all_text)

with open(pdf_path.replace(".pdf", ".txt"), "w", encoding="utf-8") as f:
    f.write(full_text)

# Summary
native_pages = sum(1 for p in all_text if "[OCR]" not in p and "[empty]" not in p)
ocr_pages = sum(1 for p in all_text if "[OCR]" in p)
print(f"Native: {native_pages}p, OCR: {ocr_pages}p, Total: {len(full_text)} chars")

Output files per download:

• {name}.pdf

  — original PDF

• {name}.txt

  — plain text extraction (native + OCR pages marked with

  [OCR]

  )

How it works:

1. Each page is first checked for native text (text layer PDF)
2. If native text < 50 chars, the page is rendered to image at 200 DPI and processed by RapidOCR
3. OCR pages are labeled

   [OCR]

   in the output for easy identification
4. Empty pages (no text and OCR fails) are labeled

   [empty]

CLI Tool (Alternative)

A CLI tool is available at

C:/Users/Cameron/Downloads/chaoxing_dl.py

:

# Single download
python ~/Downloads/chaoxing_dl.py "VIEWER_URL" -n "文件名"

# Batch from JSON file
python ~/Downloads/chaoxing_dl.py --batch tasks.json

# With page validation
python ~/Downloads/chaoxing_dl.py "URL" -n "name" --json

# Force overwrite
python ~/Downloads/chaoxing_dl.py "URL" -n "name" -f

Batch JSON format:

[
  {"name": "文件名", "url": "viewer_url_or_objectid", "pages": 22},
  ...
]

Batch Processing (Without CLI Tool)

For multiple downloads without the CLI, use bash loop:

for oid_name in "OBJECTID1:名称1" "OBJECTID2:名称2"; do
  oid="${oid_name%%:*}"; name="${oid_name##*:}"
  info=$(curl -s -L "https://contestyd.chaoxing.com/app/files/$oid/getYunFiles?key=allData")
  pagenum=$(echo "$info" | grep -o '"pagenum":[0-9]*' | cut -d: -f2)
  pdf_url=$(echo "$info" | grep -o '"pdf":"[^"]*"' | head -1 | tr -d '"' | sed 's/^pdf://')
  echo "$name: ${pagenum}p"
  curl -s -L -o ~/Downloads/chaoxing_pdfs/${name}.pdf "$pdf_url"
done

Key Notes

• Only

  objectid

  is needed — no

  resid

  ,

  tk

  ,

  addPointInfo

  , or cookies
• Always validate page count against user expectation
• The PDF URLs on

  s3.cldisk.com

  are direct links, publicly accessible
• If

  data.pdf

  is empty, fall back to

  data.download

• Skip files that already exist unless user specifies overwrite