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 ---\
{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 = "\
".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}] ---\
{ocr_text}")

doc.close()
full_text = "\
".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 \x3C 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