MediaCrawler/docs/excel_export_guide.md

Excel Export Guide

Overview

MediaCrawler now supports exporting crawled data to formatted Excel files (.xlsx) with professional styling and multiple sheets for contents, comments, and creators.

Features

• Multi-sheet workbooks: Separate sheets for Contents, Comments, and Creators
• Professional formatting:
  • Styled headers with blue background and white text
  • Auto-adjusted column widths
  • Cell borders and text wrapping
  • Clean, readable layout
• Smart export: Empty sheets are automatically removed
• Organized storage: Files saved to data/{platform}/ directory with timestamps

Installation

Excel export requires the openpyxl library:

# Using uv (recommended)
uv sync

# Or using pip
pip install openpyxl

Usage

Basic Usage

1. Configure Excel export in config/base_config.py:

SAVE_DATA_OPTION = "excel"  # Change from json/csv/db to excel

2. Run the crawler:

# Xiaohongshu example
uv run main.py --platform xhs --lt qrcode --type search

# Douyin example
uv run main.py --platform dy --lt qrcode --type search

# Bilibili example
uv run main.py --platform bili --lt qrcode --type search

3. Find your Excel file in data/{platform}/ directory:
   • Filename format: {platform}_{crawler_type}_{timestamp}.xlsx
   • Example: xhs_search_20250128_143025.xlsx

Command Line Examples

# Search by keywords and export to Excel
uv run main.py --platform xhs --lt qrcode --type search --save_data_option excel

# Crawl specific posts and export to Excel
uv run main.py --platform xhs --lt qrcode --type detail --save_data_option excel

# Crawl creator profile and export to Excel
uv run main.py --platform xhs --lt qrcode --type creator --save_data_option excel

Excel File Structure

Contents Sheet

Contains post/video information:

• note_id: Unique post identifier
• title: Post title
• desc: Post description
• user_id: Author user ID
• nickname: Author nickname
• liked_count: Number of likes
• comment_count: Number of comments
• share_count: Number of shares
• ip_location: IP location
• image_list: Comma-separated image URLs
• tag_list: Comma-separated tags
• note_url: Direct link to post
• And more platform-specific fields...

Comments Sheet

Contains comment information:

• comment_id: Unique comment identifier
• note_id: Associated post ID
• content: Comment text
• user_id: Commenter user ID
• nickname: Commenter nickname
• like_count: Comment likes
• create_time: Comment timestamp
• ip_location: Commenter location
• sub_comment_count: Number of replies
• And more...

Creators Sheet

Contains creator/author information:

• user_id: Unique user identifier
• nickname: Display name
• gender: Gender
• avatar: Profile picture URL
• desc: Bio/description
• fans: Follower count
• follows: Following count
• interaction: Total interactions
• And more...

Advantages Over Other Formats

vs CSV

• ✅ Multiple sheets in one file
• ✅ Professional formatting
• ✅ Better handling of special characters
• ✅ Auto-adjusted column widths
• ✅ No encoding issues

vs JSON

• ✅ Human-readable tabular format
• ✅ Easy to open in Excel/Google Sheets
• ✅ Better for data analysis
• ✅ Easier to share with non-technical users

vs Database

• ✅ No database setup required
• ✅ Portable single-file format
• ✅ Easy to share and archive
• ✅ Works offline

Tips & Best Practices

1. Large datasets: For very large crawls (>10,000 rows), consider using database storage instead for better performance

2. Data analysis: Excel files work great with:

   • Microsoft Excel
   • Google Sheets
   • LibreOffice Calc
   • Python pandas: pd.read_excel('file.xlsx')

3. Combining data: You can merge multiple Excel files using:

   import pandas as pd
   df1 = pd.read_excel('file1.xlsx', sheet_name='Contents')
   df2 = pd.read_excel('file2.xlsx', sheet_name='Contents')
   combined = pd.concat([df1, df2])
   combined.to_excel('combined.xlsx', index=False)
   

4. File size: Excel files are typically 2-3x larger than CSV but smaller than JSON

Troubleshooting

"openpyxl not installed" error

# Install openpyxl
uv add openpyxl
# or
pip install openpyxl

Excel file not created

Check that:

1. SAVE_DATA_OPTION = "excel" in config
2. Crawler successfully collected data
3. No errors in console output
4. data/{platform}/ directory exists

Empty Excel file

This happens when:

• No data was crawled (check keywords/IDs)
• Login failed (check login status)
• Platform blocked requests (check IP/rate limits)

Example Output

After running a successful crawl, you'll see:

[ExcelStoreBase] Initialized Excel export to: data/xhs/xhs_search_20250128_143025.xlsx
[ExcelStoreBase] Stored content to Excel: 7123456789
[ExcelStoreBase] Stored comment to Excel: comment_123
...
[Main] Excel file saved successfully

Your Excel file will have:

• Professional blue headers
• Clean borders
• Wrapped text for long content
• Auto-sized columns
• Separate organized sheets

Advanced Usage

Programmatic Access

from store.excel_store_base import ExcelStoreBase

# Create store
store = ExcelStoreBase(platform="xhs", crawler_type="search")

# Store data
await store.store_content({
    "note_id": "123",
    "title": "Test Post",
    "liked_count": 100
})

# Save to file
store.flush()

Custom Formatting

You can extend ExcelStoreBase to customize formatting:

from store.excel_store_base import ExcelStoreBase

class CustomExcelStore(ExcelStoreBase):
    def _apply_header_style(self, sheet, row_num=1):
        # Custom header styling
        super()._apply_header_style(sheet, row_num)
        # Add your customizations here

Support

For issues or questions:

• Check 常见问题
• Open an issue on GitHub
• Join the WeChat discussion group

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Note: Excel export is designed for learning and research purposes. Please respect platform terms of service and rate limits.