================================================================================
PRACTICAL PYTHON SCRIPTING - CHALLENGE 2 SOLUTION
Chapter 5: Building rebuild_typescript_course.py
Challenge: Parse Chapter Metadata
================================================================================

PROBLEM:
Create a script that:
1. Finds all chapter HTML files
2. For each file, extract: chapter number, title from <h2>
3. Display a table with all chapters
4. Show chapter count

SOLUTION:
================================================================================

from pathlib import Path
import re

def parse_chapters():
    """Parse chapter metadata from HTML files."""

    print("=" * 80)
    print("CHAPTER METADATA PARSER")
    print("=" * 80 + "\n")

    # Find script directory
    script_dir = Path(__file__).resolve().parent
    chapters_dir = script_dir / "courses" / "Programming" / "TypeScript" / "html"

    if not chapters_dir.exists():
        print(f"❌ Directory not found: {chapters_dir}")
        return

    # Find all chapter files
    print("📚 Finding chapter files...\n")
    html_files = sorted(chapters_dir.glob("ts1-*.html"))

    if not html_files:
        print("⚠️ No chapter files found!")
        return

    print(f"✅ Found {len(html_files)} files\n")

    # Parse metadata from each file
    chapters = []

    for html_file in html_files:
        try:
            # Read file content
            html_content = html_file.read_text(encoding='utf-8')

            # Extract chapter number from filename (ts1-1.html → 1)
            match = re.match(r"ts1-(\d+)", html_file.stem)
            if not match:
                continue
            chapter_num = int(match.group(1))

            # Extract title from <h2> tag
            title_match = re.search(r'<h2>(.*?)</h2>', html_content)
            if title_match:
                chapter_title = title_match.group(1).strip()
            else:
                chapter_title = f"Chapter {chapter_num}"

            # Get file size
            file_size = html_file.stat().st_size

            chapters.append({
                'number': chapter_num,
                'title': chapter_title,
                'filename': html_file.name,
                'size': file_size
            })

            print(f"✅ Chapter {chapter_num}: {chapter_title}")

        except Exception as e:
            print(f"❌ Error parsing {html_file.name}: {e}")
            continue

    # Display results as table
    print("\n" + "=" * 80)
    print("CHAPTER SUMMARY")
    print("=" * 80 + "\n")

    # Print header
    print(f"{'#':<3} {'Title':<40} {'File':<20} {'Size':<10}")
    print("-" * 80)

    # Print rows
    for ch in chapters:
        size_kb = ch['size'] / 1024
        print(f"{ch['number']:<3} {ch['title']:<40} {ch['filename']:<20} {size_kb:>8.1f} KB")

    # Print footer
    print("-" * 80)
    print(f"\n📊 Total chapters: {len(chapters)}")
    total_size = sum(ch['size'] for ch in chapters)
    total_size_mb = total_size / 1024 / 1024
    print(f"📊 Total size: {total_size_mb:.2f} MB")


if __name__ == "__main__":
    parse_chapters()

================================================================================

HOW IT WORKS:
================================================================================

1. EXTRACT CHAPTER NUMBER
   match = re.match(r"ts1-(\d+)", html_file.stem)
   chapter_num = int(match.group(1))

   - (\d+) captures one or more digits
   - group(1) extracts the captured digits
   - int() converts string to integer

2. EXTRACT TITLE FROM HTML
   title_match = re.search(r'<h2>(.*?)</h2>', html_content)
   chapter_title = title_match.group(1).strip()

   - r'<h2>(.*?)</h2>' matches: <h2>ANYTHING</h2>
   - (.*?) is a non-greedy match (stops at first </h2>)
   - .strip() removes leading/trailing whitespace

3. BUILD TABLE
   print(f"{'#':<3} {'Title':<40} {'File':<20} {'Size':<10}")

   - {value:<width} left-aligns text
   - {value:>width} right-aligns text
   - {value:^width} center-aligns text

4. CALCULATE TOTALS
   total_size = sum(ch['size'] for ch in chapters)

   - List comprehension: sum all file sizes
   - Divide by 1024 twice to get MB

================================================================================

TESTING:
================================================================================

python parse_metadata.py

Output:
================================================================================
CHAPTER METADATA PARSER
================================================================================

📚 Finding chapter files...

✅ Found 12 files

✅ Chapter 1: Why TypeScript & Setup
✅ Chapter 2: Basic Types & Type System
✅ Chapter 3: Objects, Arrays & Tuples
...
✅ Chapter 12: Building Real Projects

================================================================================
CHAPTER SUMMARY
================================================================================

#   Title                                    File                 Size
--------------------------------------------------------------------------------
1   Why TypeScript & Setup                   ts1-1.html          45.2 KB
2   Basic Types & Type System                ts1-2.html          52.1 KB
3   Objects, Arrays & Tuples                 ts1-3.html          48.5 KB
...
12  Building Real Projects                   ts1-12.html         51.8 KB
--------------------------------------------------------------------------------

📊 Total chapters: 12
📊 Total size: 0.61 MB

================================================================================

KEY CONCEPTS:
================================================================================

Regular Expression Pattern: r'<h2>(.*?)</h2>'

<h2>     - Match literal "<h2>"
(.*?)    - Capture any characters (non-greedy)
</h2>    - Match literal "</h2>"

Examples:
<h2>Chapter 1</h2>           → Captures: "Chapter 1"
<h2>Advanced Types</h2>      → Captures: "Advanced Types"

Why non-greedy (.*?) instead of greedy (.*)?

✅ Non-greedy (.*?):
   <h2>Title 1</h2> <h2>Title 2</h2>
   Matches: "Title 1" (stops at first </h2>)

❌ Greedy (.*):
   <h2>Title 1</h2> <h2>Title 2</h2>
   Matches: "Title 1</h2> <h2>Title 2" (goes to last </h2>)

Non-greedy is usually what you want!

================================================================================

EXTENDING THIS SCRIPT:
================================================================================

You could add:

1. Word count:
   word_count = len(html_content.split())
   print(f"Words: {word_count}")

2. Code block count:
   code_blocks = html_content.count('<code>')
   print(f"Code blocks: {code_blocks}")

3. Link count:
   links = len(re.findall(r'<a href=', html_content))
   print(f"Links: {links}")

4. Export to CSV:
   import csv
   with open('chapters.csv', 'w') as f:
       writer = csv.DictWriter(f, fieldnames=['number', 'title', 'size'])
       writer.writeheader()
       writer.writerows(chapters)

================================================================================

KEY TAKEAWAYS:
================================================================================

✅ Use regex to extract data from HTML
✅ Non-greedy matching (.*?) for HTML tags
✅ .strip() removes whitespace
✅ Build formatted tables with f-string alignment
✅ Calculate sums with sum() and list comprehensions
✅ Convert sizes (bytes → KB → MB)

The pattern for parsing:
1. Read file content
2. Use regex to extract information
3. Store in data structure (list of dicts)
4. Format and display

This is exactly what rebuild_typescript_course.py does!

================================================================================