init

.opencode/skills/threejs/scripts/generate_csv_from_json.py

@@ -0,0 +1,135 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Generate CSV files from examples-raw.json
+"""
+
+import csv
+import json
+from pathlib import Path
+
+DATA_DIR = Path(__file__).parent.parent / "data"
+SKILL_DIR = Path(__file__).parent.parent
+
+
+def extract_keywords_from_file(filename):
+    """Extract keywords from filename"""
+    base = filename.replace('.html', '')
+    parts = base.split('_')
+    return ', '.join([p for p in parts if len(p) > 1])
+
+
+def extract_name_from_file(filename):
+    """Extract display name from filename"""
+    base = filename.replace('.html', '')
+    parts = base.split('_')[1:]  # Remove prefix like 'webgl'
+    return ' / '.join(parts)
+
+
+def generate_csvs():
+    """Generate tracking and examples CSVs from JSON"""
+    json_file = DATA_DIR / "examples-raw.json"
+
+    with open(json_file, 'r', encoding='utf-8') as f:
+        examples = json.load(f)
+
+    print(f"Loaded {len(examples)} examples from JSON")
+
+    # Count by category
+    categories = {}
+    for ex in examples:
+        cat = ex['c']
+        categories[cat] = categories.get(cat, 0) + 1
+
+    print("\nExamples by category:")
+    for cat, count in sorted(categories.items(), key=lambda x: -x[1]):
+        print(f"  {cat}: {count}")
+
+    # Generate tracking CSV
+    tracking_file = SKILL_DIR / "extraction-progress.csv"
+    tracking_rows = []
+    for i, ex in enumerate(examples, 1):
+        tracking_rows.append({
+            'ID': i,
+            'Category': ex['c'],
+            'Name': extract_name_from_file(ex['f']),
+            'File': ex['f'],
+            'URL': f"https://threejs.org/examples/{ex['f']}",
+            'Keywords': extract_keywords_from_file(ex['f']),
+            'Status': 'extracted',
+            'Extracted_At': '2026-01-21'
+        })
+
+    with open(tracking_file, 'w', newline='', encoding='utf-8') as f:
+        writer = csv.DictWriter(f, fieldnames=['ID', 'Category', 'Name', 'File', 'URL', 'Keywords', 'Status', 'Extracted_At'])
+        writer.writeheader()
+        writer.writerows(tracking_rows)
+    print(f"\nGenerated {len(tracking_rows)} entries in {tracking_file}")
+
+    # Generate examples-all.csv
+    examples_file = DATA_DIR / "examples-all.csv"
+    examples_rows = []
+    for i, ex in enumerate(examples, 1):
+        name = extract_name_from_file(ex['f'])
+        keywords = extract_keywords_from_file(ex['f'])
+
+        # Determine complexity based on category
+        complexity = "medium"
+        if "advanced" in ex['c'] or "gpgpu" in ex['f'] or "compute" in ex['f']:
+            complexity = "high"
+        elif "basic" in ex['f'] or ex['c'] in ['css2d', 'css3d', 'svg']:
+            complexity = "low"
+
+        # Generate use cases based on keywords
+        use_cases = []
+        file_lower = ex['f'].lower()
+        if 'animation' in file_lower:
+            use_cases.append('character animation')
+        if 'loader' in file_lower:
+            use_cases.append('model loading')
+        if 'material' in file_lower:
+            use_cases.append('material effects')
+        if 'postprocessing' in file_lower:
+            use_cases.append('visual effects')
+        if 'shadow' in file_lower:
+            use_cases.append('realistic lighting')
+        if 'physics' in file_lower:
+            use_cases.append('physics simulation')
+        if 'xr' in file_lower or 'vr' in file_lower or 'ar' in file_lower:
+            use_cases.append('VR/AR experience')
+        if 'interactive' in file_lower or 'raycaster' in file_lower:
+            use_cases.append('user interaction')
+        if 'particle' in file_lower or 'points' in file_lower:
+            use_cases.append('particle effects')
+        if 'terrain' in file_lower or 'geometry' in file_lower:
+            use_cases.append('procedural generation')
+        if 'tsl' in file_lower:
+            use_cases.append('shader programming')
+        if 'compute' in file_lower:
+            use_cases.append('GPU compute')
+        if not use_cases:
+            use_cases.append('3D visualization')
+
+        desc = f"Three.js {ex['c']} example demonstrating {name.replace(' / ', ', ')}"
+
+        examples_rows.append({
+            'ID': i,
+            'Category': ex['c'],
+            'Name': name,
+            'File': ex['f'],
+            'URL': f"https://threejs.org/examples/{ex['f']}",
+            'Keywords': keywords,
+            'Complexity': complexity,
+            'Use Cases': '; '.join(use_cases),
+            'Description': desc
+        })
+
+    with open(examples_file, 'w', newline='', encoding='utf-8') as f:
+        writer = csv.DictWriter(f, fieldnames=['ID', 'Category', 'Name', 'File', 'URL', 'Keywords', 'Complexity', 'Use Cases', 'Description'])
+        writer.writeheader()
+        writer.writerows(examples_rows)
+    print(f"Generated {len(examples_rows)} entries in {examples_file}")
+
+
+if __name__ == "__main__":
+    generate_csvs()