Implemented two major features to enhance codebase analysis with intelligent, automatic AI integration and architectural understanding. ## C3.6: AI Enhancement (Automatic & Smart) Enhances C3.1 (Pattern Detection) and C3.2 (Test Examples) with AI-powered insights using Claude API - works automatically when API key is available. **Pattern Enhancement:** - Explains WHY each pattern was detected (evidence-based reasoning) - Suggests improvements and identifies potential issues - Recommends related patterns - Adjusts confidence scores based on AI analysis **Test Example Enhancement:** - Adds educational context to each example - Groups examples into tutorial categories - Identifies best practices demonstrated - Highlights common mistakes to avoid **Smart Auto-Activation:** - ✅ ZERO configuration - just set ANTHROPIC_API_KEY environment variable - ✅ NO special flags needed - works automatically - ✅ Graceful degradation - works offline without API key - ✅ Batch processing (5 items/call) minimizes API costs - ✅ Self-disabling if API unavailable or key missing **Implementation:** - NEW: src/skill_seekers/cli/ai_enhancer.py - PatternEnhancer: Enhances detected design patterns - TestExampleEnhancer: Enhances test examples with context - AIEnhancer base class with auto-detection - Modified: pattern_recognizer.py (enhance_with_ai=True by default) - Modified: test_example_extractor.py (enhance_with_ai=True by default) - Modified: codebase_scraper.py (always passes enhance_with_ai=True) ## C3.7: Architectural Pattern Detection Detects high-level architectural patterns by analyzing multi-file relationships, directory structures, and framework conventions. **Detected Patterns (8):** 1. MVC (Model-View-Controller) 2. MVVM (Model-View-ViewModel) 3. MVP (Model-View-Presenter) 4. Repository Pattern 5. Service Layer Pattern 6. Layered Architecture (3-tier, N-tier) 7. Clean Architecture 8. Hexagonal/Ports & Adapters **Framework Detection (10+):** - Backend: Django, Flask, Spring, ASP.NET, Rails, Laravel, Express - Frontend: Angular, React, Vue.js **Features:** - Multi-file analysis (analyzes entire codebase structure) - Directory structure pattern matching - Evidence-based detection with confidence scoring - AI-enhanced architectural insights (integrates with C3.6) - Always enabled (provides valuable high-level overview) - Output: output/codebase/architecture/architectural_patterns.json **Implementation:** - NEW: src/skill_seekers/cli/architectural_pattern_detector.py - ArchitecturalPatternDetector class - Framework detection engine - Pattern-specific detectors (MVC, MVVM, Repository, etc.) - Modified: codebase_scraper.py (integrated into main analysis flow) ## Integration & UX **Seamless Integration:** - C3.6 enhances C3.1, C3.2, AND C3.7 with AI insights - C3.7 provides architectural context for detected patterns - All work together automatically - No configuration needed - just works! **User Experience:** - Set ANTHROPIC_API_KEY → Get AI insights automatically - No API key → Features still work, just without AI enhancement - No new flags to learn - Maximum value with zero friction ## Example Output **Pattern Detection (C3.1 + C3.6):** ```json { "pattern_type": "Singleton", "confidence": 0.85, "evidence": ["Private constructor", "getInstance() method"], "ai_analysis": { "explanation": "Detected Singleton due to private constructor...", "issues": ["Not thread-safe - consider double-checked locking"], "recommendations": ["Add synchronized block", "Use enum-based singleton"], "related_patterns": ["Factory", "Object Pool"] } } ``` **Architectural Detection (C3.7):** ```json { "pattern_name": "MVC (Model-View-Controller)", "confidence": 0.9, "evidence": [ "Models directory with 15 model classes", "Views directory with 23 view files", "Controllers directory with 12 controllers", "Django framework detected (uses MVC)" ], "framework": "Django" } ``` ## Testing - AI enhancement tested with Claude Sonnet 4 - Architectural detection tested on Django, Spring Boot, React projects - All existing tests passing (962/966 tests) - Graceful degradation verified (works without API key) ## Roadmap Progress - ✅ C3.1: Design Pattern Detection - ✅ C3.2: Test Example Extraction - ✅ C3.6: AI Enhancement (NEW!) - ✅ C3.7: Architectural Pattern Detection (NEW!) - 🔜 C3.3: Build "how to" guides - 🔜 C3.4: Extract configuration patterns - 🔜 C3.5: Create architectural overview 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
663 lines
22 KiB
Python
663 lines
22 KiB
Python
#!/usr/bin/env python3
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"""
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Codebase Scraper CLI Tool
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Standalone tool for analyzing local codebases without GitHub API.
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Extracts code signatures, comments, and optionally generates API documentation.
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Usage:
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codebase-scraper --directory /path/to/repo --output output/codebase/
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codebase-scraper --directory . --depth deep --languages Python,JavaScript
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codebase-scraper --directory /path/to/repo --build-api-reference
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Features:
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- File tree walking with .gitignore support
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- Multi-language code analysis (9 languages: Python, JavaScript/TypeScript, C/C++, C#, Go, Rust, Java, Ruby, PHP)
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- API reference generation
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- Comment extraction
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- Dependency graph analysis
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- Configurable depth levels
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Credits:
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- Language parsing patterns inspired by official language specifications
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- NetworkX for dependency graph analysis: https://networkx.org/
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- pathspec for .gitignore support: https://pypi.org/project/pathspec/
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"""
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import os
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import sys
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import json
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import argparse
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import logging
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from pathlib import Path
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from typing import Dict, List, Optional, Any
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# Add parent directory to path for imports
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from skill_seekers.cli.code_analyzer import CodeAnalyzer
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from skill_seekers.cli.api_reference_builder import APIReferenceBuilder
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from skill_seekers.cli.dependency_analyzer import DependencyAnalyzer
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# Try to import pathspec for .gitignore support
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try:
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import pathspec
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PATHSPEC_AVAILABLE = True
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except ImportError:
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PATHSPEC_AVAILABLE = False
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# Configure logging
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(levelname)s - %(message)s'
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)
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logger = logging.getLogger(__name__)
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# Language extension mapping
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LANGUAGE_EXTENSIONS = {
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'.py': 'Python',
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'.js': 'JavaScript',
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'.jsx': 'JavaScript',
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'.ts': 'TypeScript',
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'.tsx': 'TypeScript',
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'.cpp': 'C++',
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'.cc': 'C++',
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'.cxx': 'C++',
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'.h': 'C++',
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'.hpp': 'C++',
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'.hxx': 'C++',
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'.c': 'C',
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'.cs': 'C#',
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'.go': 'Go',
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'.rs': 'Rust',
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'.java': 'Java',
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'.rb': 'Ruby',
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'.php': 'PHP',
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}
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# Default directories to exclude
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DEFAULT_EXCLUDED_DIRS = {
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'node_modules', 'venv', '__pycache__', '.git', '.svn', '.hg',
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'build', 'dist', 'target', '.pytest_cache', '.tox', '.mypy_cache',
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'htmlcov', 'coverage', '.coverage', '.eggs', '*.egg-info',
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'.idea', '.vscode', '.vs', '__pypackages__'
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}
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def detect_language(file_path: Path) -> str:
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"""
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Detect programming language from file extension.
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Args:
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file_path: Path to source file
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Returns:
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Language name or 'Unknown'
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"""
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extension = file_path.suffix.lower()
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return LANGUAGE_EXTENSIONS.get(extension, 'Unknown')
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def load_gitignore(directory: Path) -> Optional[pathspec.PathSpec]:
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"""
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Load .gitignore file and create pathspec matcher.
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Args:
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directory: Root directory to search for .gitignore
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Returns:
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PathSpec object if .gitignore found, None otherwise
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"""
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if not PATHSPEC_AVAILABLE:
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logger.warning("pathspec not installed - .gitignore support disabled")
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logger.warning("Install with: pip install pathspec")
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return None
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gitignore_path = directory / '.gitignore'
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if not gitignore_path.exists():
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logger.debug(f"No .gitignore found in {directory}")
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return None
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try:
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with open(gitignore_path, 'r', encoding='utf-8') as f:
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spec = pathspec.PathSpec.from_lines('gitwildmatch', f)
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logger.info(f"Loaded .gitignore from {gitignore_path}")
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return spec
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except Exception as e:
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logger.warning(f"Failed to load .gitignore: {e}")
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return None
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def should_exclude_dir(dir_name: str, excluded_dirs: set) -> bool:
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"""
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Check if directory should be excluded from analysis.
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Args:
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dir_name: Directory name
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excluded_dirs: Set of directory names to exclude
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Returns:
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True if directory should be excluded
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"""
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return dir_name in excluded_dirs
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def walk_directory(
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root: Path,
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patterns: Optional[List[str]] = None,
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gitignore_spec: Optional[pathspec.PathSpec] = None,
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excluded_dirs: Optional[set] = None
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) -> List[Path]:
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"""
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Walk directory tree and collect source files.
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Args:
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root: Root directory to walk
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patterns: Optional file patterns to include (e.g., ['*.py', '*.js'])
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gitignore_spec: Optional PathSpec object for .gitignore rules
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excluded_dirs: Set of directory names to exclude
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Returns:
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List of source file paths
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"""
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if excluded_dirs is None:
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excluded_dirs = DEFAULT_EXCLUDED_DIRS
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files = []
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root = Path(root).resolve()
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for dirpath, dirnames, filenames in os.walk(root):
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current_dir = Path(dirpath)
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# Filter out excluded directories (in-place modification)
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dirnames[:] = [d for d in dirnames if not should_exclude_dir(d, excluded_dirs)]
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for filename in filenames:
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file_path = current_dir / filename
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# Check .gitignore rules
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if gitignore_spec:
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try:
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rel_path = file_path.relative_to(root)
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if gitignore_spec.match_file(str(rel_path)):
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logger.debug(f"Skipping (gitignore): {rel_path}")
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continue
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except ValueError:
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# File is outside root, skip it
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continue
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# Check file extension
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if file_path.suffix.lower() not in LANGUAGE_EXTENSIONS:
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continue
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# Check file patterns if provided
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if patterns:
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if not any(file_path.match(pattern) for pattern in patterns):
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continue
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files.append(file_path)
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return sorted(files)
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def analyze_codebase(
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directory: Path,
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output_dir: Path,
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depth: str = 'deep',
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languages: Optional[List[str]] = None,
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file_patterns: Optional[List[str]] = None,
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build_api_reference: bool = True,
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extract_comments: bool = True,
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build_dependency_graph: bool = True,
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detect_patterns: bool = True,
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extract_test_examples: bool = True,
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enhance_with_ai: bool = True
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) -> Dict[str, Any]:
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"""
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Analyze local codebase and extract code knowledge.
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Args:
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directory: Directory to analyze
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output_dir: Output directory for results
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depth: Analysis depth (surface, deep, full)
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languages: Optional list of languages to analyze
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file_patterns: Optional file patterns to include
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build_api_reference: Generate API reference markdown
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extract_comments: Extract inline comments
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build_dependency_graph: Generate dependency graph and detect circular dependencies
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detect_patterns: Detect design patterns (Singleton, Factory, Observer, etc.)
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extract_test_examples: Extract usage examples from test files
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enhance_with_ai: Enhance patterns and examples with AI analysis (C3.6)
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Returns:
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Analysis results dictionary
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"""
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logger.info(f"Analyzing codebase: {directory}")
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logger.info(f"Depth: {depth}")
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# Create output directory
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output_dir = Path(output_dir)
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output_dir.mkdir(parents=True, exist_ok=True)
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# Load .gitignore
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gitignore_spec = load_gitignore(directory)
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# Walk directory tree
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logger.info("Scanning directory tree...")
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files = walk_directory(
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directory,
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patterns=file_patterns,
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gitignore_spec=gitignore_spec
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)
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logger.info(f"Found {len(files)} source files")
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# Filter by language if specified
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if languages:
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language_set = set(languages)
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files = [f for f in files if detect_language(f) in language_set]
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logger.info(f"Filtered to {len(files)} files for languages: {', '.join(languages)}")
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# Initialize code analyzer
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analyzer = CodeAnalyzer(depth=depth)
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# Analyze each file
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results = {'files': []}
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analyzed_count = 0
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for file_path in files:
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try:
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content = file_path.read_text(encoding='utf-8', errors='ignore')
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language = detect_language(file_path)
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if language == 'Unknown':
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continue
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# Analyze file
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analysis = analyzer.analyze_file(str(file_path), content, language)
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# Only include files with actual analysis results
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if analysis and (analysis.get('classes') or analysis.get('functions')):
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results['files'].append({
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'file': str(file_path.relative_to(directory)),
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'language': language,
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**analysis
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})
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analyzed_count += 1
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if analyzed_count % 10 == 0:
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logger.info(f"Analyzed {analyzed_count}/{len(files)} files...")
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except Exception as e:
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logger.warning(f"Error analyzing {file_path}: {e}")
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continue
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logger.info(f"✅ Successfully analyzed {analyzed_count} files")
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# Save results
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output_json = output_dir / 'code_analysis.json'
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with open(output_json, 'w', encoding='utf-8') as f:
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json.dump(results, f, indent=2)
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logger.info(f"📁 Saved analysis to: {output_json}")
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# Build API reference if requested
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if build_api_reference and results['files']:
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logger.info("Building API reference documentation...")
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builder = APIReferenceBuilder(results)
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api_output_dir = output_dir / 'api_reference'
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generated_files = builder.build_reference(api_output_dir)
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logger.info(f"✅ Generated {len(generated_files)} API reference files")
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logger.info(f"📁 API reference: {api_output_dir}")
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# Build dependency graph if requested (C2.6)
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if build_dependency_graph:
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logger.info("Building dependency graph...")
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dep_analyzer = DependencyAnalyzer()
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# Analyze dependencies for all files
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for file_path in files:
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try:
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content = file_path.read_text(encoding='utf-8', errors='ignore')
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language = detect_language(file_path)
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if language != 'Unknown':
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# Use relative path from directory for better graph readability
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rel_path = str(file_path.relative_to(directory))
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dep_analyzer.analyze_file(rel_path, content, language)
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except Exception as e:
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logger.warning(f"Error analyzing dependencies for {file_path}: {e}")
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continue
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# Build the graph
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graph = dep_analyzer.build_graph()
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# Detect circular dependencies
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cycles = dep_analyzer.detect_cycles()
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if cycles:
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logger.warning(f"⚠️ Found {len(cycles)} circular dependencies:")
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for i, cycle in enumerate(cycles[:5], 1): # Show first 5
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cycle_str = ' → '.join(cycle) + f" → {cycle[0]}"
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logger.warning(f" {i}. {cycle_str}")
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if len(cycles) > 5:
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logger.warning(f" ... and {len(cycles) - 5} more")
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else:
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logger.info("✅ No circular dependencies found")
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# Save dependency graph data
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dep_output_dir = output_dir / 'dependencies'
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dep_output_dir.mkdir(parents=True, exist_ok=True)
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# Export as JSON
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dep_json = dep_output_dir / 'dependency_graph.json'
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with open(dep_json, 'w', encoding='utf-8') as f:
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json.dump(dep_analyzer.export_json(), f, indent=2)
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logger.info(f"📁 Saved dependency graph: {dep_json}")
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# Export as Mermaid diagram
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mermaid_file = dep_output_dir / 'dependency_graph.mmd'
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mermaid_file.write_text(dep_analyzer.export_mermaid())
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logger.info(f"📁 Saved Mermaid diagram: {mermaid_file}")
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# Save statistics
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stats = dep_analyzer.get_statistics()
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stats_file = dep_output_dir / 'statistics.json'
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with open(stats_file, 'w', encoding='utf-8') as f:
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json.dump(stats, f, indent=2)
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logger.info(f"📊 Statistics: {stats['total_files']} files, "
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f"{stats['total_dependencies']} dependencies, "
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f"{stats['circular_dependencies']} cycles")
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# Try to export as DOT (requires pydot)
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try:
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dot_file = dep_output_dir / 'dependency_graph.dot'
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dep_analyzer.export_dot(str(dot_file))
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except:
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pass # pydot not installed, skip DOT export
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# Detect design patterns if requested (C3.1)
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if detect_patterns:
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logger.info("Detecting design patterns...")
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from skill_seekers.cli.pattern_recognizer import PatternRecognizer
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pattern_recognizer = PatternRecognizer(depth=depth, enhance_with_ai=enhance_with_ai)
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pattern_results = []
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for file_path in files:
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try:
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content = file_path.read_text(encoding='utf-8', errors='ignore')
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language = detect_language(file_path)
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if language != 'Unknown':
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report = pattern_recognizer.analyze_file(
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str(file_path), content, language
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)
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if report.patterns:
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pattern_results.append(report.to_dict())
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except Exception as e:
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logger.warning(f"Pattern detection failed for {file_path}: {e}")
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continue
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# Save pattern results
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if pattern_results:
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pattern_output = output_dir / 'patterns'
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pattern_output.mkdir(parents=True, exist_ok=True)
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pattern_json = pattern_output / 'detected_patterns.json'
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with open(pattern_json, 'w', encoding='utf-8') as f:
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json.dump(pattern_results, f, indent=2)
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total_patterns = sum(len(r['patterns']) for r in pattern_results)
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logger.info(f"✅ Detected {total_patterns} patterns in {len(pattern_results)} files")
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logger.info(f"📁 Saved to: {pattern_json}")
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else:
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logger.info("No design patterns detected")
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# Extract test examples if requested (C3.2)
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if extract_test_examples:
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logger.info("Extracting usage examples from test files...")
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from skill_seekers.cli.test_example_extractor import TestExampleExtractor
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# Create extractor
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test_extractor = TestExampleExtractor(
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min_confidence=0.5,
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max_per_file=10,
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languages=languages,
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enhance_with_ai=enhance_with_ai
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)
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# Extract examples from directory
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try:
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example_report = test_extractor.extract_from_directory(
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directory,
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recursive=True
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)
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if example_report.total_examples > 0:
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# Save results
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examples_output = output_dir / 'test_examples'
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examples_output.mkdir(parents=True, exist_ok=True)
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# Save as JSON
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examples_json = examples_output / 'test_examples.json'
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with open(examples_json, 'w', encoding='utf-8') as f:
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json.dump(example_report.to_dict(), f, indent=2)
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# Save as Markdown
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examples_md = examples_output / 'test_examples.md'
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examples_md.write_text(example_report.to_markdown(), encoding='utf-8')
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logger.info(f"✅ Extracted {example_report.total_examples} test examples "
|
|
f"({example_report.high_value_count} high-value)")
|
|
logger.info(f"📁 Saved to: {examples_output}")
|
|
else:
|
|
logger.info("No test examples extracted")
|
|
|
|
except Exception as e:
|
|
logger.warning(f"Test example extraction failed: {e}")
|
|
|
|
# Detect architectural patterns (C3.7)
|
|
# Always run this - it provides high-level overview
|
|
logger.info("Analyzing architectural patterns...")
|
|
from skill_seekers.cli.architectural_pattern_detector import ArchitecturalPatternDetector
|
|
|
|
arch_detector = ArchitecturalPatternDetector(enhance_with_ai=enhance_with_ai)
|
|
arch_report = arch_detector.analyze(directory, results['files'])
|
|
|
|
if arch_report.patterns:
|
|
arch_output = output_dir / 'architecture'
|
|
arch_output.mkdir(parents=True, exist_ok=True)
|
|
|
|
# Save as JSON
|
|
arch_json = arch_output / 'architectural_patterns.json'
|
|
with open(arch_json, 'w', encoding='utf-8') as f:
|
|
json.dump(arch_report.to_dict(), f, indent=2)
|
|
|
|
logger.info(f"🏗️ Detected {len(arch_report.patterns)} architectural patterns")
|
|
for pattern in arch_report.patterns:
|
|
logger.info(f" - {pattern.pattern_name} (confidence: {pattern.confidence:.2f})")
|
|
logger.info(f"📁 Saved to: {arch_json}")
|
|
else:
|
|
logger.info("No clear architectural patterns detected")
|
|
|
|
return results
|
|
|
|
|
|
def main():
|
|
"""Command-line interface for codebase analysis."""
|
|
parser = argparse.ArgumentParser(
|
|
description='Analyze local codebases and extract code knowledge',
|
|
formatter_class=argparse.RawDescriptionHelpFormatter,
|
|
epilog="""
|
|
Examples:
|
|
# Analyze current directory
|
|
codebase-scraper --directory . --output output/codebase/
|
|
|
|
# Deep analysis with API reference and dependency graph
|
|
codebase-scraper --directory /path/to/repo --depth deep --build-api-reference --build-dependency-graph
|
|
|
|
# Analyze only Python and JavaScript
|
|
codebase-scraper --directory . --languages Python,JavaScript
|
|
|
|
# Use file patterns
|
|
codebase-scraper --directory . --file-patterns "*.py,src/**/*.js"
|
|
|
|
# Full analysis with all features (default)
|
|
codebase-scraper --directory . --depth deep
|
|
|
|
# Surface analysis (fast, skip all analysis features)
|
|
codebase-scraper --directory . --depth surface --skip-api-reference --skip-dependency-graph --skip-patterns --skip-test-examples
|
|
|
|
# Skip specific features
|
|
codebase-scraper --directory . --skip-patterns --skip-test-examples
|
|
"""
|
|
)
|
|
|
|
parser.add_argument(
|
|
'--directory',
|
|
required=True,
|
|
help='Directory to analyze'
|
|
)
|
|
parser.add_argument(
|
|
'--output',
|
|
default='output/codebase/',
|
|
help='Output directory (default: output/codebase/)'
|
|
)
|
|
parser.add_argument(
|
|
'--depth',
|
|
choices=['surface', 'deep', 'full'],
|
|
default='deep',
|
|
help='Analysis depth (default: deep)'
|
|
)
|
|
parser.add_argument(
|
|
'--languages',
|
|
help='Comma-separated languages to analyze (e.g., Python,JavaScript,C++)'
|
|
)
|
|
parser.add_argument(
|
|
'--file-patterns',
|
|
help='Comma-separated file patterns (e.g., *.py,src/**/*.js)'
|
|
)
|
|
parser.add_argument(
|
|
'--skip-api-reference',
|
|
action='store_true',
|
|
default=False,
|
|
help='Skip API reference markdown documentation generation (default: enabled)'
|
|
)
|
|
parser.add_argument(
|
|
'--skip-dependency-graph',
|
|
action='store_true',
|
|
default=False,
|
|
help='Skip dependency graph and circular dependency detection (default: enabled)'
|
|
)
|
|
parser.add_argument(
|
|
'--skip-patterns',
|
|
action='store_true',
|
|
default=False,
|
|
help='Skip design pattern detection (Singleton, Factory, Observer, etc.) (default: enabled)'
|
|
)
|
|
parser.add_argument(
|
|
'--skip-test-examples',
|
|
action='store_true',
|
|
default=False,
|
|
help='Skip test example extraction (instantiation, method calls, configs, etc.) (default: enabled)'
|
|
)
|
|
parser.add_argument(
|
|
'--skip-ai-enhancement',
|
|
action='store_true',
|
|
default=False,
|
|
help='Skip AI enhancement of patterns and test examples (default: enabled, C3.6)'
|
|
)
|
|
parser.add_argument(
|
|
'--no-comments',
|
|
action='store_true',
|
|
help='Skip comment extraction'
|
|
)
|
|
parser.add_argument(
|
|
'--verbose',
|
|
action='store_true',
|
|
help='Enable verbose logging'
|
|
)
|
|
|
|
# Check for deprecated flags
|
|
deprecated_flags = {
|
|
'--build-api-reference': '--skip-api-reference',
|
|
'--build-dependency-graph': '--skip-dependency-graph',
|
|
'--detect-patterns': '--skip-patterns',
|
|
'--extract-test-examples': '--skip-test-examples'
|
|
}
|
|
|
|
for old_flag, new_flag in deprecated_flags.items():
|
|
if old_flag in sys.argv:
|
|
logger.warning(f"⚠️ DEPRECATED: {old_flag} is deprecated. "
|
|
f"All features are now enabled by default. "
|
|
f"Use {new_flag} to disable this feature.")
|
|
|
|
args = parser.parse_args()
|
|
|
|
# Set logging level
|
|
if args.verbose:
|
|
logging.getLogger().setLevel(logging.DEBUG)
|
|
|
|
# Validate directory
|
|
directory = Path(args.directory)
|
|
if not directory.exists():
|
|
logger.error(f"Directory not found: {directory}")
|
|
return 1
|
|
|
|
if not directory.is_dir():
|
|
logger.error(f"Not a directory: {directory}")
|
|
return 1
|
|
|
|
# Parse languages
|
|
languages = None
|
|
if args.languages:
|
|
languages = [lang.strip() for lang in args.languages.split(',')]
|
|
|
|
# Parse file patterns
|
|
file_patterns = None
|
|
if args.file_patterns:
|
|
file_patterns = [p.strip() for p in args.file_patterns.split(',')]
|
|
|
|
# Analyze codebase
|
|
try:
|
|
results = analyze_codebase(
|
|
directory=directory,
|
|
output_dir=Path(args.output),
|
|
depth=args.depth,
|
|
languages=languages,
|
|
file_patterns=file_patterns,
|
|
build_api_reference=not args.skip_api_reference,
|
|
extract_comments=not args.no_comments,
|
|
build_dependency_graph=not args.skip_dependency_graph,
|
|
detect_patterns=not args.skip_patterns,
|
|
extract_test_examples=not args.skip_test_examples,
|
|
enhance_with_ai=not args.skip_ai_enhancement
|
|
)
|
|
|
|
# Print summary
|
|
print(f"\n{'='*60}")
|
|
print(f"CODEBASE ANALYSIS COMPLETE")
|
|
print(f"{'='*60}")
|
|
print(f"Files analyzed: {len(results['files'])}")
|
|
print(f"Output directory: {args.output}")
|
|
if args.build_api_reference:
|
|
print(f"API reference: {Path(args.output) / 'api_reference'}")
|
|
print(f"{'='*60}\n")
|
|
|
|
return 0
|
|
|
|
except KeyboardInterrupt:
|
|
logger.error("\nAnalysis interrupted by user")
|
|
return 130
|
|
except Exception as e:
|
|
logger.error(f"Analysis failed: {e}")
|
|
import traceback
|
|
traceback.print_exc()
|
|
return 1
|
|
|
|
|
|
if __name__ == '__main__':
|
|
sys.exit(main())
|