Delete analyze_code_style.py
Browse files- analyze_code_style.py +0 -139
analyze_code_style.py
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from typing import Dict, Any, List, Tuple, Iterator
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import json
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from prompt_analyzer import create_handler
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def analyze_code_style(sources_data: Dict[str, Any]) -> Dict[str, Any]:
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"""Analyzes developer's coding style patterns for stylometric analysis"""
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handler = create_handler()
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combined_results = {}
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for repo_name, repo_data in sources_data.items():
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print(f"\nAnalyzing repository: {repo_name}")
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prompt = f"""
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CODE STYLE ANALYSIS
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You are an expert in code stylometry and developer behavior analysis. Analyze this repository to create a detailed profile of the developer's coding patterns, preferences, and habits.
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Repository: {repo_name}
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Code samples and structure:
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{json.dumps(repo_data, indent=2)}
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Focus on identifying unique, individual coding patterns that could distinguish this developer's style. Analyze how they:
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- Structure their code and control flow
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- Handle data and state
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- Approach problem-solving
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- Maintain code quality
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- Handle edge cases and errors
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IMPORTANT CONSTRAINTS:
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- Maximum 10 patterns per list category
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- No repeating similar patterns
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- Use "Unknown" if pattern cannot be determined
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- Focus on distinctive, personal coding traits
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Generate a JSON profile with this EXACT structure:
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{{
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"code_organization": {{
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"file_structure": {{
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"preferred_file_size": number, // Average lines per file
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"module_organization": string, // e.g. "feature-based", "layer-based", "domain-based"
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"separation_patterns": [string] // Common ways they separate concerns
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}},
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"code_layout": {{
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"indentation": {{ "type": string, "width": number }},
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"line_length": {{ "average": number, "max_observed": number }},
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"spacing_style": {{
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"around_operators": string,
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"after_commas": boolean,
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"around_blocks": string
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}}
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}}
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}},
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"naming_patterns": {{
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"variables": {{
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"primary_style": string, // e.g. "snake_case", "camelCase"
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"consistency_score": number, // 0-100
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"length_preference": {{ "average": number, "range": [number, number] }},
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"semantic_patterns": [string] // How they choose names, e.g. "verb_noun_pairs", "hungarian_notation"
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}},
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"functions": {{
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"primary_style": string,
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"common_prefixes": [string],
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"common_patterns": [string],
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"length_preference": {{ "average": number, "range": [number, number] }}
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}}
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}},
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"coding_patterns": {{
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"control_flow": {{
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"preferred_loop_type": string, // e.g. "for", "while", "comprehension"
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"nesting_depth": {{ "average": number, "max_observed": number }},
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"branching_patterns": [string], // e.g. "early returns", "guard clauses"
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"condition_complexity": {{ "average": number, "max_observed": number }}
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}},
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"data_handling": {{
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"preferred_structures": [string], // Favorite data structures
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"mutation_patterns": {{
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"prefers_immutable": boolean,
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"common_patterns": [string]
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}},
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"state_management": {{
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"approach": string, // e.g. "functional", "stateful", "mixed"
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"patterns": [string]
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}}
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}}
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}},
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"error_handling": {{
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"strategy": string, // e.g. "defensive", "fail-fast", "hybrid"
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"patterns": [string], // Common error handling patterns
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"error_checking": {{
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"input_validation": boolean,
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"null_checking": boolean,
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"type_checking": boolean
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}}
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}},
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"code_quality": {{
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"documentation": {{
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"style": string, // e.g. "detailed", "minimal", "moderate"
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"coverage_ratio": number, // 0-100
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"preferred_formats": [string]
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}},
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"testing": {{
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"approach": string, // e.g. "unit-heavy", "integration-focused", "minimal"
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"patterns": [string]
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}},
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"complexity_metrics": {{
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"cyclomatic_complexity": {{ "average": number, "max_observed": number }},
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"cognitive_complexity": {{ "average": number, "max_observed": number }}
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}}
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}},
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"distinctive_traits": {{
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"unique_patterns": [string], // Highly individual coding patterns
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"favored_techniques": [string], // Preferred coding approaches
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"consistent_habits": [string] // Reliable behavioral patterns
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}}
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}}
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Critical requirements:
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1. OUTPUT ONLY VALID JSON
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2. NO markdown, NO comments, NO explanations
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3. Use EXACT key names shown
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4. All arrays MAXIMUM 10 items
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5. Use numbers for metrics where specified
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6. Use "Unknown" for undeterminable values
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"""
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try:
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result = handler.generate_json_response(prompt)
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if result:
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combined_results[repo_name] = result
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except Exception as e:
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print(f"Error analyzing {repo_name}: {str(e)}")
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combined_results[repo_name] = {"error": str(e)}
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return combined_results
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