Codebase MCP Server

#!/usr/bin/env python3 """Generate deterministic test repository for baseline performance testing. Creates a test repository with N Python files containing realistic code patterns for benchmarking the MCP server's indexing and search performance. Usage: python scripts/generate_test_repo.py --files 100 --output test_repos/baseline_repo Constitutional Compliance: - Principle VIII: Type Safety (mypy --strict compliance) - Principle V: Production Quality (comprehensive error handling) """ from __future__ import annotations import argparse import random import sys from pathlib import Path from typing import Final # ============================================================================== # Constants # ============================================================================== SEED: Final[int] = 42 MIN_LINES_PER_FILE: Final[int] = 50 MAX_LINES_PER_FILE: Final[int] = 100 # Sample code templates for deterministic generation CLASS_NAMES: Final[list[str]] = [ "DataProcessor", "FileHandler", "ConfigManager", "APIClient", "CacheManager", "LoggerFactory", "ValidationEngine", "SerializerBase", "ConnectionPool", "TaskExecutor", ] FUNCTION_NAMES: Final[list[str]] = [ "process_data", "validate_input", "transform_output", "fetch_resource", "parse_config", "serialize_object", "deserialize_json", "calculate_metrics", "cleanup_resources", "initialize_service", ] METHOD_NAMES: Final[list[str]] = [ "setup", "teardown", "validate", "execute", "process", "transform", "serialize", "deserialize", "connect", "disconnect", ] PARAM_NAMES: Final[list[str]] = [ "data", "config", "options", "context", "payload", "metadata", "parameters", "settings", "attributes", "properties", ] TYPE_HINTS: Final[list[str]] = [ "str", "int", "bool", "dict[str, Any]", "list[str]", "Path", "datetime", "UUID", ] # ============================================================================== # Code Generation Functions # ============================================================================== def generate_module_docstring(module_num: int) -> str: """Generate a module-level docstring. Args: module_num: Module number for deterministic content Returns: Module docstring with description """ return f'''"""Module {module_num:04d} - Synthetic test module. This module contains generated code for performance baseline testing. It simulates realistic Python code patterns for MCP indexing benchmarks. """ ''' def generate_function(func_idx: int, rng: random.Random) -> str: """Generate a standalone function with type hints. Args: func_idx: Function index for deterministic naming rng: Random number generator for deterministic choices Returns: Complete function definition as string """ func_name = rng.choice(FUNCTION_NAMES) param1 = rng.choice(PARAM_NAMES) param2 = rng.choice(PARAM_NAMES) type1 = rng.choice(TYPE_HINTS) type2 = rng.choice(TYPE_HINTS) return_type = rng.choice(TYPE_HINTS) return f''' def {func_name}_{func_idx}({param1}: {type1}, {param2}: {type2}) -> {return_type}: """Process {param1} and {param2} to produce result. Args: {param1}: Input {type1} value {param2}: Additional {type2} parameter Returns: Processed {return_type} result """ result = f"{{{param1}}} - {{{param2}}}" return result # type: ignore[return-value] ''' def generate_class(class_idx: int, rng: random.Random) -> str: """Generate a class with methods and type hints. Args: class_idx: Class index for deterministic naming rng: Random number generator for deterministic choices Returns: Complete class definition as string """ class_name = rng.choice(CLASS_NAMES) method1 = rng.choice(METHOD_NAMES) method2 = rng.choice(METHOD_NAMES) param1 = rng.choice(PARAM_NAMES) param2 = rng.choice(PARAM_NAMES) type1 = rng.choice(TYPE_HINTS) type2 = rng.choice(TYPE_HINTS) return f''' class {class_name}{class_idx}: """Generated class for testing purposes. This class demonstrates typical Python class patterns used in real-world codebases. """ def __init__(self, {param1}: {type1}) -> None: """Initialize {class_name}{class_idx}. Args: {param1}: Configuration {type1} """ self.{param1} = {param1} def {method1}(self, {param2}: {type2}) -> bool: """Perform {method1} operation. Args: {param2}: Input {type2} parameter Returns: Operation success status """ return True def {method2}(self) -> str: """Perform {method2} operation. Returns: Operation result string """ return f"{{self.{param1}}}" ''' def generate_python_file(file_num: int, target_lines: int) -> str: """Generate a complete Python file with specified line count. Args: file_num: File number for deterministic content target_lines: Target number of lines (approximate) Returns: Complete Python file content """ # Use seeded random for determinism rng = random.Random(SEED + file_num) lines: list[str] = [] # Add imports lines.append("from __future__ import annotations\n") lines.append("") lines.append("import random") lines.append("from pathlib import Path") lines.append("from typing import Any") lines.append("from datetime import datetime") lines.append("from uuid import UUID") lines.append("") # Add module docstring lines.append(generate_module_docstring(file_num)) lines.append("") current_lines = len(lines) # Generate functions and classes to reach target line count func_idx = 0 class_idx = 0 while current_lines < target_lines: if rng.random() < 0.5: # Generate function func_code = generate_function(func_idx, rng) lines.append(func_code) func_idx += 1 current_lines += func_code.count("\n") else: # Generate class class_code = generate_class(class_idx, rng) lines.append(class_code) class_idx += 1 current_lines += class_code.count("\n") return "".join(lines) def create_test_repository(output_dir: Path, num_files: int) -> None: """Create test repository with specified number of files. Args: output_dir: Output directory path num_files: Number of Python files to generate Raises: OSError: If directory creation or file writing fails """ # Create output directory output_dir.mkdir(parents=True, exist_ok=True) # Use seeded random for line counts rng = random.Random(SEED) print(f"Generating {num_files} Python files in {output_dir}...") for i in range(num_files): # Deterministic line count between MIN_LINES and MAX_LINES target_lines = rng.randint(MIN_LINES_PER_FILE, MAX_LINES_PER_FILE) # Generate file content content = generate_python_file(i, target_lines) # Write file file_path = output_dir / f"module_{i:04d}.py" file_path.write_text(content, encoding="utf-8") # Progress indicator every 10 files if (i + 1) % 10 == 0: print(f" Generated {i + 1}/{num_files} files...") print(f"\nCompleted! Generated {num_files} files in {output_dir}") print(f"Total size: {sum(f.stat().st_size for f in output_dir.glob('*.py')) / 1024:.1f} KB") # ============================================================================== # CLI Entry Point # ============================================================================== def parse_args() -> argparse.Namespace: """Parse command-line arguments. Returns: Parsed arguments namespace """ parser = argparse.ArgumentParser( description="Generate deterministic test repository for performance baselines", formatter_class=argparse.ArgumentDefaultsHelpFormatter, ) parser.add_argument( "--files", type=int, default=100, help="Number of Python files to generate", ) parser.add_argument( "--output", type=Path, default=Path("test_repos/baseline_repo"), help="Output directory path", ) return parser.parse_args() def main() -> int: """Main entry point. Returns: Exit code (0 for success, 1 for failure) """ try: args = parse_args() # Validate arguments if args.files <= 0: print("Error: --files must be positive", file=sys.stderr) return 1 # Create test repository create_test_repository(args.output, args.files) return 0 except KeyboardInterrupt: print("\nInterrupted by user", file=sys.stderr) return 1 except Exception as e: print(f"Error: {e}", file=sys.stderr) return 1 if __name__ == "__main__": sys.exit(main())