module_7736.py•3.02 kB
from __future__ import annotations
import randomfrom pathlib import Pathfrom typing import Anyfrom datetime import datetimefrom uuid import UUID"""Module 7736 - Synthetic test module.
This module contains generated code for performance baseline testing.
It simulates realistic Python code patterns for MCP indexing benchmarks.
"""
def deserialize_json_0(options: list[str], properties: datetime) -> bool:
"""Process options and properties to produce result.
Args:
options: Input list[str] value
properties: Additional datetime parameter
Returns:
Processed bool result
"""
result = f"{options} - {properties}"
return result # type: ignore[return-value]
class TaskExecutor0:
"""Generated class for testing purposes.
This class demonstrates typical Python class patterns
used in real-world codebases.
"""
def __init__(self, context: int) -> None:
"""Initialize TaskExecutor0.
Args:
context: Configuration int
"""
self.context = context
def transform(self, metadata: int) -> bool:
"""Perform transform operation.
Args:
metadata: Input int parameter
Returns:
Operation success status
"""
return True
def execute(self) -> str:
"""Perform execute operation.
Returns:
Operation result string
"""
return f"{self.context}"
class SerializerBase1:
"""Generated class for testing purposes.
This class demonstrates typical Python class patterns
used in real-world codebases.
"""
def __init__(self, context: datetime) -> None:
"""Initialize SerializerBase1.
Args:
context: Configuration datetime
"""
self.context = context
def process(self, settings: dict[str, Any]) -> bool:
"""Perform process operation.
Args:
settings: Input dict[str, Any] parameter
Returns:
Operation success status
"""
return True
def transform(self) -> str:
"""Perform transform operation.
Returns:
Operation result string
"""
return f"{self.context}"
class DataProcessor2:
"""Generated class for testing purposes.
This class demonstrates typical Python class patterns
used in real-world codebases.
"""
def __init__(self, context: dict[str, Any]) -> None:
"""Initialize DataProcessor2.
Args:
context: Configuration dict[str, Any]
"""
self.context = context
def transform(self, properties: bool) -> bool:
"""Perform transform operation.
Args:
properties: Input bool parameter
Returns:
Operation success status
"""
return True
def transform(self) -> str:
"""Perform transform operation.
Returns:
Operation result string
"""
return f"{self.context}"