#!/usr/bin/env python3
"""Example demonstrating common LLM coding errors that MCP Pyrefly catches."""
# Example 1: Type error
def process_user_id(user_id: str) -> dict:
"""Process a user ID and return user data."""
return {"id": user_id, "name": f"User {user_id}"}
# LLM often makes this mistake - passing wrong type
# result = process_user_id(12345) # ERROR: Expected str, got int
# Example 2: Naming inconsistency
def get_user_data(user_id: str) -> dict:
"""Get user data from database."""
# Imagine this is a database call
return {"id": user_id, "name": "John Doe"}
# Later in the code, LLM uses different naming convention
# This is a common LLM error - inconsistent naming
# user_info = getUserData("123") # Should be get_user_data
# Example 3: Another common pattern - mixing naming styles
class UserManager:
def fetch_user(self, id: str) -> dict:
return get_user_data(id)
# LLM might later add this method with inconsistent naming
# def fetchUserById(self, id: str) -> dict: # Should be fetch_user_by_id
# return self.fetch_user(id)
# Example 4: Parameter order confusion
def create_user(name: str, email: str, age: int) -> dict:
return {"name": name, "email": email, "age": age}
# LLM might mix up parameter order
# new_user = create_user("john@example.com", "John Doe", 25) # Wrong order!
# Example 5: Return type mismatch
def calculate_total(items: list[float]) -> int:
# Bug: Returning float but declared return type is int
return sum(items) * 1.1 # This will be a float!
if __name__ == "__main__":
# Correct usage examples
user = process_user_id("123")
print(f"User: {user}")
data = get_user_data("456")
print(f"Data: {data}")
manager = UserManager()
fetched = manager.fetch_user("789")
print(f"Fetched: {fetched}")
# This would be caught by Pyrefly
# total = calculate_total([10.0, 20.0, 30.0]) # Return type error
