import json
from typing import List, Optional
from pydantic import BaseModel, Field, EmailStr, ValidationError

# --- Simplified Class Definition using Pydantic ---

class Relation(BaseModel):
    """A Pydantic model for a single relation."""
    citizen_id: str = Field(..., min_length=1)
    relation_type: str = Field(..., min_length=1)

class Customer(BaseModel):
    """
    A simplified and robust class to represent a customer using Pydantic.
    Validation is handled automatically based on type hints.
    """
    # Attributes with validation rules
    name: str = Field(..., min_length=1, description="Customer's full name.")
    birth: int = Field(..., gt=0, description="Customer's birth must be a positive number.")
    current_position: str = Field(..., min_length=1)
    # citizen_id: str = Field(..., min_length=12, max_length=12)
    email: EmailStr # Automatic email format validation
    # phone: str = Field(..., pattern=r'^\+?[0-9]{9,15}$', description="Phone number with country code.")
    
    # Optional list of relations
    relations: List[Relation] = []

    def save(self, filepath: str = "customers.jsonl"):
        """
        Saves the customer data to a JSONL file.
        Each customer is appended as a new line.
        """
        try:
            with open(filepath, 'a', encoding='utf-8') as f:
                # Pydantic has a built-in method to dump the model to a JSON string
                f.write(self.model_dump_json() + '\n')
            print(f"✅ Successfully saved customer '{self.name}' to {filepath}")
        except IOError as e:
            print(f"❌ Error saving file: {e}")
    
    def as_string(self) -> str:
        """Returns the customer data as a formatted string."""
        return f"""
        Customer Information:
        Name: {self.name}
        Birth: {self.birth}
        Position: {self.current_position}
        Email: {self.email}
        Phone: {self.phone}
        Relations:
        {self.relations}
        """

# --- Example Usage ---

# 1. Creating a valid customer
print("--- Attempting to create a valid customer ---")
try:
    valid_customer = Customer(
        name="Đảng Cộng sản Việt Nam",
        birth=1930,
        current_position="Đảng cầm quyền và là chính đảng duy nhất được phép hoạt động tại Việt Nam",
        email="ngjabach@example.com",
    )
    print("Customer created successfully:")
    print(valid_customer)
    
    # Save the customer to a file
    valid_customer.save()

except ValidationError as e:
    print("Validation Error:", e)

print("\n" + "="*50 + "\n")

# 2. Creating an invalid customer (bad email and age)
# print("--- Attempting to create an invalid customer ---")
# try:
#     invalid_customer = Customer(
#         name="Trần Thị Bình",
#         age=-5, # Invalid: age must be > 0
#         current_position="Project Manager",
#         citizen_id="098765432109",
#         email="tran.binh@", # Invalid: not a valid email format
#         phone="123", # Invalid: does not match pattern
#         relations=[]
#     )
# except ValidationError as e:
#     print("❌ Caught expected validation errors:")
#     print(e)