Challenge: Type-Enforced Data Model

You are building a reusable validation layer for a financial data model. Your task is to implement a descriptor hierarchy and apply it to two classes.

1. Implement a base class Validator with:

   • __set_name__(self, owner, name) that stores the attribute name in self._name;
   • __get__(self, obj, objtype=None) that returns self when obj is None, otherwise returns obj.__dict__.get(self._name);
   • __set__(self, obj, value) that calls self.validate(self._name, value) and then stores the value in obj.__dict__[self._name];
   • an abstract validate(self, name, value) method that raises NotImplementedError.

2. Implement PositiveFloat(Validator) whose validate raises ValueError if value is not a positive int or float.

3. Implement NonEmptyString(Validator) whose validate raises ValueError if value is not a non-empty string after stripping whitespace.

4. Apply the descriptors to the following two classes:

    class Trade:
        # ticker: NonEmptyString
        # quantity: PositiveFloat
        # price: PositiveFloat
        def __init__(self, ticker, quantity, price):
            self.ticker = ticker
            self.quantity = quantity
            self.price = price
    
    class Account:
        # account_id: NonEmptyString
        # balance: PositiveFloat
        def __init__(self, account_id, balance):
            self.account_id = account_id
            self.balance = balance
   

5. Create a Trade instance called trade with ticker="AAPL", quantity=50.0, price=189.50.

6. Create an Account instance called account with account_id="ACC-001", balance=10000.0.

7. Print trade.ticker, trade.quantity, account.account_id, and account.balance.