214. Type Erasure in Python

🔹 1. Type Hints Are Erased at Runtime

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from typing import List

def process_data(data: List[int]):
    print(f"Received: {data}")

print(process_data.__annotations__)
# Output: {'data': typing.List[int]} (Only visible in annotations, not enforced)

🔍 Key Takeaway:

• List[int] does not exist at runtime—only List is used.

• Type hints are stored in __annotations__, but Python does not enforce them.

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🔹 2. Generic Type Arguments Are Not Retained

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from typing import List

lst: List[int] = [1, 2, 3]

print(type(lst))  # <class 'list'> (No int information retained)

🔍 Key Takeaway:

• List[int] becomes just list at runtime—type information is erased.

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🔹 3. Checking If a Variable is a List (Without Type Info)

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from typing import List

def check_type(data: List[int]):
    print(isinstance(data, list))  # True

check_type([1, 2, 3])

🔍 Key Takeaway:

• List[int] is completely erased at runtime, so we only check for list.

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🔹 4. Type Erasure in Function Parameters

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from typing import List

def process_numbers(numbers: List[int]):
    print(type(numbers))  # <class 'list'>

process_numbers(["hello", "world"])  # No error at runtime!

🔍 Key Takeaway:

• Even though List[int] is specified, Python allows List[str] at runtime.

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🔹 5. Type Erasure with Custom Generics

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from typing import TypeVar, Generic

T = TypeVar("T")

class Box(Generic[T]):
    def __init__(self, value: T):
        self.value = value

b = Box(42)
print(type(b))  # <class '__main__.Box'> (No int info retained)

🔍 Key Takeaway:

• Generic parameters (T) are erased, so Box[int] is just Box at runtime.

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🔹 6. Type Annotations vs. Actual Behavior

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from typing import List

def process_list(lst: List[str]):
    return lst[0].upper()  # Assumes str

print(process_list([1, 2, 3]))  # No type error! Returns '1'

🔍 Key Takeaway:

• Python does not enforce type hints at runtime; they are just for static checks.

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🔹 7. Checking a Type Using __orig_bases__

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from typing import Generic, TypeVar

T = TypeVar("T")

class CustomList(Generic[T]):
    pass

obj = CustomList[int]()
print(obj.__class__.__orig_bases__)  
# Output: (Generic[int],)  (Shows original type argument)

🔍 Key Takeaway:

• While type arguments are erased, they can be accessed using __orig_bases__.

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🔹 8. Type Erasure in Subclassing

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from typing import List

class MyList(List[int]):
    pass

obj = MyList()
print(isinstance(obj, list))  # True
print(isinstance(obj, List[int]))  # TypeError: Subscripted generics cannot be used with isinstance()

🔍 Key Takeaway:

• List[int] cannot be used with isinstance(), as it's erased at runtime.

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🔹 9. Recovering Type Information Using get_type_hints()

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from typing import List, get_type_hints

class Example:
    def method(self, values: List[int]) -> None:
        pass

hints = get_type_hints(Example.method)
print(hints)  # {'values': typing.List[int], 'return': None}

🔍 Key Takeaway:

• get_type_hints() lets us recover erased type information.

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🔹 10. Type Checking Using isinstance() with typing Types (Fails)

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from typing import List

lst = [1, 2, 3]
print(isinstance(lst, List))  # TypeError: 'List' is not a class

🔍 Key Takeaway:

• List[int] cannot be used in isinstance() checks—only list works.

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🚀 Summary: Type Erasure in Python

Concept

Description

Type Hints Are Ignored at Runtime

Python does not enforce type hints during execution.

Generic Types Become Their Base Type

List[int] becomes just list.

No Type Checking for Function Arguments

Python allows mismatched types at runtime.

Type Information Can Be Retrieved

Use __annotations__ or get_type_hints().

Cannot Use isinstance() with List[int]

It raises an error—use list instead.

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🚀 Best Practices

✅ Use Type Hints for Readability, Not Enforcement ✅ Use Static Type Checkers (e.g., mypy) for Catching Errors ✅ Remember That Generics Are Erased at Runtime ✅ Use get_type_hints() for Type Introspection