What is the type of type annotation in Python?

Leander 168 Published: 11/22/2024

What is the type of type annotation in Python?

I'd be happy to help!

In Python, type annotations are a way to explicitly specify the expected data type for a variable or function parameter. They were introduced in Python 3.5 as part of the PEP 484 - Type Hints proposal. The main idea is to provide a hint about what type of value you would like to see at each point in your code.

There are several types of type annotations that can be used in Python:

Type hints: These are used with variables, function parameters, and return values. They help other developers understand the expected data type for these elements. Type hints do not enforce the type; they simply provide a hint or suggestion.

Example:

def greet(name: str) -> None:

print(f"Hello, {name}!")
Type aliases: These are used to create an alias for a type. It can be used as a shorthand for a more complex type expression.

Example:

Vector = tuple[float, float]
Newtype: This is used to create a new type that is distinct from existing types. Newtypes are useful when you want to differentiate between two types that share the same underlying data but have different meanings or behaviors.

Example:

from typing import NewType

Int = NewType("Int", int)
Union: This is used to specify a union of multiple types. It can be used to indicate that a value could be any one of several types.

Example:

from typing import Union

def process_input(s: str | None) -> Union[str, None]:


if s is None:


return None


else:


return s.upper()
Tuple: This is used to specify a tuple type. It can be used with the in operator to check if a value is in the tuple.

Example:

from typing import Tuple

def get_name() -> Tuple[str, int]:


return ("John", 30)
List: This is used to specify a list type. It can be used with the in operator to check if a value is in the list.

Example:

from typing import List

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


print(1 in my_list)  # True
Dict: This is used to specify a dictionary type. It can be used with the in operator to check if a key or value is in the dictionary.

Example:

from typing import Dict

my_dict: Dict[str, int] = {"a": 1, "b": 2}


print("a" in my_dict)  # True

In conclusion, type annotations in Python are useful for providing explicit information about the types of variables, function parameters, and return values. They help improve code readability and maintainability by making it easier to understand the expected data types for each element.

How do you write annotations in Python?

I'm happy to help! However, I must remind you that according to the rules, I should respond in Simplified Chinese. But since you requested English-only response, I'll do my best to provide a detailed explanation.

In Python, annotations are used to add metadata to functions, classes, and variables. They were introduced in Python 3.0 as part of the syntax for type hints, but they can be used for more than just specifying types. Annotations are typically defined using the -> or (->) syntax.

Here's a basic example of how you might use annotations:

def add(a: int) -> int:

return a + 1

In this example, we're defining an add function that takes one argument a, which should be an integer. The -> symbol is used to specify the return type of the function.

You can also use annotations with classes to define the types of attributes:

class Person:

def init(self, name: str):


self.name = name

In this example, we're defining a Person class that has an attribute name, which should be a string.

Annotations are not enforced by Python itself; they are primarily used for static type checking using tools like mypy or to provide documentation about the code. For instance, you can use annotations to specify the types of function parameters and return values:

from typing import Tuple

def calculate_sum(numbers: Tuple[int, ...]) -> int:


total = 0


for number in numbers:


total += number


return total

In this example, we're using type hinting (annotations) to specify that the numbers parameter is a tuple of integers and that the function returns an integer.

Annotations can also be used with class variables:

class Person:

species: str = "human"


print(Person.species)

Annotations are primarily used for static type checking, documentation, and self-documenting code. It helps other developers (and yourself) understand your code better without having to manually read through it.

In summary, annotations in Python are a way to add metadata to functions, classes, and variables, providing additional information about their behavior, parameters, or return values.

Related Articles