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Type hints in Python provide a way to indicate the expected types of parameters and return values in function signatures. While Python is dynamically typed, type hints can enhance code readability, facilitate code analysis, and help catch potential errors early. In this tutorial, we will explore the basics of using type hints in Python functions with code examples.
Type hints are annotations added to function parameters and return values using the - syntax. You can use various types such as built-in types, user-defined classes, and generic types.
In this example:
Type hints are optional, and Python will not enforce them at runtime. They are mainly for documentation and development tools. To access the type hints programmatically, you can use the _annotations_ attribute of the function.
When using default parameter values, type hints should be placed after the : but before the =.
In this example, times: int = 2 indicates that the default value for the times parameter is 2, and its type is int.
Type hints can also be applied to elements in collections such as lists, tuples, and dictionaries.
Here, List[int] indicates a list of integers, and Dict[str, int] indicates a dictionary with string keys and integer values.
Type hints can be generic, allowing you to indicate that a function works with multiple types.
In this example, TypeVar('T') is used to define a generic type, and List[T] indicates a list of elements of type T.
Type hints in Python provide a way to add optional static typing to your code, improving documentation and enabling better tooling support. While not enforced at runtime, type hints can be checked using tools like MyPy. Use type hints judiciously to strike a balance between code readability and the benefits of static typing.
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