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in this tutorial, we will delve into the concept of generic types in python. generic types allow us to write code that is flexible and reusable across different data types while still maintaining type safety. we'll explore how to define generic types, utilize them in functions and classes, and understand their significance in python programming.
generic types, also known as generics, are a way to define functions, classes, or data structures that can operate on multiple data types. they provide flexibility without sacrificing type safety, as they allow us to write code that is abstracted over specific data types.
python introduced support for generics in version 3.5 through the typing module, providing a way to annotate functions and classes with type hints that can handle generic types.
generic types are defined using type variables, which are placeholders for actual types. these type variables are typically represented by single uppercase letters, such as t, u, v, etc.
in python's typing module, the typevar function is used to declare type variables. let's see an example:
in the above example:
generic types can be used in functions, classes, and type aliases to create reusable and type-safe code.
generic types in python, introduced with the typing module, allow us to write flexible and reusable code while ensuring type safety. by using type variables and annotations, we can create functions, classes, and data structures that work seamlessly with different data types. this enhances code readability, maintainability, and reduces the likelihood of runtime errors related to type mismatches.
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