Python 3 and static typing смотреть онлайн

Python is a popular programming language known for its simplicity, readability, and dynamic typing system. However, in recent versions of Python, static typing has been introduced to improve code quality, maintainability, and catch errors at an earlier stage. This tutorial will provide you with a comprehensive introduction to Python 3 and static typing, including code examples to help you get started.
In static typing, variables are declared with explicit data types at compile-time, and the data types are checked for correctness before the program is executed. This is in contrast to dynamic typing, where variable types are determined at runtime.
Python introduced static typing via the typing module and type hinting. Type hinting allows you to declare the expected types of variables, function arguments, and return values, making your code more self-documenting and enabling tools like linters and IDEs to provide better code analysis.
Before we dive into static typing, you need to have Python 3.5 or later installed on your system. If you haven't already, you can download and install Python from the official Python website.
To add type hints to your Python code, you use type annotations. These annotations provide information about the expected data type of a variable or function argument. Here's how you can use type annotations:
In the example above, we've annotated a variable x with the int type and defined a function add that takes two arguments, both of which are annotated as int, and returns an int.
To check your code for type correctness, you can use the mypy tool, which is a popular static type checker for Python. Install mypy using pip:
Once installed, you can run mypy on your Python code to find type-related issues:
If your code has no type errors, mypy will produce no output. If there are issues, it will provide detailed error messages to help you identify and fix them.
Here are some common type annotations you can use in your Python code:
Here's an example that demonstrates these annotations:
In this example, process_data takes a list of elements that can be either integers or strings and returns a list of integers.
You can also use type hints in class definitions. Here's an example: