Summary  
It demonstrates how to determine a variable’s data type using the `type()` function, showing that arithmetic operations can produce floats even when the result appears to be an integer.

General domain of usage  
numeric computation

We've previously come across float and integer types, so now we can tell whether a value is a __float__ or an __integer__. Can you guess what the result of the math operation `6/1.5` might be? It's easy to calculate that it equals `4`, but what type does `4` belong to? It might seem like an integer, but it's actually a float. To confirm its type, you can use the `type()` function.

variable = 6/1.5
print(variable)
print(type(variable))

import unittest
from contextlib import redirect_stdout
import io
import importlib


class TestUserCode(unittest.TestCase):
    def test_number1_declared(self):
        self._testMethodName = 'number1 is declared'
        import user_code
        self.assertTrue(hasattr(user_code, 'number1'), "Expected number1 to be defined.")

    def test_number1_is_float(self):
        self._testMethodName = 'number1 is of type float'
        import user_code
        self.assertTrue(hasattr(user_code, 'number1'), "Expected number1 to be defined.")
        self.assertIsInstance(user_code.number1, float, f"Expected number1 to be a float, but got {type(user_code.number1).__name__}.")

    def test_number2_declared(self):
        self._testMethodName = 'number2 is declared'
        import user_code
        self.assertTrue(hasattr(user_code, 'number2'), "Expected number2 to be defined.")

    def test_number2_is_int(self):
        self._testMethodName = 'number2 is of type int'
        import user_code
        self.assertTrue(hasattr(user_code, 'number2'), "Expected number2 to be defined.")
        self.assertIsInstance(user_code.number2, int, f"Expected number2 to be a int, but got {type(user_code.number2).__name__}.")

    def test_type_number1_printed(self):
        self._testMethodName = "The type of number1 is <class 'float'> is printed"
        output = self._runcode_output()
        self.assertIn("number1 is <class 'float'>", output, "Expected the output to contain 'The type of number1 is <class \'float\'>'")

    def test_type_number2_printed(self):
        self._testMethodName = "The type of number2 is <class 'int'> is printed"
        output = self._runcode_output()
        self.assertIn("is <class 'int'>", output, "Expected the output to contain 'The type of number2 is <class \'float\'>'")
    
    def _runcode_output(self):
        import user_code
        f = io.StringIO()
        with redirect_stdout(f):
            importlib.reload(user_code)
        s = f.getvalue().strip()
        return s
if __name__ == '__main__':
    unittest.main()

test_main.py

Gain a solid understanding of Python's core data types and learn how to work with them effectively. Explore numbers, booleans, and strings through hands-on exercises and practical examples. Build confidence in performing basic operations and develop the foundational skills needed to write clean and efficient Python code.

Discover the essentials of numerical data types in Python and learn how to work with integers and floating-point numbers. Master basic arithmetic operations, explore the concept of immutability, and get hands-on experience using Python's built-in functions and tools to handle numbers efficiently in real-world scenarios.

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Learn how to handle data types effectively to ensure accuracy and consistency in your programs. Convert values to the appropriate type, clean text before comparison, and separate numeric operations from text formatting. You'll also discover how to manage missing data deliberately and handle human-readable text differently from raw input, achieving reliable, consistent, and easy-to-read results.

How to Define a Type

解答