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Python Advanced Concepts
Python Advanced Concepts
Using Assertions
In Python, the assert statement is a built-in feature designed to verify that specific conditions are true within your code. It serves as a sanity check, confirming that certain prerequisites are met at specific points during program execution.
The syntax for the assert statement is as follows:
In Python, assertions are carried out by the assert
statement. An assertion checks a condition, and if the condition evaluates to False, it raises an AssertionError exception with an optional error message.
def calculate_average(grades): assert len(grades) > 0, "List of grades cannot be empty" return sum(grades) / len(grades) calculate_average([]) # Throw an error
In this example, the function calculates the average grade, and the assertion ensures that the list of grades is not empty before calculating the average. If grades are empty, the assertion fails, preventing division by zero and indicating a clear error in program logic.
Here are some commonly utilized categories of assertions:
-
Value Assertions: These assertions are often employed in debugging and testing scenarios to verify that the values utilized in a program meet the expected criteria. For example, you might use assertions like
assert x >= 18
or as previously illustrated,assert len(grades) > 0
; -
Type Assertions: Type assertions are especially valuable in dynamically typed languages like Python, where the type of a variable may shift. For instance, using assert
isinstance(x, int)
confirms that x is indeed an integer; -
Collection Assertions: These assertions are used to check whether a collection (like a list or dictionary) includes particular elements or meets specific criteria. Examples include
assert item in my_list
orassert key in my_dict
; -
Exception Assertions: These are predominantly used in unit testing (which we will learn in the last section) to ensure that code correctly handles exceptions. For example,
assert_raises(ValueError, int, 'abc')
checks that converting 'abc' to an integer raises a ValueError. Similarly,assert_raises(ExceptionType, my_function, arg1, arg2)
verifies that calling my_function with arg1 and arg2 raises an exception of type ExceptionType.
Now, let’s implement assertions in an existing project to verify certain conditions are met during the program’s execution.
Swipe to show code editor
Add assertions to a sample project that manages user data, ensuring that user information meets certain criteria.
- Check that the
user_id
is not already in theusers
dictionary to avoid duplicates; - Ensure that
user_id
is an integer, maintaining consistency in user ID types; - Confirm that
user_info
is passed as a dictionary to prevent data type errors.
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Using Assertions
In Python, the assert statement is a built-in feature designed to verify that specific conditions are true within your code. It serves as a sanity check, confirming that certain prerequisites are met at specific points during program execution.
The syntax for the assert statement is as follows:
In Python, assertions are carried out by the assert
statement. An assertion checks a condition, and if the condition evaluates to False, it raises an AssertionError exception with an optional error message.
def calculate_average(grades): assert len(grades) > 0, "List of grades cannot be empty" return sum(grades) / len(grades) calculate_average([]) # Throw an error
In this example, the function calculates the average grade, and the assertion ensures that the list of grades is not empty before calculating the average. If grades are empty, the assertion fails, preventing division by zero and indicating a clear error in program logic.
Here are some commonly utilized categories of assertions:
-
Value Assertions: These assertions are often employed in debugging and testing scenarios to verify that the values utilized in a program meet the expected criteria. For example, you might use assertions like
assert x >= 18
or as previously illustrated,assert len(grades) > 0
; -
Type Assertions: Type assertions are especially valuable in dynamically typed languages like Python, where the type of a variable may shift. For instance, using assert
isinstance(x, int)
confirms that x is indeed an integer; -
Collection Assertions: These assertions are used to check whether a collection (like a list or dictionary) includes particular elements or meets specific criteria. Examples include
assert item in my_list
orassert key in my_dict
; -
Exception Assertions: These are predominantly used in unit testing (which we will learn in the last section) to ensure that code correctly handles exceptions. For example,
assert_raises(ValueError, int, 'abc')
checks that converting 'abc' to an integer raises a ValueError. Similarly,assert_raises(ExceptionType, my_function, arg1, arg2)
verifies that calling my_function with arg1 and arg2 raises an exception of type ExceptionType.
Now, let’s implement assertions in an existing project to verify certain conditions are met during the program’s execution.
Swipe to show code editor
Add assertions to a sample project that manages user data, ensuring that user information meets certain criteria.
- Check that the
user_id
is not already in theusers
dictionary to avoid duplicates; - Ensure that
user_id
is an integer, maintaining consistency in user ID types; - Confirm that
user_info
is passed as a dictionary to prevent data type errors.
Дякуємо за ваш відгук!