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Using Assertions | Error Handling
Python Advanced Concepts
course content

Course Content

Python Advanced Concepts

Python Advanced Concepts

1. Modules and Imports
2. Error Handling
3. File Handling
4. Pytest Framework
5. Unittest Framework
6. Iterators and Generators

bookUsing 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.

12345
def calculate_average(grades): assert len(grades) > 0, "List of grades cannot be empty" return sum(grades) / len(grades) calculate_average([]) # Throw an error
copy

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 or assert 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.

Task
test

Swipe to show code editor

Add assertions to a sample project that manages user data, ensuring that user information meets certain criteria.

  1. Check that the user_id is not already in the users dictionary to avoid duplicates;
  2. Ensure that user_id is an integer, maintaining consistency in user ID types;
  3. Confirm that user_info is passed as a dictionary to prevent data type errors.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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Section 2. Chapter 4
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bookUsing 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.

12345
def calculate_average(grades): assert len(grades) > 0, "List of grades cannot be empty" return sum(grades) / len(grades) calculate_average([]) # Throw an error
copy

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 or assert 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.

Task
test

Swipe to show code editor

Add assertions to a sample project that manages user data, ensuring that user information meets certain criteria.

  1. Check that the user_id is not already in the users dictionary to avoid duplicates;
  2. Ensure that user_id is an integer, maintaining consistency in user ID types;
  3. Confirm that user_info is passed as a dictionary to prevent data type errors.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 2. Chapter 4
toggle bottom row

bookUsing 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.

12345
def calculate_average(grades): assert len(grades) > 0, "List of grades cannot be empty" return sum(grades) / len(grades) calculate_average([]) # Throw an error
copy

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 or assert 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.

Task
test

Swipe to show code editor

Add assertions to a sample project that manages user data, ensuring that user information meets certain criteria.

  1. Check that the user_id is not already in the users dictionary to avoid duplicates;
  2. Ensure that user_id is an integer, maintaining consistency in user ID types;
  3. Confirm that user_info is passed as a dictionary to prevent data type errors.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

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.

12345
def calculate_average(grades): assert len(grades) > 0, "List of grades cannot be empty" return sum(grades) / len(grades) calculate_average([]) # Throw an error
copy

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 or assert 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.

Task
test

Swipe to show code editor

Add assertions to a sample project that manages user data, ensuring that user information meets certain criteria.

  1. Check that the user_id is not already in the users dictionary to avoid duplicates;
  2. Ensure that user_id is an integer, maintaining consistency in user ID types;
  3. Confirm that user_info is passed as a dictionary to prevent data type errors.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 2. Chapter 4
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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