Kursusindhold

Python Advanced Concepts

1. Mastering Python Modules and Imports

Python Project Structure: Organizing Code for Scalability Understanding Python Modules Importing Modules in Python: Best Practices for Code Reusability Exploring Python Libraries: Built-in and Third-Party Solutions Python Standard Library: Essential Modules for Everyday Tasks Managing Python Packages

2. Mastering Error Handling in Python

Fundamentals of Error Handling in Python: Preventing Code Crashes Raising Exceptions in Python: Triggering and Managing Errors Executing Code After Exceptions: Handling Cleanup Operations Using Assertions in Python: Debugging and Ensuring Code Integrity Best Practices for Exception Handling

3. Mastering File Handling in Python

Introduction to File Handling in Python Reading and Writing Files: Handling Text and Data Efficiently Advanced File Operations: Modifying and Managing File Content Working with File Paths in Python Using Context Managers for File Handling in Python Creating Custom Context Managers Handling Binary Files in Python

4. Mastering Pytest Framework

Introduction to Testing in Python Pytest Framework: Setting Up and Running Automated Tests Using the Assert Statement in Pytest: Validating Test Conditions Test Parametrization in Pytest: Running Tests with Multiple Inputs

5. Mastering Unittest Framework

Introduction to Unittest in Python: Writing Structured Unit Tests Using Assert Methods in Unittest: Validating Test Results SetUp and TearDown in Unittest: Managing Test Environments Mocking Techniques in Unittest: Simulating Dependencies Advanced Mocking in Unittest

6. Mastering Iterators and Generators in Python

Python Iterables: Understanding Sequences and Data Structures Understanding Iterators in Python Lazy Evaluation in Python: Optimizing Memory and Performance Introduction to Generators: Yielding Values for Efficient Iteration Practical Applications of Generators: Real-World Use Cases

Using Assertions in Python: Debugging and Ensuring Code Integrity

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:

python

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

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.

Opgave

Swipe to start coding

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 the users 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.

Løsning

Skift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder

Var alt klart?

Tak for dine kommentarer!

Sektion 2. Kapitel 4

Using Assertions in Python: Debugging and Ensuring Code Integrity

The syntax for the assert statement is as follows:

python


              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

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.

Opgave

Swipe to start coding

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 the users 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.

Løsning

Skift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder

Var alt klart?

Tak for dine kommentarer!

Sektion 2. Kapitel 4

Skift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder