Вивчайте Using Python for Test Coverage Analysis

Test coverage is a critical concept for any QA engineer working with automated tests. It refers to the measure of how much of your codebase is actually executed when your test suite runs. High test coverage means that most of your code is being exercised by tests, making it more likely that bugs will be caught before reaching production. Low coverage, on the other hand, can leave large portions of your code untested and vulnerable to hidden defects. Understanding and analyzing test coverage helps you prioritize where to add more tests and ensures your testing efforts are effective.


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# Simulating code coverage analysis in Python by tracking function calls

called_functions = set()

def coverage_tracker(func):
    def wrapper(*args, **kwargs):
        called_functions.add(func.__name__)
        return func(*args, **kwargs)
    return wrapper

@coverage_tracker
def login(user, password):
    return user == "admin" and password == "secret"

@coverage_tracker
def logout():
    return True

@coverage_tracker
def reset_password(user):
    return f"Password reset for {user}"

# Simulated test execution
login("admin", "secret")
logout()

# At this point, reset_password was not called during tests
print("Functions called during tests:", called_functions)

When you analyze coverage data, you are looking for which parts of your code were actually executed by your tests and which parts were missed. In the previous example, you can see that the login and logout functions were called, but reset_password was not. This means that your tests do not currently exercise the password reset functionality, and you may want to add or update tests to cover this code path. By interpreting coverage data, you can identify untested areas and improve your overall test suite quality.


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# Summarizing coverage results in a readable format

all_functions = {"login", "logout", "reset_password"}

untested_functions = all_functions - called_functions

print("Coverage Summary:")
print("Tested functions:", ", ".join(sorted(called_functions)))
print("Untested functions:", ", ".join(sorted(untested_functions)))

1. What is test coverage and why is it important?

2. How can you track which functions are exercised by your tests in Python?

3. Fill in the blank: `called_functions.add(func_name)` tracks _____

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Секція 3. Розділ 6

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Suggested prompts:

Can you explain how to increase test coverage in this example?

What tools can I use to measure test coverage in real-world Python projects?

Why is it important to identify untested functions in my code?

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# Simulating code coverage analysis in Python by tracking function calls

called_functions = set()

def coverage_tracker(func):
    def wrapper(*args, **kwargs):
        called_functions.add(func.__name__)
        return func(*args, **kwargs)
    return wrapper

@coverage_tracker
def login(user, password):
    return user == "admin" and password == "secret"

@coverage_tracker
def logout():
    return True

@coverage_tracker
def reset_password(user):
    return f"Password reset for {user}"

# Simulated test execution
login("admin", "secret")
logout()

# At this point, reset_password was not called during tests
print("Functions called during tests:", called_functions)


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# Summarizing coverage results in a readable format

all_functions = {"login", "logout", "reset_password"}

untested_functions = all_functions - called_functions

print("Coverage Summary:")
print("Tested functions:", ", ".join(sorted(called_functions)))
print("Untested functions:", ", ".join(sorted(untested_functions)))

1. What is test coverage and why is it important?

2. How can you track which functions are exercised by your tests in Python?

3. Fill in the blank: `called_functions.add(func_name)` tracks _____

Все було зрозуміло?

Дякуємо за ваш відгук!

Секція 3. Розділ 6

Using Python for Test Coverage Analysis

1. What is test coverage and why is it important?

2. How can you track which functions are exercised by your tests in Python?

3. Fill in the blank: called_functions.add(func_name) tracks _____

Using Python for Test Coverage Analysis

1. What is test coverage and why is it important?

2. How can you track which functions are exercised by your tests in Python?

3. Fill in the blank: called_functions.add(func_name) tracks _____

3. Fill in the blank: `called_functions.add(func_name)` tracks _____

3. Fill in the blank: `called_functions.add(func_name)` tracks _____