Python Testing and Debugging

Python Testing and Debugging - Important Points

31.		What is a test fixture in Python testing?

A. A set of preconditions that must be met before a test can be run

B. A function that sets up the environment for a test

C. A set of test cases that are run together

D. A function that tears down the environment after a test

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Answer: option b

Explanation:

A test fixture is a function that sets up the environment for a test. This may include creating objects or data that are necessary for the test, and configuring the environment to ensure that the test can be run correctly.

32.		What is the purpose of a test runner in Python testing?

A. To run tests and report the results

B. To generate test data for use in testing

C. To analyze code performance during testing

D. To identify and fix errors in test code

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Answer: option a

Explanation:

A test runner is a tool used to run tests and report the results. It may also provide features such as test discovery, which automatically identifies and runs tests within a project, and test reporting, which generates detailed reports about the results of the tests.

33.		Which module in Python provides support for integration testing?

A. unittest

B. pytest

C. selenium

D. all of the above

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Answer: option d

Explanation:

Python provides support for integration testing through multiple modules, including unittest, pytest, and selenium. Integration testing is used to test the interaction between different components of a system and may involve testing user interfaces or communication between different systems.

34.		What is a debugger statement in Python?

A. A statement that allows developers to pause code execution and examine the state of the program

B. A statement that generates a warning message

C. A statement that terminates program execution

D. A statement that logs a message to a file

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Answer: option a

Explanation:

A debugger statement is a statement that allows developers to pause code execution and examine the state of the program. It is often used in conjunction with a debugger tool to help identify and fix errors in code.

35.		Which tool in Python can be used for load testing?

A. locust

B. pytest-benchmark

C. httperf

D. all of the above

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Answer: option a

Explanation:

Python provides multiple tools for load testing, including locust, pytest-benchmark, and httperf. Load testing is used to test the performance of a system under heavy loads, such as high levels of traffic or large volumes of data.

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