Python Pytest Interview Practice Questions are meticulously designed to bridge the gap between basic scripting and professional-grade test automation mastery. Whether you are preparing for a senior QA automation role or looking to solidify your backend engineering credentials, this comprehensive question bank dives deep into the mechanics of test discovery, complex fixture scopes, and the nuances of dependency injection. You will navigate through real-world challenges including indirect parameterization, sophisticated mocking with pytest-mock, and scaling test suites using pytest-xdist for CI/CD pipelines. Each question is crafted to mimic the pressure of a technical interview, ensuring you don't just memorize syntax but truly understand how to architect resilient, DRY, and high-performance testing frameworks that stand up to the rigors of modern software development.

Exam Domains & Sample Topics

Core Mechanics: Test discovery, assertion rewriting, and CLI mastery (-k, -m, -x).
Fixture Architecture: Scoping (Session to Function), yield teardowns, and conftest. py inheritance.
Advanced Patterns: Indirect parameterization, custom hooks, and plugin integration.
Isolation Techniques: Monkeypatching, mocking context managers, and database transaction safety.
Professional DevOps: CI/CD integration, JUnit XML reporting, and security linting.

Sample Practice Questions

1. Which of the following best describes the behavior of a fixture with scope="module" and autouse=True defined in a conftest. py file at the root of a project? A. It executes once before every individual test function in the entire project. B. It executes once per Python file (module) that contains test functions. C. It only executes if explicitly requested as an argument in a test function. D. It executes once for the entire test session, regardless of the number of modules. E. It executes once per class defined within the test modules. F. It is ignored unless the test module specifically imports it from conftest. py.

Correct Answer: B
Overall Explanation: The scope determines the lifetime and frequency of the fixture, while autouse=True ensures it runs without being explicitly called. A "module" scope means the fixture is invoked once per Python module (file).
Option A Incorrect: This describes scope="function".
Option B Correct: Module scope triggers the fixture once for each test file encountered.
Option C Incorrect: autouse=True removes the need for explicit requesting.
Option D Incorrect: This describes scope="session".
Option E Incorrect: This describes scope="class".
Option F Incorrect: Pytest automatically discovers fixtures in conftest. py without imports.

2. When using pytest.mark.parametrize, what is the primary advantage of setting indirect=True for a specific argument? A. It allows the test to skip execution if the data is missing. B. It forces the argument to be treated as a plain string rather than a variable. C. It passes the parameter value to a fixture of the same name instead of the test directly. D. It enables the test to run in parallel using the xdist plugin. E. It hides the parameter values from the terminal output for security. F. It allows the test to accept an unlimited number of arguments.

Correct Answer: C
Overall Explanation: Indirect parameterization is a powerful feature that allows you to "pipe" data through a fixture (using request.param) before it reaches the test function, allowing for complex setup based on the data.
Option A Incorrect: Skipping is handled by pytest.mark.skipif.
Option B Incorrect: Indirect refers to the injection path, not the data type.
Option C Correct: The value is sent to a fixture, which can then perform setup/teardown logic.
Option D Incorrect: Parallelization is a CLI/Plugin feature, not a parameterization setting.
Option E Incorrect: Parameter values are typically visible unless custom hooks are used.
Option F Incorrect: There is no "unlimited" relationship tied specifically to the indirect flag.

3. If you need to mock a database connection that is used as a Context Manager within a function, which pytest-mock (mocker) approach is most appropriate? A. mocker.patch('module.db_connection', return_value=None) B. mocker.patch('module.db_connection().__enter__') C. mocker.spy('module.db_connection') D. mocker.patch('module.db_connection') and configure the __enter__ return value. E. mocker.stopall() F. mocker.patch.object(db_connection, 'close')

Correct Answer: D
Overall Explanation: To mock a context manager, you must mock the object and then ensure its __enter__ method returns the object (or a mock of it) that the with statement expects to use.
Option A Incorrect: Setting return_value to None will cause the with statement to fail.
Option B Incorrect: While you can patch __enter__, it's cleaner to patch the main object and configure the child mock.
Option C Incorrect: A spy tracks calls but does not replace the behavior; the real DB would still be hit.
Option D Correct: This allows you to control the entire lifecycle of the context manager.
Option E Incorrect: This is used for cleanup, not for setting up a specific mock.
Option F Incorrect: Mocking close does not handle the entry/context logic of the with block.

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