Python for DevOps Practice Tests: 200 Questions Explained

Are you starting to write Python scripts for DevOps work? These practice tests check the basics a beginner needs before automating anything: setting up Python and your tools, data types, strings and operators, and then conditions, loops, lists and dictionaries, functions, error handling and working with files and folders. You get 4 practice tests with 200 questions in total (50, 50, 50, 50).

Every question was checked twice before release: once by the author against the official documentation, and once by an independent reviewer who answered it blind - any disagreement was settled with a source. What makes the explanations usefulEach answer tells you why the right option is right and why each wrong option is wrong. The wrong options are real features, commands and settings that are easy to pick by mistake - that is where most of the learning is.

How the tests are builtPractice Test 1: Python Setup, Tools and First Scripts: installing Python, the REPL, PyCharm and VS Code, Google Colab, pip and virtual environments, Git basics, Vim, print(), comments and PEP 8. Practice Test 2: Data Types, Variables, Strings and Operators: variables and naming rules, data types and type conversion, input(), string indexing, slicing and methods, arithmetic, modulo, order of operations and comparisons. Practice Test 3: Control Flow, Data Structures, Functions and Files: if, elif and else, logical operators, for and while loops, lists, tuples and dictionaries, comprehensions, functions, try/except, files, os and shutil.

Practice Test 4: Full Mock Exam: a mixed exam across all three areas - take it last, in one sitting. Questions use single-answer and multiple-answer formats; the number of answers to pick is always stated. Suggested time: 75 minutes per test.

Versions: Python 3. 14 (and Python 3. 13), pip and venv, PEP 8, PyCharm and VS Code, Google Colab, Git and Vim 9, as of October 2026.

Please note: these are original practice questions written by an instructor. This course is not affiliated with or endorsed by the Python Software Foundation; Python and the Python logos are Python Software Foundation trademarks.