Core Python Fundamentals Interview Questions

Python is simple, interpreted, dynamically typed, object-oriented, and supports multiple programming paradigms with a large standard library.

Python is a high-level, interpreted programming language used for web development, data science, automation, and AI.

Python is an interpreted language, meaning code is executed line by line by the Python interpreter.

Common Python data types include int, float, str, list, tuple, set, dict, and bool.

Type casting is converting one data type into another using functions like int(), float(), str(), etc.

Lists are mutable, while tuples are immutable. Lists use [], tuples use ().

Indentation defines code blocks in Python and is mandatory for loops, functions, and conditionals.

A variable is a container for storing data values and does not require explicit type declaration.

Keywords are reserved words like if, else, for, while, def, class that have special meaning in Python.

PEP 8 is the official Python style guide that defines coding conventions for readability and consistency.

== compares values, while is compares memory locations (identity).

Comments are used to explain code and are ignored by the interpreter. They start with # or triple quotes.

Slicing is used to extract a portion of sequences like lists or strings using start:end:step syntax.

input() is used to take user input from the console as a string.

The Python interpreter executes Python code line by line and converts it into machine-readable instructions.

Name concrete modules (collections, itertools, pathlib, typing) and how they support Core Python Fundamentals. Prefer stdlib before third-party when it is enough.

Explain the classic default-list bug and closures in loops. Show a safe pattern when Core Python Fundamentals uses defaults or lambdas.

pytest with fixtures, parametrize, and coverage. Mock I/O at boundaries so Core Python Fundamentals unit tests stay deterministic.

Annotate public APIs, use mypy/pyright in CI, and prefer Protocols for duck typing. Catch Core Python Fundamentals contract breaks before runtime.

Generators save memory for large streams; comprehensions are clear for small transforms. Justify the choice for Core Python Fundamentals data sizes.