Python Interview Questions

Lists are mutable, while tuples are immutable.

Lists can be changed after creation, while tuples are fixed. Tuples are useful for stable records and can be hashable when their values are hashable.

Decorators wrap functions or classes to extend behavior.

A decorator takes a callable and returns another callable, often used for logging, caching, validation, authorization, or timing without changing the original body.

The Global Interpreter Lock allows one CPython thread to execute Python bytecode at a time.

The GIL simplifies memory management but limits CPU-bound threading. Threads still help for I/O-bound work, while multiprocessing helps CPU-bound work.

A generator lazily produces values using yield.

Generators keep only their current state in memory, making them useful for streams, large files, and pipelines where a full list would be expensive.

A shallow copy copies the outer object; a deep copy recursively copies nested objects.

Shallow copies still share nested mutable values, while deep copies duplicate nested values to avoid accidental shared mutation.

They are created once at function definition time, so later calls can share the same object.

A default like items=[] keeps state across calls, which can create surprising bugs. Use None as the default and create a new list or dict inside the function.

They guarantee setup and cleanup around a block of code.

Context managers power patterns like with open(...) because __enter__ prepares the resource and __exit__ releases it even when an exception occurs.

An iterable can create an iterator; an iterator returns values one at a time with next().

Lists are iterable because iter(list) returns an iterator. An iterator keeps iteration state and raises StopIteration when exhausted.