Fundamentals Interview Questions

Python is a high-level, interpreted programming language known for its readability, simplicity, and versatility. Key features include dynamic typing, automatic memory management, an extensive standard library, support for multiple programming paradigms (procedural, object-oriented, functional), and a large ecosystem of third-party packages.

Python uses automatic memory management through a private heap containing all Python objects and data structures. It employs reference counting for garbage collection and a cyclic garbage collector to detect and collect reference cycles, ensuring efficient memory usage without manual intervention.

Lists are mutable, allowing modifications like adding, removing, or changing elements. Tuples are immutable, meaning once created, their elements cannot be altered. Lists use square brackets [ ], while tuples use parentheses ( ). Tuples can be used as keys in dictionaries due to their immutability.

Python's built-in data types include numeric types (int, float, complex), sequence types (list, tuple, range), text type (str), mapping type (dict), set types (set, frozenset), boolean type (bool), and binary types (bytes, bytearray, memoryview).

You can create a virtual environment using the `venv` module by running `python -m venv myenv`, where `myenv` is the name of the environment. Activate it with `source myenv/bin/activate` on Unix or `myenv\Scripts\activate` on Windows, isolating dependencies for your project.

The `__init__` method is the constructor in Python classes. It initializes the instance attributes of a class when a new object is created, setting up the initial state of the object.

List comprehensions provide a concise way to create lists by iterating over an iterable and optionally including conditional logic. Example: `[x**2 for x in range(10) if x % 2 == 0]` creates a list of squares of even numbers from 0 to 9.

Python uses reference counting to keep track of the number of references to each object. When an object's reference count drops to zero, it's immediately deallocated. Additionally, a cyclic garbage collector handles reference cycles by periodically identifying and collecting objects involved in cycles.

Decorators are functions that modify or enhance other functions or methods without changing their code. They are applied using the `@decorator_name` syntax above a function definition. Common uses include logging, access control, and memoization.

Exceptions are handled using `try` and `except` blocks. Code that may raise an exception is placed inside the `try` block, and the `except` block catches and handles specific exceptions. Optionally, `finally` can be used to execute code regardless of whether an exception occurred.