Python

Python generators allow you to iterate over data efficiently using the yield keyword. They are not only memory-efficient but also enable lazy evaluation, making them ideal for handling large datasets or infinite sequences. However, many beginners find generators confusing due to their unique behavior compared to regular functions and lists.

Python has a few different terms that can be confusing to new developers: modules, packages, and namespaces. Understanding these fundamental concepts helps when reading documentation, organizing code and debugging from logs and errors.

Python's @dataclass (introduced in Python 3.7) is a decorator that automatically generates boilerplate methods for classes that primarily store data. It simplifies class creation; no need to manually write `__init__`, `__repr__`, etc.

Working with JSON in Python seems straightforward — the built‑in json module can load data from a file and dump Python objects back to disk. Many new developers, however, run into confusing errors, odd behaviour or inefficient patterns when handling real‑world JSON.

The __pycache__ folder in Python is where the interpreter stores compiled bytecode files to optimize program execution. But what exactly does that mean, and why is it important?

Have you ever written a Python script, run it successfully, and then imported it into another program only to watch it behave strangely? Maybe it printed a prompt you didn’t expect or started an expensive computation as soon as you imported it.

Python variables have different scopes: local, enclosing, global, and built-in, organized by the LEGB rule. Use globals() and locals() to inspect variable scope, and follow best practices to avoid naming conflicts

Partials in Python is a function that behaves like an existing function but with some arguments already filled in. It is created using the functools.partial function from the functools module

Python has three division operators: /, //, and %. The / operator performs true division, // performs floor division, and % gives the modulus.

Pythons functool provides a number of functions and utilities for functional programming, such as higher-order functions, partial function application, and memoization.