1. #1

   Juniordata-structuresfundamentals

   What is the difference between a list and a tuple in Python?

   Lists are mutable and meant for homogeneous, changing collections; tuples are immutable, hashable, and suited to fixed records.

2. #2

   Mid-levelfunctionspitfalls

   Why are mutable default arguments dangerous in Python?

   A default argument is evaluated once at definition, so a mutable default like [] is shared across all calls, accumulating state unexpectedly.

3. #3

   Juniorcomprehensionsidioms

   What are list comprehensions and when should you use them?

   Comprehensions build lists, sets, or dicts in one readable expression with an optional filter, replacing simple map/filter loops.

4. #4

   Juniorfunctionsarguments

   What do *args and **kwargs do?

   *args collects extra positional arguments into a tuple; **kwargs collects extra keyword arguments into a dict, enabling flexible variadic functions.

5. #5

   Mid-leveldecoratorsfunctions

   What are decorators in Python?

   A decorator is a callable that wraps a function to extend its behaviour — logging, caching, auth — without modifying the original function’s code.

6. #6

   Mid-levelgeneratorsmemory

   What are generators and how do they save memory?

   Generators yield values one at a time and compute lazily, so they process large or infinite sequences without holding everything in memory.

7. #7

   Mid-leveloperatorsidentity

   What is the difference between == and is in Python?

   == compares values for equality; is compares identity (whether two names point to the same object in memory).

8. #8

   Mid-levelcontext-managersresources

   What are context managers and the with statement?

   Context managers guarantee setup and cleanup via __enter__/__exit__, so the with statement reliably releases resources like files and locks even on errors.

9. #9

   Seniorconcurrencygil

   What is the GIL and how does it affect concurrency?

   The Global Interpreter Lock lets only one thread execute Python bytecode at a time, so threads help I/O-bound work but not CPU-bound parallelism.

10. #10

    Seniorasyncconcurrency

    How does asyncio enable concurrency in Python?

    asyncio runs an event loop where async functions cooperatively yield at await points, enabling high-concurrency I/O on a single thread without the GIL’s limits.