POC Performance Optimization 3

Question 1

Which Python library provides JIT compilation to speed up numerical Python code?

Accepted Answer

Numba

Answer

Numba uses LLVM to JIT-compile Python functions decorated with @jit, achieving near-C speed for numeric loops.

Question 2

What is the purpose of using `memoryview` in Python?

Accepted Answer

To access buffer protocol objects without copying data

Answer

memoryview exposes the buffer protocol, letting you slice and pass large byte sequences to functions without copying the underlying data.

Question 3

In Python, what is a generator's key performance advantage over returning a list?

Accepted Answer

Generators produce values lazily, reducing peak memory usage

Answer

Generators yield one item at a time and don't hold the full sequence in memory, making them ideal for large or infinite data streams.

Question 4

Which profiling tool provides line-by-line memory usage statistics for Python code?

Accepted Answer

memory_profiler

Answer

memory_profiler's @profile decorator reports memory consumption on a per-line basis, helping pinpoint memory-hungry code.

Question 5

What does Python's Global Interpreter Lock (GIL) primarily affect?

Accepted Answer

CPU-bound threads running Python bytecode simultaneously

Answer

The GIL prevents multiple native threads from executing Python bytecode at the same time, limiting CPU-bound parallelism within one process.

(POC) Python Online Certification Practice Test