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Networking And Restful ApismediumMultiple SelectObjective-mapped

PCPP1 Networking And Restful Apis Practice Question

Which TWO of the following are potential pitfalls when using multithreading for network operations in Python?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Race conditions when accessing shared state

Global Interpreter Lock (GIL) limitations and race conditions on shared objects are common issues in Python multithreading.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Race conditions when accessing shared state

    Why this is correct

    Shared memory across threads often requires locking.

  • The GIL prevents true parallelism for CPU-bound tasks

    Why this is correct

    The GIL is a known bottleneck for CPU-bound operations in threads.

  • Threads always execute slower than single-threaded code

    Why it's wrong here

    They can improve I/O-bound performance significantly.

  • Threads consume more memory than processes

    Why it's wrong here

    Threads are generally lighter than processes.

  • Socket objects are automatically thread-safe

    Why it's wrong here

    Socket objects are not inherently thread-safe for shared operations.

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Written and reviewed by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

Last reviewed August 2026 · checked against the official Python Institute exam blueprint

This PCPP1 practice question is part of Courseiva's free Python Institute certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PCPP1 exam.