Concurrent and Parallel Programming in Python - Threading, Multiprocessing, Async Introduction

Concurrent and Parallel Programming in Python - Threading, Multiprocessing, Async Introduction

Assessment

Interactive Video

•

Information Technology (IT), Architecture

•

University

•

Practice Problem

•

Hard

Created by

Wayground Content

FREE Resource

The video tutorial introduces concurrent programming, highlighting its benefits over sequential programming. It explains how to utilize multiple CPU cores for efficient metric calculations and handle network IO using threads. The tutorial also covers asynchronous programming to avoid blocking, discusses Python's Global Interpreter Lock (GIL), and emphasizes thread safety. Finally, it compares threads with multiprocessing, outlining their differences and use cases.

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10 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the primary focus of the introduction to concurrency?

Comparison of different programming paradigms

Overview and importance of concurrency

Detailed coding examples

History of programming languages

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a common characteristic of sequential programs?

They require complex debugging

They are always faster than concurrent programs

They execute tasks one after another

They utilize multiple CPU cores simultaneously

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How can multiple CPU cores be utilized in concurrent programming?

By running the same task on all cores

By avoiding the use of threads

By using only one core for all tasks

By calculating independent tasks simultaneously on different cores

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a key advantage of using threads for network-bound tasks?

They simplify the program logic

They eliminate the need for a database

They allow tasks to proceed while waiting for network responses

They increase the CPU usage

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the Global Interpreter Lock (GIL) in Python?

A tool for debugging concurrent programs

A mechanism that allows multiple threads to run simultaneously

A feature that restricts Python to run only one thread at a time

A library for managing network requests

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a race condition in concurrent programming?

A situation where threads run faster than expected

A method to optimize thread performance

A condition where two threads access shared data simultaneously, leading to unpredictable results

A type of error that occurs only in sequential programs

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Why is thread safety important in concurrent programming?

To ensure threads do not interfere with each other when accessing shared data

To increase the speed of thread execution

To reduce memory usage

To simplify the program structure

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