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Concurrent Programming in Python [Video]

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Concurrent Programming in Python [Video]

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Harness the power of modern code structures with Python to improve performance and flexibility
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Video Details

ISBN 139781788998031
Course Length2 hours and 20 minutes

Video Description

In this course, you will skill-up with techniques related to various aspects of concurrent programming in Python, including common thread programming techniques and approaches to parallel processing.

Filled with examples, this course will show you all you need to know to start using concurrency in Python. You will learn about the principal approaches to concurrency that Python has to offer, including libraries and tools needed to exploit the performance of your processor. Learn the basic theory and history of parallelism and choose the best approach when it comes to parallel processing.

After taking this course you will have gained an in-depth knowledge of using threads and processes with the help of real-world examples.

Style and Approach

An exhaustive course—packed with step-by-step instructions, working examples, and helpful advice—to ensure you master the libraries and tools needed to exploit concurrent programming in Python.

Table of Contents

Introduction to Concurrent Programming
The Course Overview
Advanced OSes and Programming Environments
Concurrency Versus Parallelism with Examples
Operating System’s Building Blocks of Parallel Execution
Libraries in Python Used to Achieve Concurrency and Parallelism
Python’s Global Interpreter Lock (GIL)
Creating and Managing Threads
Overview of Threading Module
Creating Threads
Managing Threads
Thread Synchronization Primitives
Synchronization in Python
Using Synchronization Primitives
Producer–Consumer Pattern
Using Python Queue Module
Multithreading in GUI Programming
Creating and Managing Processes
Limitations Imposed by GIL
Multiprocessing
Similarities Between Thread and Process Management
Difference Between Thread and Process Management
Libraries for Practice
Synchronization and Inter-Process Communication
Process Synchronization
Inter-Process Communication
Best Practices and Anti-Patterns
Using a Pool of Workers
Pool of Workers for Maximizing Usage of the Hardware
When and How to Use a Pool of Workers
Best Practices and Anti-Patterns

What You Will Learn

  • Increase your awareness of concurrency in Python
  • Distinguish between parallel programming and concurrent programming
  • Explore Python's threading module
  • Familiarize yourself with Python's Global Interpreter Lock (GIL)
  • Master the similarities between thread and process management
  • Practice with open source Libraries
  • Learn process synchronization and inter-process communication
  • Work with best practices and caveats

Authors

Table of Contents

Introduction to Concurrent Programming
The Course Overview
Advanced OSes and Programming Environments
Concurrency Versus Parallelism with Examples
Operating System’s Building Blocks of Parallel Execution
Libraries in Python Used to Achieve Concurrency and Parallelism
Python’s Global Interpreter Lock (GIL)
Creating and Managing Threads
Overview of Threading Module
Creating Threads
Managing Threads
Thread Synchronization Primitives
Synchronization in Python
Using Synchronization Primitives
Producer–Consumer Pattern
Using Python Queue Module
Multithreading in GUI Programming
Creating and Managing Processes
Limitations Imposed by GIL
Multiprocessing
Similarities Between Thread and Process Management
Difference Between Thread and Process Management
Libraries for Practice
Synchronization and Inter-Process Communication
Process Synchronization
Inter-Process Communication
Best Practices and Anti-Patterns
Using a Pool of Workers
Pool of Workers for Maximizing Usage of the Hardware
When and How to Use a Pool of Workers
Best Practices and Anti-Patterns

Video Details

ISBN 139781788998031
Course Length2 hours and 20 minutes
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