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Python Concurrency Simplified

  • Development
  • Mar 30, 2025
SynopsisPython Concurrency Simplified, available at $39.99, has an av...
Python Concurrency Simplified  No.1

Python Concurrency Simplified, available at $39.99, has an average rating of 3.5, with 66 lectures, 2 quizzes, based on 28 reviews, and has 213 subscribers.

You will learn about This course is for Python developers who want to learn concurrency techniques to build high-performance applications with Python. This course is ideal for individuals who are Increase your awareness of concurrency in Python or Distinguish between parallel programming and concurrent programming or Explore Pythons threading module or Familiarize yourself with Pythons Global Interpreter Lock (GIL) or Learn the similarities between thread and process management or Practice with open source libraries or Learn process synchronization and inter-process communication or Work with best practices and caveats or Know how to handle the hardest part in a concurrent system: shared resources or Build concurrent systems with Communicating Sequential Processes (CSPs) or Maintain all concurrent systems and master them It is particularly useful for Increase your awareness of concurrency in Python or Distinguish between parallel programming and concurrent programming or Explore Pythons threading module or Familiarize yourself with Pythons Global Interpreter Lock (GIL) or Learn the similarities between thread and process management or Practice with open source libraries or Learn process synchronization and inter-process communication or Work with best practices and caveats or Know how to handle the hardest part in a concurrent system: shared resources or Build concurrent systems with Communicating Sequential Processes (CSPs) or Maintain all concurrent systems and master them.

Enroll now: Python Concurrency Simplified

Summary

Title: Python Concurrency Simplified

Price: $39.99

Average Rating: 3.5

Number of Lectures: 66

Number of Quizzes: 2

Number of Published Lectures: 66

Number of Published Quizzes: 2

Number of Curriculum Items: 68

Number of Published Curriculum Objects: 68

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

  • This course is for Python developers who want to learn concurrency techniques to build high-performance applications with Python.
  • Who Should Attend

  • Increase your awareness of concurrency in Python
  • Distinguish between parallel programming and concurrent programming
  • Explore Pythons threading module
  • Familiarize yourself with Pythons Global Interpreter Lock (GIL)
  • Learn 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
  • Know how to handle the hardest part in a concurrent system: shared resources
  • Build concurrent systems with Communicating Sequential Processes (CSPs)
  • Maintain all concurrent systems and master them
  • Target Audiences

  • Increase your awareness of concurrency in Python
  • Distinguish between parallel programming and concurrent programming
  • Explore Pythons threading module
  • Familiarize yourself with Pythons Global Interpreter Lock (GIL)
  • Learn 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
  • Know how to handle the hardest part in a concurrent system: shared resources
  • Build concurrent systems with Communicating Sequential Processes (CSPs)
  • Maintain all concurrent systems and master them
  • Python is a very high level, general purpose language that is utilized heavily in fields such as data science and research, as well as being one of the top choices for general purpose programming for programmers around the world. It features a wide number of powerful, high and low-level libraries and frameworks that complement its delightful syntax and enable Python programmers to create.

    This course introduces some of the most popular libraries and frameworks and goes in-depth into how you can leverage these libraries for your own high-concurrent, highly-performant Python programs. You will learn the fundamental concepts of concurrency needed to be able to write your own concurrent and parallel software systems in Python. You will also learn the concepts such as debugging and exception handling as well as the libraries and frameworks that allow you to create event-driven and reactive systems.

    Contents and Overview

    This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.

    The first course, Learning Concurrency in Python, introduces some of the most popular libraries and frameworks and goes in-depth into how you can leverage these libraries for your own high-concurrent, highly-performant Python programs. You will learn the fundamental concepts of concurrency needed to be able to write your own concurrent and parallel software systems in Python.

    In the second course, Concurrent Programming in Python, 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.

    By the end of this course, you will have learned the techniques to write incredibly efficient concurrent systems that follow best practices.

    Meet Your Expert(s):

    We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:

    ●??????? Elliot Forbes has worked as a full-time software engineer at a leading financial firm for the last two years. He graduated from the University of Strathclyde in Scotland in the spring of 2015 and worked as a freelancer developing web solutions while studying there. He has worked on numerous different technologies such as Golang, Node.js, and plain old Java, and he has spent years working on concurrent enterprise systems.Elliot has even worked at Barclays Investment Bank for a summer internship in London and has maintained a couple of software development websites for the last three years.

    BignumWorks Software LLP is an India-based software consultancy that provides consultancy services in the area of software development and technical training. Our domain expertise includes web, mobile, cloud app development, data science projects, in-house software training services, and up-skilling services.

    Course Curriculum

    Chapter 1: Learning Concurrency in Python

    Lecture 1: The Course Overview

    Lecture 2: Threads and Multithreading

    Lecture 3: Processes and Event-Driven Programming

    Lecture 4: Concurrent Image Download

    Lecture 5: Improving Number Crunching with Multiprocessing

    Lecture 6: Concurrency and I/O Bottlenecks

    Lecture 7: Understanding Parallelism

    Lecture 8: Computer Memory Architecture Styles

    Lecture 9: Threads in Python

    Lecture 10: Starting a Thread

    Lecture 11: Handling Threads in Python

    Lecture 12: How Does the Operating System Handle Threads?

    Lecture 13: Deadlocks and Race Condition

    Lecture 14: Shared Resources and Data Races

    Lecture 15: Conditions and Semaphores

    Lecture 16: Events and Barriers

    Lecture 17: Sets and Decorator

    Lecture 18: Queues

    Lecture 19: Queue and Deque Objects

    Lecture 20: Appending, Popping, and Inserting Elements

    Lecture 21: Defining Your Own Thread-Safe Communication Structures

    Lecture 22: Testing Strategies

    Lecture 23: Debugging

    Lecture 24: Benchmarking

    Lecture 25: Profiling

    Lecture 26: Concurrent Futures

    Lecture 27: Future Objects

    Lecture 28: Setting Callbacks and Exception Classes

    Lecture 29: ProcessPoolExecutor

    Lecture 30: Improving Our Crawler

    Lecture 31: Working Around the GIL and Daemon Processes

    Lecture 32: Identifying and Terminating Processes

    Lecture 33: Multiprocessing Pools

    Lecture 34: Communication Between Processes

    Lecture 35: Multiprocessing Manager

    Lecture 36: Communicating Sequential Processes

    Lecture 37: Event-Driven Programming

    Lecture 38: Getting Started with Asyncio

    Lecture 39: Debugging Asyncio Programs

    Lecture 40: Twisted

    Lecture 41: Gevent

    Chapter 2: Concurrent Programming in Python

    Lecture 1: The Course Overview

    Lecture 2: Advanced OSes and Programming Environments

    Lecture 3: Concurrency Versus Parallelism with Examples

    Lecture 4: Operating System’s Building Blocks of Parallel Execution

    Lecture 5: Libraries in Python Used to Achieve Concurrency and Parallelism

    Lecture 6: Python’s Global Interpreter Lock (GIL)

    Lecture 7: Overview of Threading Module

    Lecture 8: Creating Threads

    Lecture 9: Managing Threads

    Lecture 10: Synchronization in Python

    Lecture 11: Using Synchronization Primitives

    Lecture 12: Producer–Consumer Pattern

    Lecture 13: Using Python Queue Module

    Lecture 14: Multithreading in GUI Programming

    Lecture 15: Limitations Imposed by GIL

    Lecture 16: Multiprocessing

    Lecture 17: Similarities Between Thread and Process Management

    Lecture 18: Difference Between Thread and Process Management

    Lecture 19: Libraries for Practice

    Lecture 20: Process Synchronization

    Lecture 21: Inter-Process Communication

    Lecture 22: Best Practices and Anti-Patterns

    Lecture 23: Pool of Workers for Maximizing Usage of the Hardware

    Lecture 24: When and How to Use a Pool of Workers

    Lecture 25: Best Practices and Anti-Patterns

    Instructors

  • Python Concurrency Simplified  No.2
    Packt Publishing
    Tech Knowledge in Motion
  • Rating Distribution

  • 1 stars: 3 votes
  • 2 stars: 4 votes
  • 3 stars: 4 votes
  • 4 stars: 11 votes
  • 5 stars: 6 votes
  • Frequently Asked Questions

    How long do I have access to the course materials?

    You can view and review the lecture materials indefinitely, like an on-demand channel.

    Can I take my courses with me wherever I go?

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