Complete Guide to Python Multithreading and Multiprocessing

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‪Idan Chen‬‏

3:02:32

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1 - Getting Started with Python

1 - Introduction to Python paralleling.mp4

04:53

2 - Installing Python and Setting Up Your Environment.mp4

03:27

3 - How to Install Python 3 and Use Virtual Environments venv on Windows Article.html

4 - How to Install Python 3 and Use Virtual Environments venv on linux Article.html

5 - How to Install Python 3 and Use Virtual Environments venv on Mac Article.html

6 - Installing Pycharm Article.html

2 - Python Programming Foundations

7 - Functions in Python Definition and Usage.mp4

05:05

7 - python-functions.zip

8 - Modules and Packages Organizing Code.mp4

03:36

8 - import-statements.zip

9 - Understanding Python Classes and Objects.mp4

06:24

9 - python-classes.zip

3 - Introduction to Concurrency in Python

10 - Understanding Concurrency Threads vs Processes.mp4

05:17

11 - Threads in Python and the Global Interpreter Lock GIL.mp4

03:25

4 - Basics of Threading in Python

12 - Creating Your First Thread Presentation.mp4

03:13

13 - Creating Your First Thread Code.mp4

02:33

13 - first-thread.zip

14 - Joining Threads Understanding join Presentation.mp4

04:32

15 - Joining Threads Understanding join Code.mp4

02:41

15 - join-thread.zip

16 - Daemon Threads Background Execution Presentation.mp4

02:16

17 - Daemon Threads Background Execution Code.mp4

02:49

17 - deamon-threads.zip

5 - Advanced Threading Techniques

18 - Thread Synchronization Using Locks Presentation.mp4

03:59

19 - Thread Synchronization Using Locks Code.mp4

04:23

19 - lock.zip

20 - Deadlocks Identification and Prevention Presentation.mp4

05:44

21 - Deadlocks Identification and Prevention Code.mp4

07:25

21 - deadlock.zip

22 - Condition Variables and Wait Groups Presentation.mp4

04:04

23 - Condition Variables and Wait Groups Code.mp4

05:47

23 - condition-variables.zip

24 - Using Barriers in Threading Presentation.mp4

04:51

25 - Using Barriers in Threading Code.mp4

03:56

25 - barrier.zip

6 - Introduction to Multiprocessing in Python

26 - Understanding Processes in Python Presentation.mp4

04:11

27 - Understanding Processes in Python Code.mp4

02:39

27 - create-process.zip

28 - Creating and Managing Processes Presentation.mp4

02:46

29 - Creating and Managing Processes Code.mp4

03:51

29 - creating-and-managing-processess.zip

30 - Memory Sharing Between Processes Presentation.mp4

04:31

31 - Memory Sharing Between Processes Value Code.mp4

03:56

31 - memory-sharing-value.zip

32 - Memory Sharing Between Processes Array Code.mp4

05:28

32 - memory-sharing-array.zip

33 - Communication Between Processes Pipes and Queues Presentation.mp4

04:29

34 - Communication Between Processes Pipes and Queues Code Part 1.mp4

04:12

34 - pipe-example.zip

35 - Communication Between Processes Pipes and Queues Code Part 2.mp4

06:33

35 - queue-example.zip

7 - Practical Applications of Threading and Multiprocessing

36 - File Searching with Threads and Processes Presentation.mp4

03:55

37 - File Searching with Threads and Processes Code.mp4

04:49

37 - file-searching.zip

38 - Matrix Multiplication Comparing Single and Multithreaded Presentation.mp4

05:50

8 - Pooling Techniques in Python

39 - Using ThreadPoolExecutor and ProcessPoolExecutor Presentation.mp4

04:22

40 - Using ThreadPoolExecutor and ProcessPoolExecutor Code.mp4

03:53

41 - Realworld Applications of Pools Presentation.mp4

03:38

42 - Realworld Applications of Pools Code.mp4

04:39

42 - image-resize.zip

43 - Debugging Multithreaded and Multiprocess Applications Presentation.mp4

06:14

44 - Debugging Multithreaded and Multiprocess Applications Code.mp4

03:59

45 - Extra Content Creating Logger class using logging library Code.mp4

04:55

45 - logger.zip

9 - Course Conclusion and Next Steps

46 - Review and Key Takeaways.mp4

03:22

47 - Additional Resources for Advanced Learning.html

Description

Parallel Programming in Python: Mastering Threading & Processing for Efficient Concurrency

What You'll Learn?

Fundamentals of Python Programming: Refresh your knowledge on Python basics including functions, classes, modules, and decorators.
Concurrency vs. Parallelism: Understand the difference and when to use each in your applications.
Introduction to Threading in Python: Learn how to create, manage, and synchronize threads using the threading module.
Deep Dive into the Global Interpreter Lock (GIL): Discover how the GIL affects multithreading in Python and strategies to work around it.
Basics of Multiprocessing: Utilize the multiprocessing module to run code across multiple CPU cores for true parallelism.
Process Communication: Master techniques for sharing data and messages between processes to build efficient parallel applications.
Advanced Threading and Multiprocessing Techniques: Explore thread pools, process pools, locks, semaphores, and condition variables to handle complex concurrency
Debugging and Optimizing: Learn how to debug and optimize threaded and multiprocessed applications for maximum performance.
Best Practices: Gain insights into best practices for writing clean, efficient, and scalable concurrent code.

Who is this for?

Intermediate Python Developers: Programmers with a solid foundation in Python looking to enhance their skills in concurrency for improved application performance.

Software Engineers: Professionals seeking to understand and implement parallel processing and threading in their Python projects.

Data Scientists and Analysts: Individuals aiming to speed up data processing tasks through parallel computing techniques.

Tech Enthusiasts: Anyone curious about how concurrent programming works in Python and eager to apply these concepts in practical scenarios.

System Administrators and DevOps Professionals: Those looking to automate and optimize tasks using Python's concurrency features for better system management.

Students and Academics: Learners in computer science or related fields seeking to deepen their understanding of concurrent programming principles and practices.

What You Need to Know?

Basic Python Knowledge: Familiarity with Python syntax and basic programming constructs such as variables, loops, and functions.

Understanding of Python Data Structures: Comfortable working with lists, dictionaries, sets, and tuples.

Introductory Level of Object-Oriented Programming: Basic understanding of classes and objects in Python.

Software Requirements: Python installed on your computer (version 3.x recommended) along with an integrated development environment (IDE) or text editor of your choice.

A Willingness to Learn: An open mind and readiness to dive into the more complex topics of multithreading and multiprocessing.

More details

Description
Unlock the Power of Concurrent Programming with Python
Welcome to "The Complete Guide to Python Multithreading and Multiprocessing," your comprehensive journey into the world of parallel programming in Python. Whether you're looking to boost the performance of your applications or simply curious about how concurrent programming works, this course is designed to equip you with the skills and knowledge you need to master threading and processing in Python.

What You Will Learn
Throughout this course, we will delve deep into the essentials and advanced concepts of multithreading and multiprocessing in Python. Starting with the basics, you'll first get acquainted with Python's programming environment and fundamental concepts. As we progress, you'll:
Understand the difference between concurrency and parallelism, and when to use each.
Explore the threading module to create, manage, and synchronize threads efficiently.
Dive into Python's multiprocessing module to execute processes in parallel, enhancing your application's performance.
Learn about process communication and memory sharing between processes, crucial for complex parallel applications.
Apply your knowledge through practical, real-world examples, from file searching to web scraping and matrix multiplication.
Tackle advanced topics such as thread and process pooling, deadlock identification, prevention, and debugging techniques for concurrent programming.

Who Is This Course For?
This course is designed for:
Programmers and developers with a basic understanding of Python looking to enhance their skills.
Software engineers are interested in making their applications faster and more efficient through parallel programming.
Anyone curious about how concurrency works in Python and eager to apply these concepts to real-world problems.

Why Choose This Course?
Comprehensive Curriculum: From the foundational concepts to advanced techniques, this course covers everything you need to know about multithreading and multiprocessing in Python.
Practical Application: Learn through doing hands-on exercises and real-world examples that ensure you can apply what you've learned immediately.
Expert Instruction: Benefit from detailed explanations and tips from an experienced developer who's passionate about making concurrency accessible to everyone.

Join us on this journey through the powerful world of concurrent programming in Python, and unlock the potential to create faster, more efficient, and scalable applications. Enroll in "The Complete Guide to Python Multithreading and Multiprocessing" today and take the first step towards mastering Python parallel programming.

Idan Chen
Who this course is for:
Intermediate Python Developers: Programmers with a solid foundation in Python looking to enhance their skills in concurrency for improved application performance.
Software Engineers: Professionals seeking to understand and implement parallel processing and threading in their Python projects.
Data Scientists and Analysts: Individuals aiming to speed up data processing tasks through parallel computing techniques.
Tech Enthusiasts: Anyone curious about how concurrent programming works in Python and eager to apply these concepts in practical scenarios.
System Administrators and DevOps Professionals: Those looking to automate and optimize tasks using Python's concurrency features for better system management.
Students and Academics: Learners in computer science or related fields seeking to deepen their understanding of concurrent programming principles and practices.

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Python

‪Idan Chen‬‏

Instructor's Courses

Hello, I'm Idan Chen, a data scientist, and lead researcher based in Israel. I hold a Bachelor's degree in Computer Science and have gained several years of experience working with data, including over 6 years of expertise using Python. Through my work, I have gained extensive knowledge of both SQL and NoSQL database systems and have a deep understanding of libraries such as Pandas.One of my greatest joys is guiding and teaching others. Over the years, I have had the privilege of helping both individuals and companies to learn more about Python and SQL, providing guidance on concepts and best practices. I am passionate about sharing my knowledge and experience with others and firmly believe that anyone can become a successful data scientist with the right tools and guidance.Whether you're seeking to improve your data analysis skills, gain more knowledge about machine learning, or dive deeper into Python and SQL, I am here to help. As an instructor at Udemy, I am committed to providing students with the necessary tools to achieve their goals and succeed. I am thrilled to share my expertise with you and help you reach your full potential in the field of data science.

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