Tutorial Playlist

Python Tutorial for Beginners

Overview

How to Install Python on Windows?

Lesson - 1

Python OOPs Concept: Here's What You Need to Know

Lesson - 2

Getting Started With Jupyter Network

Lesson - 3

PyCharm Tutorial: Getting Started with PyCharm

Lesson - 4

A Beginner’s Guide To Python Variables

Lesson - 5

Python Numbers: Integers, Floats, Complex Numbers

Lesson - 6

Learn A to Z About Python Functions

Lesson - 7

The Basics of Python Loops

Lesson - 8

Introduction to Python While Loop

Lesson - 9

Python For Loops Explained With Examples

Lesson - 10

Understanding Python If-Else Statement

Lesson - 11

Introduction to Python Strings

Lesson - 12

Everything You Need to Know About Python Slicing

Lesson - 13

All You Need To Know About Python List

Lesson - 14

Python Regular Expression (RegEX)

Lesson - 15

An Introduction to Python Threading

Lesson - 16

Objects and Classes in Python: Create, Modify and Delete

Lesson - 17

The Best Python Pandas Tutorial

Lesson - 18

A Beginner's Guide To Web Scraping With Python

Lesson - 19

A Handy Guide to Python Tuples

Lesson - 20

How to Easily Implement Python Sets and Dictionaries

Lesson - 21

Everything You Need to Know About Python Arrays

Lesson - 22

An Introduction to Matplotlib for Beginners

Lesson - 23

An Introduction to Scikit-Learn: Machine Learning in Python

Lesson - 24

Top 10 Python IDEs in 2020: Choosing The Best One

Lesson - 25

The Best NumPy Tutorial for Beginners

Lesson - 26

Python Django Tutorial: The Best Guide on Django Framework

Lesson - 27

Top 10 Reason Why You Should Learn Python

Lesson - 28

How To Become a Python Developer

Lesson - 29

Top 50 Python Interview Questions and Answers in 2020

Lesson - 30
An Introduction to Python Threading

Python is one of the most popular and versatile programming languages available today, deployed across many industries and used for web development, machine learning, and data science. Given its widespread use and high demand in interrelated fields such as machine learning and big data, it's not surprising that Python has surpassed Java as the top programming language. 

In this article, you will learn about Python threading and how it works. We’ll cover:

  • What is Python threading?
  • What is the process?
  • Advantages of threading
  • Daemon thread
  • Python threading functions
    • threading.active_count()
    • threading.main_thread()
    • threading.timer()
  • Synchronization using lock

What is Python Threading?

Threading is a sequence of instructions in a program that can be executed independently of the remaining process. You can see them as different units of your process that do jobs independently when scheduled. If they need to wait for a slow external operation to finish (such as a network request, or disk access), they sleep for a while and enable the scheduler to spend time executing another thread. 

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What is the Process?

A process is an executable instance of a computer program. Usually, a process is executed in a single sequence of control flow. 

Advantages of Threading

  • Threaded programs run faster on computer systems that have multiple CPUs. 
  • Threads of a process can share the memory of global variables. If the variable's value is changed in one thread, it is applicable for all threads.

basic-python

Fig: Basic Python threading program

The above code executes as follows. We have imported the threading module and created a method thread labeled 't.' This thread 't' will run show() function because that is the target of a particular thread.  

There are two types of thread:

  1. Daemon thread
  2. Non-daemon thread

Daemon Thread

A daemon thread runs without blocking the main program when it exits and when associated daemon threads are also killed.

Example:

daemon

Fig: Daemon thread

We create a daemon thread by adding extra argument daemon = true. 

We added an extra argument—daemon = true—which created a daemon thread.

Python Threading Functions

1. threading.active_count()

 This function tells us about the number of threads in execution.

Example:

/threading.

Fig: threading.active_count()

2. threading.main_thread()

This function returns the main thread in the program.

Example:

/threading-main

Fig: threading.main_thread()

3. threading.Timer()

This function is used to create a new thread and specify the time after which it should start. Once it starts, it should call the specified function.

Example:

https://s3.amazonaws.com/static2.simplilearn.com/ice9/free_resources_article_thumb/threading-timer.JPG

Fig: threading.Timer()

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Synchronization Using Lock

The lock helps us in the synchronization of two or more threads. It has two primary methods: acquire() and release().

acquire() method is used to acquire the lock. 

release() is used to free an acquired lock. 

Example:

/lock

Fig: lock() function in Python threading

Conclusion

In this article, we explored the basic concepts of Python threading. We learned about the different functions and objects associated with threading. 

If you have any questions or concerns, please share them in the comments section, and we'll have our experts get back to you.

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About the Author

Aryan GuptaAryan Gupta

Aryan is a tech enthusiast who likes to stay updated about trending technologies of today. He is passionate about all things technology, a keen researcher, and writes to inspire. Aside from technology, he is an active football player and a keen enthusiast of the game.

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