Alec  Nikolaus

Alec Nikolaus

1600999200

Understanding Python Multithreading and Multiprocessing via Simulation

Python is a great general-purpose language with applications in various fields. However, sometimes you just hope it can speed up further. One way to improve the speed is to parallel the works, with either multithreading or multiprocessing.

There are numerous great resources out there that illustrate the concepts of both. To not duplicate the efforts, here are a few I found very helpful.

In this article, I want to provide a simple simulation for anyone who wants to explore the concepts further and test it out on their own laptop. So here we go!

#multiprocessing #python #programming #simulation #multithreading

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Buddha Community

Understanding Python Multithreading and Multiprocessing via Simulation
Ray  Patel

Ray Patel

1619518440

top 30 Python Tips and Tricks for Beginners

Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.

1) swap two numbers.

2) Reversing a string in Python.

3) Create a single string from all the elements in list.

4) Chaining Of Comparison Operators.

5) Print The File Path Of Imported Modules.

6) Return Multiple Values From Functions.

7) Find The Most Frequent Value In A List.

8) Check The Memory Usage Of An Object.

#python #python hacks tricks #python learning tips #python programming tricks #python tips #python tips and tricks #python tips and tricks advanced #python tips and tricks for beginners #python tips tricks and techniques #python tutorial #tips and tricks in python #tips to learn python #top 30 python tips and tricks for beginners

Ray  Patel

Ray Patel

1619510796

Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Alec  Nikolaus

Alec Nikolaus

1600999200

Understanding Python Multithreading and Multiprocessing via Simulation

Python is a great general-purpose language with applications in various fields. However, sometimes you just hope it can speed up further. One way to improve the speed is to parallel the works, with either multithreading or multiprocessing.

There are numerous great resources out there that illustrate the concepts of both. To not duplicate the efforts, here are a few I found very helpful.

In this article, I want to provide a simple simulation for anyone who wants to explore the concepts further and test it out on their own laptop. So here we go!

#multiprocessing #python #programming #simulation #multithreading

August  Larson

August Larson

1625032260

Multithreading vs. Multiprocessing in Python

Part I Talking In Theory

Before we start discussing multithreading and multiprocessing, let me briefly introduce what is **process **and thread in computer and program:

  • A process is what we call a program that has been loaded into memory along with all the resources it needs to operate.
  • A thread is the unit of execution within a process.
  • A process can have multiple threads running as a part of it, each thread uses the process’s memory space and shares the same memory space with other threads while the processes have separate memory.

After knowing the relationship between processes and threads, now we could forward to dig into the details of them as well as practically using python code to see how they speed up the program.

#multiprocessing #threads #multithreading #programming #python #multithreading vs. multiprocessing in python

Ray  Patel

Ray Patel

1619708820

How To Run Python Code Concurrently Using Multithreading

A machine learning enthusiast with a knack for finding patterns.…

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Free Online Resources To Get Started On Cloud Computing

Multithreading enables CPUs to run different parts(threads) of a process concurrently. But what does that mean? Processes can be divided into different parts; let’s take the example of an online multiplayer game. One thread of the game could be responsible for communicating with the servers and rendering the graphics. The communication thread requires minimal computation and would involve some wait time, on the other hand, the render thread is computationally intensive with minimal wait time. Multithreading enables the CPU to run the render thread while the communication thread is waiting for a response from the server, increasing the CPU utilisation.

Note that multithreading is not to be confused with multi-processing. Modern CPUs have multiple cores; multi-processing utilizes these cores to run processes in parallel. Multithreading, however, aims to maximize the utilization of each of these cores by running multiple threads concurrently. Multithreading is useful when the task has IO or network operations that involve waiting; multiprocessing makes computation-intensive tasks of a process faster. Continuing the online game example, the render thread of most games are run in parallel on a GPU with thousands of cores, each thread rendering different aspects of the game. While the communication and IO threads are run concurrently on the CPU.

#developers corner #creating a thread in python #multiprocessing #multithreading #multithreading in python #python multithreading