How does Python enables computation parallelization? Git Concepts and Workflow for Beginners Majority of our computers now have a multi-core architecture, and terms as multi-threading are often ringing to our ears as a way to improve the processing efficiency of applications. Python does offer several tools to parallelize computation, but they are not often well known. Let’s pierce their secrets in this article.
Majority of our computers now have a multi-core architecture, and terms as multi-threading are often ringing to our ears as a way to improve the processing efficiency of applications. Python does offer several tools to parallelize computation, but they are not often well known. Let’s pierce their secrets in this article.
First a small reminder about threading. What is a thread? It’s a lightweight process that run on your computer, executing it’s own set of instructions. When you run two programs on your computer, you actually create two processes. Each of them has a set of instructions(open your browser or increase the volume) that they want to be processed by the scheduler (the referee who decides who gets first). The particularity of threads versus processes is that they can share variables.
For us in terms of coding, when we run two threads, we allow two pieces of code to run at the same time. It is however different that just executing two programs at the same time since threads give us more control. For example we can share some variables between threads or we can wait for the threads to finish, merge the results and go on with the rest of the code. It is a very powerful tool that can allow faster computation or the ability to handle concurrent events (think of robots with multiple sensor data to process).
Let’s digress a bit and analyze the different possibilities Python offers to run computation in parallel. The three laureates are: Threads,** Thread Pools, and **Multi-Processing.
The most Python programs will consist of three steps — getting input into the program, processing the input in some way, and outputting the results of the processing. I’m going to focus on one part of that step — getting input into a program — by prompting the user to enter some data and then reading the data into the program. This is a mostly straightforward process except for some data conversions that have to occur when you are inputting numbers.
In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.
This LIVE session on 'Python Libraries' will help you understand the topmost trending Python libraries toy must learn.
Today you're going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates. We gonna use Python OS remove( ) method to remove the duplicates on our drive. Well, that's simple you just call remove ( ) with a parameter of the name of the file you wanna remove done.
Basic programming concept in any language will help but not require to attend this tutorial