Curated Video
Java Multithreading and Parallel Programming Masterclass - Parallel Versus Concurrent Versus Asynchronous Versus Non-Blocking
This video explains the difference between parallel versus concurrent versus asynchronous versus non-blocking concepts.
Curated Video
Concurrent and Parallel Programming in Python - Combining Async and Multiprocessing
Combining Async and Multiprocessing
Curated Video
Concurrent and Parallel Programming in Python - The Async Wait Statement
In this video, we will look at how we can wait for specific tasks to complete before we execute the code we want to run. Unlike the gather function that waits for all tasks to complete before running a code, this statement waits for...
Curated Video
Concurrent and Parallel Programming in Python - Using Asynchronous Libraries
Here, you will learn how some libraries support asynchronous libraries, and others do not. You will also learn to look for those libraries and compare them.
Curated Video
Concurrent and Parallel Programming in Python - Creating Asynchronous For Loops
This lesson elaborates on what a for loop does and does not do in an asynchronous program code.
Curated Video
Concurrent and Parallel Programming in Python - Using Async Timeouts
This video will explain what a timeout does in asynchronous programming and how to place timeouts in our syntax.
Curated Video
Concurrent and Parallel Programming in Python - Async Gather Method
Let's understand how to combine two APIs using the gather method with the await function. Here, the function waits for all tasks to complete before executing the next task assigned.
Curated Video
Concurrent and Parallel Programming in Python - Asynchronous Tasks
Here, you will learn to assign asynchronous functions to tasks to execute on the asynchronous syntax.
Curated Video
Concurrent and Parallel Programming in Python - Introduction to Writing Asynchronous Programs
In this video, we will understand what asynchronous programming is and the fundamental differences between synchronous and asynchronous programming. We will also write our first asynchronous program.
Curated Video
Concurrent and Parallel Programming in Python - Multiprocessing Checking Elements in List in Certain Ranges
In this video, we will finally revisit the initially more CPU-intensive functions we were using, which will be checking how many values in our comparison list are in a specific range.
Curated Video
Concurrent and Parallel Programming in Python - Multiprocessing Multiple Varying Arguments
In the previous video, we have seen how to provide additional arguments using a partial library in the functools built-in tool; you will now learn to add different elements such as a power list instead.
Curated Video
Concurrent and Parallel Programming in Python - Multiprocessing Pool Map Multiple Arguments
Let's learn how to pass multiple arguments, passing lists instead of elements in a list or class while executing a code.
Curated Video
Concurrent and Parallel Programming in Python - Multiprocessing Pool
After learning how to distribute the work by multiprocessing over different CPUs, you will learn to replicate the process over a multiprocessing program surrounding multiprocessing classes.
Curated Video
Concurrent and Parallel Programming in Python - Multiprocessing Queues
Now that we have understood multiprocessing, you will learn how to split our segments over multiple processes in the form of queues to speed up processing and take a load off the process execution.
Curated Video
Concurrent and Parallel Programming in Python - Multiprocessing Introduction
Here, we will understand multiprocessing and monitor how our CPU functions during multiprocessing.
Curated Video
Concurrent and Parallel Programming in Python - Locking
This lecture will cover the locking process and things we need to vary when threading.
Curated Video
Concurrent and Parallel Programming in Python - Final Program Cleanup
Apart from a final cleanup to make our project more functional, you will learn to create local environment variables for actual testing.
Curated Video
Concurrent and Parallel Programming in Python - Improving All Workers and Adding Monitoring
In this lecture, you will learn to clean up the Yaml pipeline executor, load the pipeline, initialize it, and join it to your main class.
Curated Video
Concurrent and Parallel Programming in Python - Improving Our Wiki Worker
After successfully creating and defining our Yaml reader, we will implement this into our main class.
Curated Video
Concurrent and Parallel Programming in Python - Creating a Yaml Reader
Now that we have the Yaml pipeline defined, we will implement something to read this file or any other file that has a queue worker structure to create our pipeline for us.
Curated Video
Concurrent and Parallel Programming in Python - Yaml File Introduction
After creating a working program, you will learn how to clean up the appearance and make it nicer to have an overview and be able to expand its features in the future.
Curated Video
Concurrent and Parallel Programming in Python - Integrating the Postgres Worker
After creating our Postgres database insertion worker, we will integrate this worker into our main function and make changes to ensure that everything is working properly.
Curated Video
Concurrent and Parallel Programming in Python - Creating a Postgres Worker
In this lesson, we will create our instruction worker using a Postgres database.
Curated Video
Concurrent and Parallel Programming in Python - Queues and Master Scheduler
In the previous lessons, you learned how to set up our Wikipedia reader and the Yahoo Finance worker; we will now systemize the process and create separate process entities. You will learn to create queues, take elements, and place them...