Explanation
In this course you’ll learn how to create nested, multi-threaded programs in Python, so you can make your programs faster. For applications that are connected to other resources, more time is spent just waiting for information to be transmitted elsewhere. You will learn how to use multi-threading as well as asynchronous programming to speed up programs that are heavily constrained by IO operations. We’ll first introduce where the speed bumps can come from and how we can solve them, then dive right into the technical content and put together a series of programs. from which data is collected. on the internet, parse it, and store it in a local database.
Other programs may be more affected by CPU limitations. We will also learn how to implement multithreading in Python, a library that allows us to use multiple CPUs in Python code. With this we will be able to spread our workload across all available cores on the machine we are using. Finally, we will also look at combining the two elements, looking at how we can use multiprocessing together with asynchronous programming to get the most benefit for yourself, increasing your use of CPU resources and reducing the time you spend in a session. – no waiting for IO response.
What will you learn?
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How to use compare and contrast in Python
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How to write multi-threaded programs
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How to write multi-process programs
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How to write asynchronous programs
Who is this course for?
- Python developers who want to make their programs faster by adding integration
Specifications of Concurrent and Parallel Programming in Python
- Publisher: Udemy
- Teacher: Maximilian Schallwig
- Language : English
- Level: Medium
- Number of courses: 28
- Duration : 6 hours and 7 minutes
Essentials of Parallel and Parallel Programming in Python
Requirements
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Basic knowledge of Python
Pictures
Sample Clip
Installation Guide
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Subtitle : English
Quality: 720p
Download Links
Password file: free download software
file size
2.12GB