Published 12/2024
Created by Chandrashekar Babu
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 12 Lectures ( 5h 30m ) | Size: 6.74 GB
Master the craft of making Python code run faster comparable to code written in C/C++ and Rust programming languages
What you’ll learn
Compare performance of a simple compute intensive program in Python, C, Java, Rust and Go
Learn how to make your python code faster comparable to similar code written in C and Rust
Learn the tips and techniques to improve performance of Python code
Learn how to use PyPy, Pythran, Cython and Numba to improve performance of Python code
Learn about the limitations and best practices for using PyPy, Pythran, Cython and Numba
Learn how to improve performance of Threads in Python
Requirements
Basic Knowledge of Python Programming
Description
There’s a famous quote that says “If you want to code faster, use Python; but if you want your code to run faster – just use C”!In this course – Python Performance Hacks – Part 1: Make Your Code Run Faster, I will teach how to make your python code run as fast as those written in C/C++/Rust. You will learn practical, hands-on techniques to enhance the speed and efficiency of your Python applications. This course is designed for Python developers who want to maximize performance without sacrificing code readability or maintainability. Whether you’re developing web applications, data analysis scripts, or backend processes, you’ll find the skills to optimize your code for high performance without sacrificing the great features, benefits and the essence of Python programming language.In this course, we’ll dive into the essential strategies for improving Python performance, covering tools and alternative language runtimes that perform Just-In-Time compilation, Ahead-Of-Time optimization and much more. You will learn how to make your python code run fast comparable to code written in C/C++/Rust. You will also learn about the best practices and use-case scenarios for these tools in your python code. You will also learn tricks to parallelize threads (circumventing the limitations of Global-Interpreter-Lock or GIL).By the end of this course, you’ll have a toolkit of performance-enhancing techniques to take your Python skills to the next level. Say goodbye to slow-running programs and hello to code that’s lean, powerful, and optimized for speed. Enroll to this course to transform your Python skills and make your code run faster than ever!
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