Mastering python high performance

Fernanperform Doglio"s book "Mastering Python High Performance" is filled via interesting conceptual occupational and also understanding. It"s excellent for Python developers looking to bolster code performance.

You watching: Mastering python high performance


*
by

Packt Publishing recently sent out me a copy of Mastering Python High Performance by Fernando Doglio. They additionally had actually me be a technical reviewer of the book before its publication. Anymeans let’s do a quick testimonial and also if you think it sounds interesting, you have the right to examine out my complete testimonial too!

Rapid Review

Why I picked it up: I got it for totally free, yet I did find the title intriguing. Why I finimelted it: As a technological reviewer of the book, I had to review it all the method with. However, it has actually most interesting ideas and it was short.I’d provide it to: Someone that demands to learn about exactly how to rise their Python code’s performance.

Publication Formats

You deserve to obtain an eBook (PDF, EPUB or MOBI) version or a softcover.

Book Contents

The book is separation up into 8 chapters via 235 peras.

Full Review

When I was originally analysis this book, I was interested in seeing just how the author would certainly speed up their code. He covers a broad selection of topics which is excellent, but that likewise hampers the book as namong the topics are covered in depth. He provides numerous small examples and reflects just how to profile prior to relocating on to optimizing them. Let’s go over each of the chapters so you can obtain a taste of what the book covers.

Chapter one is all around profiling your code. It covers the distinctions between statistical and event-based profiling, what profiling is and why it’s important, bottlenecks and also memory leaks. It also goes over running time intricacy (linear, factorial, quadratic, etc) and profiling best practices.

See more: Book Summary And Reviews Of Dear Daughter Book Review, Dear Daughter

Then we logically move into chapter 2 wright here we learn around some profilers we can usage through Python. The two that are covered are cProfile (consisted of with Python) and also line_profiler. The author demonstprices various ways to use cProfile to meacertain your code and also exactly how to usage Python’s pstats module, which is used for analyzing the outcomes you obtain from cProfile. Then the writer moves on to utilizing line_profiler and also kernprof to analyze the same (or similar) examples used through cProfile. I think this is one of the ideal balanced chapters in the book and really fairly amazing all by itself.

Chapter 3 goes right into making use of visual devices to aid you understand your profiler’s output. In this chapter, you will certainly learn around KCacheGrind / pyprof2calltree and RunSnakeRun. For the many part, you’ll just learn how to use these devices to figure out what your data means.

Chapter 5 digs into multithreading and also multiprocessing. You’ll learn around the pros and cons of each. You will additionally learn about the Global Interpreter Lock and also just how that affects you as soon as you pick one of these approaches.

Chapter 6 goes right into utilizing PyPy and also Cython and exactly how they have the right to be valuable for additional optimizations to your code. I delighted in this chapter, although I didn’t feel that PyPy acquired as a lot attention as Cython. Tright here likewise weren’t extremely many type of coding examples.

If you’re right into number crunching, then chapter salso is for you. It goes over exactly how to use Numba, Parakeet, and pandas. Quite frankly, out of the 3 of libraries, I had actually just ever heard of pandas. I personally don’t must carry out many number crunching in my line of work, but it was amazing to view how each of the libraries operated and get a basic concept of what they might be supplied for.

Finally in chapter eight, the writer attempts to put it all together. This chapter more than likely must have been twice as long as it is so that he could have actually covered every little thing. But in the finish, it covers simply barely sufficient and also you execute get to watch a complete instance gain optimized from beginning to finish.

Overall, I delighted in this book. I would recommfinish this to anyone that requirements principles for optimizing their Python code or simply for learning about profiling in basic.