Mastering Python - Second Edition: Write powerful and efficient code using the full range of Python's capabilities 2nd ed. Edition

If you are an intermediate python programmer I think "Mastering Python" from Rick Van Hattem could be a great addition to your library. After have programming for a few years my skills got to the point where you can solve most problems I came across, but I still felt like I wanted to learn more complicated concepts and wanted to write code that was more efficient. One area that I wanted to learn more about and multiprocessing and multi threading, Rick Van Hattem did a really nice job approaching this concept, much better than what I have read on the the internet.This book should be able to take your python skills to the next level. In addition to that I really enjoyed his explanation of classes, structures, decorators, generators, and coroutines. In case you need a refresher on environments or dependencies and other basic concepts the book also has you covered. That being said if you are new to python programming, I am not sure this would be my 1st book to purchase, it might be a little overwhelming give it has 700 pages of content. If you want to improve you knowledge and skills this is a nice book to have in your library.

Overall amazing combination of all the content in a single book for python. It is quite comprehensive.It gives a brief idea with examples which he starts from environment/package management, to docstrings, list, set and dict, hinting and testing, and many more.If you are a recent graduate or have started working on python recently, then you have lots to learn from this book in systematic format.Even if you have worked for around 3+ years in python this book will teach you some of the most basic tricks which will be helpful in day to day coding and shortening the code.This book has a chapter for machine learning for those folks who want to get some help in ML and Python coding.Overall this book is nice and would provide good information for new grads and someone with 3-4+ years of python exp.

The book has has an excellently laid out structure. Although, it does say that the book is not for beginners, I feel like it is - which is a good thing as more people would be able to understand the book. The content covered seems comprehensive and it is well written. Topics covered are highly useful for someone starting python.That being said, I also have some concerns. The book sometimes tends to use redundant words - again not a bad thing. For example, in the numpy chapter, I read something like “numpy.ndarray object is implemented in C and offers a very fast and memory-efficient array. It can be represented as a single-dimension array or a multi-dimensional matrix ”. We already established the fact that numpy is fast and is written in C, why would you repeat it again for a function of numpy? Another thing, if you look at it, arrays are always single dimension. The moment we add one more dimension to an array, it becomes a matrix and similarly, a single dimension matrix is nothing but an array. In mathematics, we tend to treat things as matrices and vectors - so I can essentially treat vectors as arrays in python - if you get the idea. Now, this is not a bad thing because, beginners might not be knowing this - so although this seems to be extra information - it’s in good taste.I also noticed that the book sometimes over-explains some topics like one above and sometimes under-explains a topic. For example for the same numpy chapter, There is a point where the book says, calculations on matrices is much faster/efficient. My question is why is it so?Other than these small caveats (which probably won’t change anything from a reader’s perspective), the book is very good. Only thing, I didn’t like is that how the book handles the ML/AI chapters. It’s not the worst thing I’ve seen, but it’s certainly not the best. The book relies on definitions and code without talking about the underlying mathematics. You can’t just completely obliterate all the mathematics, even if the book was for beginners. There’s no machine learning without mathematics and if you’re covering it, you should cover numerical algebra and probability theory. For the most part, I feel like this AI/ML chapter could be a completely different book, but that’s just my opinion - the book provides a good enough introductory code but again, unfortunately, I don’t like it.There are few more small things which might make this book seem unpolished, but I think I have already said too much and most of those things would be considered nitpicking, I guess. So, in conclusion, the book is great, great insights, well structured and comprehensive. A few things here and there can be touched upon and they can make it perfect.

I know python at a decent level but I’m always looking for more books to pick up new ideas and ways of coding. Good book for my needs. Probably not the friendliest book for a total beginner.

Mastering Python, 2nd ed. (Seconda edizione, lingua Inglese)L’AUTORE e IL LIBRO:L'autore da Rick van Hattem è raggiungibile nel canale Discord dedicato al libro e in questa seconda edizione il libro edito da Packt Publishing è incentrato nella presentazione dei concetti avanzati e offre esempi chiari e ben documentati. L’introduzione “Usa le funzionalità avanzate di Python per scrivere codice e pacchetti leggibili e di alta qualità” dai più smaliziati potrebbe essere colto come una raccolta di esempi di soluzioni, lo è ed è molto comodo.Il centro del libro sono le novità di Python 3.10, ed è dettagliatamente descritto nei minimi particolari, con esempi commentati e spesso calati nella realtà di un programmatore. Quindi nella versione elettronica potrà essere una ottima fonte di soluzioni da cui prendere spunto.PER CHI È E PER CHI NON È?Mastering Python è una fonte di soluzioni e idee per chi sa già cosa desidera ottenere da Python nella release stabile più recente (siamo ancora alla 3.10.6). Le breve introduzioni e il codice commentato rendono tutto più semplice e più pratico.Il libro per quanto chiaro e bel strutturato, con crescendo di difficoltà, non è per chi si è appena affacciato al mondo della programmazione. Lo trovo più indicato a chi sa già programmare in altri linguaggi e vuole imparare Python con una curva di apprendimento corta.RICOMPREREI ALTRE EDIZIONI?Sì, per me questo libro vale i soldi spesi. Ho scelto la versione Kindle per la comodità di ricercarlo e poterlo leggere sia sui dispositivi che sul computer partendo dal sito leggi[.]amazon[.]itIl libro è disponibile sul sito dell’editore Packt Publishing oltre alla versione cartaceo anche in vari formati elettronici, tra cui pdf, epub… etc.SOMMARIO (liberamente tradotto):Capitolo 1: Un ambiente (virtuale) per il progettoCapitolo 2: Interpreti Python interattiviCapitolo 3: Sintassi Python e insidie ​​comuniCapitolo 4: Pattern di progettazione PythonCapitolo 5: Programmazione funzionale: leggibilità contro brevitàCapitolo 6: Decoratori – Abilitazione del riutilizzo del codice decorandoCapitolo 7: Generatori e Coroutine – L'infinito, un passo alla voltaCapitolo 8: Metaclassi: rendere le classi (non le istanze) più intelligentiCapitolo 9: Documentazione – Come usare Sphinx e reStructuredTextCapitolo 10: Test e log – Preparazione ai bugCapitolo 11: Debug – Risoluzione dei bugCapitolo 12: Prestazioni: monitoraggio e riduzione dell'utilizzo della memoria e della CPUCapitolo 13: asyncio – Multithreading senza threadCapitolo 14: Multiprocessing – Quando un singolo core della CPU non è sufficienteCapitolo 15: Uso di Python in ambito scientifico e graficiCapitolo 16: Intelligenza ArtificialeCapitolo 17: Estensioni in C/C++, chiamate di sistema e librerie C/C++Capitolo 18: Packaging – Creazione di librerie o applicazioni personalizzate

O livro é grande, mas tem uma leitura muito suave e rápida visto ter imensas referências que são boas para se conhecer mas não ser um especialista nelas. Uma excelente opção para guiar e moldar um developer Python com alguns anos de experiência.A qualidade da impressão é um bocado fraca.

The book lacks depth, it gives you one page on NLTK, one page on Spacy, One page on gensim. Similarly for seaborn, bokeh, matplotlib, similarly for pytorch, sklearn and tensoflow... No topic is elaborated. The topics which are elaborated are useful but only if this is the only book which contained it A book like fluent python is much better choice. What i hated about the book about that, the code on black window. Sooner or latee the black ink will be going to stick on other page as well. There were no thought, on how to put the code on book. There is nothing power packed about the book. Useless, don't waste your money. Packt all the recent publications on python lacks depth. Please print something which has depth even if it contains 5 topics. The book has many topics but you can just read it, you can't try to make anything useful from the 2 paragraph introduction. I am sorry but not a useful book at all

The book is not well bonded at all