PDF Ebook Python Cookbook, Third edition, by David Beazley, Brian K. Jones
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Python Cookbook, Third edition, by David Beazley, Brian K. Jones
PDF Ebook Python Cookbook, Third edition, by David Beazley, Brian K. Jones
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If you need help writing programs in Python 3, or want to update older Python 2 code, this book is just the ticket. Packed with practical recipes written and tested with Python 3.3, this unique cookbook is for experienced Python programmers who want to focus on modern tools and idioms.
Inside, you’ll find complete recipes for more than a dozen topics, covering the core Python language as well as tasks common to a wide variety of application domains. Each recipe contains code samples you can use in your projects right away, along with a discussion about how and why the solution works.
Topics include:
- Data Structures and Algorithms
- Strings and Text
- Numbers, Dates, and Times
- Iterators and Generators
- Files and I/O
- Data Encoding and Processing
- Functions
- Classes and Objects
- Metaprogramming
- Modules and Packages
- Network and Web Programming
- Concurrency
- Utility Scripting and System Administration
- Testing, Debugging, and Exceptions
- C Extensions
- Sales Rank: #15747 in Books
- Published on: 2013-06-01
- Original language: English
- Number of items: 1
- Dimensions: 9.21" h x 1.45" w x 7.02" l, 2.50 pounds
- Binding: Paperback
- 706 pages
About the Author
David Beazley is an independent software developer and book author living in the city of Chicago. He primarily works on programming tools, provide custom software development, and teach practical programming courses for software developers, scientists, and engineers. He is best known for his work with the Python programming language, for which he has created several open-source packages (e.g., Swig and PLY) and authored the acclaimed Python Essential Reference. He also has significant experience with systems programming in C, C++, and assembly language.
Brian K. Jones is a system administrator in the department of computer science at Princeton University.
Most helpful customer reviews
44 of 45 people found the following review helpful.
Python 3: The Power is Yours!
By Alej Cabrera
This book is an amazing resource for making the most of Python 3. This book truly makes it apparent what you're missing out on in the land of Python 2 and shows what can be accomplished more concisely in Python 3.
For example, as early as chapter 1, you're introduced to advanced unpacking techniques available in Python 3:
head, *tail = elems
The equivalent in Python 2 is:
head, tail = elems[0], elems[1:]
The chapter on generators and iterations techniques alone is worth the price of this book. It shows you how to "Loop Like a Native", all the way through using partial function application combined with lambdas to lazily loop over the contents of a file, ending when there's nothing left to read. Elegant!
There's more gems here, but I'll leave them for you to discover. The authors did a wonderful job of putting this book together, and I highly recommend this to anyone interested in becoming an effective Pythonista!
43 of 45 people found the following review helpful.
The Python Domestic Science Textbook?
By renaissance geek
A few years ago now I was working in a job that required me to code in PERL. My PERL is passable but no better than that so when I found a copy of the PERL cookbook it was something of a life saver and constant companion. The PERL cookbook is deeply pragmatic and addresses real world problems with the language almost as an afterthought. (Which now I think about is actually a pretty good description of PERL anyway!) The Python cookbook is a very different beast and is much more an exercise in learning the intricacies and nuances of the language. I'm not sure cookbook is the right title - if the PERL Cookbook is a cookbook then the Python Cookbook is more of a domestic science textbook. A bit deeper, a bit dryer and not so focused on immediate problems. This is no way meant to imply that it's a bad book, on the contrary it's a very good book just not entirely what I was expecting.
The book itself is divided into fifteen large sections covering the likes of data structures and algorithms; functions; metaprogramming and concurrency with each section consisting of a number of problems. The problems are structured as a definition of the problem, a solution and a discussion of the solution and how it can be extended. Due to the nature of the Python language a large part of solving the problems lies in knowing which module(s) to include in your code so each problem is generally only a couple of pages, but that is certainly enough to give the solution and reasonably detailed discussion. As with all books of this type there is going to be some complaints of why is X included and not Y and to be honest if you tried to cover all the possible problems a practicing python programmer is likely to run across the book would end up so large as to be unusable. That being said there was, for me at least, one glaring omission. I do a lot of data processing with reasonably large data sets, and with the buzz around big data I'm sure I'm not the only one, and frequently find that I have to break down the data sets or I simply consume all the system resources and the program exits. I would have expected at least some treatment of working with very large data sets which seems to be entirely missing. However this is an issue based on what I use Python for and may very well not matter to you. Even though there may not be exactly the solution you are looking for, there are 260 problems and solutions in the Python cookbook so if you don't learn something new you are probably a certified Python genius and beyond manuals anyway.
There are a couple of quick final points to make about the Python cookbook. Firstly it uses Python 3 and as many very useful third party modules haven't been ported from Python 2.X over to Python 3 yet Python 2.X is still probably still more widely used. Secondly although this is a language learning book it's not aimed at the novice programmer, think of it more as language nuances and inflections for the experienced Pythonista rather than a how to learn Python book and you won't go far wrong.
15 of 16 people found the following review helpful.
Extensive tome of recipes for the Python 3 programmer
By Devendra
Python Cookbook is an extensive tome of recipes for the Python 3 programmer. It is a perfect companion book for those migrating Python 2 code to Python 3. If you are stuck with Python 2, you may still find the second edition of the book for sale, but the recipes may be dated as they cover Python 2.4. It is not a beginners book. If you are looking for a beginners book, I recommend Learning Python by Mark Lutz.
A quick chapter summary follows.
Chapter 1 has recipes involving manipulation of built-in structures such as dictionaries and sequences. Usage of heapq module for implementing priority queues is demonstrated. Chapter 2 covers string and text manipulation, with extensive use of regular expressions. Chapter 3 has recipes for working with numbers, dates, and times. Usage of numpy module for matrix and linear algebra calculations is demonstrated.
Chapter 4 provides recipes for implementing iterators and generators. Chapter 5 covers File and I/O, including recipes for reading and writing compressed files, memory mapping binary files, and communicating with serial ports. Chapter 6 moves on to more advanced recipes for encoding and processing, such as reading and writing CSV, JSON, XML, Hex digits, and Base64.
Chapter 7 provides recipes for functions and closures. Chapter 8 provides recipes for classes and objects, such as creating managed attributes, lazily computed properties, and extending classes with mixins. It also covers common patterns such as state, and visitor. Chapter 9 digs deeper into metaprogramming. Chapter 10 has recipes for modules and packages, such as for splitting a module into multiple files using packages, and loading modules from another machine using import hooks.
Chapter 11 provides recipes for network and web programming. I didn't know you could use ip_network objects to generate IP addresses and check for membership. It also covers event-driven I/O but does not introduce any new framework. Chapter 12 has recipes for concurrency. It discusses implementing concurrency using generators (coroutines), but doesn't cover frameworks such as gevent, it does mention PEP 3156 that covers those.
Chapter 13 has recipes for writing utility scripts for system administration. Chapter 14 has recipes for unit testing, debugging, exception handling, and profiling. Chapter 15 wraps it up with recipes for extending Python using C.
I've added this book to my list of references to look into, before heading to Google. Source code listings use syntax highlighting, a nice touch that makes the code easier, and less boring, to read.
I thank O'Reilly media for providing the book for review.
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