The Classics of Python programming

Usually a hot segment of the technical field of development to a period of time will appear 3 to 5 of the classic books, these books with each other to form a more complete knowledge system, for the promotion and development of the technology to make a contribution. All we need to do is to study these books carefully and practice them, which is enough to improve our technical level greatly. We usually call this phenomenon "classics phenomenon".

In the process of learning python, if you can find Python's "classics", both in terms of time and money is a very economic choice. From the vast Python books to select a few fine reading enough, the following small series to select 4 from the "Classics" standard to meet the Python simple introduction. These books are advanced, and the target audience is the programmer who wants to step up to the next level of familiarity with the basic Python syntax.

First book: "Fluent Python"

Highly recommended ... Small knitting thinks this book is published this year the best of a Python book, no one, watercress scoring 9.1. One of the highlights of this book is the extended reading and the gossip behind each chapter. Extended Readings provide additional information about the contents of this chapter, or books, or official websites, or blogs. It's like the technical gossip of the Python world.

The Second: "Python Cookbook"

watercress score 8.9. The style of the book is to first ask a small question, and then give the solution, the final summary. This book provides a lot of tips for solving some of the little problems that actually come up, suitable as a reference book, encountered problems turned over, nothing turned over, sleep before turning over, wake up and turn over, turned over you will be shocked: rely on, you can play like this ...

Third: "Python Advanced Programming (2nd edition)"

recently published, Watercress no score. The book is one of the best Python books to be published this year, and there's a (none of that is called "fluent Python"). The highlight of this book is to choose a good name , deploy the code , manage the Code , document your project , and so on. These chapters are not in other books (at least not seen in the small series).

Fourth: "Data analysis using Python"

Watercress score 8.5. One of the most widely used areas of Python is scientific computing, while the two most famous libraries in Python science are numpy and pandas. This book is written by the author of the Pandas Library. This book is mainly about the use of Python data control, processing, collation, analysis and other aspects of the specific details and basic requirements (small series in doing log information extraction will also use a similar concept, the place will recommend this book).

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