Dive Into Python 3

Dive Into Python 3

Python now comes in two flavors–Python 3 and Python 2. The philosophy of programming in Python 3 diverges from Python 2 to the point that print statements written in three don’t even run properly in two. Unfortunately, so many of the books written using Python over the last few years are still using version 2.6 – which is backwards compatible with all previous versions. If you are buying this book because you are taking a class in which the teacher is using Python rather than teaching it -bioinformatics or visualization for example – this may cause you trouble. If you need to learn 2.6 or an earlier version of Python 2, please buy the previous edition.

If you are learning Python for the first time and it’s up to you as to what flavor of Python to learn, then I suggest you start with Python 3. It does fix some longtime problems with the Python language. In that case, this edition of “Dive Into Python” is what you want.

I tend to learn languages more readily if I write a simple program first then add to its complexity by having more complex aspects of the language revealed to me, which is basically the approach of “Dive Into Python”. What worked best for me when I learned Python 2 was to read the free online guide “Dive Into Python” which is incomplete but top-down, then switch to “Learning Python”, which is detailed but more academic and more of a bottom-up approach. For example, while this book is about 500 pages, the new “Learning Python” book by Mark Lutz is 1200 pages long.

The author of this book has continued his tradition of placing his book online free of charge if you wish to look through it. I have read this updated version in order to update to Python 3. However, the author realizes that if you like his book you’ll want a copy for yourself to carry about and in which to scribble notes. Sometimes you can make more money by being generous.

In summary, I highly recommend this book as a way to get started, but then you’ll probably want to proceed to “Learning Python” for advanced topics and as a reference.

 

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A Primer on Scientific Programming with Python

A Primer on Scientific Programming with Python

Don’t be fooled by the title or the first chapter, this book provides a solid introduction for using Python in scientific applications. The main application areas covered are calculating the value of functions, both built in and user supplied, plotting data, finding the roots of equations, difference equations, numerical differentiation, numerical integration and the solution to differential equations by numerical methods.

Along the way you will learn how to use lists, tuples, dictionaries, loops, list comprehension, lambda functions, Numpy arrays, file I/O and Python Classes for programming scientific applications. Two main highlights of the book are the thorough explanations the author provides on how to use most of the features of Python and the copious number of examples with answers. Other features are an example on how to extract data from a Web Page and scitools. Scitools provides a Matlab type of interface to gnuplot. About the only thing missing is a summary on how to install Numpy, Scipy, Scitools, gunplot, and gnuplotpy.

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