Update: I've slightly modified the language of this review, which as my wife correctly pointed out to me, was unnecessarily harsh. While I stand by my previous evaluation of the book, I think the same things can be said in a more constructive tone.
While this isn't strictly a SciPy post, I've already have a few questions about this book, so I guess I'll tag it as 'scipy' as well, for those interested. I recently reviewed the book Expert Python Programming by Tarek Ziadé. While not aimed at a scientific audience, the book covers a number of topics that we frequently discuss on the Numpy and Scipy lists (such as documentation and testing, workflows, API decisions, etc). Since I really prefer to write longer text in reST using Emacs than in a blog editor, I've posted the review over at my static site. Feel free to head over there if you are interested in the full review, I've only reproduced here the summary:
Summary Expert Python Programming covers a list of very interesting topics regarding real-world development using Python. It assumes a reader who already knows the basics of the language and covers a number of important topics, both in the more advanced parts of the language and in terms of developing applications using Python. There is a strong emphasis on agile development practices, testing, documentation, application life cycle management and other aspects of 'real world' work. The list of topics covered is excellent, and the book is well printed and bound.
However, unfortunately it suffers from rather poor editing throughout, with a broken idea flow that makes for choppy reading. Very few ideas are properly developed, as the book relies excessively on code snippets, bullet lists and stand-out info boxes. Ultimately, this gives it more the feel of a set of notes than that of a coherent volume. This should not be read as an indictment of the book: the table of contents alone is a list of 'right things to do' when using Python, and there is a great deal of useful material in all of the chapters.
If you are looking for reference material, links and starting points for further reading, Expert Python Programming can be an excellent resource and well worth your investment. However, if you are searching for a text that develops complex concepts at length, delving into details and subtleties, it might not be the ideal tool for you. I hope this provides a useful picture of the qualities of this book.
While this isn't strictly a SciPy post, I've already have a few questions about this book, so I guess I'll tag it as 'scipy' as well, for those interested. I recently reviewed the book Expert Python Programming by Tarek Ziadé. While not aimed at a scientific audience, the book covers a number of topics that we frequently discuss on the Numpy and Scipy lists (such as documentation and testing, workflows, API decisions, etc). Since I really prefer to write longer text in reST using Emacs than in a blog editor, I've posted the review over at my static site. Feel free to head over there if you are interested in the full review, I've only reproduced here the summary:
Summary Expert Python Programming covers a list of very interesting topics regarding real-world development using Python. It assumes a reader who already knows the basics of the language and covers a number of important topics, both in the more advanced parts of the language and in terms of developing applications using Python. There is a strong emphasis on agile development practices, testing, documentation, application life cycle management and other aspects of 'real world' work. The list of topics covered is excellent, and the book is well printed and bound.
However, unfortunately it suffers from rather poor editing throughout, with a broken idea flow that makes for choppy reading. Very few ideas are properly developed, as the book relies excessively on code snippets, bullet lists and stand-out info boxes. Ultimately, this gives it more the feel of a set of notes than that of a coherent volume. This should not be read as an indictment of the book: the table of contents alone is a list of 'right things to do' when using Python, and there is a great deal of useful material in all of the chapters.
If you are looking for reference material, links and starting points for further reading, Expert Python Programming can be an excellent resource and well worth your investment. However, if you are searching for a text that develops complex concepts at length, delving into details and subtleties, it might not be the ideal tool for you. I hope this provides a useful picture of the qualities of this book.
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