- Taschenbuch: 138 Seiten
- Verlag: Packt Publishing (25. April 2013)
- Sprache: Englisch
- ISBN-10: 1782169938
- ISBN-13: 978-1782169932
- Größe und/oder Gewicht: 19 x 0,8 x 23,5 cm
- Durchschnittliche Kundenbewertung: 1 Kundenrezension
- Amazon Bestseller-Rang: Nr. 202.104 in Fremdsprachige Bücher (Siehe Top 100 in Fremdsprachige Bücher)
Learning IPython for Interactive Computing and Data Visualization (Englisch) Taschenbuch – 25. April 2013
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Über den Autor und weitere Mitwirkende
Cyrille Rossant is a French researcher in quantitative neuroscience. A graduate of the Ecole Normale Supérieure, Paris, he holds a Master's degree and a Ph.D. in Mathematics and Computer Science. He uses IPython every day to model and simulate the brain and to analyze experimental data. He is the creator of a few scientific Python packages, including Playdoh (parallel computing) and Galry (high-performance interactive visualization).
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It's a mini title, but it does contain a lot of information I was very pleased to see. First and foremost, this is the first book to focus on the IPython Notebook. That's huge. Also:
The installation section is thorough and goes well beyond the obvious, discussing options like using prepackaged all-in-one Python distributions like Anaconda.
Some of the improvements IPython can make to a programming workflow are nicely introduced, like the ease of debugging, source code inspection, and profiling with the appropriate magics.
The section on writing new IPython extensions is extremely valuable - it contains more complete examples than the official documentation does and would have saved me lots of time and excess code if I'd had it when I was writing ipython-sql.
There are introductions to all the classic uses that scientists doing numerical simulations value IPython for: convenience in array handling, Pandas integration, plotting, parallel computing, image processing, Cython for faster CPU-bound operations, etc. The book makes no claim to go deeply into any of these, but it gives introductory examples that at least give an idea of how the problems are approached and why IPython excels at them.
So what don't I like? Well, I wish for more. It's not fair to ask for more bulk in a small book that was brought to market swiftly, but I can wish for a more forward-looking, imaginative treatment. The IPython Notebook is ready to go far beyond IPython's traditional core usership in the SciPy community, but this book doesn't really make that pitch. It only touches lightly on how easily and beautifully IPython can replace shell scripting. It doesn't get much into the unexplored possibilities that IPython Notebook's rich display capabilities open up. (I'm thinking of IPython Blocks as a great example of things we can do with IPython Notebook that we never imagined at first glance). This book is a good introduction to IPython's uses as traditionally understood, but it's not the manifesto for the upcoming IPython Notebook Revolution.
The power of hybrid documentation/programs for learning and individual and group productivity is one more of IPython Notebook's emerging possibilities that this book only mentions in passing, and passes up a great chance to demonstrate. The sample code is downloadable as IPython Notebook .ipynb files, but the bare code is alone in the cells, with no use of Markdown cells to annotate or clarify. Perhaps this is just because Packt was afraid that more complete Notebook files would be pirated, but it's a shame.
Overall, this is a short book that achieves its modest goal: a technical introduction to IPython in its traditional uses. You should get it, because IPython Notebook is too important to sit around waiting for the ultimate book - you should be using the Notebook today. But save space on your bookshelf for future books, because there's much more to be said on the topic, some of which hasn't even been imagined yet.
(copy of the review posted at http://catherinedevlin.blogspot.com/2013/05/review-of-learning-ipython-for.html)
(The book uses Python 2).
The book has six chapters, so it's a quick read. In the first two chapters, the author helps the reader getting started with using IPython (installation, basic things to do, using IPython as a shell) and also using IPython notebook for interactive python programming. He demonstrates how to perform basic profiling, measuring the run time of your scripts/statements and also discusses plotting with matplotlib (via pylab) from IPython notebook.
Chapter 3 introduces vector operations and using NumPy for performing the same. Topics such as indexing, reshaping are introduced in this chapter. This chapter also introduces the Pandas tool and demonstrates using it using a publicly available data set.
Chapter 4 discusses plotting, graphing and visualization in detail using matplotlib and others.
Chapter 5 discusses two main of concepts. One, running your programs on multiple cores and basics of using the Message Passing Interface (MPI). The second main concept discussed is using Cython. At the end, the chapter also mentions libraries such as Blaze and Numba which are of potential usefulness to the intended audience.
The final chapter of the book discusses customizing IPython (creating profiles, etc.), and also shows you can create an extension that introduces a new cell magic.
Up -to-date information and references
Just enough information for the reader to learn and explore more
The book is interesting and pleasant to read and follow. It does well in introducing features of IPython and other tools of interest to the book's audience. Definitely worth buying.
He covers everything from installation to advanced topics like high performance computing and customizing IPython, using clear, worked examples with publicly available datasets. In addition to IPython, he also briefly covers using important scientific computing Python packages such as NumPy, SciPy, Cython and Pandas.
If you haven't yet tried IPython or if you've only just started using it, I'd highly recommend it. There's even plenty of stuff in there for more experiened users too.
In conclusion, this book definitely achieves its goal to provide a technical introduction to IPython. It is intended for Python users who want an easy to follow introduction to IPython, but also experienced users will find this book useful. It is to notice that, at the moment, this is the only book about IPython.