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Top (max 10) reviews: A Primer on Scientific Programming with Python (Texts in Computational Science and Engineering).

4.2 out of 5.0    10 total reviews.

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5.0 out of 5.0 -

by MSE fanatic on Dec. 26, 2013

I'll first address why I think Python should be the preferred choice of scripting/programming for engineers. Don't get me wrong Matlab is a great programming environment with a lot of functionality. However, it is a costly and you have to purchase additional modules to extend its functionality. This is where python stands on top. Python is a freely available programming language provided under a version of the GNU General Public License. This means you never will have to purchase it. Furthermore, the python libraries that provide similar capability as Matlab usually have a similar licensing style. These included some of the best like NumPy, SciPy, MatPlotLib, Sci-Tools, SymPy,etc.
Why I like this book:
1. This text has an unbelievable price tag for how much content it covers.
2. The Book is really broken down into two parts a) Python basics b) Implementing numerical math/science in python.
3. Tons of examples and problems to work out. This is a great feature!
4. Well written with code snippets that are not confusing or lengthy.
5. Discusses many of the freely available python libraries.
What I'm not crazy about:
1. This thing is heavy!
2. Not easy to find specific types of code/examples.
3. Some of the problems are boring.
4. Wish it had more of programming for simulations (i.e. Finite-Differences, Finite-Elements).
If your an undergraduate in mechanical, electrical, or materials engineering looking to learn programming for the first time this is an excellent text to start from. If you've already had a similar course in this topic but with another language like Fortran or C and are more interested in leveraging python to write fast and simple code I think the authors book "Python Scripting for Computational Science" might be better suited for you (Note: I actually have not read that book).

4.0 out of 5.0 -

by Public Byyer on April 5, 2014

An excellent primer text for Python newbies. The author assumes a Python 2.x installation, and I would prefer a focus on Python 3.x, but this isn't a great hurdle to overcome.

4.0 out of 5.0 -

by wc on March 19, 2014

Been using C++ w/Perl for the past 19 years, but making the switch from Perl. Book is a good intro, but a more complete index would better serve the working programmer.

5.0 out of 5.0 -

by Todds Books on June 18, 2013

If you are not a scientist or engineer, some of the math may be a bit puzzling. Nonetheless, the book is still an excellent reference for programming in Python. Many examples, code snipits, charts, and diagrams plus plenty of exercises to test your learning.

4.0 out of 5.0 -

by W. Scott Best on Sept. 4, 2014

Excellent reference text.

5.0 out of 5.0 -

by rpv on April 22, 2013

Instead of calling this book "a primer," a more apt title would be A detailed treatise on scientific programming with Python. This voluminous book offers an excellent and detailed explanation of programming paradigms and mathematical lexicons. Learning a programming language for the first time is a challenge, because it requires thinking in a different way to write efficient programs. Twenty to 30 years ago, people learned programming in languages like Pascal, C, and Fortran. Python is a modern language, popular with academics and industry professionals for certain tasks. For someone who is well versed in programming languages, this book can become overkill. Downey's book, Think Python is a better alternative for someone with prior experience who has limited time and wants to learn Python quickly.
The author includes many programs, explanations, and exercises. The Python programs are neatly embedded in blue shaded boxes and separated by explanations. The book progresses through various control structures like loops, lists, functions, and object-oriented concepts, and shows how to weave them together. Examples include how to plot graphs, draw circles, and execute mathematical functions. This book will prove very useful for mathematicians and statisticians. This book covers the mathematical concepts beautifully, and programmatically demonstrates them with Python. This really showcases the power of this language. If you are looking to do other things, such as string processing or network programming, this is not the right book for you. This big (really big!) book covers scientific programming in painstaking depth. I applaud the author for his efforts and encourage readers to set aside sufficient time to master the concepts.
Highly recommend!

5.0 out of 5.0 -

by pat on Aug. 17, 2014

This book really is the perfect introduction to programming for maths, stats, science or engineering. The first sections give an excellent introduction to the main features of the Python language, and uses (what I think) are non-trivial and interesting examples (mainly from maths/physics) to demonstrate syntax and ideas. I can't think of another book which gives a more generally useful introduction to Python.
The second section is, I think, unique in the science/engineering literature - design of object orientated software and why it is a helpful paradigm for numerical analysis. I can't think of another book at this level which really nails that concept like this book.
This is not a compendium of methods for numerical analysis (a la Numerical Recipes etc). Also it is not a text on numerical analysis (say like the classic Morton & Mayers or Richtmayer & Morton in the PDE (my) area). But it never pretends to be, which is good.
I think having at least first year undergraduate maths would helpful (although not mandatory), as it would make understanding some of the examples used easier so as to focus on the programming.
In summary, I believe this is an essentially flawless introduction to the Python language and programming for scientists. It's greatest strength is its delivery of OO design concepts - really unique in the area.

5.0 out of 5.0 -

by George J. Lees Jr. on Sept. 30, 2014

This book flows like water gliding down a tropical rain forest waterfall. It teaches you python and computational science by example. They took a hands on approach and wrote their own codes for this book. A lot of codes to go along with the theoretical which more computer science books need !

2.0 out of 5.0 -

by Amazon Customer on Sept. 7, 2013

This book has limited viewing capability on small mobile devices such as smart phones. I could not view it on my Samsung Statosphere 2