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Effective Computation in Physics: Field Guide to Research with Python 1st Edition
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More physicists today are taking on the role of software developer as part of their research, but software development isnâ??t always easy or obvious, even for physicists. This practical book teaches essential software development skills to help you automate and accomplish nearly any aspect of research in a physics-based field.
Written by two PhDs in nuclear engineering, this book includes practical examples drawn from a working knowledge of physics concepts. Youâ??ll learn how to use the Python programming language to perform everything from collecting and analyzing data to building software and publishing your results.
In four parts, this book includes:
- Getting Started: Jump into Python, the command line, data containers, functions, flow control and logic, and classes and objects
- Getting It Done: Learn about regular expressions, analysis and visualization, NumPy, storing data in files and HDF5, important data structures in physics, computing in parallel, and deploying software
- Getting It Right: Build pipelines and software, learn to use local and remote version control, and debug and test your code
- Getting It Out There: Document your code, process and publish your findings, and collaborate efficiently; dive into software licenses, ownership, and copyright procedures
- ISBN-101491901535
- ISBN-13978-1491901533
- Edition1st
- PublisherO'Reilly Media
- Publication dateAugust 4, 2015
- LanguageEnglish
- Dimensions7 x 1.25 x 9.19 inches
- Print length550 pages
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Editorial Reviews
About the Author
Kathryn Huff is a Fellow with the Berkeley Institute for Data Science and a postdoctoral scholar with the Nuclear Science and Security Consortium at the University of California Berkeley. In 2013, she received her Ph.D. in Nuclear Engineering from the University of Wisconsin Madison. She also holds a bachelor's degree in Physics from the University of Chicago. She has participated in varied research including experimental cosmological astrophysics, experimental non-equilibrium granular material phase dynamics, computational nuclear fuel cycle analysis, and computational reactor accident neutronics. At Wisconsin, she was a founder of The Hacker Within scientific computing group and has been an instructor for Software Carpentry since 2011. Among other professional service, she is currently an division officer in the American Nuclear Society and has served two consecutive years as the Technical Program Co-Chair of the Scientific Computing with Python (SciPy) conference.
Product details
- Publisher : O'Reilly Media
- Publication date : August 4, 2015
- Edition : 1st
- Language : English
- Print length : 550 pages
- ISBN-10 : 1491901535
- ISBN-13 : 978-1491901533
- Item Weight : 2.05 pounds
- Dimensions : 7 x 1.25 x 9.19 inches
- Best Sellers Rank: #1,539,224 in Books (See Top 100 in Books)
- #414 in Mathematical Physics (Books)
- #806 in Python Programming
- #1,032 in Software Development (Books)
- Customer Reviews:
About the authors

Kathryn Huff is a Fellow with the Berkeley Institute for Data Science and a postdoctoral scholar with the Nuclear Science and Security Consortium at the University of California Berkeley. In 2013, she received her Ph.D. in Nuclear Engineering from the University of Wisconsin Madison. She also holds a bachelor's degree in Physics from the University of Chicago. She has participated in varied research including experimental cosmological astrophysics, experimental non-equilibrium granular material phase dynamics, computational nuclear fuel cycle analysis, and computational reactor accident neutronics. At Wisconsin, she was a founder of The Hacker Within scientific computing group and has been an instructor for Software Carpentry since 2011. She is now the Chair of the Software Carpentry Foundation Steering Committee. Among other professional service, she is currently an division officer in the American Nuclear Society and has served three consecutive years on the organizing committee of the Scientific Computing with Python (SciPy) conference.

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Customer reviews
Customer Reviews, including Product Star Ratings help customers to learn more about the product and decide whether it is the right product for them.
To calculate the overall star rating and percentage breakdown by star, we don’t use a simple average. Instead, our system considers things like how recent a review is and if the reviewer bought the item on Amazon. It also analyzed reviews to verify trustworthiness.
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- Reviewed in the United States on August 12, 2015Format: PaperbackVerified PurchaseThis book should be required (and enjoyable) reading for any student/researcher/scientist/engineer new to scientific computing. The book presents a modern account of the Python scientific computing environment from the command line to publication and everything good in between e.g. NumPy to parallel computing to version control and much more (see http://physics.codes for more). The book also helps you get quickly going with Python on your computer via the Anaconda environment which is very nice. I bought the Kindle version and plan to read it on my iPad while I try the programs (freely available for download at the above website) on my Macbook (ideal combination in my opinion) - it's never been more fun to be in scientific computing that it is these days and this book will help you get started or, like me, maintain and update your overall computational skill set. A must buy and a must read! Enjoy!
- Reviewed in the United States on September 17, 2025Format: PaperbackVerified PurchaseGood content, but my book came damaged
- Reviewed in the United States on January 11, 2020Format: PaperbackVerified PurchaseI use different coding languages for different purposes. MATLAB is my go-to for scientific programming that is visual-intensive. C++ or C is my preferred language for heavy computational work that does not necessarily require plotting images (I follow up with quick plots in gnuplot). Unix is amazing for fast computations, working with files and directories on my computer, and working with supercomputers. HTML is great for websites (it was the first coding language I learned, I was 13 years old at the time). For me personally, I prefer Python for plotting purposes, you can do some really cool things with Matplotlib. Good book for familiarizing yourself with Python in a computational physics context.
- Reviewed in the United States on May 21, 2021Format: KindleVerified PurchaseThis is more of a "here's how we physicists do scientific computation, oh and here's some Python basics" rather than a real tutorial on Python. This will get you into the ecosystem but that's about it, you'll need another solution to actually learn Python in any practical manner. On the other hand, it is a good attempt at addressing the breadth of knowledge useful to those of us that work in scientific or engineering computation. But for the most part I was hoping for more depth. Some very bare bones parts in here, like "here's a python package you'll want for doing this general thing, now go and look on stackoverflow or the package docs on how to actually use it", pattern repeated throughout. But if you aren't familiar about what the field of scientific computation entails this is a good primer.
- Reviewed in the United States on May 14, 2021Format: KindleVerified PurchaseAmazingly practical book. I anticipate this will remain a staple in my reference library. I truly wish other books were as thorough as this one. Highest recommendation.
- Reviewed in the United States on November 4, 2015Format: PaperbackVerified PurchaseThis book has been teaching me more than effective computation! I've learned about the community, the myths and the jokes so that I can laugh as well. The digital version contains color-coded python code, really awesome
- Reviewed in the United States on December 13, 2019Format: PaperbackVerified PurchaseAs the title of the book says; you learn computation in physics with little bit of python.
If you want to learn python and no physics/science; this book IS NOT for you. If you are a scientist who wants to learn automation for you projects; this book IS for you.
I bought this book for learning python, I am not a scientist nor a phycicist. Every practice in this book revolves around physics and atoms, they are very hard to understand if you're not a scientist yourself.
First one hundred pages are decent python learning material, the rest is for automating atom science applications.
I should've done more research about this book before spending over 40 dollars for this. Well this was a lesson.
Top reviews from other countries
Karate KidReviewed in Germany on October 16, 20205.0 out of 5 stars Great resource for Python programming for scientists, not only Physicists
Format: PaperbackVerified PurchaseI thought it might be too "beginerrish" for me, but I was wrong. It covers a wide range of topics, and seems to be very thorough. One of the programming books you can simple read. :)
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Giancarlo V.Reviewed in Italy on February 9, 20225.0 out of 5 stars ottimo!
Format: PaperbackVerified Purchaseottimo!
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marcio.pmzReviewed in Brazil on July 24, 20243.0 out of 5 stars Conteúdo básico
Format: PaperbackVerified PurchaseO título faz supor um conteúdo avançado sobre modelagem física, mas o conteúdo é o básico de Linux e python.
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Pablo Orellana ChornyakReviewed in Spain on December 17, 20252.0 out of 5 stars Pagina rota
Format: PaperbackVerified PurchaseNo quiero criticar el contenido del libro, pero tiene un problema de impresión que destroza esa página del libro. Aparte la portada está un poco rota.
No quiero criticar el contenido del libro, pero tiene un problema de impresión que destroza esa página del libro. Aparte la portada está un poco rota.2.0 out of 5 stars
Pablo Orellana ChornyakPagina rota
Reviewed in Spain on December 17, 2025
Images in this review
APReviewed in the United Kingdom on February 27, 20195.0 out of 5 stars Very useful
Format: PaperbackVerified PurchaseThis is a really good book, including for those who don't aren't Physicists. It's great for anyone doing any kind of numerical research work that requires/could greatly benefit from good computational skills. It covers a wide range of topics, so it's great for getting introduced to a lot of different things. It doesn't go into great detail for all that it covers, but at the very least gives a good sense of the material, which you can then dig into further elsewhere. It's nice to have strong coverage on command line work, version control, general Python stuff, and development-type work all in one book, making it a useful one to own a copy of.
























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