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Effective Computation in Physics: Field Guide to Research with Python 1st Edition

4.4 out of 5 stars (104)

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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

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Editorial Reviews

About the Author

Anthony Scopatz is a computational physicist and long time Python developer, Anthony holds his BS in Physics from UC, Santa Barbara and a Ph.D. in Mechanical / Nuclear Engineering from UT Austin. A former Enthought employee, he spent his post-doctoral studies at the FLASH Center at the University of Chicago in the Astrophysics Department. He is currently a Staff Scientist at the University of Wisconsin-Maidson in Engineering Physics. Anthony’s research interests revolve around essential physics modeling of the nuclear fuel cycle, and information theory & entropy. Anthony is proudly a fellow of the Python Software Foundation and has published and spoken at numerous conferences on a variety of science & software development topics.

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)
  • Customer Reviews:
    4.4 out of 5 stars (104)

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Customer reviews

4.4 out of 5 stars
104 global ratings

Top reviews from the United States

  • Reviewed in the United States on August 12, 2015
    Format: PaperbackVerified Purchase
    This 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!
    10 people found this helpful
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  • Reviewed in the United States on September 17, 2025
    Format: PaperbackVerified Purchase
    Good content, but my book came damaged
  • Reviewed in the United States on January 11, 2020
    Format: PaperbackVerified Purchase
    I 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.
    3 people found this helpful
    Report
  • Reviewed in the United States on May 21, 2021
    Format: KindleVerified Purchase
    This 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.
    3 people found this helpful
    Report
  • Reviewed in the United States on May 14, 2021
    Format: KindleVerified Purchase
    Amazingly 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.
    2 people found this helpful
    Report
  • Reviewed in the United States on November 4, 2015
    Format: PaperbackVerified Purchase
    This 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
    3 people found this helpful
    Report
  • Reviewed in the United States on December 13, 2019
    Format: PaperbackVerified Purchase
    As 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.
    12 people found this helpful
    Report
  • Reviewed in the United States on June 5, 2020
    Format: PaperbackVerified Purchase
    Very well
    One person found this helpful
    Report

Top reviews from other countries

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  • Karate Kid
    5.0 out of 5 stars Great resource for Python programming for scientists, not only Physicists
    Reviewed in Germany on October 16, 2020
    Format: PaperbackVerified Purchase
    I 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. :)
  • Giancarlo V.
    5.0 out of 5 stars ottimo!
    Reviewed in Italy on February 9, 2022
    Format: PaperbackVerified Purchase
    ottimo!
    Report
  • marcio.pmz
    3.0 out of 5 stars Conteúdo básico
    Reviewed in Brazil on July 24, 2024
    Format: PaperbackVerified Purchase
    O título faz supor um conteúdo avançado sobre modelagem física, mas o conteúdo é o básico de Linux e python.
  • Pablo Orellana Chornyak
    2.0 out of 5 stars Pagina rota
    Reviewed in Spain on December 17, 2025
    Format: PaperbackVerified Purchase
    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.
    Customer image
    Pablo Orellana Chornyak
    2.0 out of 5 stars
    Pagina rota

    Reviewed in Spain on December 17, 2025
    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.
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    Customer image Customer image
  • AP
    5.0 out of 5 stars Very useful
    Reviewed in the United Kingdom on February 27, 2019
    Format: PaperbackVerified Purchase
    This 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.