Showing posts with label python. Show all posts
Showing posts with label python. Show all posts

Rapid GUI Programming with Python and Qt (Prentice Hall Open Source Software Development) Review

Rapid GUI Programming with Python and Qt (Prentice Hall Open Source Software Development)
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Rapid GUI Programming with Python and Qt (Prentice Hall Open Source Software Development) ReviewFor any open source programming tool, there are always those who are quick to point out that free online documentation is of excellent quality and that a commercially published book adds questionable value. Indeed, the open process by which open source tools are made, which reveals the why's & wherefore's of the internal workings to anyone who looks, leads directly to the production of excellent online documentation; this is one of the great strengths of open source software. But everyone's needs are different. A college student or free software volunteer often has looser deadlines, less budget, and a more perfectionist attitude than, for example, a non-expert programmer, working in industry, trying to expeditiously solve a specific problem. A book of this genre is intended mainly for the latter audience, whereas the former may be disappointed at spending $50 when a web browser could have done the job. Cash-strapped college students, I know your pain; I used to be one. This book is not a particularly cost-effective study aid. If you live and breathe GUI progamming and can type out GTK2 and wxwidget classes by heart, then this book is probably a waste of time for you.
Having said that, I review this book with a view toward its value to its intended audience: Does buying this book and using it get the job done $50 cheaper, including the value of your own professional time, compared to the best available alternative? My experience is yes.
I am an electrical engineer, but not a programming expert. I have, at various times in my career, flipped bits in assembly language, suffered the rigors of Fortran, and slapped together contraptions in Matlab, VEE, Labview, etc. I have also had the misfortune of programming production test automation in Visual Basic, because that is what commercial instruments natively support. It is the shortcomings of VB that bring me to PyQT. I need to write test code that is portable, maintainable, and reliable. To give just one example, I don't want to fly across the Pacific Ocean to program workarounds for bugs in VB, because machines in the Chinese factory run Win98, and my development system in the US runs Win2k, and VB doesn't behave the same. But this is a book review, not a place to extol the virtues of PyQT nor criticize VB.
I have programmed in Python before, though for me Python has always been a language for one-off numerical or string processing tasks, where a spreadsheet is too limited and my bash script-fu is short of the task. I found the first three chapters on Python a helpful review, though it is not a complete instruction in Python. Compete beginners to Python will probably want to buy a separate book or work through the python.org tutorials. The author glosses over things that could trip up beginners; tellingly, he uses the term 'pythonic' without introduction. He is, however, careful to point out pitfalls that can waylay real-world production code, or would be of interest to experienced Perl/Ruby/VB programmers, like how Python handles the distinctions regarding {im}mutable types and {deep|shallow} copying.
I have never programmed QT before, and this book is indeed a complete introduction to QT. You don't need to know anything about QT nor how to program in C++ (QT's native language). Being able to read C++ syntax helps, though, because this book is not a QT reference, so you will probably have to look things up in the online QT references, which are written in C++.
It is something of a truism that the best way to learn a language is to read & understand someone else's well-written code, and then use that to write a program of your own. That is the approach used here, and the printed book format permits interleaving fragments of code with explanatory material in a way that doesn't work well on a computer screen. As such the text complements rather than duplicates the online documentation.
Regarding the book as a physical object, the quality is good but some extra features would have been nice. No CD is included, which I consider an oversight for a book at this price. Even the shortest examples lack source code listings, except as snippets woven into the text. You have to download the example code from a URL buried in the introduction, which is odd considering how important the example code is to this style of instruction. Occasional sidebar topics, icons, and cross-references help to organize the material, though not to the spoon-feeding level of "For {Dummies|Idiots}" books. The index is a bit above average for a book of this type, better than pure machine-generated grep output that sometimes passes for an index these days, but not as good as the best manual indices of decades past. The cover, binding, & paper stock are of decent quality. The book will stay open to just about any page when laid on a table, and the glue looks like it will, well probably, hold the sheaves in for many years. No color is used, nor edge printing to help find the chapters, which would have been helpful for a book this long.Rapid GUI Programming with Python and Qt (Prentice Hall Open Source Software Development) Overview
The Insider's Best-Practice Guide to Rapid PyQt 4 GUI Development
Whether you're building GUI prototypes or full-fledged cross-platform GUI applications with native look-and-feel, PyQt 4 is your fastest, easiest, most powerful solution. Qt expert Mark Summerfield has written the definitive best-practice guide to PyQt 4 development.

With Rapid GUI Programming with Python and Qt you'll learn how to build efficient GUI applications that run on all major operating systems, including Windows, Mac OS X, Linux, and many versions of Unix, using the same source code for all of them. Summerfield systematically introduces every core GUI development technique: from dialogs and windows to data handling; from events to printing; and more. Through the book's realistic examples you'll discover a completely new PyQt 4-based programming approach, as well as coverage of many new topics, from PyQt 4's rich text engine to advanced model/view and graphics/view programming. Every key concept is illuminated with realistic, downloadable examples—all tested on Windows, Mac OS X, and Linux with Python 2.5, Qt 4.2, and PyQt 4.2, and on Windows and Linux with Qt 4.3 and PyQt 4.3.

Coverge includes

Python basics for every PyQt developer: data types, data structures, control structures, classes, modules, and more

Core PyQt GUI programming techniques: dialogs, main windows, and custom file formats

Using Qt Designer to design user interfaces, and to implement and test dialogs, events, the Clipboard, and drag-and-drop

Building custom widgets: Widget Style Sheets, composite widgets, subclassing, and more

Making the most of Qt 4.2's new graphics/view architecture

Connecting to databases, executing SQL queries, and using form and table views

Advanced model/view programming: custom views, generic delegates, and more

Implementing online help, internationalizing applications, and using PyQt's networking and multithreading facilities


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Python Scripting for Computational Science (Texts in Computational Science and Engineering) Review

Python Scripting for Computational Science (Texts in Computational Science and Engineering)
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Python Scripting for Computational Science (Texts in Computational Science and Engineering) ReviewThe author has 2 main goals:
1) To improve the productivity of scientists familiar with specific software systems (especially Matlab, Maple, and Mathematica) by teaching them to "glue" applications together.
2) To advocate Python as the preferred "glue" language. In his own words, "I hope to convince computational scientists having experience with Perl that Python is a preferable alternative, especially for large long-term projects."
He has certainly done a creditable job. As an expert in computational differential equations, he neglects neither efficiency nor correctness, while stressing both simplicity and reliability. In this sense, he has done a great service to the Python community.
The question is: What justifies the purchase of his book?
The answer is: Chapters 4, 9, and 10.
Contents:
1. Introduction--26pp
Very convincing arguments.
2. Getting Started With Python Scripting--38pp
Interesting examples.
3. Basic Python--56pp
A too-quick tutorial. Go to python dot org instead.
4. Numerical Computing in Python--48pp
Stellar explanations of vectorized array operations.
5. Combining Python with Fortran, C, and C++--36pp
Details use of Fortran2Py and SWIG. Mentions many alternatives.
6. Introduction to GUI Programming--70pp
Useful examples of Tkinter/pmw widgets.
7. Web Interfaces and CGI Programming--24pp
Good source of ideas.
8. Advanced Python--132pp
Deep and extensive. Includes: option parsing, regular expressions, data persistence and compression, object-oriented programming, exceptions, generic programming, efficiency.
9. Fortran Programming with NumPy Arrays--32pp
All about efficiency and re-use.
10. C and C++ Programming with NumPy Arrays--40pp
More about efficiency. NumPy C API, C++ objects, and SCXX.
11. More Advanced GUI Programming--73pp
Tedious discussion of both Web and standalone GUIs. BLT, canvas, cgi.
12. Tools and Examples--70pp
Excellent examples of PDE solvers, with a powerful GUI, but quite long and tedious.
A. Setting up the Required Software Environment--16pp
Wonderfully specific installation instructions!
B. Elements of Software Engineering--50pp
Python's strength! Very practical advice on modularity, documentation, coding style, regression-testing, version-control.Strengths:
+ Downloadable py4cs package, esp. numpytools module
+ Great advice everywhere, e.g. CGI checklist, Pythonic programming, and trouble-shooting.
+ Concrete evidence for most assertions.
+ Very attractive presentation. Sturdy, high-quality cover, binding and pages. Brief, elegant code fragments (except in Chapter 12). Readable prose. No wasted space.
+ Available as 5MB pdf file, after purchase of hardcopy. Very nice.
+ Slides, installation instructions, and errata also at web site. Very professional.My peeves:
- Not enough tables to be a useful manual.
- On p.428(#7) he points out that handling a raised exception is very slow. However, when I time his example with a positive argument, the try-except version is 20% faster (b/c the if clause is skipped), so he is actually giving bad advice for the general case. Luckily, he contradicts himself later, on page 685: "Exceptions should be used instead of if-else tests." The best advice: Avoid common exceptions in inner loops.
- The 10-page index is not as great as it at first seems. (See Martelli's Python in a Nutshell for a better one.)
- Pure interface functions should 'raise NotImplementedError', rather than 'return'.
- Exceptions should never be trapped mindlessly with 'except:'. That would hide your own SyntaxErrors!
- Too many exercises. (It's published as a textbook.) Since there are no answers, the exercises are useless for non-students. (See Lutz's Learning Python for effective exercises with answers.)Overall rating:
This contains the best information on numerical programming in Python that I've seen. Though expensive, it could easily be your only Python book, given the excellent online documenation already available.Python Scripting for Computational Science (Texts in Computational Science and Engineering) OverviewWith a primary focus on examples and applications of relevance to computational scientists, this brilliantly useful book shows computational scientists how to develop tailored, flexible, and human-efficient working environments built from small scripts written in the easy-to-learn, high-level Python language. All the tools and examples in this book are open source codes. This third edition features lots of new material. It is also released after a comprehensive reorganization of the text. The author has inserted improved examples and tools and updated information, as well as correcting any errors that crept in to the first imprint.

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Mobile Phone Programming: and its Application to Wireless Networking Review

Mobile Phone Programming: and its Application to Wireless Networking
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Mobile Phone Programming: and its Application to Wireless Networking ReviewI have more than 6 years experience in this industry and can tell that this is the first book of this kind I saw. It will allow you to get your own hands-on experience with many different platforms, from Series 60 to Qtopia. Due to real programming examples, it is very praxis oriented, but also with several scientific aspect rising open questions. And all this without any "hypes" or "bubbles", as you maybe know from other books about "mobile". If you are an expert, it will also allow you to get a piratical impression of other platforms in a short time. So, in the nutshell, this books is worth each $$ use spent on it! Great book!Mobile Phone Programming: and its Application to Wireless Networking OverviewThis book provides a solid overview of mobile phone programming for readers in both academia and industry. Coverage includes all commercial realizations of the Symbian, Windows Mobile and Linux platforms. The text introduces each programming language (JAVA, Python, C/C++) and offers a set of development environments "step by step," to help familiarize developers with limitations, pitfalls, and challenges. The accompanying DVD includes all presented development environments and source code examples.

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Distributed Operating Systems: Concepts and Design Review

Distributed Operating Systems: Concepts and Design
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Distributed Operating Systems: Concepts and Design ReviewConcepts and coverage is excellent for learning and the content are not too in-depth especially towards a student. Cover areas like file organisation as well as memory management which is lacking in many similar topic publications. Chapters discussed are comprehensive and relevant to learners in these fields. Diagrams are illustrative and easy to understand. A good choice especially to students that are beginners in operating systems concepts.Distributed Operating Systems: Concepts and Design OverviewDistributed Operating Systems will provide engineers, educators, and researchers with an in-depth understanding of the full range of distributed operating systems components. Each chapter addresses de-facto standards, popular technologies, and design principles applicable to a wide variety of systems. Complete with chapter summaries, end-of-chapter exercises and bibliographies, Distributed Operating Systems concludes with a set of case studies that provide real-world insights into four distributed operating systems.

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Handbook of Open Source Tools Review

Handbook of Open Source Tools
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Handbook of Open Source Tools ReviewThis book on Open Source Tools covers some of the well known open source tools such as GCC, OpenOffice, OpenSSH, VNC, Apache, and Boost. But it goes much further than that, it presents a detailed description of many of the underlying open source components of Linux. It describes how to install and use the programming languages such as Erlang and X10 which are making inroads in high performance computing.
For developers the book is an ideal reference and introductory guide for libraries such as HDF5, APR, XML and compression libraries. Overall an excellent reference for practitioners using Open Source Technologies.
The book also describes most of the mathematical software used on Linux such as R, Maxima, and GLPK.Handbook of Open Source Tools OverviewHandbook of Open Source Tools introduces a comprehensive collection of advanced open source tools useful in developing software applications. The book contains information on more than 200 open-source tools which include software construction utilities for compilers, virtual-machines, database, graphics, high-performance computing, OpenGL, geometry, algebra, graph theory , GUIs and more. Special highlights for software construction utilities and application libraries are included. Each tool is covered in the context of a real like application development setting. This unique handbook presents a comprehensive discussion of advanced tools, a valuable asset used by most application developers and programmers; includes a special focus on Mathematical Open Source Software not available in most Open Source Software books, and introduces several tools (eg ACL2, CLIPS, CUDA, and COIN) which are not known outside of select groups, but are very powerful.Handbook of Open Source Tools is designed for application developers and programmers working with Open Source Tools. Advanced-level students concentrating on Engineering, Mathematics and Computer Science will find this reference a valuable asset as well.

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