Content and opinions

The book starts with two protocols that can be used, X10 and C-Bus. X10 uses the power lines to communicate between elements, and C-Bus uses a proprietary protocol on a specific bus that must be installed by a specific company. It can also use a wireless protocol. Both seem to be widely available in America, but in Europe, it’s different. The chapter presents a lot of appliances, but I don’t know f they are available on Europe power lines for X10 or even if they are sold in Europe (for both of them). It’s too bad the author didn’t choose a better support (like a real ISO and open standard like KNX). X10 is somewhat limited like C-Bus is although in a different way.

The second chapter is about different hardwares that can be used. The first is the well-known NSLU2, then are other gaming consoles. It seems that safe for the high end consoles, every other hardware is either discontinued or difficult to hack (there are a lot of hacking to do according to the book). For instance Arduino needs some soldering. What about hardware like the Sheeva plug ?

The next chapter explains how media data can be stored and accessed. It’s more or less a sum up of what can be found on the Internet. In fact, the rest of the book is material like this. A real big sum up of what can be found on media use on the Internet, and a lot of shell code to make it work.

Conclusion

It’s not that the book is of no use. If you have X10 appliances or C-Bus ones, if you need a big tutorial on media control, this book might be for you. If you want to do home automation, I’m afraid only the first chapter deals with what home automation is mainly about: light and heating control.

Smart Home Automation with Linux
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by Steven Goodwin
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Content and opinions

The first part is dedicated to the reasons why a software project can fail. It starts with 12 reasons of why software is different than other fields. This implies some assumptions that can differ from the usual project management. The last chapter is a simulation of what a failing software project is. All in all, the main message passes, but I think it is too harsh. The underlying idea is that software is different than all the other fields, but in fact, it may be all the same (at least on the points that were underlined): building a bridge is something we know how to do through usual management, but it can still run late/too expensive/… Besides, the example is overdone. It cumulates all the typical mistakes that we know now how to avoid.

The second part gives the pieces of advice to fix what the first part uncovered. Three agile processes are explained, then tools to budget with one of these processes. the last is the example of the first part reloaded with agile methods. I agree that agile methods are an answer to the software management project, but each time software management is really opposed to usual management. There are issues that are still really different in software projects: defining the needs of the users. When you build a bridge or when you build a house, you know what you want. You know the number of ways, or the number of doors/windows/rooms, … In software projects, you don’t know how many doors you need. Another issue is that people think that software is easy to do, so it’s easy to add something else (mainly because it is mandatory… or not).

Conclusion

If the book is really easy to read, there are some shortcuts that did bother me: the two examples are caricatures of reality (not even a real example where things went well or really bad, they are a story), and software management is also exagerated compared to project management. Perhaps the real conclusion is this one: exageration. Software project management is too difficult to be explained by a caricature: it may lead to the opposite effect.

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by George Stepanek
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| 4.5 | 6

Content and opinions

After a small introduction where all elements of the book are used for a simple example, the author tells us how to install Python and the different modules that will be needed for our task. Then, the langage itself is fastly introduced. If you don’t know any object-oriented langage or Python, you may find the introduction too light, so you may need to read a book dedicated to the Python langage if you want to master it. It’s obviously not the goal of the book.

Two chapters deal with data management and extracting it from a file. Why can data be stored? How to parse and retrieve what we need? The answer to these questions are in these chapters (even if the more complex formats as XML are not deal with, you’ll have to dig in the documentation) in a simple and efficient way.

Display is of course the key element here. It’s the Matplotlib module which has this responsibility. It’s a complex module, but it is explained so that is is easy to use. Then Numpy, Scipy and PIL have each their chapter. They cannot be fully presented, only with a data analysis orientation. For more advanced functions, you will once again have to use the associated documentation.

The last chapter is dedicated to useful but not mandatory modules, like Pickle. This chapter can be skipped at first, but then the modules will help optimizing your time for more complex visualizations.

Conclusion

The author took the challenge of only showing the data analysis and visualization part of Python. The text is simple and goes straight to the point. By reading the book, one is able to do 99% of data analysis and quality controls (QCs). The challenge is thus a success.

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by Shai Vaingast
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| 4 | 14