February Mini Book Reviews
Over the past month, I've read four books that I wanted to review for you: Learning Perl Objects, References & Modules, Text Processing in Python, Core PHP Programming, 3rd Ed. and MySQL 2nd Ed.. All of them are good books for the audience each is trying to hit. Take a look below for some more information.
I tend to review books that are interesting to me (no surprise there), but if you'd like me to review a book, let me know at firstname.lastname@example.org, and I'll do my best to put it in my reading pile.
In addition to a short review of each book, I'm also rating them on a scale of 1 to 10. Tens represent something pretty close to life changing, so don't look for them too often.
Many years ago, I found a copy of Randal Schwartz's Learning Perl, which I really loved. I've suggested it to a number of Perl neophytes since then. I even bought a copy for my daughter last year so she could get a feel for what Perl can do. I'd always wanted a follow up that was more approachable, and now Randal and Tom have provided exactly the book I was looking for.
Learning Perl Objects, References & Modules is a fairly small book, 179 pages discounting exercise answers and appendix, but it packs a solid amount of information into that small space. The book is laid out to support a Perl training class, and permission (and advice) is given for instructors who want to use it as a text book. It works perfectly well for self-guided learning though, so don't worry about picking it up for yourself.
My only nit was that some of the OO related bits are familiar to avid readers of Randal's work. Other than that, I really enjoyed the book. The chapter on Essential Testing probably is my favorite, although a number of good things are scattered throughout. I'm giving this book a solid 9 stars--and I'm giving a copy of it to my daughter as soon as she finishes Learning Perl.
Upon picking up and leafing through Text Processing in Python, I immediately took a liking to it. David skips over a lot of the extraneous clutter that tends to fill books. His preface (chapter 0) has a meatiness missing from most others. While not huge, 416 pages in all, the book presents a fairly dense chunk of information.
Although David manages to convey both the philosophy of text processing and the use of Python quite well, it sometimes felt as though I was reading a Python reference with some of text munging information tossed in. Another downside to David's presentation is his typography is quite different from what you'll see in most other books. The book is easily readable though, so neither of these should present a big problem.
Although the book is quite good overall, I think I learned the most from Chapter 4, "Parsers and State Machines". I'll keep this book handy for a while, and try to absorb some of its lessons as I go back to it with specific problems to solve. Text Processing in Python gets 8 stars.
-- -pate http://on-ruby.blogspot.com
Practical Task Scheduling Deployment
July 20, 2016 12:00 pm CDT
One of the best things about the UNIX environment (aside from being stable and efficient) is the vast array of software tools available to help you do your job. Traditionally, a UNIX tool does only one thing, but does that one thing very well. For example, grep is very easy to use and can search vast amounts of data quickly. The find tool can find a particular file or files based on all kinds of criteria. It's pretty easy to string these tools together to build even more powerful tools, such as a tool that finds all of the .log files in the /home directory and searches each one for a particular entry. This erector-set mentality allows UNIX system administrators to seem to always have the right tool for the job.
Cron traditionally has been considered another such a tool for job scheduling, but is it enough? This webinar considers that very question. The first part builds on a previous Geek Guide, Beyond Cron, and briefly describes how to know when it might be time to consider upgrading your job scheduling infrastructure. The second part presents an actual planning and implementation framework.
Join Linux Journal's Mike Diehl and Pat Cameron of Help Systems.
Free to Linux Journal readers.Register Now!
- SUSE LLC's SUSE Manager
- My +1 Sword of Productivity
- Murat Yener and Onur Dundar's Expert Android Studio (Wrox)
- Non-Linux FOSS: Caffeine!
- Managing Linux Using Puppet
- Tech Tip: Really Simple HTTP Server with Python
- Doing for User Space What We Did for Kernel Space
- Rogue Wave Software's Zend Server
- SuperTuxKart 0.9.2 Released
- Parsing an RSS News Feed with a Bash Script
With all the industry talk about the benefits of Linux on Power and all the performance advantages offered by its open architecture, you may be considering a move in that direction. If you are thinking about analytics, big data and cloud computing, you would be right to evaluate Power. The idea of using commodity x86 hardware and replacing it every three years is an outdated cost model. It doesn’t consider the total cost of ownership, and it doesn’t consider the advantage of real processing power, high-availability and multithreading like a demon.
This ebook takes a look at some of the practical applications of the Linux on Power platform and ways you might bring all the performance power of this open architecture to bear for your organization. There are no smoke and mirrors here—just hard, cold, empirical evidence provided by independent sources. I also consider some innovative ways Linux on Power will be used in the future.Get the Guide