Using Python to Query MySQL over the Net
Recently, I became the owner of more than a thousand records of Go (an ancient oriental strategic board game) games played by professional or amateur players. All the games were stored in Smart Game Format (SGF), which is a text-based format designed to keep records of board games for two players. Naturally, I made them available to other players through my web page.
To make searching through the archive easier, I first used an HTML form with only one text input field. The user could enter a string (for example, a player name) that was passed to a Python CGI script which, in turn, invoked good old grep to find the matching files, as shown in Figure 1. But this is a crude way of finding information. For instance, it can be used to find all the games played by a certain player but not to find more complicated things, such as all the games that player played with black stones or all the games won by that player in 1995.
In order to make a better search engine, I had to use a different approach. First, the database should describe the collection of game files. Then, a multiple input field form should be created to allow the user to search for various pieces of information at the same time. Finally, there should be a way to set up communication between the browser and database server, in order to make the result of the database query available to the user as an HTML document. Thus, the whole search would be performed as mapped in Figure 2.
I chose MySQL 3.22.32 as the database and Python 1.5.2 for CGI scripting. I have played with Perl but prefer the feel of Python. The installation procedure for these programs has been explained already in many articles and will not be covered here. The reader should check the web sites in Resources for further details concerning installation. Communication between MySQL and Python is handled by a contributed module, presented below.
Python makes MySQL queries through a special module designed by Joerg Senekowitsch. Of course, several other modules are available on the Net, but MySQLmodule1.4 was easy to install and learn, and it worked very well for me. On some systems (like FreeBSD) it is possible to install this module at the same time as Python. On my Slackware 7.1 Linux, I had to build and install it as a dynamically loadable module. This is a three-step procedure: untar the MySQLmodule archive, compile the shared module and install the module somewhere in Python's library path.
Step one is fairly simple. As root, one would type:
myhost:~# tar xvzf MySQLmodule-1.4.tar.gz
A new directory named MySQLmodule-1.4/ will be created with several files, the most important of which are MySQLmodule.c (the source for the module to be compiled) and README (a file with installation and use information).
There are several tricky things about step two. For instance, one must know precisely where the libraries and include files for MySQL and Python can be found. On my system, MySQL 3.22.32 places the mysqlclient library in /usr/lib/mysql and the mysql.h include file in /usr/include/mysql. Python libraries can be found in /usr/lib/python1.5/config and the include file in /usr/include/python1.5. The command to compile MySQLmodule is:
myhost:~# gcc -shared -I/usr/include/mysql MySQLmodule.so
Another hint: the order of items in the above command line is important and must not be changed! Believe me, this is a hard-learned truth.
Step three consists of copying MySQLmodule.so to a directory where it can be found by Python at runtime. For Python 1.5 this could be /usr/lib/python1.5/lib-dynload, where other shared object files also reside. With Python 2.0 (which I also tested) I would recommend using the directory /usr/lib/python2.0/site-packages/.
Once the module is installed, it should be available from Python. It is a good idea to check this right away with a simple import statement such as:
myhost:~$ python Python 1.5.2 (#1, May 28 2000, 18:04:10) Copyright 1991-1995 Stichting Matematisch Centrum, Amsterdam >>> import MySQL >>>
If Python doesn't complain with an error message, chances are the MySQL module is properly installed and working.
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.
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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.
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