For those of you who don’t know what SETI@Home optimizers are, they are essentially specialized versions of the standard version of the SETI@Home client which take advantage of extended floating-point instruction sets available to certain x86 (Intel, AMD, or the like) processors. Using these instruction sets allows optimized clients to complete work many times faster than it could before with the standard client. For example, prior to using an SSSE3 optimized client on my Intel Core 2 Quad Q6600 my recent average credit (RAC) on SETI was in the 500 range including one other active machine and now my RAC has spiked over 2,500 not including the other active machine.

Before we get started, you should make sure that all other active work units you have running are completed before replacing the standard client with an optimized one. Then you may choose which optimize client you will run. Keep in mind that currently, only Intel Core 2 based CPUs and a single VIA CPU are capable of running SSSE3 instructions. For more details on this you should refer to the SSSE3 wikipedia page. Otherwise, you will likely be able to run an SSE3 optimized client, unless your CPU is more than several years old, also refer to wikipedia for more information on this. If you’ve got an even older CPU, there are also clients for MMX, SSE, and SSE2.

Optionally you may check which instruction sets are supported by your CPU using the following command:

[maddog39@desktop ~]$ cat /proc/cpuinfo | grep flags | tail -n 1
flags		: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe nx lm constant_tsc arch_perfmon pebs bts pni monitor ds_cpl vmx est tm2 ssse3 cx16 xtpr lahf_lm

First thing we want to do is download the client for your respective CPU and kernel version (most likely SSE3 or SSSE3 and kernel 2.6) from this page and extract the tarball. If your using an older CPU requiring an older instruction set, see this page instead.

Before we actually drop in the optimized client, its probably best to suspend the SETI@Home project in BOINC for safe measure.

Now we get to physically install our new SETI@Home optimizer. In the folder you extracted from the tarball, you should find a binary (executable) and an app_info.xml file, either in the folder’s top directory or in a subsequent sub-folder.

You want to copy these files and launch nautilus (or your file manager of choice) as root and point it to the /var/lib/boinc folder. Hit Alt+F2 to bring up a run dialog and enter the command:

gksudo nautilus /var/lib/boinc/projects/setiathome.berkeley.edu

Paste the optimizer files into the directory and when comes up. Finally, you will need to restart the BOINC daemon. On my distribution, Arch Linux its:

sudo /etc/rc.d/boinc restart

Although if you are using Ubuntu, Debian, or a derivative its:

sudo /etc/init.d/boinc restart

Then, to start using your new SETI optimized client, you simply launch BOINC manager and resume the SETI@Home project. It should start downloading new workunits immediatley and your in business. I hope you found this article useful and keep in mind that I tried to keep it as easy as possible for the newer Linux users out there.

Download QOverclock 0.1

Download QOverclock 0.1 (Win32 Binary)

Basically you just stick the file in your home directory (or at your option in /usr/bin or /usr/local/bin) and add it to your auto-started applications in GNOME or KDE or put it in your xinitrc or whatever you want. For GNOME users I happen to know that you can do this from System > Preferences > Sessions > Startup Programs > Add. For windows users this script will never run because Banshee is *nix only as well as DBus (as far as I know). Enjoy!

Download pidgin_banshee_status.py

Now all we have to do is make a connection to Banshee via DBus and start calling methods. For this we will just use an interactive python interpreter which can be accessed by simply typing “python” at any command line prompt. Firstly, we will import the DBuslibrary.

import dbus

Next, we will make a connection to the session bus.

bus = dbus.SessionBus()

Then we will get Banshee’s PlayerEngine object which will let us control the player itself (Play, Pause, Next, Previous, Current Track, etc).

banshee = bus.get_object("org.bansheeproject.Banshee", "/org/bansheeproject/Banshee/PlayerEngine")

The first argument we pass, “org.bansheeproject.Banshee”, is the interface we want to connect to and “/org/bansheeproject/Banshee/PlayerEngine” is the path to the object that we want to use. Now we can start doing stuff with Banshee. You can pretty much take any of the methods listed in D-Feet and run them. For example:

banshee.Open("file:///home/maddog39/Music/Eisbrecher - Antikörper.mp3")

And to play the song…

banshee.Play()

Once you have had enough….

banshee.Pause()

Although note that you dont have to using the Open() method to use the Play() and Pause() methods, but Open() lets you open an arbitrary media file otherwise those other methods use the currently playing track. Now, to access properties you generally just take the name of the property and prepend ‘Get’ to it and make it a method. So for example:

banshee.GetCanPause()

Returns:

dbus.Boolean(False)

Or if we wanted to display all the information about the currently playing track we might do…

for key in currentTrack.keys():
	print key + ": " + str(currentTrack[key])

Which gives us:

album: Issues
rating: 0
name: Falling Away From Me
artist: Korn
URI: file:///home/maddog39/Music/Korn%20-%20Beating%20Me%20Down.mp3
length: 271.211
disc: 0
track-count: 16
year: 1999
track-number: 2

Another cool thing you can do with DBus is receive signals. What this allows us to do is run code when a given signal is triggered or received. We do this by connecting a python method with a signal on our bus. So if we wanted to do something every time Banshee changes its state (playing, paused, loading, loaded, etc) this is what would happen. We would first have to setup a main loop as it is required for a signals to function.

import gobject
from dbus.mainloop.glib import DBusGMainLoop
dbus.mainloop.glib.DBusGMainLoop(set_as_default=True)

Then we would create a callback method which would be run every time the signal is triggered.

def stateChanged(state):
	print "State Changed: %s" % state

Now we can add our signal receiver to our method.

bus.add_signal_receiver(stateChanged,
dbus_interface="org.bansheeproject.Banshee.PlayerEngine",
                        signal_name="StateChanged")

Finally, at the end of a script that uses signals we would want to run our main loop.

gobject.MainLoop().run()

Well thats pretty much it! Just keep in mind that this was not intended to be a tutorial but merely a guideline on how to do interact and do things with Banshee over DBus. So feel free to sit down and write some of your own scripts based on what you have learned here and I hope this helps. I have already written my own program to integrate Banshee into another application which I will talk about in another article. Enjoy!

So this is a simple little tutorial on how to write a basic “Hello World” bot using PyBotlib. The library itself is only a single file so I have not bothered to repackage it or write setup scripts as you will only need import that single file within your application. You may get the latest source code for the library at any time here (google code/SVN) or here (blog). So here we go…

Lets start by defining our bot class and its constructor.

import botlib
 
# Create a new class for our bot, extending the Bot class from botlib
class HelloWorldBot(botlib.Bot):
    def __init__(self, server, channel, nick, password=None):
        botlib.Bot.__init__(self, server, 6667, channel, nick)
 
        # Send nickserv password if available
        if password != None:
            self.protocol.privmsg("nickserv", "identify" % password)

Next we are going to want to override the __actions__ function of the Bot class which will handle all of our bots actions. This acts as essentially a main loop and is called infinitely until the bot is shutdown. In here we put code for our commands, responders, whatever other interaction with the IRC channel that we need.

    def __actions__(self):
        botlib.Bot.__actions__(self)
 
        # Create a Hello World responder/command
        if botlib.check_found(self.data, "!hello"):
            # Get the senders username
            username = self.get_username()
 
            # Send user a message in response
            self.protocol.privmsg(self.channel, "Hello %s!" % username)

So here, we have created a simple command called !hello which runs the code underneath its if statement when an instance of that command is found in the chat. Then we call the get_username() function of the Bot class (remember that we inherited from the Bot class) to get the user name of the person who initiated the command. After that, we simply send a message back to the channel using the equivalent function for IRC’s PRIVMSG command. Now all we to do is instantiate and run our new bot.

 if __name__ == "__main__":
    # Create new instance of our bot and run it
    HelloWorldBot("irc.wyldryde.org", "#maddog39", "HelloWorldBot").run()

Keep in mind that when you are instantiating Bot object, that because PyBotlib is entirely threaded, you can make as many instances of your bot as you would like. I do have a BotManager class in PyBotlib intended for managing sets of multiple bots on the same process however I have never actually tested it so your results may vary. Here is the script in its entirety.

import botlib
 
# Create a new class for our bot, extending the Bot class from botlib
class HelloWorldBot(botlib.Bot):
    def __init__(self, server, channel, nick, password=None):
        botlib.Bot.__init__(self, server, 6667, channel, nick)
 
        # Send nickserv password if availible
        if password != None:
            self.protocol.privmsg("nickserv", "identify" % password)
 
    def __actions__(self):
        botlib.Bot.__actions__(self)
 
        # Create a Hello World responder/command
        if botlib.check_found(self.data, "!hello"):
            # Get the senders username
            username = self.get_username()
 
            # Send user a message in response
            self.protocol.privmsg(self.channel, "Hello %s!" % username)
 
if __name__ == "__main__":
    # Create new instance of our bot and run it
    HelloWorldBot("irc.wyldryde.org", "#maddog39", "HelloWorldBot").run()

Finally, to run your new bot, simply issue the command:

python helloworldbot.py

At the terminal prompt or command prompt (windows). Also note that you must make sure that your botlib.py file is in the same directory as your bot. Have fun!

I realized that I had wasted several months of my time developing what I called a “framework” for PHP when it was really not very full featured and actually made things extremely hard for myself in the large scheme of things. After doing some homework, I had found really rich libraries that allowed me to do things beyond my wildest dreams before. Projects such as Smarty, jQuery, and TinyMCE just to name a few. What really gets me though is that many free (as in beer or potentially as in free speech) projects constantly fall behind because they take  forever to their own things such as rich text editors and ajax frameworks while their users are wondering why they don’t have the features they are looking for.

So  this is a call to all web developers out there. You really need to start reassessing  the libraries you write and think of how you could possibly use others’ great Open Source projects to assist you in the development of your application. Stop reinventing the wheel and start innovating, that’s what we are all about, right?

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