I have been working on this for quite a while, with initial plans to make it a service. But I have changed plans, and am releasing it to the world.
What have I been working on, you ask? Not that I like sliced bread, but it's at least as good as that: It solves some problems while it introduces some others. It's a proxy between Twitter and your email client that sits on your computer or a server translating mail-language(POP, SMTP) to Twtter-language(REST API).
This way you can read your tweets in your mail client, store them in folders, search though them, and do all the other stuff mail clients are good at. It even allows you to reply and forward(retweet in Twitter lingo) tweets.
Here is how to get it. You go to my GitHub repo, which lives at the link below, and pull/download the code.
The next step is to get the dependencies, which include Twisted, OAuth2 and Twitter-Text-Python. You might try to use setup.py for that, but I'm not sure it works.
Now you simply run "twistd -ny twemail.tac" in the Twemail directory. If everything went well you'll see some messages rolling by about starting services.
Now all that remains is to configure your mail client with the following information"
A long time ago I saw a challenge on a Python forum about writing a Rock-Paper-Scissors bot that performs better than a random bot.
As strange as it might seem, Rock-Paper-Scissors is anything but random. As long as it's played by people, they'll always try to come up with a winning move. I've been told there are even championships with this game.
So while trying to improve my Clojure skills I came up with the idea of using a Markov chain to write a Rock-Paper-Scissors bot.
Markov chains - as I recently learnt - are a random process where every step is only based on the previous. I'm not a psychologist, but when I play Rock-Paper-Scissors, I usually go like "I just lost using paper, so lets try rock" or "I won using rock, lets do it again", so I think it suits the challenge.
I use this map to define the probability of certain actions:
So with this example data, If I used rock, and won. I'll choose rock again, now I lose, so I choose the item inferior to rock: scissors. Draw, so I'll choose the item superior to scissors: rock.
The roulette function takes a map like {:same 1, :inferior 2, :superior 4} and returns one of the keys with the probability of the value. Calling this 7 times should approximately return 4 times :superior, 2 times :inferior and :same only once.
The guess function uses the Markov map to predict my action, and take the item that wins from mine.
Then there is the check function, which just returns if I won or lost based on the 2 items, and the relation fn which does the same for determining which of the 2 items is better.
Then there is the play function which focuses on getting your input, comparing results, and updating the Markov data to represent your actual actions.
You should update the map with the map that is printed at the end of the game, to improve the learning process of my bot. If you collect a lot of data, it could be interesting to send it in, so I can improve my bot to have a proper data set to start with.
Since the last keynote, where Apple announced iTunes 10, I've heard a lot of complaints about the vertical close buttons and the new icons.
For the close buttons you should keep an eye on http://hints.macworld.com/, but at least I solved the problem of the ugly icon. Before updating, save the old icon by right-clicking on iTunes, and then on "Show package contents", then browse to Content/Resources and copy iTunes.icns somewhere safe. Now upgrade iTunes, and do the same thing in reverse, so you'll overwrite the new iTunes.icns. Below is a video and the original icon, in case you are to late to copy it yourself. You might need to start and stop iTunes a few times, or even reboot to se the "new" icon.