This is a project combined with three parts to research how to predict the air flights' price change.

Based on urllib2 and some other functions, my own simple spider could fetch data from ceair.com.

Using matplotlib and wx, I built a UI to see how price of different places and time changed. Then identify some basic pattern in the changes to help build a model.

Each price record has some parameters, and I believe decision tree can help me understand what role played by each parameter in the model. According to parameters given, the trained decision tree will generate a result: "buy" or "wait".