dmangame/dmangame @ GitHub

the AI module

Each AI lives in a python module. AI modules execute in the python environment, with a few modifications (See the notes below). After the modules are passed to the engine from command line, the game engine loads the module. It then looks to the module variable AIClass for the name of your AI.

Once the engine knows the class name, it loads the class from the ai module. Once the AIs are collected, they are instantiated and passed to the world. The world then takes care of calling each AI’s functions every turn.

notes

settings

There is a global, settings, that is exposed to each AI that contains information about the game state. The data contained in it is calculated by the world based on map size and other factors specified in the map settings file.

# prints information about the world state and what settings are
# available.
print settings

dependencies

The AI module comes with a dependency loader that will automatically import required modules from github or local filesystem depending on where the AI was loaded from. This is used on app engine, so ladder matches are always pulling the latest code from github.

# will add another_module to the current namespace, it acts like
# 'import another_module'
require_dependency("another_module")

keywords

Because the game has to run on python 2.5 (using appengine), there are a few keywords (for example next()) missing. To account for this, dmangame manually injects python keywords into the AI scope. If a keyword is missing, feel free to open an issue on github or fix it yourself and let me know.

restricted modules

By default, AIs loaded via the remote AI are run in restricted mode. This means that only a subset of modules are allowed to be loaded and writes to the file system are restricted. If you are writing an AI, don’t load sys or os if you want other people to run your AI.

This also restricts which builtins are callable - if you are calling a builtin and it fails, it’s probably because someone thought it was unsafe. (for example, compile())

ai.BareAI

If you don’t care for _unit_died and _unit_spawned (or want to do your own book keeping), you can subclass from ai.BareAI - in which case you need to implement the following two functions:

    def turn(self):
    def init(self):