Code in this repository is modified for Sentdex's tutorials
An easy-to-use library for writing AI Bots for StarCraft II in Python 3. The ultimate goal is simplicity and ease of use, while still preserving all functionality. A really simple worker rush bot should be no more than twenty lines of code, not two hundred. However, this library intends to provide both high and low level abstractions.
This library (currently) covers only the raw scripted interface. At this time I don't intend to add support for graphics-based interfaces.
Documentation is in the Wiki.
For automaticly running multiple matches, check out Dentosal/sc2-bot-match-runner.
You'll need Python 3.6 or newer.
pip3 install --user --upgrade sc2
Please note that not all commits are not released to PyPI. Releases are tagged with version number. You can see latest released versions from tags page.
You'll also need an StarCraft II executable. If you are running Windows or macOS, just install the normal SC2 from blizzard app. The free starter edition works too.. Linux users must use the Linux binary.
You probably want some maps too. Official map downloads are available from Blizzard/s2client-proto. Notice: the map files are to be extracted into subdirectories of the install-dir/Maps directory.
After installing the library, a StarCraft II executable, and some maps, you're ready to get started. Simply run a bot file to fire up an instance of StarCraft II with the bot running. For example:
python3 examples/protoss/cannon_rush.py
As promised, worker rush in less than twenty lines:
import sc2
from sc2 import run_game, maps, Race, Difficulty
from sc2.player import Bot, Computer
class WorkerRushBot(sc2.BotAI):
async def on_step(self, iteration):
if iteration == 0:
for worker in self.workers:
await self.do(worker.attack(self.enemy_start_locations[0]))
run_game(maps.get("Abyssal Reef LE"), [
Bot(Race.Zerg, WorkerRushBot()),
Computer(Race.Protoss, Difficulty.Medium)
], realtime=True)This is probably the simplest bot that has any realistic chances of winning the game. I have ran it against the medium AI a few times, and once in a while it wins.
You can find more examples in the examples/ folder.
If you have any issues, ideas or feedback, please create a new issue. Pull requests are also welcome!