A python interface for training Reinforcement Learning bots to battle on pokemon showdown.
The pokemon showdown Python environment
A Python interface to create battling pokemon agents.
poke-env offers an easy-to-use interface for creating rule-based or training Reinforcement Learning bots to battle on pokemon showdown.
Agents are instance of python classes inheriting from
Player. Here is what your first agent could look like:
class YourFirstAgent(Player): def choose_move(self, battle): for move in battle.available_moves: if move.base_power > 90: # A powerful move! Let's use it return self.create_order(move) # No available move? Let's switch then! for switch in battle.available_switches: if switch.current_hp_fraction > battle.active_pokemon.current_hp_fraction: # This other pokemon has more HP left... Let's switch it in? return self.create_order(switch) # Not sure what to do? return self.choose_random_move(battle)
To get started, take a look at our documentation!
Documentation and examples
Documentation, detailed examples and starting code can be found on readthedocs.
This project requires python >= 3.6 and a Pokemon Showdown server.
pip install poke-env
You can use smogon's server to try out your agents against humans, but having a development server is strongly recommended. In particular, it is recommended to use the
--no-security flag to run a local server with most rate limiting and throttling turned off. Please refer to the docs for detailed setup instructions.
git clone https://github.com/smogon/pokemon-showdown.git
You can also clone the latest master version with:
git clone https://github.com/hsahovic/poke-env.git
Dependencies and development dependencies can then be installed with:
pip install -r requirements.txt pip install -r requirements-dev.txt
This project is a follow-up of a group project from an artifical intelligence class at Ecole Polytechnique.
Team data comes from Smogon forums' RMT section.
Data files are adapted version of the
js data files of Pokemon Showdown.
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