# Copyright 2019 The TensorTrade Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License
import pandas as pd
from abc import ABCMeta, abstractmethod
from tensortrade.trades import Trade
[docs]class RewardStrategy(object, metaclass=ABCMeta):
def __init__(self):
pass
@property
def exchange(self) -> 'InstrumentExchange':
"""The exchange being used by the current trading environment. Setting the exchange causes the strategy to reset."""
return self._exchange
@exchange.setter
def exchange(self, exchange: 'InstrumentExchange'):
self._exchange = exchange
self.reset()
[docs] def reset(self):
"""Optionally implementable method for resetting stateful strategies."""
pass
[docs] @abstractmethod
def get_reward(self, current_step: int, trade: Trade) -> float:
"""
Arguments:
current_step: The environment's current timestep.
trade: The trade executed and filled this timestep.
Returns:
A float corresponding to the benefit earned by the action taken this timestep.
"""
raise NotImplementedError()