class tensortrade.env.generic.environment.TradingEnv(action_scheme: tensortrade.env.generic.components.action_scheme.ActionScheme, reward_scheme: tensortrade.env.generic.components.reward_scheme.RewardScheme, observer: tensortrade.env.generic.components.observer.Observer, stopper: tensortrade.env.generic.components.stopper.Stopper, informer: tensortrade.env.generic.components.informer.Informer, renderer: tensortrade.env.generic.components.renderer.Renderer, **kwargs)[source]

Bases: gym.core.Env, tensortrade.core.base.TimeIndexed

Parameters: action_scheme (ActionScheme) – A component for generating an action to perform at each step of the environment. reward_scheme (RewardScheme) – A component for computing reward after each step of the environment. observer (Observer) – A component for generating observations after each step of the environment. informer (Informer) – A component for providing information after each step of the environment. renderer (Renderer) – A component for rendering the environment. kwargs (keyword arguments) – Additional keyword arguments needed to create the environment.
agent_id = None
close() → None[source]

Closes the environment.

components

The components of the environment. (Dict[str,Component], read-only)

episode_id = None
render(**kwargs) → None[source]

Renders the environment.

reset() → numpy.array[source]

Resets the environment.

Returns: obs (np.array) – The first observation of the environment.
save() → None[source]

Saves the rendered view of the environment.

step(action: Any) → Tuple[numpy.array, float, bool, dict][source]

Makes on step through the environment.

Parameters: action (Any) – An action to perform on the environment. np.array – The observation of the environment after the action being performed. float – The computed reward for performing the action. bool – Whether or not the episode is complete. dict – The information gathered after completing the step.