Bonsai_extra_state_machine (bonsai.bonsai.extra.state_machin.Bonsai_extra_state

module Bonsai := Bonsai.Cont

module Effect := Bonsai.Effect

val state_machine0_dynamic_model : 
  ?sexp_of_action:('action -> Core.Sexp.t) ->
  ?sexp_of_model:('model -> Core.Sexp.t) ->
  ?equal:('model -> 'model -> bool) ->
  model:
    [< `Computed of ('model option -> 'model) Bonsai.t
    | `Given of 'model Bonsai.t ] ->
  apply_action:
    (('action, unit) Bonsai.Apply_action_context.t ->
      'model ->
      'action ->
      'model) ->
  Bonsai.graph @ local ->
  'model Bonsai.t * ('action -> unit Effect.t) Bonsai.t

This function is identical to Bonsai.state_machine0 except that the default_model is initially unset, but can be computed or defaulted to a dynamic value.

This means that before an apply_action occurs, the model can change out from underneath the state machine as the default_model value changes. If this is undesirable, you may want to freeze the default_model first.

val state_machine1_dynamic_model : 
  ?sexp_of_action:('action -> Core.Sexp.t) ->
  ?sexp_of_model:('model -> Core.Sexp.t) ->
  ?equal:('model -> 'model -> bool) ->
  model:
    [< `Computed of ('model option -> 'model) Bonsai.t
    | `Given of 'model Bonsai.t ] ->
  apply_action:
    (('action, unit) Bonsai.Apply_action_context.t ->
      'input ->
      'model ->
      'action ->
      'model) ->
  'input Bonsai.t ->
  Bonsai.graph @ local ->
  'model Bonsai.t * ('action -> unit Effect.t) Bonsai.t

Read the docs for state_machine0_dynamic_model. This one has an extra 'input value that can be taken into account when the apply_action is invoked.

val state_dynamic_model : 
  ?sexp_of_model:('model -> Core.Sexp.t) ->
  ?equal:('model -> 'model -> bool) ->
  model:
    [< `Computed of ('model option -> 'model) Bonsai.t
    | `Given of 'model Bonsai.t ] ->
  Bonsai.graph @ local ->
  'model Bonsai.t * ('model -> unit Effect.t) Bonsai.t

The analog of Bonsai.state, but with a dynamic model. Read the docs for state_machine0_dynamic_model.

When passed a `Given model, behaves like value_with_override; takes on the initial value of the given model and has its value overwritten when the callback is scheduled.

When passed a `Computed f model, takes initial value f None. When the callback is scheduled with input i, takes the value f i.