cognition.decision.chain

Support for a decision process generated via an iterable value.

Classes

Link	A link in a chained decision process
ChainState	State of a chained decision process

Functions

create_chain_dp(chain, link_handler[, init_accumulator])

Decision process via an iterable that with a handler at each value accumulating a result

Module Contents

class cognition.decision.chain.Link[CV, CA]

A link in a chained decision process

value: CV

current iterated value

accumulator: CA | None

current (optional) user-accumulated value

class cognition.decision.chain.ChainState[CV, CA](chain, init_acc=None)

State of a chained decision process

Parameters represent…

• CV: type of iterated (v)alues

• CA: type of an optional (a)ccumulator

Parameters:

• chain (collections.abc.Iterable[CV]) – something iterable

• init_acc (CA | None) – (optional) initial accumulator value

__str__()

Return type:

str

property done: bool

Returns:

True if the iterable (chain) has been exhausted

Return type:

bool

property current_link: Link[CV, CA] | None

Returns:

current link in the chain, or None if exhausted

Return type:

Link[CV, CA] | None

property accumulator: CA | None

Returns:

current accumulator value

Return type:

CA | None

next(acc)

Proceeds with the chain

Parameters:

acc (CA | None) – optional new accumulator value

Return type:

None

cognition.decision.chain.create_chain_dp[CV, CA](chain, link_handler, init_accumulator=None)

Decision process via an iterable that with a handler at each value accumulating a result

Parameters:

• chain (collections.abc.Iterable[CV]) – sequence of values

• link_handler (cognition.util.functypes.BiFunction[Link[CV, CA], cognition.decision.core.IOContainer, CA | None]) – function called at each chain link that can update the accumulator

• init_accumulator (CA | None) – initial (optional) accumulator value

Returns:

produced decision process

Return type:

cognition.decision.dp.DecisionProcess[ChainState[CV, CA]]