"""
Enrichment-related models: Enricher.
"""

from dataclasses import dataclass

from .core import Element, Poset, Relation
from .posetspace import PosetSpace


@dataclass
class Enricher:
    """An enricher that can enrich poset relations with additional structure.

    The Enricher class provides functionality to augment poset relations with
    semantic information from an enrichment posetspace. This allows relations
    to carry additional meaning beyond simple ordering.

    Attributes:
        poset: The poset whose relations will be enriched.
        enrichment: The posetspace providing enrichment elements.

    Examples:
        >>> from coposet.models.posetspace import PosetSpace
        >>> from coposet.models.core import Element, Poset, Relation
        >>> from coposet.types import PosetSpaceName, Description, ElementName, PosetName
        >>>
        >>> # Create a poset for environmental policies
        >>> policy_space = PosetSpace(
        ...     name=PosetSpaceName("Environmental Policies"),
        ...     description=Description("Climate action priorities")
        ... )
        >>>
        >>> # Policy elements
        >>> carbon_tax = Element(
        ...     name=ElementName("Carbon Tax"),
        ...     description=Description("Tax on carbon emissions"),
        ...     posetspace=policy_space
        ... )
        >>> renewables = Element(
        ...     name=ElementName("Renewable Subsidies"),
        ...     description=Description("Support for clean energy"),
        ...     posetspace=policy_space
        ... )
        >>> regulations = Element(
        ...     name=ElementName("Emission Standards"),
        ...     description=Description("Regulatory limits"),
        ...     posetspace=policy_space
        ... )
        >>>
        >>> # Create enrichment space for reasoning
        >>> reason_space = PosetSpace(
        ...     name=PosetSpaceName("Policy Reasoning"),
        ...     description=Description("Reasons for policy preferences")
        ... )
        >>>
        >>> # Enrichment elements explaining preferences
        >>> economic = Element(
        ...     name=ElementName("Economic Impact"),
        ...     description=Description("Based on economic analysis"),
        ...     posetspace=reason_space
        ... )
        >>> urgency = Element(
        ...     name=ElementName("Climate Urgency"),
        ...     description=Description("Based on climate science"),
        ...     posetspace=reason_space
        ... )
        >>> feasibility = Element(
        ...     name=ElementName("Political Feasibility"),
        ...     description=Description("Based on political reality"),
        ...     posetspace=reason_space
        ... )
        >>>
        >>> # Create policy poset
        >>> policy_poset = Poset(
        ...     name=PosetName("Expert Ranking"),
        ...     description=Description("Climate expert preferences"),
        ...     posetspace=policy_space,
        ...     relations=[
        ...         Relation(less=carbon_tax, greater=renewables),
        ...         Relation(less=regulations, greater=renewables),
        ...     ]
        ... )
        >>>
        >>> # Create enricher
        >>> enricher = Enricher(poset=policy_poset, enrichment=reason_space)
        >>>
        >>> # Enrich relations with reasoning (when implemented)
        >>> # enriched_poset = enricher.enrich({
        >>> #     (policy_poset.relations[0], urgency),    # renewables > carbon_tax due to urgency
        >>> #     (policy_poset.relations[1], feasibility), # renewables > regulations due to feasibility
        >>> # })

    Note:
        Enrichment is useful for:
        - Adding semantic labels to relations (e.g., "strongly preferred")
        - Attaching metadata like confidence levels or reasons
        - Creating multi-criteria orderings
    """

    poset: Poset
    enrichment: PosetSpace

    def enrich(self, relations: set[tuple[Relation, Element]]) -> Poset:
        """Enrich the poset relations with elements from the enrichment posetspace.

        This method creates a new poset where specified relations are augmented
        with enrichment elements. The enrichment elements provide additional
        semantic information about the nature or strength of each relation.

        Args:
            relations: Set of tuples mapping Relation objects to enrichment Element
                      objects. Each tuple (rel, elem) indicates that relation rel
                      should be enriched with element elem from the enrichment space.

        Returns:
            A new Poset with the same elements and ordering but with enriched
            relations carrying the specified enrichment elements.

        Raises:
            NotImplementedError: Enrichment algorithm is not yet implemented.

        Examples:
            >>> # Create confidence-based enrichment
            >>> confidence_space = PosetSpace(
            ...     name=PosetSpaceName("Confidence Levels"),
            ...     description=Description("Voting confidence")
            ... )
            >>>
            >>> high = Element(ElementName("High"), Description("90%+ confident"), confidence_space)
            >>> medium = Element(ElementName("Medium"), Description("60-90% confident"), confidence_space)
            >>> low = Element(ElementName("Low"), Description("<60% confident"), confidence_space)
            >>>
            >>> # Enrich relations based on voting confidence
            >>> enrichments = {
            ...     (strong_preference_relation, high),    # Very confident about this
            ...     (weak_preference_relation, low),       # Less certain
            ...     (derived_relation, medium),            # Inferred with medium confidence
            ... }
            >>>
            >>> confidence_enricher = Enricher(poset=voted_poset, enrichment=confidence_space)
            >>> enriched_poset = confidence_enricher.enrich(enrichments)
            >>>
            >>> # Access enriched relations (conceptual)
            >>> for rel in enriched_poset.relations:
            ...     if rel.enrichment:
            ...         print(f"{rel.less.name} < {rel.greater.name} "
            ...               f"(confidence: {rel.enrichment.name})")
            >>>
            >>> # Multi-criteria enrichment example
            >>> criteria_space = PosetSpace(
            ...     name=PosetSpaceName("Decision Criteria"),
            ...     description=Description("Multiple decision factors")
            ... )
            >>>
            >>> cost = Element(ElementName("Cost-based"), Description("Economic factors"), criteria_space)
            >>> quality = Element(ElementName("Quality-based"), Description("Performance factors"), criteria_space)
            >>> time = Element(ElementName("Time-based"), Description("Schedule factors"), criteria_space)
            >>>
            >>> # Tag each relation with its primary decision criterion
            >>> multi_enrichments = {
            ...     (supplier_a_better_than_b, cost),     # A > B due to cost
            ...     (supplier_b_better_than_c, quality),   # B > C due to quality
            ...     (supplier_a_better_than_c, time),      # A > C due to delivery time
            ... }

        Note:
            - Relations not specified in the input remain unenriched
            - Enrichment elements must come from the enricher's enrichment space
            - The resulting poset maintains the same ordering structure
        """
        # Skeleton implementation
        raise NotImplementedError("Enrichment algorithm not yet implemented")
