package com.twitter.product_mixer.component_library.selector

import com.twitter.product_mixer.component_library.model.candidate.BaseTweetCandidate
import com.twitter.product_mixer.component_library.model.candidate.IsPinnedFeature
import com.twitter.product_mixer.core.feature.featuremap.FeatureMapBuilder
import com.twitter.product_mixer.core.model.common.presentation.ItemCandidateWithDetails
import com.twitter.product_mixer.core.model.common.presentation.CandidatePipelines
import com.twitter.product_mixer.core.model.common.presentation.CandidateSources
import com.twitter.product_mixer.core.model.common.presentation.CandidateSourcePosition

/**
 * Once a pair of duplicate candidates has been found we need to someone 'resolve' the duplication.
 * This may be as simple as picking whichever candidate came first (see [[PickFirstCandidateMerger]]
 * but this strategy could mean losing important candidate information. Candidates might, for
 * example, have different features. [[CandidateMergeStrategy]] lets you define a custom behavior
 * for resolving duplication to help support these more nuanced situations.
 */
trait CandidateMergeStrategy {
  def apply(
    existingCandidate: ItemCandidateWithDetails,
    newCandidate: ItemCandidateWithDetails
  ): ItemCandidateWithDetails
}

/**
 * Keep whichever candidate was encountered first.
 */
object PickFirstCandidateMerger extends CandidateMergeStrategy {
  override def apply(
    existingCandidate: ItemCandidateWithDetails,
    newCandidate: ItemCandidateWithDetails
  ): ItemCandidateWithDetails = existingCandidate
}

/**
 * Keep the candidate encountered first but combine all candidate feature maps.
 */
object CombineFeatureMapsCandidateMerger extends CandidateMergeStrategy {
  override def apply(
    existingCandidate: ItemCandidateWithDetails,
    newCandidate: ItemCandidateWithDetails
  ): ItemCandidateWithDetails = {
    // Prepend new because list set keeps insertion order, and last operations in ListSet are O(1)
    val mergedCandidateSourceIdentifiers =
      newCandidate.features.get(CandidateSources) ++ existingCandidate.features
        .get(CandidateSources)
    val mergedCandidatePipelineIdentifiers =
      newCandidate.features.get(CandidatePipelines) ++ existingCandidate.features
        .get(CandidatePipelines)

    // the unitary features are pulled from the existing candidate as explained above, while
    // Set Features are merged/accumulated.
    val mergedCommonFeatureMap = FeatureMapBuilder()
      .add(CandidatePipelines, mergedCandidatePipelineIdentifiers)
      .add(CandidateSources, mergedCandidateSourceIdentifiers)
      .add(CandidateSourcePosition, existingCandidate.sourcePosition)
      .build()

    existingCandidate.copy(features =
      existingCandidate.features ++ newCandidate.features ++ mergedCommonFeatureMap)
  }
}

/**
 * Keep the pinnable candidate. For cases where we are dealing with duplicate entries across
 * different candidate types, such as different sub-classes of
 * [[com.twitter.product_mixer.component_library.model.candidate.BaseTweetCandidate]], we will
 * prioritize the candidate with [[IsPinnedFeature]] because it contains additional information
 * needed for the positioning of a pinned entry on a timeline.
 */
object PickPinnedCandidateMerger extends CandidateMergeStrategy {
  override def apply(
    existingCandidate: ItemCandidateWithDetails,
    newCandidate: ItemCandidateWithDetails
  ): ItemCandidateWithDetails =
    Seq(existingCandidate, newCandidate)
      .collectFirst {
        case candidate @ ItemCandidateWithDetails(_: BaseTweetCandidate, _, features)
            if features.getTry(IsPinnedFeature).toOption.contains(true) =>
          candidate
      }.getOrElse(existingCandidate)
}