package com.twitter.home_mixer
package functional_component.feature_hydrator

import com.twitter.finagle.stats.StatsReceiver
import com.twitter.home_mixer.model.HomeFeatures.AuthorIdFeature
import com.twitter.home_mixer.param.HomeMixerInjectionNames.MetricCenterUserCountingFeatureRepository
import com.twitter.home_mixer.util.ObservedKeyValueResultHandler
import com.twitter.onboarding.relevance.features.{thriftjava => rf}
import com.twitter.product_mixer.component_library.model.candidate.TweetCandidate
import com.twitter.product_mixer.core.feature.Feature
import com.twitter.product_mixer.core.feature.featuremap.FeatureMap
import com.twitter.product_mixer.core.feature.featuremap.FeatureMapBuilder
import com.twitter.product_mixer.core.functional_component.feature_hydrator.BulkCandidateFeatureHydrator
import com.twitter.product_mixer.core.model.common.CandidateWithFeatures
import com.twitter.product_mixer.core.model.common.identifier.FeatureHydratorIdentifier
import com.twitter.product_mixer.core.pipeline.PipelineQuery
import com.twitter.servo.keyvalue.KeyValueResult
import com.twitter.servo.repository.KeyValueRepository
import com.twitter.stitch.Stitch
import com.twitter.util.Future

import javax.inject.Inject
import javax.inject.Named
import javax.inject.Singleton

object MetricCenterUserCountingFeature
    extends Feature[TweetCandidate, Option[rf.MCUserCountingFeatures]]

@Singleton
class MetricCenterUserCountingFeatureHydrator @Inject() (
  @Named(MetricCenterUserCountingFeatureRepository) client: KeyValueRepository[Seq[
    Long
  ], Long, rf.MCUserCountingFeatures],
  override val statsReceiver: StatsReceiver)
    extends BulkCandidateFeatureHydrator[PipelineQuery, TweetCandidate]
    with ObservedKeyValueResultHandler {

  override val identifier: FeatureHydratorIdentifier =
    FeatureHydratorIdentifier("MetricCenterUserCounting")

  override val features: Set[Feature[_, _]] = Set(MetricCenterUserCountingFeature)

  override val statScope: String = identifier.toString

  override def apply(
    query: PipelineQuery,
    candidates: Seq[CandidateWithFeatures[TweetCandidate]]
  ): Stitch[Seq[FeatureMap]] = {
    Stitch.callFuture {
      val possiblyAuthorIds = extractKeys(candidates)
      val userIds = possiblyAuthorIds.flatten

      val response: Future[KeyValueResult[Long, rf.MCUserCountingFeatures]] = if (userIds.isEmpty) {
        Future.value(KeyValueResult.empty)
      } else {
        client(userIds)
      }

      response.map { result =>
        possiblyAuthorIds.map { possiblyAuthorId =>
          val value = observedGet(key = possiblyAuthorId, keyValueResult = result)

          FeatureMapBuilder()
            .add(MetricCenterUserCountingFeature, value)
            .build()
        }
      }
    }
  }

  private def extractKeys(
    candidates: Seq[CandidateWithFeatures[TweetCandidate]]
  ): Seq[Option[Long]] = {
    candidates.map { candidate =>
      candidate.features
        .getTry(AuthorIdFeature)
        .toOption
        .flatten
    }
  }
}