from decimal import Decimal
from typing import override

from django.core.cache import cache
from django.test import TestCase
from django.utils import timezone

from apps.decision.services import decide_for_flag
from apps.events.services import process_events_batch
from apps.events.tests.helpers import make_event_type, make_exposure_type
from apps.experiments.models import ExperimentStatus
from apps.experiments.services import (
    experiment_approve,
    experiment_complete,
    experiment_create,
    experiment_start,
    experiment_submit_for_review,
    variant_create,
)
from apps.experiments.tests.helpers import (
    add_two_variants,
    make_experiment,
    make_flag,
)
from apps.metrics.services import (
    experiment_metric_add,
    metric_definition_create,
)
from apps.reports.services import build_experiment_report
from apps.reviews.services import review_settings_update
from apps.reviews.tests.helpers import make_approver, make_experimenter


class FullHappyPathTest(TestCase):
    @override
    def setUp(self) -> None:
        cache.clear()
        review_settings_update(
            default_min_approvals=1,
            allow_any_approver=True,
        )

        self.owner = make_experimenter("_hp")
        self.approver = make_approver("_hp")

        self.experiment = make_experiment(
            owner=self.owner,
            suffix="_hp",
            traffic_allocation=Decimal("100.00"),
        )
        self.v_control, self.v_treatment = add_two_variants(self.experiment)

        self.metric = metric_definition_create(
            key="ctr_hp",
            name="CTR",
            metric_type="ratio",
            direction="higher_is_better",
            calculation_rule={
                "numerator_event": "hp_click",
                "denominator_event": "hp_exposure",
            },
        )
        experiment_metric_add(
            experiment=self.experiment,
            metric=self.metric,
            is_primary=True,
        )

        make_exposure_type(name="hp_exposure")
        make_event_type(
            name="hp_click",
            display_name="Click",
            requires_exposure=True,
        )

        self.experiment = experiment_submit_for_review(
            experiment=self.experiment, user=self.owner
        )
        self.experiment = experiment_approve(
            experiment=self.experiment, approver=self.approver
        )
        self.experiment = experiment_start(
            experiment=self.experiment, user=self.owner
        )

    def test_full_decide_event_report_flow(self) -> None:
        decisions = []
        for i in range(10):
            cache.clear()
            d = decide_for_flag("flag_hp", f"user_{i}", {"country": "US"})
            self.assertEqual(d["reason"], "experiment_assigned")
            self.assertIsNotNone(d["variant_id"])
            decisions.append(d)

        now = timezone.now().isoformat()
        exposure_events = [
            {
                "event_id": f"hp_exp_{i}",
                "event_type": "hp_exposure",
                "decision_id": d["decision_id"],
                "subject_id": f"user_{i}",
                "timestamp": now,
                "properties": {},
            }
            for i, d in enumerate(decisions)
        ]
        result = process_events_batch(exposure_events)
        self.assertEqual(result.accepted, 10)

        click_events = [
            {
                "event_id": f"hp_click_{i}",
                "event_type": "hp_click",
                "decision_id": d["decision_id"],
                "subject_id": f"user_{i}",
                "timestamp": now,
                "properties": {},
            }
            for i, d in enumerate(decisions[:5])
        ]
        result = process_events_batch(click_events)
        self.assertEqual(result.accepted, 5)

        report = build_experiment_report(self.experiment)
        self.assertEqual(str(report["experiment_id"]), str(self.experiment.pk))
        total_exposures = sum(v["exposures"] for v in report["variants"])
        self.assertEqual(total_exposures, 10)

    def test_lifecycle_with_rollout_outcome(self) -> None:
        cache.clear()
        d = decide_for_flag("flag_hp", "subject_1", {})
        self.assertEqual(d["reason"], "experiment_assigned")

        self.experiment = experiment_complete(
            experiment=self.experiment,
            user=self.owner,
            outcome="rollout",
            rationale="Treatment wins",
            winning_variant_id=str(self.v_treatment.pk),
        )
        self.assertEqual(self.experiment.status, ExperimentStatus.COMPLETED)

    def test_decide_returns_default_after_complete(self) -> None:
        self.experiment = experiment_complete(
            experiment=self.experiment,
            user=self.owner,
            outcome="no_effect",
            rationale="No significant difference",
        )

        cache.clear()
        d = decide_for_flag("flag_hp", "subject_2", {})
        self.assertEqual(d["reason"], "no_active_experiment")
        self.assertEqual(d["value"], "a")

    def test_targeting_mismatch_returns_default(self) -> None:
        owner = make_experimenter("_tm")
        approver = make_approver("_tm")

        flag = make_flag(suffix="_tm", default="a")

        exp = experiment_create(
            flag=flag,
            name="Targeting Test",
            owner=owner,
            traffic_allocation=Decimal("100.00"),
            targeting_rules='country IN ["DE"]',
        )
        variant_create(
            experiment=exp,
            user=owner,
            name="control",
            value="a",
            weight=Decimal("50.00"),
            is_control=True,
        )
        variant_create(
            experiment=exp,
            user=owner,
            name="treatment",
            value="b",
            weight=Decimal("50.00"),
        )
        exp = experiment_submit_for_review(experiment=exp, user=owner)
        exp = experiment_approve(experiment=exp, approver=approver)
        exp = experiment_start(experiment=exp, user=owner)

        cache.clear()
        d = decide_for_flag("flag_tm", "subject_3", {"country": "US"})
        self.assertEqual(d["reason"], "targeting_mismatch")
        self.assertEqual(d["value"], "a")

    def test_report_with_period_filter(self) -> None:
        cache.clear()
        d = decide_for_flag("flag_hp", "user_rp", {})
        now = timezone.now()

        process_events_batch(
            [
                {
                    "event_id": "hp_rp_exp",
                    "event_type": "hp_exposure",
                    "decision_id": d["decision_id"],
                    "subject_id": "user_rp",
                    "timestamp": now.isoformat(),
                    "properties": {},
                }
            ]
        )

        future = now + timezone.timedelta(hours=1)
        report = build_experiment_report(
            self.experiment,
            start_date=future,
            end_date=future + timezone.timedelta(hours=1),
        )
        total_exposures = sum(v["exposures"] for v in report["variants"])
        self.assertEqual(total_exposures, 0)