import pytest
from pydantic import ValidationError as PydanticValidationError

from src.models.metric_labels import (
    MAX_LABEL_RESULTS,
    ListMetricLabelsRequest,
    ListMetricLabelValuesRequest,
)


class TestListLabelsRequest:
    def test_valid_request_defaults_limit(self):
        req = ListMetricLabelsRequest.model_validate(
            {
                "cluster_id": "123",
                "env": "prod",
                "deploy_type": "premium",
            }
        )
        assert req.limit == MAX_LABEL_RESULTS
        assert req.match is None

    def test_normalizes_scope(self):
        req = ListMetricLabelsRequest.model_validate(
            {
                "cluster_id": " 123 ",
                "env": " Prod ",
                "deploy_type": " Premium ",
            }
        )
        assert req.cluster_id == "123"
        assert req.env == "prod"
        assert req.deploy_type == "premium"

    def test_limit_bounds(self):
        with pytest.raises(PydanticValidationError):
            ListMetricLabelsRequest.model_validate(
                {
                    "cluster_id": "123",
                    "env": "prod",
                    "deploy_type": "premium",
                    "limit": 0,
                }
            )
        with pytest.raises(PydanticValidationError):
            ListMetricLabelsRequest.model_validate(
                {
                    "cluster_id": "123",
                    "env": "prod",
                    "deploy_type": "premium",
                    "limit": 101,
                }
            )

    def test_rejects_non_string_cluster_id(self):
        with pytest.raises(PydanticValidationError):
            ListMetricLabelsRequest.model_validate(
                {
                    "cluster_id": 123,
                    "env": "prod",
                    "deploy_type": "premium",
                }
            )

    def test_accepts_start_end(self):
        req = ListMetricLabelsRequest.model_validate(
            {
                "cluster_id": "123",
                "env": "prod",
                "deploy_type": "premium",
                "start": "2024-01-01T00:00:00Z",
                "end": "2024-01-01T01:00:00Z",
            }
        )
        assert req.start == "2024-01-01T00:00:00Z"
        assert req.end == "2024-01-01T01:00:00Z"


class TestLabelValuesRequest:
    def test_valid_request(self):
        req = ListMetricLabelValuesRequest.model_validate(
            {
                "cluster_id": "123",
                "env": "prod",
                "deploy_type": "premium",
                "label": "instance",
            }
        )
        assert req.label == "instance"
        assert req.limit == MAX_LABEL_RESULTS

    def test_rejects_empty_label(self):
        with pytest.raises(PydanticValidationError):
            ListMetricLabelValuesRequest.model_validate(
                {
                    "cluster_id": "123",
                    "env": "prod",
                    "deploy_type": "premium",
                    "label": "   ",
                }
            )

    def test_rejects_invalid_label_name(self):
        with pytest.raises(PydanticValidationError):
            ListMetricLabelValuesRequest.model_validate(
                {
                    "cluster_id": "123",
                    "env": "prod",
                    "deploy_type": "premium",
                    "label": "bad-label",
                }
            )

    def test_accepts_start_end(self):
        req = ListMetricLabelValuesRequest.model_validate(
            {
                "cluster_id": "123",
                "env": "prod",
                "deploy_type": "premium",
                "label": "instance",
                "start": "2024-01-01T00:00:00Z",
                "end": "2024-01-01T01:00:00Z",
            }
        )
        assert req.start == "2024-01-01T00:00:00Z"
        assert req.end == "2024-01-01T01:00:00Z"