"""Unit tests for response schemas."""

import pytest
from pydantic import ValidationError

from src.enums import EventType
from src.schemas.responses import (
    AdjustmentFilePrepareResponse,
    AdjustmentFilePrepareResponseData,
    AdjustmentFilePrepareResponseDetail,
    AdjustmentFilePrepareResponseMetadata,
)


class TestAdjustmentFilePrepareResponse:
    """Tests for AdjustmentFilePrepareResponse model."""

    def test_valid_response_with_all_fields(self):
        """Test AdjustmentFilePrepareResponse with all fields."""
        response = AdjustmentFilePrepareResponse(
            detail_type=EventType.ADJUSTMENT_BATCH_PREPARED,
            detail=AdjustmentFilePrepareResponseDetail(
                metadata=AdjustmentFilePrepareResponseMetadata(
                    target_type='worksheet_flowthrough_batch',
                    target_id=123,
                    correlation_id='corr-123',
                ),
                data=AdjustmentFilePrepareResponseData(
                    valid_row_count=1000,
                    invalid_row_count=10,
                    total_file_amount_multicurrency=5000.50,
                    total_rounded_amount_multicurrency=5001.00,
                    s3_bucket='test-bucket',
                    s3_key='staging/123/prepared.csv.gz',
                ),
            ),
        )

        assert response.detail_type == EventType.ADJUSTMENT_BATCH_PREPARED
        assert response.detail.metadata.correlation_id == 'corr-123'
        assert response.detail.data.valid_row_count == 1000
        assert response.detail.data.invalid_row_count == 10

    def test_valid_response_without_correlation_id(self):
        """Test AdjustmentFilePrepareResponse without optional correlation_id."""
        response = AdjustmentFilePrepareResponse(
            detail_type=EventType.ADJUSTMENT_BATCH_PREPARED,
            detail=AdjustmentFilePrepareResponseDetail(
                metadata=AdjustmentFilePrepareResponseMetadata(
                    target_type='worksheet_flowthrough_batch',
                    target_id=123,
                ),
                data=AdjustmentFilePrepareResponseData(
                    valid_row_count=500,
                    invalid_row_count=5,
                    total_file_amount_multicurrency=2500.25,
                    total_rounded_amount_multicurrency=2500.00,
                    s3_bucket='test-bucket',
                    s3_key='staging/456/prepared.csv.gz',
                ),
            ),
        )

        assert response.detail_type == EventType.ADJUSTMENT_BATCH_PREPARED
        assert response.detail.metadata.correlation_id is None
        assert response.detail.data.valid_row_count == 500
        assert response.detail.data.invalid_row_count == 5

    def test_missing_required_field_raises_error(self):
        """Test missing required fields raise ValidationError."""
        with pytest.raises(ValidationError) as exc_info:
            AdjustmentFilePrepareResponseData(
                s3_bucket='test-bucket',
                s3_key='staging/123/prepared.csv.gz',
            )
        assert 'valid_row_count' in str(exc_info.value)

        with pytest.raises(ValidationError) as exc_info:
            AdjustmentFilePrepareResponseData(
                valid_row_count=100,
                invalid_row_count=10,
                total_file_amount_multicurrency=1000.0,
                total_rounded_amount_multicurrency=1000.0,
                s3_key='staging/123/prepared.csv.gz',
            )
        assert 's3_bucket' in str(exc_info.value)

        # s3_key is now optional, so this should not raise an error
        data = AdjustmentFilePrepareResponseData(
            valid_row_count=100,
            invalid_row_count=10,
            total_file_amount_multicurrency=1000.0,
            total_rounded_amount_multicurrency=1000.0,
            s3_bucket='test-bucket',
        )
        assert data.s3_key is None

    def test_invalid_field_type_raises_error(self):
        """Test invalid field type raises ValidationError."""
        with pytest.raises(ValidationError) as exc_info:
            AdjustmentFilePrepareResponseData(
                valid_row_count='not-an-int',
                invalid_row_count=10,
                total_file_amount_multicurrency=1000.0,
                total_rounded_amount_multicurrency=1000.0,
                s3_bucket='test-bucket',
                s3_key='staging/123/prepared.csv.gz',
            )
        assert 'valid_row_count' in str(exc_info.value)

    def test_model_dump_with_all_fields(self):
        """Test model_dump() returns correct dict with all fields."""
        response = AdjustmentFilePrepareResponse(
            detail_type=EventType.ADJUSTMENT_BATCH_PREPARED,
            detail=AdjustmentFilePrepareResponseDetail(
                metadata=AdjustmentFilePrepareResponseMetadata(
                    target_type='worksheet_flowthrough_batch',
                    target_id=123,
                    correlation_id='corr-xyz',
                ),
                data=AdjustmentFilePrepareResponseData(
                    valid_row_count=5000,
                    invalid_row_count=50,
                    total_file_amount_multicurrency=10000.75,
                    total_rounded_amount_multicurrency=10001.00,
                    s3_bucket='test-bucket',
                    s3_key='staging/789/prepared.csv.gz',
                ),
            ),
        )
        response_dict = response.model_dump()

        assert response_dict['detail_type'] == 'adjustment_batch.prepared'
        assert response_dict['detail']['data'] == {
            'valid_row_count': 5000,
            'invalid_row_count': 50,
            'total_file_amount_multicurrency': 10000.75,
            'total_rounded_amount_multicurrency': 10001.00,
            's3_bucket': 'test-bucket',
            's3_key': 'staging/789/prepared.csv.gz',
        }
        assert response_dict['detail']['metadata']['correlation_id'] == 'corr-xyz'

    def test_model_dump_without_correlation_id(self):
        """Test model_dump() returns correct dict without correlation_id."""
        response = AdjustmentFilePrepareResponse(
            detail_type=EventType.ADJUSTMENT_BATCH_PREPARED,
            detail=AdjustmentFilePrepareResponseDetail(
                metadata=AdjustmentFilePrepareResponseMetadata(
                    target_type='worksheet_flowthrough_batch',
                    target_id=123,
                ),
                data=AdjustmentFilePrepareResponseData(
                    valid_row_count=250,
                    invalid_row_count=25,
                    total_file_amount_multicurrency=1250.50,
                    total_rounded_amount_multicurrency=1251.00,
                    s3_bucket='test-bucket',
                    s3_key='staging/999/prepared.csv.gz',
                ),
            ),
        )
        response_dict = response.model_dump()

        assert response_dict['detail_type'] == 'adjustment_batch.prepared'
        assert response_dict['detail']['data'] == {
            'valid_row_count': 250,
            'invalid_row_count': 25,
            'total_file_amount_multicurrency': 1250.50,
            'total_rounded_amount_multicurrency': 1251.00,
            's3_bucket': 'test-bucket',
            's3_key': 'staging/999/prepared.csv.gz',
        }
        assert response_dict['detail']['metadata']['correlation_id'] is None