# tests/unit/utils/test_csv_processor.py
"""Unit tests for CSV processor with translation support."""

from unittest.mock import Mock, patch

import pandas as pd
import pytest
import requests
import requests.exceptions

from app.utils.csv_processor import CSVProcessor
from models.database.marketplace_product import MarketplaceProduct


@pytest.mark.unit
class TestCSVProcessor:
    def setup_method(self):
        self.processor = CSVProcessor()

    @patch("requests.get")
    def test_download_csv_encoding_fallback(self, mock_get):
        """Test CSV download with encoding fallback"""
        # Create content with special characters that would fail UTF-8 if not properly encoded
        special_content = (
            "marketplace_product_id,title,price\nTEST001,Café MarketplaceProduct,10.99"
        )

        mock_response = Mock()
        mock_response.status_code = 200
        # Use latin-1 encoding which your method should try
        mock_response.content = special_content.encode("latin-1")
        mock_response.raise_for_status.return_value = None
        mock_get.return_value = mock_response

        csv_content = self.processor.download_csv("http://example.com/test.csv")

        mock_get.assert_called_once_with("http://example.com/test.csv", timeout=30)
        assert isinstance(csv_content, str)
        assert "Café MarketplaceProduct" in csv_content

    @patch("requests.get")
    def test_download_csv_encoding_ignore_fallback(self, mock_get):
        """Test CSV download falls back to UTF-8 with error ignoring"""
        # Create problematic bytes that would fail most encoding attempts
        mock_response = Mock()
        mock_response.status_code = 200
        # Create bytes that will fail most encodings
        mock_response.content = b"marketplace_product_id,title,price\nTEST001,\xff\xfe MarketplaceProduct,10.99"
        mock_response.raise_for_status.return_value = None
        mock_get.return_value = mock_response

        csv_content = self.processor.download_csv("http://example.com/test.csv")

        mock_get.assert_called_once_with("http://example.com/test.csv", timeout=30)
        assert isinstance(csv_content, str)
        # Should still contain basic content even with ignored errors
        assert "marketplace_product_id,title,price" in csv_content
        assert "TEST001" in csv_content

    @patch("requests.get")
    def test_download_csv_request_exception(self, mock_get):
        """Test CSV download with request exception"""
        mock_get.side_effect = requests.exceptions.RequestException("Connection error")

        with pytest.raises(requests.exceptions.RequestException):
            self.processor.download_csv("http://example.com/test.csv")

    @patch("requests.get")
    def test_download_csv_http_error(self, mock_get):
        """Test CSV download with HTTP error"""
        mock_response = Mock()
        mock_response.status_code = 404
        mock_response.raise_for_status.side_effect = requests.exceptions.HTTPError(
            "404 Not Found"
        )
        mock_get.return_value = mock_response

        with pytest.raises(requests.exceptions.HTTPError):
            self.processor.download_csv("http://example.com/nonexistent.csv")

    @patch("requests.get")
    def test_download_csv_failure(self, mock_get):
        """Test CSV download failure"""
        # Mock failed HTTP response - need to make raise_for_status() raise an exception
        mock_response = Mock()
        mock_response.status_code = 404
        mock_response.raise_for_status.side_effect = requests.exceptions.HTTPError(
            "404 Not Found"
        )
        mock_get.return_value = mock_response

        with pytest.raises(requests.exceptions.HTTPError):
            self.processor.download_csv("http://example.com/nonexistent.csv")

    def test_parse_csv_content(self):
        """Test CSV content parsing"""
        csv_content = """marketplace_product_id,title,price,marketplace
TEST001,Test MarketplaceProduct 1,10.99,TestMarket
TEST002,Test MarketplaceProduct 2,15.99,TestMarket"""

        df = self.processor.parse_csv(csv_content)

        assert len(df) == 2
        assert "marketplace_product_id" in df.columns
        assert df.iloc[0]["marketplace_product_id"] == "TEST001"
        assert df.iloc[1]["price"] == 15.99

    def test_normalize_columns_google_shopping(self):
        """Test column normalization for Google Shopping feed format"""
        csv_content = """g:id,g:title,g:description,g:price,g:brand,g:product_type
TEST001,Product 1,Description 1,19.99 EUR,Brand1,Category1"""

        df = self.processor.parse_csv(csv_content)
        df = self.processor.normalize_columns(df)

        assert "marketplace_product_id" in df.columns
        assert "title" in df.columns
        assert "description" in df.columns
        assert "product_type_raw" in df.columns  # Renamed from product_type
        assert df.iloc[0]["marketplace_product_id"] == "TEST001"
        assert df.iloc[0]["title"] == "Product 1"

    def test_extract_translation_data(self):
        """Test extraction of translation fields from product data"""
        product_data = {
            "marketplace_product_id": "TEST001",
            "title": "Test Product",
            "description": "Test Description",
            "short_description": "Short desc",
            "price": "19.99",
            "brand": "TestBrand",
        }

        translation_data = self.processor._extract_translation_data(product_data)

        # Translation fields should be extracted
        assert translation_data["title"] == "Test Product"
        assert translation_data["description"] == "Test Description"
        assert translation_data["short_description"] == "Short desc"

        # Product data should no longer have translation fields
        assert "title" not in product_data
        assert "description" not in product_data
        assert "short_description" not in product_data

        # Non-translation fields should remain
        assert product_data["marketplace_product_id"] == "TEST001"
        assert product_data["price"] == "19.99"
        assert product_data["brand"] == "TestBrand"

    def test_parse_price_to_cents(self):
        """Test price string to cents conversion"""
        assert self.processor._parse_price_to_cents("19.99 EUR") == 1999
        assert self.processor._parse_price_to_cents("19,99 EUR") == 1999
        assert self.processor._parse_price_to_cents("$29.99") == 2999
        assert self.processor._parse_price_to_cents("100") == 10000
        assert self.processor._parse_price_to_cents(None) is None
        assert self.processor._parse_price_to_cents("") is None

    def test_clean_row_data_with_prices(self):
        """Test row data cleaning with price parsing to cents"""
        row_data = {
            "marketplace_product_id": "TEST001",
            "title": "Test Product",
            "price": "19.99 EUR",
            "sale_price": "14.99 EUR",
            "gtin": "1234567890123",
        }

        cleaned = self.processor._clean_row_data(row_data)

        assert cleaned["price_cents"] == 1999  # Integer cents
        assert cleaned["sale_price_cents"] == 1499  # Integer cents
        assert cleaned["currency"] == "EUR"

    @pytest.mark.asyncio
    async def test_process_marketplace_csv_from_url(self, db):
        """Test complete marketplace CSV processing"""
        with (
            patch.object(self.processor, "download_csv") as mock_download,
            patch.object(self.processor, "parse_csv") as mock_parse,
        ):
            # Mock successful download and parsing
            mock_download.return_value = "csv_content"
            mock_df = pd.DataFrame(
                {
                    "marketplace_product_id": ["TEST001", "TEST002"],
                    "title": ["MarketplaceProduct 1", "MarketplaceProduct 2"],
                    "price": ["10.99", "15.99"],
                    "marketplace": ["TestMarket", "TestMarket"],
                    "vendor_name": ["TestVendor", "TestVendor"],
                }
            )
            mock_parse.return_value = mock_df

            result = await self.processor.process_marketplace_csv_from_url(
                "http://example.com/test.csv",
                "TestMarket",
                "TestVendor",
                1000,
                db,
                language="en",
            )

            assert "imported" in result
            assert "updated" in result
            assert "total_processed" in result

            assert "language" in result
            assert result["language"] == "en"

    @pytest.mark.asyncio
    async def test_process_batch_creates_translations(self, db):
        """Test that batch processing creates translation records"""
        # Clean up any existing test data
        existing = (
            db.query(MarketplaceProduct)
            .filter(
                MarketplaceProduct.marketplace_product_id.in_(
                    ["TRANS_TEST_001", "TRANS_TEST_002"]
                )
            )
            .all()
        )
        for p in existing:
            db.delete(p)
        db.commit()

        # Create test DataFrame
        batch_df = pd.DataFrame(
            {
                "marketplace_product_id": ["TRANS_TEST_001", "TRANS_TEST_002"],
                "title": ["Product One", "Product Two"],
                "description": ["Description One", "Description Two"],
                "price": ["19.99 EUR", "29.99 EUR"],
                "brand": ["Brand1", "Brand2"],
            }
        )

        result = await self.processor._process_marketplace_batch(
            batch_df,
            "TestMarket",
            "TestVendor",
            db,
            batch_num=1,
            language="en",
            source_file="test.csv",
        )

        assert result["imported"] == 2
        assert result["errors"] == 0

        # Verify products were created
        products = (
            db.query(MarketplaceProduct)
            .filter(
                MarketplaceProduct.marketplace_product_id.in_(
                    ["TRANS_TEST_001", "TRANS_TEST_002"]
                )
            )
            .all()
        )
        assert len(products) == 2

        # Verify translations were created
        for product in products:
            assert len(product.translations) == 1
            translation = product.translations[0]
            assert translation.language == "en"
            assert translation.title is not None
            assert translation.source_file == "test.csv"

        # Verify get_title method works
        product1 = next(
            p for p in products if p.marketplace_product_id == "TRANS_TEST_001"
        )
        assert product1.get_title("en") == "Product One"
        assert product1.get_description("en") == "Description One"

        # Clean up
        for p in products:
            db.delete(p)
        db.commit()

    @pytest.mark.asyncio
    async def test_process_batch_updates_existing_translations(self, db):
        """Test that batch processing updates existing translation records"""
        # Clean up any existing test data
        existing = (
            db.query(MarketplaceProduct)
            .filter(MarketplaceProduct.marketplace_product_id == "UPDATE_TEST_001")
            .first()
        )
        if existing:
            db.delete(existing)
            db.commit()

        # Create initial product with translation
        batch_df = pd.DataFrame(
            {
                "marketplace_product_id": ["UPDATE_TEST_001"],
                "title": ["Original Title"],
                "description": ["Original Description"],
                "price": ["19.99 EUR"],
            }
        )

        await self.processor._process_marketplace_batch(
            batch_df, "TestMarket", "TestVendor", db, 1, language="en"
        )

        # Update with new data
        update_df = pd.DataFrame(
            {
                "marketplace_product_id": ["UPDATE_TEST_001"],
                "title": ["Updated Title"],
                "description": ["Updated Description"],
                "price": ["24.99 EUR"],
            }
        )

        result = await self.processor._process_marketplace_batch(
            update_df, "TestMarket", "TestVendor", db, 1, language="en"
        )

        assert result["updated"] == 1
        assert result["imported"] == 0

        # Verify translation was updated
        product = (
            db.query(MarketplaceProduct)
            .filter(MarketplaceProduct.marketplace_product_id == "UPDATE_TEST_001")
            .first()
        )
        assert product.get_title("en") == "Updated Title"
        assert product.get_description("en") == "Updated Description"

        # Clean up
        db.delete(product)
        db.commit()

    @pytest.mark.asyncio
    async def test_process_batch_multi_language(self, db):
        """Test importing same product in multiple languages"""
        # Clean up
        existing = (
            db.query(MarketplaceProduct)
            .filter(MarketplaceProduct.marketplace_product_id == "MULTI_LANG_001")
            .first()
        )
        if existing:
            db.delete(existing)
            db.commit()

        # Import English version
        en_df = pd.DataFrame(
            {
                "marketplace_product_id": ["MULTI_LANG_001"],
                "title": ["English Title"],
                "description": ["English Description"],
                "price": ["19.99 EUR"],
                "brand": ["TestBrand"],
            }
        )

        await self.processor._process_marketplace_batch(
            en_df, "TestMarket", "TestVendor", db, 1, language="en"
        )

        # Import French version (same product, different language)
        fr_df = pd.DataFrame(
            {
                "marketplace_product_id": ["MULTI_LANG_001"],
                "title": ["Titre Français"],
                "description": ["Description Française"],
                "price": ["19.99 EUR"],
                "brand": ["TestBrand"],
            }
        )

        result = await self.processor._process_marketplace_batch(
            fr_df, "TestMarket", "TestVendor", db, 1, language="fr"
        )

        assert result["updated"] == 1  # Product existed, so it's an update

        # Verify both translations exist
        product = (
            db.query(MarketplaceProduct)
            .filter(MarketplaceProduct.marketplace_product_id == "MULTI_LANG_001")
            .first()
        )
        assert len(product.translations) == 2

        # Verify each language
        assert product.get_title("en") == "English Title"
        assert product.get_title("fr") == "Titre Français"
        assert product.get_description("en") == "English Description"
        assert product.get_description("fr") == "Description Française"

        # Test fallback to English for unknown language
        assert product.get_title("de") == "English Title"

        # Clean up
        db.delete(product)
        db.commit()

    @pytest.mark.asyncio
    async def test_process_batch_skips_missing_title(self, db):
        """Test that rows without title are skipped"""
        batch_df = pd.DataFrame(
            {
                "marketplace_product_id": ["NO_TITLE_001", "HAS_TITLE_001"],
                "title": [None, "Has Title"],
                "price": ["19.99", "29.99"],
            }
        )

        result = await self.processor._process_marketplace_batch(
            batch_df, "TestMarket", "TestVendor", db, 1, language="en"
        )

        assert result["imported"] == 1
        assert result["errors"] == 1  # Missing title is an error

        # Clean up
        product = (
            db.query(MarketplaceProduct)
            .filter(MarketplaceProduct.marketplace_product_id == "HAS_TITLE_001")
            .first()
        )
        if product:
            db.delete(product)
            db.commit()

    @pytest.mark.asyncio
    async def test_process_batch_skips_missing_product_id(self, db):
        """Test that rows without marketplace_product_id are skipped"""
        batch_df = pd.DataFrame(
            {
                "marketplace_product_id": [None, "HAS_ID_001"],
                "title": ["No ID Product", "Has ID Product"],
                "price": ["19.99", "29.99"],
            }
        )

        result = await self.processor._process_marketplace_batch(
            batch_df, "TestMarket", "TestVendor", db, 1, language="en"
        )

        assert result["imported"] == 1
        assert result["errors"] == 1  # Missing ID is an error

        # Clean up
        product = (
            db.query(MarketplaceProduct)
            .filter(MarketplaceProduct.marketplace_product_id == "HAS_ID_001")
            .first()
        )
        if product:
            db.delete(product)
            db.commit()