# utils/data_processing.py
"""Data processing utilities for GTIN validation and price parsing.

This module provides classes and functions for:
- GTIN (Global Trade Item Number) validation and normalization
- Price parsing with currency detection
- Data cleaning and validation utilities
"""

import logging
import re
from typing import Optional, Tuple

import pandas as pd

logger = logging.getLogger(__name__)


class GTINProcessor:
    """Handles GTIN normalization and validation."""

    VALID_LENGTHS = [8, 12, 13, 14]

    def normalize(self, gtin_value: any) -> Optional[str]:
        """
        Normalize GTIN to proper format.

        Returns None for invalid GTINs.
        """
        if not gtin_value or pd.isna(gtin_value):
            return None

        gtin_str = str(gtin_value).strip()
        if not gtin_str:
            return None

        # Remove decimal point (e.g., "889698116923.0" -> "889698116923")
        if "." in gtin_str:
            gtin_str = gtin_str.split(".")[0]

        # Keep only digits
        gtin_clean = "".join(filter(str.isdigit, gtin_str))

        if not gtin_clean:
            return None

        # Validate and normalize length
        length = len(gtin_clean)

        if length in self.VALID_LENGTHS:
            # Standard lengths - pad appropriately
            if length == 8:
                return gtin_clean.zfill(8)  # EAN-8
            elif length == 12:
                return gtin_clean.zfill(12)  # UPC-A
            elif length == 13:
                return gtin_clean.zfill(13)  # EAN-13
            elif length == 14:
                return gtin_clean.zfill(14)  # GTIN-14

        elif length > 14:
            # Too long - truncate to EAN-13
            logger.warning(f"GTIN too long, truncating: {gtin_clean}")
            return gtin_clean[-13:]

        elif 0 < length < 8:
            # Too short - pad to EAN-13
            logger.warning(f"GTIN too short, padding: {gtin_clean}")
            return gtin_clean.zfill(13)

        logger.warning(f"Invalid GTIN format: '{gtin_value}'")
        return None

    def validate(self, gtin: str) -> bool:
        """Validate GTIN format."""
        if not gtin:
            return False
        return len(gtin) in self.VALID_LENGTHS and gtin.isdigit()


class PriceProcessor:
    """Handles price parsing and currency extraction."""

    CURRENCY_PATTERNS = {
        # Amount followed by currency
        r"([0-9.,]+)\s*(EUR|€)": lambda m: (m.group(1), "EUR"),
        r"([0-9.,]+)\s*(USD|\$)": lambda m: (m.group(1), "USD"),
        r"([0-9.,]+)\s*(GBP|£)": lambda m: (m.group(1), "GBP"),
        r"([0-9.,]+)\s*(CHF)": lambda m: (m.group(1), "CHF"),
        r"([0-9.,]+)\s*(CAD|AUD|JPY|¥)": lambda m: (m.group(1), m.group(2).upper()),
        # Currency followed by amount
        r"(EUR|€)\s*([0-9.,]+)": lambda m: (m.group(2), "EUR"),
        r"(USD|\$)\s*([0-9.,]+)": lambda m: (m.group(2), "USD"),
        r"(GBP|£)\s*([0-9.,]+)": lambda m: (m.group(2), "GBP"),
        # Generic 3-letter currency codes
        r"([0-9.,]+)\s*([A-Z]{3})": lambda m: (m.group(1), m.group(2)),
        r"([A-Z]{3})\s*([0-9.,]+)": lambda m: (m.group(2), m.group(1)),
    }

    def parse_price_currency(
        self, price_str: any
    ) -> Tuple[Optional[str], Optional[str]]:
        """
        Parse price string into (price, currency) tuple.

        Returns (None, None) if parsing fails
        """
        if not price_str or pd.isna(price_str):
            return None, None

        price_str = str(price_str).strip()
        if not price_str:
            return None, None

        # Try each pattern
        for pattern, extract_func in self.CURRENCY_PATTERNS.items():
            match = re.search(pattern, price_str, re.IGNORECASE)
            if match:
                try:
                    price_val, currency_val = extract_func(match)
                    # Normalize price (remove spaces, handle comma as decimal)
                    price_val = price_val.replace(" ", "").replace(",", ".")
                    # Validate numeric
                    float(price_val)
                    return price_val, currency_val.upper()
                except (ValueError, AttributeError):
                    continue

        # Fallback: extract just numbers
        number_match = re.search(r"([0-9.,]+)", price_str)
        if number_match:
            try:
                price_val = number_match.group(1).replace(",", ".")
                float(price_val)  # Validate
                return price_val, None
            except ValueError:
                pass

        logger.warning(f"Could not parse price: '{price_str}'")
        return price_str, None