"""
WordPress CSV Parser Module

This module provides utilities for parsing WordPress user export CSV files
and transforming them into LOAF platform-compatible data structures.

Key Features:
- Parse PHP serialized data (WordPress capabilities)
- Map WordPress roles to LOAF roles and statuses
- Validate and standardize user data (DOB, phone numbers)
- Generate smart status suggestions based on approval and subscription data
- Comprehensive data quality analysis and error reporting

Author: Claude Code
Date: 2025-12-24
"""

import csv
import re
import logging
from datetime import datetime
from typing import Dict, List, Optional, Tuple
import phpserialize

logger = logging.getLogger(__name__)


# ============================================================================
# WordPress Role Mapping Configuration
# ============================================================================

ROLE_MAPPING = {
    # WordPress admin roles → LOAF admin roles (auto-active)
    'administrator': ('superadmin', 'active'),
    'loaf_admin': ('admin', 'active'),
    'loaf_treasure': ('finance', 'active'),
    'loaf_communication': ('admin', 'active'),

    # WordPress member roles → LOAF member role (status from approval)
    'pms_subscription_plan_63': ('member', None),  # Status determined by approval
    'registered': ('guest', None),  # Default WordPress role

    # Fallback for unknown roles
    '__default__': ('guest', None)
}

# Role priority order (higher index = higher priority)
ROLE_PRIORITY = [
    'registered',
    'pms_subscription_plan_63',
    'loaf_communication',
    'loaf_treasure',
    'loaf_admin',
    'administrator'
]


# ============================================================================
# PHP Serialization Parsing
# ============================================================================

def parse_php_serialized(data: str) -> List[str]:
    """
    Parse WordPress PHP serialized capabilities string.

    WordPress stores user capabilities as serialized PHP arrays like:
    a:1:{s:10:"registered";b:1;}
    a:2:{s:10:"registered";b:1;s:24:"pms_subscription_plan_63";b:1;}

    Args:
        data: PHP serialized string

    Returns:
        List of role names (e.g., ['registered', 'pms_subscription_plan_63'])

    Examples:
        >>> parse_php_serialized('a:1:{s:10:"registered";b:1;}')
        ['registered']
        >>> parse_php_serialized('a:2:{s:10:"registered";b:1;s:24:"pms_subscription_plan_63";b:1;}')
        ['registered', 'pms_subscription_plan_63']
    """
    if not data or pd.isna(data):
        return []

    try:
        # Use phpserialize library to parse
        parsed = phpserialize.loads(data.encode('utf-8'))

        # Extract role names (keys where value is True)
        if isinstance(parsed, dict):
            roles = [key.decode('utf-8') if isinstance(key, bytes) else key
                    for key, value in parsed.items() if value]
            return roles

        return []
    except Exception as e:
        logger.warning(f"Failed to parse PHP serialized data: {data[:50]}... Error: {str(e)}")
        return []


# ============================================================================
# Role and Status Mapping
# ============================================================================

def map_wordpress_role(wp_roles: List[str]) -> Tuple[str, Optional[str]]:
    """
    Map WordPress roles to LOAF role and suggested status.

    Priority logic:
    1. If user has any admin role → corresponding LOAF admin role with 'active' status
    2. If user has subscription → 'member' role (status from approval)
    3. Otherwise → 'guest' role (status from approval)

    Args:
        wp_roles: List of WordPress role names

    Returns:
        Tuple of (loaf_role, suggested_status)
        - loaf_role: One of: superadmin, admin, finance, member, guest
        - suggested_status: One of: active, pre_validated, payment_pending, None (determined by approval)

    Examples:
        >>> map_wordpress_role(['loaf_admin'])
        ('admin', 'active')
        >>> map_wordpress_role(['loaf_treasure'])
        ('finance', 'active')
        >>> map_wordpress_role(['pms_subscription_plan_63', 'registered'])
        ('member', None)
        >>> map_wordpress_role(['registered'])
        ('guest', None)
    """
    if not wp_roles:
        return ROLE_MAPPING['__default__']

    # Sort roles by priority (highest priority last)
    prioritized_roles = sorted(
        wp_roles,
        key=lambda r: ROLE_PRIORITY.index(r) if r in ROLE_PRIORITY else -1
    )

    # Map highest priority role
    highest_role = prioritized_roles[-1] if prioritized_roles else 'registered'
    return ROLE_MAPPING.get(highest_role, ROLE_MAPPING['__default__'])


def suggest_status(approval_status: str, has_subscription: bool, wordpress_role: str = 'guest') -> str:
    """
    Suggest LOAF user status based on WordPress approval and subscription data.

    Logic:
    1. Admin roles (loaf_admin, loaf_treasure, administrator) → always 'active'
    2. approved + subscription → 'active'
    3. approved without subscription → 'pre_validated'
    4. pending → 'payment_pending'
    5. Other/empty → 'pre_validated'

    Args:
        approval_status: WordPress approval status (approved, pending, unapproved, etc.)
        has_subscription: Whether user has pms_subscription_plan_63 role
        wordpress_role: LOAF role mapped from WordPress (for admin check)

    Returns:
        Suggested LOAF status: active, pre_validated, payment_pending, or inactive

    Examples:
        >>> suggest_status('approved', True, 'member')
        'active'
        >>> suggest_status('approved', False, 'member')
        'pre_validated'
        >>> suggest_status('pending', True, 'member')
        'payment_pending'
        >>> suggest_status('', False, 'admin')
        'active'
    """
    # Admin roles are always active
    if wordpress_role in ('superadmin', 'admin', 'finance'):
        return 'active'

    # Normalize approval status
    approval = (approval_status or '').lower().strip()

    if approval == 'approved':
        return 'active' if has_subscription else 'pre_validated'
    elif approval == 'pending':
        return 'payment_pending'
    elif approval == 'unapproved':
        return 'inactive'
    else:
        # Empty or unknown approval status
        return 'pre_validated'


# ============================================================================
# Data Validation and Standardization
# ============================================================================

def standardize_phone(phone: str) -> str:
    """
    Standardize phone number by extracting digits only.

    Removes all non-digit characters:
    - (713) 560-7850 → 7135607850
    - 713-725-8902 → 7137258902
    - Empty/None → 0000000000 (fallback)

    Args:
        phone: Phone number in any format

    Returns:
        10-digit phone number string (or 0000000000 if invalid)

    Examples:
        >>> standardize_phone('(713) 560-7850')
        '7135607850'
        >>> standardize_phone('713-725-8902')
        '7137258902'
        >>> standardize_phone('')
        '0000000000'
    """
    if not phone or pd.isna(phone):
        return '0000000000'

    # Extract all digits
    digits = re.sub(r'\D', '', str(phone))

    # Return 10 digits or fallback
    if len(digits) == 10:
        return digits
    elif len(digits) == 11 and digits[0] == '1':
        # Remove leading 1 (US country code)
        return digits[1:]
    else:
        logger.warning(f"Invalid phone format: {phone} (extracted: {digits})")
        return '0000000000'


def validate_dob(dob_str: str) -> Tuple[Optional[datetime], Optional[str]]:
    """
    Validate and parse date of birth.

    Validation rules:
    - Must be in MM/DD/YYYY format
    - Year must be between 1900 and current year
    - Cannot be in the future
    - Reject year 0000 or 2025+ (data quality issues in WordPress export)

    Args:
        dob_str: Date of birth string in MM/DD/YYYY format

    Returns:
        Tuple of (parsed_datetime, warning_message)
        - parsed_datetime: datetime object if valid, None if invalid
        - warning_message: Descriptive error message if invalid, None if valid

    Examples:
        >>> validate_dob('08/02/1962')
        (datetime(1962, 8, 2), None)
        >>> validate_dob('08/02/0000')
        (None, 'Invalid year: 0000')
        >>> validate_dob('08/02/2025')
        (None, 'Date is in the future')
    """
    if not dob_str or pd.isna(dob_str):
        return None, 'Missing date of birth'

    try:
        # Parse MM/DD/YYYY format
        parsed = datetime.strptime(str(dob_str).strip(), '%m/%d/%Y')

        # Validate year range
        if parsed.year == 0:
            return None, 'Invalid year: 0000 (data quality issue)'
        elif parsed.year < 1900:
            return None, f'Year too old: {parsed.year} (likely invalid)'
        elif parsed.year > datetime.now().year:
            return None, f'Date is in the future: {parsed.year}'
        elif parsed > datetime.now():
            return None, 'Date is in the future'

        return parsed, None

    except ValueError as e:
        return None, f'Invalid date format: {dob_str} (expected MM/DD/YYYY)'


# ============================================================================
# CSV Analysis and Preview Generation
# ============================================================================

def analyze_csv(file_path: str, existing_emails: Optional[set] = None) -> Dict:
    """
    Analyze WordPress CSV file and generate preview data with status suggestions.

    This is the main entry point for CSV processing. It:
    1. Reads and parses the CSV file
    2. Validates each row and generates warnings
    3. Maps WordPress roles to LOAF roles
    4. Suggests status for each user
    5. Tracks data quality metrics
    6. Checks for duplicate emails (both within CSV and against existing database)
    7. Returns comprehensive analysis and preview data

    Args:
        file_path: Path to WordPress CSV export file
        existing_emails: Set of emails already in the database (optional)

    Returns:
        Dictionary containing:
        - total_rows: Total number of user rows
        - valid_rows: Number of rows without critical errors
        - warnings: Total warning count
        - errors: Total critical error count
        - preview_data: List of row dictionaries with suggestions
        - data_quality: Dictionary of data quality metrics

    Example output:
        {
            'total_rows': 183,
            'valid_rows': 176,
            'warnings': 66,
            'errors': 7,
            'preview_data': [
                {
                    'row_number': 1,
                    'email': 'user@example.com',
                    'first_name': 'John',
                    'last_name': 'Doe',
                    'phone': '7135607850',
                    'date_of_birth': '1962-08-02',
                    'wordpress_roles': ['registered', 'pms_subscription_plan_63'],
                    'suggested_role': 'member',
                    'suggested_status': 'active',
                    'warnings': [],
                    'errors': []
                },
                ...
            ],
            'data_quality': {
                'invalid_dob': 66,
                'missing_phone': 7,
                'duplicate_email_csv': 0,
                'duplicate_email_db': 3,
                'unparseable_roles': 2
            }
        }
    """
    import pandas as pd

    # Read CSV with pandas
    df = pd.read_csv(file_path)

    total_rows = len(df)
    preview_data = []
    data_quality = {
        'invalid_dob': 0,
        'missing_phone': 0,
        'duplicate_email_csv': 0,
        'duplicate_email_db': 0,
        'unparseable_roles': 0,
        'missing_email': 0
    }

    # Track seen emails for CSV duplicate detection
    seen_emails = {}

    # Convert existing_emails to set if provided
    if existing_emails is None:
        existing_emails = set()

    for idx, row in df.iterrows():
        row_num = idx + 1
        warnings = []
        errors = []

        # Extract and validate email
        email = str(row.get('user_email', '')).strip().lower()
        if not email or email == 'nan':
            errors.append('Missing email address')
            data_quality['missing_email'] += 1
        else:
            # Check for duplicates within CSV
            if email in seen_emails:
                errors.append(f'Duplicate email in CSV (also in row {seen_emails[email]})')
                data_quality['duplicate_email_csv'] += 1
            # Check for duplicates in existing database
            elif email in existing_emails:
                errors.append(f'Email already exists in database')
                data_quality['duplicate_email_db'] += 1
            else:
                seen_emails[email] = row_num

        # Extract basic fields
        first_name = str(row.get('first_name', '')).strip()
        last_name = str(row.get('last_name', '')).strip()

        # Parse and validate DOB
        dob_parsed, dob_warning = validate_dob(row.get('date_of_birth'))
        if dob_warning:
            warnings.append(dob_warning)
            data_quality['invalid_dob'] += 1

        # Standardize phone
        phone = standardize_phone(row.get('cell_phone'))
        if phone == '0000000000':
            warnings.append('Missing or invalid phone number')
            data_quality['missing_phone'] += 1

        # Parse WordPress roles
        wp_capabilities = row.get('wp_capabilities', '')
        wp_roles = parse_php_serialized(wp_capabilities)
        if not wp_roles and wp_capabilities:
            warnings.append('Could not parse WordPress roles')
            data_quality['unparseable_roles'] += 1

        # Map to LOAF role and status
        loaf_role, role_suggested_status = map_wordpress_role(wp_roles)

        # Determine if user has subscription
        has_subscription = 'pms_subscription_plan_63' in wp_roles

        # Get approval status
        approval_status = str(row.get('wppb_approval_status', '')).strip()

        # Suggest final status
        if role_suggested_status:
            # Admin roles have fixed status from role mapping
            suggested_status = role_suggested_status
        else:
            # Regular users get status from approval logic
            suggested_status = suggest_status(approval_status, has_subscription, loaf_role)

        # Build preview row
        preview_row = {
            'row_number': row_num,
            'email': email,
            'first_name': first_name,
            'last_name': last_name,
            'phone': phone,
            'date_of_birth': dob_parsed.isoformat() if dob_parsed else None,
            'wordpress_user_id': int(row.get('ID', 0)) if pd.notna(row.get('ID')) else None,
            'wordpress_registered': str(row.get('user_registered', '')),
            'wordpress_roles': wp_roles,
            'wordpress_approval_status': approval_status,
            'has_subscription': has_subscription,
            'suggested_role': loaf_role,
            'suggested_status': suggested_status,
            'warnings': warnings,
            'errors': errors,
            'newsletter_consent': str(row.get('newsletter_consent', '')).lower() == 'yes',
            'newsletter_checklist': str(row.get('newsletter_checklist', '')).lower() == 'yes'
        }

        preview_data.append(preview_row)

    # Calculate summary statistics
    valid_rows = sum(1 for row in preview_data if not row['errors'])
    total_warnings = sum(len(row['warnings']) for row in preview_data)
    total_errors = sum(len(row['errors']) for row in preview_data)

    return {
        'total_rows': total_rows,
        'valid_rows': valid_rows,
        'warnings': total_warnings,
        'errors': total_errors,
        'preview_data': preview_data,
        'data_quality': data_quality
    }


# ============================================================================
# Utility Functions
# ============================================================================

def get_status_badge_color(status: str) -> str:
    """
    Get appropriate badge color for status display in UI.

    Args:
        status: User status string

    Returns:
        Tailwind CSS color class
    """
    colors = {
        'active': 'bg-green-100 text-green-800',
        'pre_validated': 'bg-blue-100 text-blue-800',
        'payment_pending': 'bg-yellow-100 text-yellow-800',
        'inactive': 'bg-gray-100 text-gray-800',
        'pending_email': 'bg-purple-100 text-purple-800',
        'awaiting_event': 'bg-indigo-100 text-indigo-800'
    }
    return colors.get(status, 'bg-gray-100 text-gray-800')


def format_preview_for_display(preview_data: List[Dict], page: int = 1, page_size: int = 50) -> Dict:
    """
    Format preview data for paginated display in frontend.

    Args:
        preview_data: Full preview data list
        page: Page number (1-indexed)
        page_size: Number of rows per page

    Returns:
        Dictionary with paginated data and metadata
    """
    total_pages = (len(preview_data) + page_size - 1) // page_size
    start_idx = (page - 1) * page_size
    end_idx = start_idx + page_size

    return {
        'page': page,
        'page_size': page_size,
        'total_pages': total_pages,
        'total_rows': len(preview_data),
        'rows': preview_data[start_idx:end_idx]
    }


# ============================================================================
# Module Initialization
# ============================================================================

# Import pandas for CSV processing
try:
    import pandas as pd
except ImportError:
    logger.error("pandas library not found. Please install: pip install pandas")
    raise

logger.info("WordPress parser module loaded successfully")