import re
import unicodedata

class ChuukeseTextProcessor:
    def __init__(self):
        self.accent_patterns = {
            'acute': ['á', 'é', 'í', 'ó', 'ú'],
            'macron': ['ā', 'ē', 'ī', 'ō', 'ū'],
            'base': ['a', 'e', 'i', 'o', 'u']
        }
        
        self.normalize_map = {
            'á': 'á', 'à': 'á', 'â': 'á',  # Standardize to acute
            'ā': 'ā', 'ă': 'ā',           # Standardize to macron
            'é': 'é', 'è': 'é', 'ê': 'é',
            'ē': 'ē', 'ĕ': 'ē',
            'í': 'í', 'ì': 'í', 'î': 'í',
            'ī': 'ī', 'ĭ': 'ī',
            'ó': 'ó', 'ò': 'ó', 'ô': 'ó',
            'ō': 'ō', 'ŏ': 'ō',
            'ú': 'ú', 'ù': 'ú', 'û': 'ú',
            'ū': 'ū', 'ŭ': 'ū'
        }
    
    def normalize_chuukese_text(self, text):
        """Normalize Chuukese text with proper accent handling"""
        # First apply Unicode normalization
        normalized = unicodedata.normalize('NFC', text)
        
        # Then apply Chuukese-specific normalization
        for variant, standard in self.normalize_map.items():
            normalized = normalized.replace(variant, standard)
        
        return normalized

class ChuukeseCulturalProcessor:
    def __init__(self):
        self.cultural_concepts = {
            'family_terms': ['semei', 'jinej', 'seme', 'jina', 'pwis', 'pwisen'],
            'traditional_items': ['emon', 'uruf', 'nous', 'ruk', 'chomw'],
            'respect_terms': ['oupwe', 'kose mochen', 'tipeew', 'sokkun'],
            'time_concepts': ['ranem', 'ekis', 'ngang', 'pwong'],
            'spatial_terms': ['met', 'ese', 'won', 'ifa']
        }
    
    def detect_cultural_context(self, text):
        """Detect cultural context indicators in Chuukese text"""
        context = {
            'cultural_density': 0,
            'respect_level': 'casual',
            'traditional_concepts': [],
            'formality_indicators': []
        }
        
        for category, terms in self.cultural_concepts.items():
            found_terms = [term for term in terms if term in text.lower()]
            if found_terms:
                context['traditional_concepts'].extend(found_terms)
                context['cultural_density'] += len(found_terms)
        
        return context

# Initialize processor
processor = ChuukeseTextProcessor()

# Process Chuukese text
text = "Kopwe pwan chomong ngonuk ekkewe chon Chuuk"
normalized = processor.normalize_chuukese_text(text)
words = processor.extract_chuukese_words(text)

print(f"Normalized: {normalized}")
print(f"Words: {words}")

# Analyze cultural context
cultural_processor = ChuukeseCulturalProcessor()
context = cultural_processor.detect_cultural_context(text)

print(f"Cultural density: {context['cultural_density']}")
print(f"Traditional concepts: {context['traditional_concepts']}")