class IR3Pidgins:
    """
    Universal language app on iR³ foundation
    ~300 lines of code
    Language as node graphs + pure flux
    """
    
    def __init__(self, foundation):
        # Connect to iR³ foundation
        self.series = foundation.series
        self.dht = foundation.dht
        self.bt = foundation.bt
        
        # Register async handlers
        self._setup_handlers()
    
    def _setup_handlers(self):
        """Set up event streams"""
        # Handle language query responses
        self.dht.on_p2p_response(self._on_language_response)
        
        # Handle language data chunks
        self.bt.on_chunk_received(self._on_language_chunk)

def add_phoneme(self, sound, language):
    """Add phoneme node (pure flux)"""
    # Append to series (immediate)
    self.series.append({
        'event': 'phoneme_added',
        'type': 'phoneme',
        'sound': sound,
        'language': language,
        't': time.time(),
        'heard_count': 0,
        'produced_count': 0,
        'links': []
    })
    
    # Return immediately (no blocking)
    return

def add_word(self, text, meaning, language, phonemes):
    """Add word node (pure flux)"""
    # Append to series (immediate)
    self.series.append({
        'event': 'word_added',
        'type': 'word',
        'text': text,
        'meaning': meaning,
        'language': language,
        't': time.time(),
        'phonemes': phonemes,  # Links to phoneme nodes
        'encounters': 0,
        'known': False,
        'links': []
    })
    
    # Return immediately (no blocking)
    return

def add_grammar_pattern(self, pattern, language, examples):
    """Add grammar node (pure flux)"""
    # Append to series (immediate)
    self.series.append({
        'event': 'grammar_added',
        'type': 'grammar',
        'pattern': pattern,
        'language': language,
        't': time.time(),
        'examples': examples,
        'confidence': 0.0,
        'links': []
    })
    
    # Return immediately (no blocking)
    return

def query_translation(self, word, from_lang, to_lang):
    """Query translation (pure flux)"""
    # Push intent to DHT (fire & forget)
    self.dht.push_intent({
        'intent': 'translate_word',
        'word': word,
        'from_language': from_lang,
        'to_language': to_lang,
        'requester': self.address
    })
    
    # Append query to series
    self.series.append({
        'event': 'translation_query',
        'word': word,
        'from': from_lang,
        'to': to_lang,
        't': time.time()
    })
    
    # Return immediately (NO WAITING)
    return

def query_universal_concept(self, concept):
    """Query universal concept across languages"""
    # Broadcast to network
    self.dht.push_intent({
        'intent': 'find_universal',
        'concept': concept,
        'requester': self.address
    })
    
    # Append to series
    self.series.append({
        'event': 'universal_query',
        'concept': concept,
        't': time.time()
    })
    
    # Return immediately
    return

def _on_language_response(self, data):
    """Async handler for language responses"""
    response_type = data.get('type')
    
    if response_type == 'translation':
        # Append translation to series
        self.series.append({
            'event': 'translation_received',
            'word': data['word'],
            'from_lang': data['from_language'],
            'to_lang': data['to_language'],
            'translation': data['translation'],
            't': time.time(),
            'from_node': data['from_node']
        })
    
    elif response_type == 'universal_concept':
        # Append universal concept
        self.series.append({
            'event': 'universal_concept_received',
            'concept': data['concept'],
            'words': data['words'],  # Words in each language
            't': time.time()
        })
    
    elif response_type == 'pidgin_word':
        # Append pidgin word
        self.series.append({
            'event': 'pidgin_word_received',
            'pidgin': data['pidgin_word'],
            'meaning': data['meaning'],
            'source_languages': data['sources'],
            't': time.time()
        })
    
    # All handled async (no blocking anywhere)

def derive_language_graph(self, language=None):
    """Derive language graph from series"""
    # Get all events
    events = self.series.get_all()
    
    # Build graph by reducing events
    graph = {
        'phonemes': [],
        'words': [],
        'grammar': [],
        'universal_concepts': [],
        'pidgin': []
    }
    
    for event in events:
        event_type = event.get('event')
        
        if event_type == 'phoneme_added':
            if language is None or event['language'] == language:
                graph['phonemes'].append({
                    'sound': event['sound'],
                    'language': event['language'],
                    'heard': event['heard_count'],
                    'produced': event['produced_count']
                })
        
        elif event_type == 'word_added':
            if language is None or event['language'] == language:
                graph['words'].append({
                    'text': event['text'],
                    'meaning': event['meaning'],
                    'language': event['language'],
                    'phonemes': event['phonemes'],
                    'known': event['known']
                })
        
        elif event_type == 'grammar_added':
            if language is None or event['language'] == language:
                graph['grammar'].append({
                    'pattern': event['pattern'],
                    'language': event['language'],
                    'examples': event['examples']
                })
        
        elif event_type == 'universal_concept_received':
            graph['universal_concepts'].append({
                'concept': event['concept'],
                'words': event['words']
            })
        
        elif event_type == 'pidgin_word_received':
            graph['pidgin'].append({
                'text': event['pidgin'],
                'meaning': event['meaning'],
                'sources': event['source_languages']
            })
    
    return graph

def speak_pidgin(self, intent, context=None):
    """Speak using pidgin (pure flux)"""
    # Derive current pidgin state
    graph = self.derive_language_graph()
    pidgin_words = graph['pidgin']
    
    # Find pidgin words for intent
    words = self._find_pidgin_words(intent, pidgin_words)
    
    # Broadcast via DHT
    self.dht.push_intent({
        'intent': 'pidgin_communication',
        'words': words,
        'meaning': intent,
        'requester': self.address
    })
    
    # Append to series
    self.series.append({
        'event': 'pidgin_spoken',
        'words': words,
        'intent': intent,
        't': time.time()
    })
    
    # Return immediately
    return

def understand_pidgin(self, pidgin_words):
    """Understand pidgin from any speaker"""
    # Derive pidgin graph
    graph = self.derive_language_graph()
    
    # Match pidgin words to meanings
    meanings = []
    for word in pidgin_words:
        pidgin_nodes = [
            p for p in graph['pidgin']
            if p['text'] == word
        ]
        if pidgin_nodes:
            meanings.append(pidgin_nodes[0]['meaning'])
    
    # Append understanding to series
    self.series.append({
        'event': 'pidgin_understood',
        'words': pidgin_words,
        'meanings': meanings,
        't': time.time()
    })
    
    return meanings

def share_language_data(self, language):
    """Share language graph as chunks"""
    # Derive language graph
    graph = self.derive_language_graph(language)
    
    # Convert to chunks
    chunks = self._graph_to_chunks(graph, language)
    
    # Store chunks in BitTorrent
    for chunk_id, chunk_data in chunks.items():
        self.bt.store_chunk(chunk_id, chunk_data)
        
        # Announce via DHT
        self.dht.push_intent({
            'intent': 'announce_language_chunk',
            'chunk_id': chunk_id,
            'language': language,
            'holder': self.address
        })
    
    # Append to series
    self.series.append({
        'event': 'language_shared',
        'language': language,
        'chunks': len(chunks),
        't': time.time()
    })
    
    # Return immediately
    return

def request_language_data(self, language):
    """Request language data from network"""
    # Push want language chunks
    self.dht.push_intent({
        'intent': 'want_language_data',
        'language': language,
        'requester': self.address
    })
    
    # Append to series
    self.series.append({
        'event': 'language_data_requested',
        'language': language,
        't': time.time()
    })
    
    # Return immediately
    # Data will flow in via P2P
    return

def _on_language_chunk(self, chunk):
    """Async handler for language chunks"""
    # Append chunk to series
    self.series.append({
        'event': 'language_chunk_received',
        'chunk_id': chunk['id'],
        'data': chunk['data'],
        't': time.time()
    })
    
    # No blocking

def discover_universal_concepts(self):
    """Find concepts present in ALL languages (pure flux)"""
    # Derive complete graph (all languages)
    graph = self.derive_language_graph()
    
    # Get all unique meanings across all languages
    all_meanings = set()
    for word in graph['words']:
        all_meanings.add(word['meaning'])
    
    # For each meaning, check if it exists in ALL languages
    for meaning in all_meanings:
        # Broadcast query to see how many languages have this
        self.dht.push_intent({
            'intent': 'check_universal',
            'meaning': meaning,
            'requester': self.address
        })
    
    # Append discovery attempt
    self.series.append({
        'event': 'universal_discovery_started',
        'meanings_checked': len(all_meanings),
        't': time.time()
    })
    
    # Return immediately
    # Responses will flow in async
    # Concepts present in ALL languages = universal!
    return

def create_pidgin_word(self, concept, translations):
    """Create pidgin word from translations"""
    # Choose simplest form
    pidgin_word = min(translations.values(), key=len)
    
    # Append to series (immediate)
    self.series.append({
        'event': 'pidgin_word_created',
        'pidgin': pidgin_word,
        'concept': concept,
        'translations': translations,
        't': time.time()
    })
    
    # Broadcast to network
    self.dht.push_intent({
        'intent': 'announce_pidgin',
        'pidgin_word': pidgin_word,
        'concept': concept,
        'sources': list(translations.keys())
    })
    
    # Return immediately
    return

# Initialize app on iR³ foundation
foundation = iR3Alpha()
pidgins = IR3Pidgins(foundation)

# Learn French phonemes (immediate)
pidgins.add_phoneme('ʁ', 'french')
pidgins.add_phoneme('ʃ', 'french')
pidgins.add_phoneme('a', 'french')

# Learn French word (immediate)
pidgins.add_word('chat', 'cat', 'french', ['ʃ', 'a'])

# Learn Spanish word (immediate)
pidgins.add_word('gato', 'cat', 'spanish', ['g', 'a', 't', 'o'])

# Query translation (fire & forget)
pidgins.query_translation('chat', 'french', 'spanish')
# → Returns immediately

# Later... derive state
graph = pidgins.derive_language_graph()
print(f"French words: {len(graph['words'])}")

# Query universal concepts (fire & forget)
pidgins.discover_universal_concepts()
# → Returns immediately

# Responses flow in asynchronously via handlers
# No waiting! Just check state when needed

# Later in your event loop or UI update:
graph = pidgins.derive_language_graph()
print(f"Universal concepts: {len(graph['universal_concepts'])}")
print(f"Pidgin words: {len(graph['pidgin'])}")

# Speak using pidgin (fire & forget)
pidgins.speak_pidgin('want_food')
# → Returns immediately

# No blocking anywhere!

# Node B has French/Spanish, responds to queries

@pidgins.dht.on_intent
def handle_language_intent(intent):
    """Handle incoming language queries"""
    intent_type = intent.get('intent')
    
    if intent_type == 'translate_word':
        # Check if we know this translation
        graph = pidgins.derive_language_graph()
        
        # Find word in source language
        source_word = next(
            (w for w in graph['words'] 
             if w['text'] == intent['word'] 
             and w['language'] == intent['from_language']),
            None
        )
        
        if source_word:
            # Find translation in target language
            target_word = next(
                (w for w in graph['words']
                 if w['meaning'] == source_word['meaning']
                 and w['language'] == intent['to_language']),
                None
            )
            
            if target_word:
                # Send P2P response
                pidgins.dht.respond_p2p(
                    to=intent['requester'],
                    data={
                        'type': 'translation',
                        'word': intent['word'],
                        'from_language': intent['from_language'],
                        'to_language': intent['to_language'],
                        'translation': target_word['text'],
                        'from_node': pidgins.address
                    }
                )
    
    elif intent_type == 'check_universal':
        # Check if concept exists in our languages
        graph = pidgins.derive_language_graph()
        concept = intent['concept']
        
        # Find words with this meaning
        translations = {}
        for word in graph['words']:
            if word['meaning'] == concept:
                translations[word['language']] = word['text']
        
        if translations:
            # Send P2P response
            pidgins.dht.respond_p2p(
                to=intent['requester'],
                data={
                    'type': 'universal_concept',
                    'concept': concept,
                    'words': translations
                }
            )

# Traditional (blocking):
translations = []
for word in word_list:
    translation = api.translate(word)  # BLOCKS
    translations.append(translation)
# Time: N * latency = SLOW

# iR³Pidgins (pure flux):
for word in word_list:
    pidgins.query_translation(word, 'en', 'fr')  # Immediate
# All queries "in flight" simultaneously

# Responses flow into series via async handlers
# Check state anytime from event loop or UI:
def on_ui_update():
    graph = pidgins.derive_language_graph()
    display_translations(graph['words'])
    # No blocking, just derive state when needed

# Time: ~latency (parallel) = FAST

def sync_language_data(self):
    """Sync language data with network"""
    # Get local language graph
    local_graph = self.derive_language_graph()
    
    # For each language known locally
    for language in self._get_known_languages():
        # Request updates from network
        self.request_language_data(language)
        
        # Share our data
        self.share_language_data(language)
    
    # All async (no blocking)
    return

def _get_known_languages(self):
    """Get list of languages in local graph"""
    graph = self.derive_language_graph()
    languages = set()
    
    for word in graph['words']:
        languages.add(word['language'])
    
    return list(languages)

# 1. Real-time translation
pidgins.query_translation('hello', 'english', 'mandarin')

# 2. Language learning
pidgins.add_word('bonjour', 'hello', 'french', ['b', 'o', 'ʒ', 'u', 'ʁ'])
pidgins.add_grammar_pattern('greeting', 'french', ['bonjour', 'salut'])

# 3. Cross-cultural communication
pidgins.speak_pidgin('want_buy_food')  # Universal pidgin
pidgins.understand_pidgin(['mi', 'want', 'eat'])

# 4. Language preservation
pidgins.share_language_data('endangered_language')

# 5. Travel assistance
pidgins.discover_universal_concepts()
graph = pidgins.derive_language_graph()
essential_words = graph['pidgin']  # Use anywhere

# All pure flux, no blocking