Spaces:
Sleeping
Sleeping
File size: 13,495 Bytes
7f335a2 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 |
import asyncio
import os
import time
from datetime import datetime
from typing import Dict, Any, Optional, Callable
from pathlib import Path
import json
import logging
from dataclasses import dataclass, asdict
from threading import Thread, Event
import queue
from src.core.log_parser import VampireBotLogParser, BotAnalysis
from src.analysis.market_analysis import TechnicalAnalysisEngine
@dataclass
class RealTimeConfig:
"""Configuração para integração em tempo real"""
log_file_path: str
check_interval: float = 1.0 # segundos
max_queue_size: int = 100
enable_notifications: bool = True
auto_analysis: bool = True
backup_logs: bool = True
@dataclass
class BotEvent:
"""Evento do bot em tempo real"""
timestamp: datetime
event_type: str # 'new_analysis', 'fibonacci_alert', 'signal_change'
data: Dict[str, Any]
priority: str = 'normal' # 'low', 'normal', 'high', 'critical'
class FileWatcher:
"""Monitor de arquivos para detectar mudanças em tempo real"""
def __init__(self, file_path: str, callback: Callable[[str], None]):
self.file_path = Path(file_path)
self.callback = callback
self.last_modified = 0
self.last_size = 0
self.running = False
self._stop_event = Event()
def start(self):
"""Inicia o monitoramento do arquivo"""
self.running = True
self._stop_event.clear()
if self.file_path.exists():
stat = self.file_path.stat()
self.last_modified = stat.st_mtime
self.last_size = stat.st_size
def stop(self):
"""Para o monitoramento"""
self.running = False
self._stop_event.set()
def check_changes(self) -> bool:
"""Verifica se o arquivo foi modificado"""
if not self.file_path.exists():
return False
try:
stat = self.file_path.stat()
current_modified = stat.st_mtime
current_size = stat.st_size
# Verifica se houve mudança
if (current_modified > self.last_modified or
current_size != self.last_size):
self.last_modified = current_modified
self.last_size = current_size
# Lê o conteúdo novo
try:
with open(self.file_path, 'r', encoding='utf-8') as f:
content = f.read()
self.callback(content)
return True
except Exception as e:
logging.error(f"Erro ao ler arquivo: {e}")
except Exception as e:
logging.error(f"Erro ao verificar arquivo: {e}")
return False
class RealTimeProcessor:
"""Processador de dados em tempo real do bot"""
def __init__(self, config: RealTimeConfig):
self.config = config
self.log_parser = VampireBotLogParser()
self.technical_engine = TechnicalAnalysisEngine()
self.event_queue = queue.Queue(maxsize=config.max_queue_size)
self.subscribers = []
self.running = False
self.last_analysis: Optional[BotAnalysis] = None
# Setup logging
self.logger = logging.getLogger(__name__)
def subscribe(self, callback: Callable[[BotEvent], None]):
"""Inscreve um callback para receber eventos"""
self.subscribers.append(callback)
def unsubscribe(self, callback: Callable[[BotEvent], None]):
"""Remove um callback da lista de inscritos"""
if callback in self.subscribers:
self.subscribers.remove(callback)
def _notify_subscribers(self, event: BotEvent):
"""Notifica todos os inscritos sobre um evento"""
for callback in self.subscribers:
try:
callback(event)
except Exception as e:
self.logger.error(f"Erro ao notificar subscriber: {e}")
def _process_new_log_data(self, log_content: str):
"""Processa novos dados de log"""
try:
# Parse do log
bot_analysis = self.log_parser.parse_log(log_content)
if bot_analysis:
# Verifica se é uma nova análise
is_new_analysis = (
self.last_analysis is None or
bot_analysis.timestamp != self.last_analysis.timestamp
)
if is_new_analysis:
# Cria evento de nova análise
event = BotEvent(
timestamp=datetime.now(),
event_type='new_analysis',
data=asdict(bot_analysis),
priority='normal'
)
# Adiciona à fila de eventos
try:
self.event_queue.put_nowait(event)
except queue.Full:
self.logger.warning("Fila de eventos cheia, removendo evento mais antigo")
try:
self.event_queue.get_nowait()
self.event_queue.put_nowait(event)
except queue.Empty:
pass
# Verifica alertas de Fibonacci
if bot_analysis.fibonacci_analysis and bot_analysis.fibonacci_analysis.alerts:
fib_event = BotEvent(
timestamp=datetime.now(),
event_type='fibonacci_alert',
data={
'alerts': bot_analysis.fibonacci_analysis.alerts,
'signal': bot_analysis.fibonacci_analysis.signal,
'confidence': bot_analysis.fibonacci_analysis.confidence
},
priority='high'
)
try:
self.event_queue.put_nowait(fib_event)
except queue.Full:
pass
# Verifica mudança de sinal
if (self.last_analysis and
bot_analysis.fibonacci_analysis and
self.last_analysis.fibonacci_analysis and
bot_analysis.fibonacci_analysis.signal != self.last_analysis.fibonacci_analysis.signal):
signal_event = BotEvent(
timestamp=datetime.now(),
event_type='signal_change',
data={
'old_signal': self.last_analysis.fibonacci_analysis.signal,
'new_signal': bot_analysis.fibonacci_analysis.signal,
'confidence': bot_analysis.fibonacci_analysis.confidence
},
priority='critical'
)
try:
self.event_queue.put_nowait(signal_event)
except queue.Full:
pass
self.last_analysis = bot_analysis
except Exception as e:
self.logger.error(f"Erro ao processar log: {e}")
def _event_processor_loop(self):
"""Loop principal de processamento de eventos"""
while self.running:
try:
# Processa eventos da fila
try:
event = self.event_queue.get(timeout=0.1)
self._notify_subscribers(event)
self.event_queue.task_done()
except queue.Empty:
continue
except Exception as e:
self.logger.error(f"Erro no loop de eventos: {e}")
time.sleep(0.1)
def start(self):
"""Inicia o processamento em tempo real"""
if self.running:
return
self.running = True
self.logger.info("Iniciando processamento em tempo real")
# Inicia thread de processamento de eventos
self.event_thread = Thread(target=self._event_processor_loop, daemon=True)
self.event_thread.start()
# Configura watcher de arquivo
self.file_watcher = FileWatcher(
self.config.log_file_path,
self._process_new_log_data
)
self.file_watcher.start()
# Inicia thread de monitoramento
self.monitor_thread = Thread(target=self._monitor_loop, daemon=True)
self.monitor_thread.start()
def stop(self):
"""Para o processamento em tempo real"""
if not self.running:
return
self.logger.info("Parando processamento em tempo real")
self.running = False
if hasattr(self, 'file_watcher'):
self.file_watcher.stop()
def _monitor_loop(self):
"""Loop de monitoramento de arquivo"""
while self.running:
try:
self.file_watcher.check_changes()
time.sleep(self.config.check_interval)
except Exception as e:
self.logger.error(f"Erro no monitoramento: {e}")
time.sleep(1)
def get_status(self) -> Dict[str, Any]:
"""Retorna status do processador"""
return {
'running': self.running,
'queue_size': self.event_queue.qsize(),
'subscribers_count': len(self.subscribers),
'last_analysis_time': self.last_analysis.timestamp if self.last_analysis else None,
'config': asdict(self.config)
}
class RealTimeIntegration:
"""Sistema principal de integração em tempo real"""
def __init__(self, log_file_path: str):
self.config = RealTimeConfig(log_file_path=log_file_path)
self.processor = RealTimeProcessor(self.config)
self.event_history = []
self.max_history = 1000
# Setup logging
self.logger = logging.getLogger(__name__)
# Inscreve callback padrão
self.processor.subscribe(self._default_event_handler)
def _default_event_handler(self, event: BotEvent):
"""Handler padrão para eventos"""
# Adiciona ao histórico
self.event_history.append(event)
# Mantém tamanho do histórico
if len(self.event_history) > self.max_history:
self.event_history = self.event_history[-self.max_history:]
# Log do evento
self.logger.info(f"Evento {event.event_type} - Prioridade: {event.priority}")
# Processamento específico por tipo
if event.event_type == 'signal_change':
self.logger.warning(
f"MUDANÇA DE SINAL: {event.data['old_signal']} -> {event.data['new_signal']} "
f"(Confiança: {event.data['confidence']}%)"
)
elif event.event_type == 'fibonacci_alert':
self.logger.info(f"Alerta Fibonacci: {len(event.data['alerts'])} alertas")
def start(self):
"""Inicia a integração em tempo real"""
self.processor.start()
self.logger.info(f"Integração em tempo real iniciada para: {self.config.log_file_path}")
def stop(self):
"""Para a integração em tempo real"""
self.processor.stop()
self.logger.info("Integração em tempo real parada")
def get_recent_events(self, limit: int = 10) -> list[BotEvent]:
"""Retorna eventos recentes"""
return self.event_history[-limit:] if self.event_history else []
def get_status(self) -> Dict[str, Any]:
"""Retorna status completo do sistema"""
processor_status = self.processor.get_status()
return {
**processor_status,
'event_history_size': len(self.event_history),
'recent_events': len([e for e in self.event_history if
(datetime.now() - e.timestamp).seconds < 300]) # últimos 5 min
}
# Exemplo de uso
if __name__ == "__main__":
# Configurar logging
logging.basicConfig(level=logging.INFO)
# Criar integração
integration = RealTimeIntegration("d:/hugging_face_spaces/text")
# Callback personalizado
def custom_handler(event: BotEvent):
print(f"[{event.timestamp}] {event.event_type}: {event.priority}")
integration.processor.subscribe(custom_handler)
try:
# Iniciar
integration.start()
# Manter rodando
while True:
time.sleep(1)
status = integration.get_status()
if status['recent_events'] > 0:
print(f"Eventos recentes: {status['recent_events']}")
except KeyboardInterrupt:
print("Parando integração...")
integration.stop() |