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| from sqlalchemy import Column, String, Float, Integer, DateTime, Text, JSON | |
| from sqlalchemy.dialects.postgresql import UUID | |
| from datetime import datetime, timezone | |
| import uuid | |
| from src.config.db import Base | |
| class ProfilingLog(Base): | |
| __tablename__ = "profiling_logs" | |
| id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4) | |
| created_at = Column(DateTime(timezone=True), default=lambda: datetime.now(timezone.utc), nullable=False) | |
| endpoint = Column(String(255), nullable=False) | |
| method = Column(String(10), nullable=False) | |
| model_name = Column(String(100), nullable=True) | |
| total_time_ms = Column(Float, nullable=False) | |
| num_predictions = Column(Integer, nullable=False, default=0) | |
| time_preprocessing_ms = Column(Float, nullable=True) | |
| time_inference_ms = Column(Float, nullable=True) | |
| time_database_ms = Column(Float, nullable=True) | |
| time_serialization_ms = Column(Float, nullable=True) | |
| top_functions = Column(JSON, nullable=True) | |
| ncalls_total = Column(Integer, nullable=True) | |
| ncalls_pandas = Column(Integer, nullable=True) | |
| ncalls_database = Column(Integer, nullable=True) | |
| cpu_percent = Column(Float, nullable=True) | |
| memory_mb = Column(Float, nullable=True) | |
| full_profile = Column(Text, nullable=True) | |
| def __repr__(self): | |
| return f"<ProfilingLog {self.endpoint} - {self.total_time_ms}ms>" |