STABLE: Final schema sync, optimized gitignore
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Kincses
@@ -1,163 +1,104 @@
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# /opt/docker/dev/service_finder/backend/app/models/service.py
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import uuid
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from sqlalchemy import Column, Integer, String, Boolean, DateTime, ForeignKey, JSON, text, Text, Float, Index, Numeric
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from sqlalchemy.orm import relationship, backref
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from datetime import datetime
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from typing import Any, List, Optional
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from sqlalchemy import Integer, String, Boolean, DateTime, ForeignKey, text, Text, Float, Index, Numeric
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from sqlalchemy.orm import Mapped, mapped_column, relationship
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from sqlalchemy.dialects.postgresql import UUID as PG_UUID, JSONB
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from geoalchemy2 import Geometry # PostGIS támogatás
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from geoalchemy2 import Geometry
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from sqlalchemy.sql import func
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from app.db.base_class import Base
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# MB 2.0: Központi aszinkron adatbázis motorból húzzuk be a Base-t
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from app.database import Base
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class ServiceProfile(Base):
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"""
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Szerviz szolgáltató kiterjesztett adatai (v1.3.1).
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Egy Organization-höz (org_type='service') kapcsolódik.
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Támogatja a hierarchiát (Franchise/Telephely) és az automatizált dúsítást.
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"""
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""" Szerviz szolgáltató adatai (v1.3.1). """
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__tablename__ = "service_profiles"
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__table_args__ = (
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# Egyedi ujjlenyomat index a robot számára a duplikációk elkerülésére
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Index('idx_service_fingerprint', 'fingerprint', unique=True),
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{"schema": "data"}
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)
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id = Column(Integer, primary_key=True, index=True)
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id: Mapped[int] = mapped_column(Integer, primary_key=True, index=True)
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organization_id: Mapped[Optional[int]] = mapped_column(Integer, ForeignKey("data.organizations.id"), unique=True)
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parent_id: Mapped[Optional[int]] = mapped_column(Integer, ForeignKey("data.service_profiles.id"))
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# --- KAPCSOLAT A CÉGES IKERHEZ (Twin) ---
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organization_id = Column(Integer, ForeignKey("data.organizations.id"), unique=True)
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fingerprint: Mapped[str] = mapped_column(String(255), index=True, nullable=False)
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location: Mapped[Any] = mapped_column(Geometry(geometry_type='POINT', srid=4326, spatial_index=False), index=True)
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# --- HIERARCHIA (Fa struktúra) ---
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# Ez tárolja a szülő egység ID-ját (pl. hálózat központja)
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parent_id = Column(Integer, ForeignKey("data.service_profiles.id"), nullable=True)
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status: Mapped[str] = mapped_column(String(20), server_default=text("'ghost'"), index=True)
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last_audit_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
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google_place_id: Mapped[Optional[str]] = mapped_column(String(100), unique=True)
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rating: Mapped[Optional[float]] = mapped_column(Float)
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user_ratings_total: Mapped[Optional[int]] = mapped_column(Integer)
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# --- ROBOT IDENTITÁS ---
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# Normalize(Név + Város + Utca) hash, hogy ne legyen duplikáció
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fingerprint = Column(String(255), nullable=False, index=True)
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vibe_analysis: Mapped[Any] = mapped_column(JSONB, server_default=text("'{}'::jsonb"))
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social_links: Mapped[Any] = mapped_column(JSONB, server_default=text("'{}'::jsonb"))
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specialization_tags: Mapped[Any] = mapped_column(JSONB, server_default=text("'{}'::jsonb"))
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# PostGIS GPS pont (SRID 4326 = WGS84 koordináták)
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location = Column(Geometry(geometry_type='POINT', srid=4326), index=True)
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trust_score: Mapped[int] = mapped_column(Integer, default=30)
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is_verified: Mapped[bool] = mapped_column(Boolean, default=False)
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verification_log: Mapped[Any] = mapped_column(JSONB, server_default=text("'{}'::jsonb"))
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# Állapotkezelés: ghost (robot találta), active, flagged, inactive
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status = Column(String(20), server_default=text("'ghost'"), index=True)
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last_audit_at = Column(DateTime(timezone=True), server_default=func.now(), onupdate=func.now())
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opening_hours: Mapped[Any] = mapped_column(JSONB, server_default=text("'{}'::jsonb"))
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contact_phone: Mapped[Optional[str]] = mapped_column(String)
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contact_email: Mapped[Optional[str]] = mapped_column(String)
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website: Mapped[Optional[str]] = mapped_column(String)
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bio: Mapped[Optional[str]] = mapped_column(Text)
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# --- GOOGLE ÉS KÜLSŐ ADATOK ---
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google_place_id = Column(String(100), unique=True)
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rating = Column(Float)
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user_ratings_total = Column(Integer)
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# Kapcsolatok
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organization: Mapped["Organization"] = relationship("Organization", back_populates="service_profile")
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expertises: Mapped[List["ServiceExpertise"]] = relationship("ServiceExpertise", back_populates="service")
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# --- MÉLYFÚRÁS (Deep Enrichment) ADATOK ---
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# AI elemzés: {"tone": "barátságos", "pricing": "közép", "reliability": "magas"}
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vibe_analysis = Column(JSONB, server_default=text("'{}'::jsonb"))
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# Közösségi háló: {"facebook": "url", "tiktok": "url", "insta": "url"}
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social_links = Column(JSONB, server_default=text("'{}'::jsonb"))
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# Speciális szűrő címkék: {"brands": ["Yamaha", "Suzuki"], "specialty": ["engine", "tuning"]}
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specialization_tags = Column(JSONB, server_default=text("'{}'::jsonb"))
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# Trust Engine (Bot Discovery=30, User Entry=50, Admin/Partner=100)
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trust_score = Column(Integer, default=30)
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is_verified = Column(Boolean, default=False)
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verification_log = Column(JSONB, server_default=text("'{}'::jsonb"))
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# --- ELÉRHETŐSÉG ---
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opening_hours = Column(JSONB, server_default=text("'{}'::jsonb"))
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contact_phone = Column(String)
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contact_email = Column(String)
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website = Column(String)
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bio = Column(Text)
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# --- KAPCSOLATOK ---
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organization = relationship("Organization", back_populates="service_profile")
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expertises = relationship("ServiceExpertise", back_populates="service")
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# --- ÖNMAGÁRA HIVATKOZÓ KAPCSOLAT (Hierarchia) ---
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sub_services = relationship(
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"ServiceProfile",
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backref=backref("parent_service", remote_side=[id]),
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cascade="all, delete-orphan"
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)
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created_at = Column(DateTime(timezone=True), server_default=func.now())
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updated_at = Column(DateTime(timezone=True), onupdate=func.now())
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created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
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updated_at: Mapped[Optional[datetime]] = mapped_column(DateTime(timezone=True), onupdate=func.now())
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class ExpertiseTag(Base):
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"""Szakmai szempontok taxonómiája."""
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__tablename__ = "expertise_tags"
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__table_args__ = {"schema": "data"}
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id = Column(Integer, primary_key=True)
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key = Column(String(50), unique=True, index=True) # pl. 'bmw_gs_specialist'
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name_hu = Column(String(100))
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category = Column(String(30)) # 'repair', 'fuel', 'food', 'emergency'
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id: Mapped[int] = mapped_column(Integer, primary_key=True)
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key: Mapped[str] = mapped_column(String(50), unique=True, index=True)
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name_hu: Mapped[Optional[str]] = mapped_column(String(100))
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category: Mapped[Optional[str]] = mapped_column(String(30))
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class ServiceExpertise(Base):
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"""Kapcsolótábla a szerviz és a szakterület között."""
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__tablename__ = "service_expertises"
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__table_args__ = {"schema": "data"}
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service_id: Mapped[int] = mapped_column(Integer, ForeignKey("data.service_profiles.id"), primary_key=True)
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expertise_id: Mapped[int] = mapped_column(Integer, ForeignKey("data.expertise_tags.id"), primary_key=True)
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validation_level: Mapped[int] = mapped_column(Integer, default=0)
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service_id = Column(Integer, ForeignKey("data.service_profiles.id"), primary_key=True)
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expertise_id = Column(Integer, ForeignKey("data.expertise_tags.id"), primary_key=True)
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# Validációs szint (0-100% - Mennyire hiteles ez a szakértelem)
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validation_level = Column(Integer, default=0)
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service = relationship("ServiceProfile", back_populates="expertises")
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expertise = relationship("ExpertiseTag")
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service: Mapped["ServiceProfile"] = relationship("ServiceProfile", back_populates="expertises")
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expertise: Mapped["ExpertiseTag"] = relationship("ExpertiseTag")
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class ServiceStaging(Base):
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"""
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Átmeneti tábla a Hunter (n8n/scraping) adatoknak.
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"""
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""" Hunter (robot) adatok tárolója. """
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__tablename__ = "service_staging"
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__table_args__ = (
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Index('idx_staging_fingerprint', 'fingerprint', unique=True),
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{"schema": "data"}
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)
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id = Column(Integer, primary_key=True, index=True)
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# --- Alapadatok ---
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name = Column(String, nullable=False, index=True)
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# --- Strukturált cím adatok ---
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postal_code = Column(String(10), index=True)
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city = Column(String(100), index=True)
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street_name = Column(String(150))
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street_type = Column(String(50))
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house_number = Column(String(20))
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stairwell = Column(String(20))
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floor = Column(String(20))
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door = Column(String(20))
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hrsz = Column(String(50))
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full_address = Column(String)
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contact_phone = Column(String, nullable=True)
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email = Column(String, nullable=True)
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website = Column(String, nullable=True)
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# --- Forrás és Azonosítás ---
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source = Column(String(50), nullable=True, index=True)
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external_id = Column(String(100), nullable=True, index=True)
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# Robot ujjlenyomat a Staging szintű deduplikációhoz
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fingerprint = Column(String(255), nullable=False)
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# --- Adatmentés ---
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raw_data = Column(JSONB, server_default=text("'{}'::jsonb"))
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# --- Státusz és Bizalom ---
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status = Column(String(20), server_default=text("'pending'"), index=True)
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trust_score = Column(Integer, default=0)
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created_at = Column(DateTime(timezone=True), server_default=func.now())
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id: Mapped[int] = mapped_column(Integer, primary_key=True, index=True)
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name: Mapped[str] = mapped_column(String, index=True, nullable=False)
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postal_code: Mapped[Optional[str]] = mapped_column(String(10), index=True)
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city: Mapped[Optional[str]] = mapped_column(String(100), index=True)
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full_address: Mapped[Optional[str]] = mapped_column(String)
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fingerprint: Mapped[str] = mapped_column(String(255), nullable=False)
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raw_data: Mapped[Any] = mapped_column(JSONB, server_default=text("'{}'::jsonb"))
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status: Mapped[str] = mapped_column(String(20), server_default=text("'pending'"), index=True)
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created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
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class DiscoveryParameter(Base):
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"""Robot vezérlési paraméterek."""
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""" Robot vezérlési paraméterek adminból. """
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__tablename__ = "discovery_parameters"
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__table_args__ = {"schema": "data"}
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id = Column(Integer, primary_key=True)
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city = Column(String(100), nullable=False)
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keyword = Column(String(100), nullable=False)
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country_code = Column(String(2), default="HU")
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is_active = Column(Boolean, default=True)
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last_run_at = Column(DateTime(timezone=True))
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id: Mapped[int] = mapped_column(Integer, primary_key=True)
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city: Mapped[str] = mapped_column(String(100))
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keyword: Mapped[str] = mapped_column(String(100))
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is_active: Mapped[bool] = mapped_column(Boolean, default=True)
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last_run_at: Mapped[Optional[datetime]] = mapped_column(DateTime(timezone=True))
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