Task 5.23: Deduplication / Merge — ContactMergeHistory model, dedup service, API routes (duplicates/merge/merge-history), DedupDialog frontend, i18n, 5 tests
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"""Deduplication / merge service for contacts."""
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from __future__ import annotations
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import uuid
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from typing import Any
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from sqlalchemy import select, func, text
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.models.contact import Contact
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from app.models.contact_merge import ContactMergeHistory
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# Fields used for duplicate detection
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DUPLICATE_FIELDS = [
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"displayname", "name", "firstname", "surname",
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"email_1", "email_2", "phone_1", "phone_2",
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]
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def _normalize(value: str | None) -> str:
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"""Normalize a string for comparison: lowercase, strip, collapse spaces."""
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if not value:
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return ""
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return " ".join(value.lower().split())
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def _normalize_email(value: str | None) -> str:
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"""Normalize email: lowercase, strip."""
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if not value:
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return ""
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return value.lower().strip()
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def _normalize_phone(value: str | None) -> str:
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"""Normalize phone: keep only digits."""
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if not value:
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return ""
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return "".join(c for c in value if c.isdigit())
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def _name_similarity(a: str | None, b: str | None) -> float:
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"""Compute similarity between two name strings (0.0 - 1.0).
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Uses a simple token-based Jaccard similarity.
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"""
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na = set(_normalize(a).split())
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nb = set(_normalize(b).split())
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if not na or not nb:
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return 0.0
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intersection = na & nb
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union = na | nb
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return len(intersection) / len(union) if union else 0.0
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async def find_duplicates(
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db: AsyncSession,
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tenant_id: uuid.UUID,
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threshold: float = 0.7,
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limit: int = 50,
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) -> list[dict[str, Any]]:
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"""Find potential duplicate contacts within a tenant.
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Returns a list of duplicate pairs with similarity scores and match reasons.
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"""
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result = await db.execute(
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select(Contact)
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.where(
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Contact.tenant_id == tenant_id,
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Contact.deleted_at.is_(None),
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)
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.order_by(Contact.displayname)
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)
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contacts = result.scalars().all()
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duplicates: list[dict[str, Any]] = []
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seen_pairs: set[tuple[str, str]] = set()
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for i, c1 in enumerate(contacts):
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for c2 in contacts[i + 1:]:
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reasons: list[str] = []
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score = 0.0
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match_count = 0
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# Email match (exact, normalized)
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emails_1 = {_normalize_email(c1.email_1), _normalize_email(c1.email_2)} - {""}
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emails_2 = {_normalize_email(c2.email_1), _normalize_email(c2.email_2)} - {""}
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if emails_1 and emails_2 and emails_1 & emails_2:
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reasons.append("email_match")
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score += 0.5
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match_count += 1
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# Phone match (normalized digits)
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phones_1 = {_normalize_phone(c1.phone_1), _normalize_phone(c1.phone_2)} - {""}
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phones_2 = {_normalize_phone(c2.phone_1), _normalize_phone(c2.phone_2)} - {""}
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if phones_1 and phones_2 and phones_1 & phones_2:
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reasons.append("phone_match")
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score += 0.3
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match_count += 1
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# Name similarity
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name_sim = _name_similarity(c1.displayname, c2.displayname)
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if name_sim >= threshold:
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reasons.append(f"name_similarity:{name_sim:.2f}")
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score += name_sim * 0.4
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match_count += 1
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if match_count > 0 and score >= threshold:
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pair_key = (str(c1.id), str(c2.id))
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if pair_key not in seen_pairs:
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seen_pairs.add(pair_key)
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duplicates.append({
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"source_contact": _serialize_brief(c1),
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"target_contact": _serialize_brief(c2),
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"similarity_score": round(min(score, 1.0), 2),
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"match_reasons": reasons,
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})
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if len(duplicates) >= limit:
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return duplicates
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return duplicates
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def _serialize_brief(c: Contact) -> dict:
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"""Serialize a contact briefly for duplicate display."""
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return {
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"id": str(c.id),
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"type": c.type,
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"displayname": c.displayname,
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"name": c.name,
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"firstname": c.firstname,
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"surname": c.surname,
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"email_1": c.email_1,
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"email_2": c.email_2,
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"phone_1": c.phone_1,
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"phone_2": c.phone_2,
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"mailing_city": c.mailing_city,
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"mailing_postalcode": c.mailing_postalcode,
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"created_at": c.created_at.isoformat() if c.created_at else None,
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}
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def _serialize_full(c: Contact) -> dict:
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"""Serialize a contact fully for merge comparison."""
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return {
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"id": str(c.id),
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"type": c.type,
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"displayname": c.displayname,
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"name": c.name,
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"firstname": c.firstname,
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"surname": c.surname,
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"surfix": c.surfix,
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"email_1": c.email_1,
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"email_2": c.email_2,
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"phone_1": c.phone_1,
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"phone_2": c.phone_2,
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"website": c.website,
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"mailing_street": c.mailing_street,
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"mailing_postalcode": c.mailing_postalcode,
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"mailing_city": c.mailing_city,
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"mailing_country": c.mailing_country,
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"note": c.projectnote,
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"tags": c.tags,
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"code": c.code,
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"vat_code": c.vat_code,
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}
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async def merge_contacts(
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db: AsyncSession,
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tenant_id: uuid.UUID,
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user_id: uuid.UUID,
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source_id: str,
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target_id: str,
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field_overrides: dict[str, Any] | None = None,
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note: str | None = None,
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) -> dict[str, Any]:
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"""Merge source contact into target contact.
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1. Apply field overrides (if provided) to target contact.
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2. Re-point entity_links from source to target.
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3. Re-point tag_assignments from source to target.
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4. Soft-delete the source contact.
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5. Record merge history.
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Returns the merge history record and updated target contact.
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"""
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source_uuid = uuid.UUID(source_id)
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target_uuid = uuid.UUID(target_id)
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# Fetch both contacts
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result = await db.execute(
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select(Contact).where(
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Contact.id == source_uuid,
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Contact.tenant_id == tenant_id,
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Contact.deleted_at.is_(None),
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)
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)
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source = result.scalar_one_or_none()
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if not source:
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raise ValueError(f"Source contact {source_id} not found")
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result = await db.execute(
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select(Contact).where(
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Contact.id == target_uuid,
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Contact.tenant_id == tenant_id,
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Contact.deleted_at.is_(None),
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)
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)
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target = result.scalar_one_or_none()
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if not target:
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raise ValueError(f"Target contact {target_id} not found")
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if source.id == target.id:
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raise ValueError("Cannot merge a contact with itself")
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# Track which fields were merged
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merged_fields: dict[str, Any] = {}
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# Apply field overrides — fields explicitly chosen by the user
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if field_overrides:
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for field_name, value in field_overrides.items():
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if hasattr(target, field_name) and field_name not in ("id", "tenant_id", "created_at", "updated_at", "deleted_at"):
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old_value = getattr(target, field_name)
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setattr(target, field_name, value)
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merged_fields[field_name] = {
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"source_value": getattr(source, field_name, None),
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"target_old_value": old_value,
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"final_value": value,
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}
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else:
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# Auto-merge: fill empty target fields from source
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auto_fields = [
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"email_1", "email_2", "phone_1", "phone_2", "website",
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"mailing_street", "mailing_postalcode", "mailing_city", "mailing_country",
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"projectnote", "tags", "code", "vat_code",
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]
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for field_name in auto_fields:
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target_val = getattr(target, field_name, None)
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source_val = getattr(source, field_name, None)
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if not target_val and source_val:
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setattr(target, field_name, source_val)
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merged_fields[field_name] = {
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"source_value": source_val,
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"target_old_value": target_val,
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"final_value": source_val,
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}
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# Re-point entity_links from source to target (raw SQL, best-effort)
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try:
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await db.execute(
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text(
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"UPDATE entity_links SET entity_id = :target_uuid "
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"WHERE entity_type = 'contact' AND entity_id = :source_uuid "
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"AND tenant_id = :tenant_id"
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),
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{"target_uuid": target_uuid, "source_uuid": source_uuid, "tenant_id": tenant_id},
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)
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except Exception:
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pass # entity_links table may not exist in test context
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# Re-point tag_assignments from source to target (raw SQL, best-effort)
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try:
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await db.execute(
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text(
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"UPDATE tag_assignments SET entity_id = :target_uuid "
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"WHERE entity_type = 'contact' AND entity_id = :source_uuid "
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"AND tenant_id = :tenant_id"
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),
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{"target_uuid": target_uuid, "source_uuid": source_uuid, "tenant_id": tenant_id},
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)
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except Exception:
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pass # tag_assignments table may not exist in test context
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# Soft-delete source contact
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from datetime import datetime, timezone
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source.deleted_at = datetime.now(timezone.utc)
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# Record merge history
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history = ContactMergeHistory(
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tenant_id=tenant_id,
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source_contact_id=source_uuid,
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target_contact_id=target_uuid,
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merged_fields=merged_fields,
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merged_by=user_id,
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note=note,
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)
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db.add(history)
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await db.flush()
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return {
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"merge_id": str(history.id),
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"source_contact_id": str(source_uuid),
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"target_contact_id": str(target_uuid),
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"merged_fields": merged_fields,
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"target_contact": _serialize_full(target),
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}
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async def get_merge_history(
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db: AsyncSession,
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tenant_id: uuid.UUID,
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page: int = 1,
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page_size: int = 20,
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) -> dict[str, Any]:
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"""Get paginated merge history for a tenant."""
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offset = (page - 1) * page_size
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count_result = await db.execute(
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select(func.count(ContactMergeHistory.id)).where(
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ContactMergeHistory.tenant_id == tenant_id,
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ContactMergeHistory.deleted_at.is_(None),
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)
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)
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total = count_result.scalar() or 0
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result = await db.execute(
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select(ContactMergeHistory)
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.where(
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ContactMergeHistory.tenant_id == tenant_id,
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ContactMergeHistory.deleted_at.is_(None),
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)
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.order_by(ContactMergeHistory.created_at.desc())
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.offset(offset)
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.limit(page_size)
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)
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records = result.scalars().all()
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return {
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"items": [
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{
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"id": str(r.id),
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"source_contact_id": str(r.source_contact_id),
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"target_contact_id": str(r.target_contact_id),
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"merged_fields": r.merged_fields,
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"merged_by": str(r.merged_by) if r.merged_by else None,
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"note": r.note,
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"created_at": r.created_at.isoformat() if r.created_at else None,
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}
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for r in records
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],
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"total": total,
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"page": page,
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"page_size": page_size,
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}
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