"""Idempotent upsert repositories bridging scraper dicts to ORM tables. Every public helper takes an ``AsyncSession`` plus one-or-more scraper-shaped dicts (the snake_case records that ``app.scraper.*`` yields) and writes them to the corresponding table via **dialect-aware Core upsert**, so the same call path is correct on: * **in-memory SQLite** — used by the test suite (``sqlite+aiosqlite``); uses ``sqlalchemy.dialects.sqlite.insert(...).on_conflict_do_update(...)``, and * **MySQL** — production (``mysql+asyncmy``); uses ``sqlalchemy.dialects.mysql.insert(...).on_duplicate_key_update(...)``. The dialect is detected at write time via ``session.bind.name``, so callers do not need to know which backend they target. Type coercion ------------- Upstream CRM values are not always typed the way the columns want them. The following coercions are applied when building column values from the input dict (see :func:`_coerce_bool`, :func:`_coerce_int`): * Booleans (``is_block`` / ``is_send`` / ``is_del`` / ``is_on_job``): ``1`` / ``"1"`` / ``True`` -> ``True``; ``0`` / ``"0"`` / ``False`` -> ``False``; ``None`` preserved. * ``gender``: ``"0"`` / ``"1"`` / ``"2"`` (str) -> ``int`` when not ``None``. * ``type_raw`` (Message): the raw upstream type code, coerced to ``int | None``. ``Message.type`` is a normalized label string and is stored as-is (no int coercion). * Timestamps (``last_chat_time`` / ``timestamp`` / ``last_update`` / ...): passed through as-is (ms-epoch ``int`` or ``None``). * ``raw_json``: the original record dict, preserved verbatim. When the input already carries a ``raw_json`` key (scraper output does), that value wins; otherwise the input dict itself is stored. Sharding note ------------- ``app.db.models.message_table_name`` exists for the future per-month sharded ``message__`` layout. For M1, the :class:`Message` model maps to a single physical ``message`` table and :func:`upsert_messages` writes to that one table. Multi-table routing is a LATER task (YAGNI for M1). """ from __future__ import annotations from typing import Any import sqlalchemy as sa from sqlalchemy.ext.asyncio import AsyncSession from sqlalchemy.orm import DeclarativeBase from app.db.models import ( ChatGroup, Customer, Department, GroupMember, Message, Staff, WechatAccount, ) __all__ = [ "upsert_chat_group", "upsert_customer", "upsert_customers", "upsert_department", "upsert_messages", "upsert_staff", "upsert_staff_from_account", "upsert_wechat_account", ] # --------------------------------------------------------------------------- # Type coercion helpers (module-level so they are unit-testable) # --------------------------------------------------------------------------- # Columns whose source values are int-as-bool and must land as actual bool. _BOOL_FIELDS: frozenset[str] = frozenset( {"is_block", "is_send", "is_del", "is_on_job", "is_upload"} ) # Columns whose source values may arrive as numeric strings. _INT_FIELDS: frozenset[str] = frozenset( { "gender", "type_raw", "pic_type", "friend_state", "delete_flag", "direction", "incoming_call", "call_status", "qc_status", } ) def _coerce_bool(value: Any) -> bool | None: """Coerce int/str/bool CRM bool fields to a real bool. ``None`` is preserved. ``1``/``"1"``/``True`` -> ``True``; ``0``/``"0"``/``False`` -> ``False``. Common textual forms (``"true"``/``"false"``/``"yes"``/``"no"``) are also accepted; any other non-empty string falls back to truthiness so a stray value never raises. """ if value is None: return None if isinstance(value, bool): return value if isinstance(value, int): return value != 0 if isinstance(value, str): s = value.strip().lower() if s in ("1", "true", "yes", "y", "t"): return True if s in ("0", "false", "no", "n", "f", ""): return False # Last-resort: try numeric compare, else truthiness of the raw string. try: return int(s) != 0 except ValueError: return bool(s) # Floats / other: Python truthiness. return bool(value) def _coerce_int(value: Any) -> int | None: """Coerce a possibly-string numeric value to ``int``; ``None`` preserved. ``"2"`` -> ``2``; ``2`` -> ``2``; ``0``/``"0"`` -> ``0``; ``None`` -> ``None``. A non-numeric string (e.g. ``"text"``) returns ``None`` — the caller (e.g. Message.type_raw) treats that as "no value". """ if value is None: return None if isinstance(value, bool): return int(value) if isinstance(value, int): return value if isinstance(value, float): return int(value) if isinstance(value, str): s = value.strip() if not s: return None try: return int(s) except ValueError: return None return None # --------------------------------------------------------------------------- # Dialect-aware Core upsert # --------------------------------------------------------------------------- def _pk_col_names(model: type[DeclarativeBase]) -> list[str]: """Return the names of the model's primary-key columns.""" return [c.name for c in model.__table__.primary_key.columns] def _build_column_values( model: type[DeclarativeBase], rec: dict[str, Any] ) -> dict[str, Any]: """Pick rec keys that match model columns, applying type coercion. * Only keys that correspond to real columns on ``model`` are kept (extra upstream keys are dropped, since they would cause Core insert() to raise on unknown columns). * Boolean / int-as-str fields are coerced via :func:`_coerce_bool` / :func:`_coerce_int`. * ``raw_json`` defaults to the entire input dict when not explicitly provided, so the verbatim upstream record is always recoverable. """ col_names = {c.name for c in model.__table__.columns} values: dict[str, Any] = {} for col_name in col_names: if col_name in rec: v = rec[col_name] if col_name in _BOOL_FIELDS: v = _coerce_bool(v) elif col_name in _INT_FIELDS: v = _coerce_int(v) values[col_name] = v # Preserve the verbatim source record. If the scraper already set raw_json # (it does), that wins; otherwise the input dict itself is the source of # truth. if "raw_json" in col_names and "raw_json" not in values: values["raw_json"] = rec return values def _build_upsert_stmt( model: type[DeclarativeBase], values: dict[str, Any], dialect_name: str ) -> sa.Insert: """Build a dialect-specific idempotent Core upsert for one row. On conflict the statement updates **every non-PK column** from the incoming row, so re-running a scrape yields one final row per PK with the freshest values (counts, version, names, raw_json, updated_at, ...). Parameters ---------- model: The ORM model class to upsert into. values: Column-name -> value dict (output of :func:`_build_column_values`). dialect_name: One of ``"sqlite"`` / ``"mysql"`` (the two backends this project targets). Any other dialect raises ``ValueError``. """ pk_cols = _pk_col_names(model) # Non-PK columns to refresh on conflict (volatile fields). update_col_names = [c.name for c in model.__table__.columns if c.name not in pk_cols] # NB: access ``excluded`` / ``inserted`` on the BARE insert (before # ``.values(...)``) and reuse that accessor when building the SET dict. # If the accessor is taken on the post-``.values()`` statement, the # ``excluded.`` references do not bind to the supplied values at # compile time and the ON CONFLICT DO UPDATE silently fails to refresh # the row (a SQLAlchemy quirk; verified on 2.0.x). if dialect_name == "sqlite": from sqlalchemy.dialects.sqlite import insert as sqlite_insert bare = sqlite_insert(model) excluded = bare.excluded set_ = {name: excluded[name] for name in update_col_names} return bare.values(**values).on_conflict_do_update( index_elements=pk_cols, set_=set_ ) if dialect_name == "mysql": from sqlalchemy.dialects.mysql import insert as mysql_insert bare = mysql_insert(model) inserted = bare.inserted update_dict = {name: inserted[name] for name in update_col_names} return bare.values(**values).on_duplicate_key_update(**update_dict) raise ValueError( f"Unsupported dialect for idempotent upsert: {dialect_name!r}. " "Only 'sqlite' (tests) and 'mysql' (prod) are supported." ) async def _dialect_name(session: AsyncSession) -> str: """Return the dialect name of the session's bind (e.g. 'sqlite'/'mysql'). Uses ``session.bind.name`` (the AsyncEngine); falls back to ``session.get_bind().dialect.name`` if ``bind`` is not set on the session. """ bind = session.bind if bind is not None and hasattr(bind, "name"): return bind.name # type: ignore[no-any-return] return session.get_bind().dialect.name async def _upsert_one(session: AsyncSession, model: type[DeclarativeBase], rec: dict[str, Any]) -> None: """Upsert a single record into ``model``.""" values = _build_column_values(model, rec) # If the record carries no values for any column (e.g. empty dict), there # is nothing to write — skip the round-trip. PK-only rows still go through # because their PK is in `values`. if not values: return dialect = await _dialect_name(session) stmt = _build_upsert_stmt(model, values, dialect) await session.execute(stmt) # --------------------------------------------------------------------------- # Public upsert helpers # --------------------------------------------------------------------------- async def upsert_customer(session: AsyncSession, rec: dict[str, Any]) -> None: """Idempotently upsert one :class:`Customer` (PK = ``friend_id``). Same ``friend_id`` twice -> one row, with non-PK fields refreshed from the later record. """ await _upsert_one(session, Customer, rec) async def upsert_customers(session: AsyncSession, recs: list[dict[str, Any]]) -> int: """Batch upsert for :class:`Customer`. Returns the number of records processed. Idempotent: duplicate ``friend_id`` values within the batch collapse to a single row (the last write wins) at the DB layer. """ for rec in recs: await _upsert_one(session, Customer, rec) return len(recs) async def upsert_messages(session: AsyncSession, recs: list[dict[str, Any]]) -> int: """Batch idempotent upsert for :class:`Message` (PK = ``msg_id``). Applies the documented coercions (``is_send``/``is_del`` -> bool, ``type_raw`` -> int). ``Message.type`` is the normalized label string and is stored as-is. Returns the number of records processed (input length); the DB collapses duplicate ``msg_id`` values to one row. .. note:: For M1 the ``Message`` model maps to a single physical ``message`` table. Real per-month sharding across ``message__`` tables (see :func:`app.db.models.message_table_name`) is a LATER task; do not implement multi-table routing here. """ for rec in recs: await _upsert_one(session, Message, rec) return len(recs) # --------------------------------------------------------------------------- # Department upsert (Task 2.0) # --------------------------------------------------------------------------- async def upsert_department(session: AsyncSession, rec: dict[str, Any]) -> None: """Idempotently upsert one :class:`Department` (PK = ``dept_id``). Same ``dept_id`` twice -> one row, with non-PK fields (``parent_id`` / ``name`` / ``path`` / ``raw_json``) refreshed from the later record. """ await _upsert_one(session, Department, rec) # --------------------------------------------------------------------------- # WechatAccount + embedded Staff (best-effort) # --------------------------------------------------------------------------- async def upsert_staff(session: AsyncSession, rec: dict[str, Any]) -> None: """Idempotently upsert one :class:`Staff` row from a staff-shaped dict. PK = ``user_id``. Same ``user_id`` twice -> one row, with non-PK fields refreshed. Applies the documented coercions (``is_on_job`` -> bool). This is the primitive staff upsert; the account-scoped helper :func:`upsert_staff_from_account` (which extracts the staff fields from a wechat-account record) delegates here, and :func:`upsert_wechat_account` calls that helper so an account upsert automatically refreshes its embedded staff row too. """ await _upsert_one(session, Staff, rec) async def upsert_wechat_account(session: AsyncSession, rec: dict[str, Any]) -> None: """Idempotently upsert a :class:`WechatAccount` AND its embedded Staff row. PK = ``wx_id``. The companion :func:`upsert_staff_from_account` covers the embedded staff row (``user_id`` + ``user_name``); this helper calls it automatically so an account scrape that lands accounts also lands the owning staff — callers do not need to upsert staff separately. The staff upsert is best-effort: an account record with no ``user_id`` (e.g. an orphaned / unassigned wechat number) still writes the account row; the staff upsert silently no-ops. """ await _upsert_one(session, WechatAccount, rec) await upsert_staff_from_account(session, rec) async def upsert_staff_from_account(session: AsyncSession, rec: dict[str, Any]) -> None: """Best-effort upsert of the Staff row embedded in a wechat-account record. Maps the account's ``user_id`` + ``user_name`` (plus ``is_on_job`` / ``phone`` / ``sale_phone`` when present) onto :class:`Staff` (PK = ``user_id``) and delegates to :func:`upsert_staff`. Silently no-ops when the record has no ``user_id`` — there is nothing to key the row on. Per Task 2.1, dept linkage for staff is inferred ELSEWHERE (from customers' ``deptRoute``); staff with no customers have no dept. This helper therefore does not populate ``dept_id`` — that is a later concern. """ user_id = rec.get("user_id") if not user_id: return staff_rec: dict[str, Any] = { "user_id": user_id, "name": rec.get("user_name"), "raw_json": rec, } # Forward any Staff-relevant fields the account record happens to carry. # ``phone`` and ``sale_phone`` are usually absent on the wxUser payload # (they come from the WhatsApp account payload); carry them through when # present so a future shared caller does not silently drop them. for key in ("is_on_job", "phone", "sale_phone"): if key in rec: staff_rec[key] = rec[key] await upsert_staff(session, staff_rec) # --------------------------------------------------------------------------- # ChatGroup + GroupMember upsert (M2) # --------------------------------------------------------------------------- async def upsert_chat_group(session: AsyncSession, rec: dict[str, Any]) -> None: """Idempotently upsert one :class:`ChatGroup` AND its :class:`GroupMember` rows. PK = ``room_id``. The group row is upserted first; then, for every id in the record's ``member_ids_list`` (the scraper-parsed, empties-dropped member wxid list), a :class:`GroupMember` row is upserted against the composite PK ``(channel, room_id, member_id)``. Re-scraping a group therefore refreshes the group row and re-asserts its members without duplication (idempotent). The ``member_ids_list`` key is the parsed list shape produced by :func:`app.scraper.wechat._normalize_chat_group`; it is NOT a ``ChatGroup`` column, so it is dropped by :func:`_build_column_values` when writing the group row (the raw semicolon-joined string is preserved on ``ChatGroup.member_ids``). Per-member ``nickname`` / ``avatar`` / ``display_name`` are left ``None`` here — Phase-0 does not yet resolve them (they need a separate per-member API; see data dictionary §9.6). The repo writes a minimal member row keyed by the composite PK so membership is captured now and enriched later. """ await _upsert_one(session, ChatGroup, rec) channel = rec.get("channel") or "wechat" room_id = rec.get("room_id") # No room_id -> nothing to key member rows on (defensive; the scraper # always sets room_id). Skip the member loop rather than raising so a # malformed record still lands its (PK-less) group upsert attempt above. if not room_id: return member_ids: list[Any] = list(rec.get("member_ids_list") or []) for member_id in member_ids: # Defensive: never insert an empty/falsy member id (would collide on # an empty-PK row). The scraper already drops empties, but a hand- # built record could slip one through. if not member_id: continue member_rec: dict[str, Any] = { "channel": channel, "room_id": room_id, "member_id": member_id, } await _upsert_one(session, GroupMember, member_rec)