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yunke/yunke-server/app/storage/repos.py
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浅念 2b79e7a232 feat: department + wechat account/staff scrapers
M2 organization scrapers for yunke-server:

- scrape_departments: POST /usercenter/dept/tree. Single request (no
  pagination). Defensively unwraps the envelope (data is node list OR an
  object wrapping nodes under children), flattens BOTH nested and flat
  shapes, and reconstructs the materialized path by walking the pId chain
  (ancestor names joined with /). Maps id/pId/name -> dept_id/parent_id/name.

- scrape_wechat_accounts: POST /wechatweb/wxUser/list. Page-number
  pagination via the existing paginate_by_page helper. Envelope differs
  from friend_list (no basicResult wrapper): data.data/data.total. Maps
  wechatId/nickName/alias/phone/userId/userName/contactsNum/groupNum/
  sendNum/receiveNum/isOnJob/dbSize/onlineStatus/lastUpdate/version to
  WechatAccount columns; carries embedded staff pair for the repo layer.

Repos:
- upsert_department: idempotent upsert into Department (PK dept_id).
- upsert_staff: primitive idempotent staff upsert (PK user_id, is_on_job
  coerced to bool).
- upsert_wechat_account: now ALSO upserts the embedded Staff row via
  upsert_staff_from_account (best-effort; skips when account has no user_id).
- upsert_staff_from_account: refactored to delegate to upsert_staff and
  forward phone/sale_phone/is_on_job when present.

Tests (TDD red->green): test_scrape_departments (nested + flat + wrapped-data
+ empty), test_scrape_wechat_accounts (2-page pagination + body advance +
empty first page), test_repos extended (dept idempotency/root parent, direct
staff upsert + bool coercion, account-also-upserts-staff, re-upsert updates
both, no-user_id skips staff). Cassettes: dept_tree_fixture (same 4 nodes in
both nested + flat shapes), wxUser_fixture (4 capture-shaped accounts incl.
departed + orphan).

Suite: 97 -> 111 passing. ruff check clean.

Co-Authored-By: Claude <noreply@anthropic.com>
2026-08-01 13:46:23 +08:00

386 lines
15 KiB
Python

"""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_<channel>_<YYYYMM>`` 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 Customer, Department, Message, Staff, WechatAccount
__all__ = [
"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.<col>`` 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_<channel>_<YYYYMM>`` 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)