feat: wechat friend scraper
Add the first list scraper for the yunke data-mirror system, establishing the reusable pagination pattern all later list scrapers will build on. - app/scraper/base.py: generic `paginate_by_page` async generator that walks page-numbered endpoints until a page comes back empty (the yunke CRM's primary "no more rows" signal), with a defensive over-fetch ceiling keyed off the declared total (strict `>` so an honest source yields exactly `total`). Plus a tiny `RateLimiter` enforcing a min interval between calls. - app/scraper/wechat.py: `scrape_wechat_friends` wraps `POST /wechatweb/wxFriends/friend_list/es`, maps each record to the `Customer` column shape (snake_case) with `channel="wechat"` and a verbatim `raw_json` copy. Optional `department_id`/`user_id` filters pass through to the request body. - tests/cassettes/wxFriends_fixture.py: two realistic, capture-shaped friend records + a response-envelope builder, reused by the scraper tests. - tests/test_scrape_wechat_friends.py: drives the real pagination + normalization logic through respx (page1 returns both records, page2 empty -> stop). Asserts exact field mappings, `raw_json` fidelity, and exactly 2 upstream calls. - tests/test_scrape_base.py: smoke tests for the RateLimiter spacing. Persistence (upsert into `Customer`) is deliberately deferred to Task 1.7; scrapers remain pure producers of normalized dicts. Co-Authored-By: Claude <noreply@anthropic.com>
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"""Scraper layer for the yunke data-mirror system.
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Scrapers sit between the session layer (:mod:`app.session.yunke_client`) and
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the persistence layer (a LATER task). Each scraper is an async generator that
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walks one upstream list endpoint and yields **normalized dicts** —
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snake_case keys matching the target ORM model columns, plus a ``raw_json`` key
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holding the original upstream record verbatim.
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Persistence (upsert into ORM tables) is intentionally out of scope here: it is
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Task 1.7. Keeping scrapers pure producers lets us test ingestion logic against
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``respx`` fixtures without a database.
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"""
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"""Reusable building blocks for list scrapers.
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This module establishes the pagination pattern every list scraper in the
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project reuses (see design doc §6.2 拉取层). It is intentionally small:
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* :func:`paginate_by_page` — a generic async generator that walks page-numbered
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endpoints until a page comes back empty (the primary stop signal used by the
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yunke CRM), with a defensive over-fetch ceiling keyed off the declared total.
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* :class:`RateLimiter` — a tiny asyncio limiter that enforces a minimum
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interval between successive calls. Scrapers that need to be polite to the
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upstream construct one and ``await`` :meth:`acquire` before each call.
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The paginator talks to :class:`app.session.yunke_client.YunkeClient` (which
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already injects auth headers + handles 401 re-login). It is generic over the
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response shape via three callables:
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* ``parse_total(resp) -> int | None`` — read the declared row count from the
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envelope (used only for the over-fetch safety; ``None`` disables it).
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* ``parse_rows(resp) -> list[dict]`` — extract the list of records.
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* ``build_body(page_num, page_size, **extra) -> dict`` — build the request
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body for a given page.
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"""
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from __future__ import annotations
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import asyncio
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import time
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from collections.abc import AsyncIterator, Callable
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from typing import Any
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from app.session.yunke_client import YunkeClient
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__all__ = ["RateLimiter", "paginate_by_page"]
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# Informal type aliases for the three response-handling callables. The yunke
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# response shapes are dict-shaped JSON and do not benefit from finer typing.
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ParseTotal = Callable[[Any], "int | None"]
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ParseRows = Callable[[Any], "list[dict[str, Any]]"]
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BuildBody = Callable[..., "dict[str, Any]"]
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async def paginate_by_page(
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client: YunkeClient,
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path: str,
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*,
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page_size: int,
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parse_total: ParseTotal,
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parse_rows: ParseRows,
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build_body: BuildBody,
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rate_limiter: RateLimiter | None = None,
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**extra: Any,
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) -> AsyncIterator[dict[str, Any]]:
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"""Walk a page-numbered list endpoint, yielding one dict per record.
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Pagination strategy
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-------------------
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Start at ``pageNum=1`` and advance while pages are non-empty. The yunke
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CRM signals "no more rows" by returning an empty ``data`` array on the
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page *after* the last real record; that empty page is the **primary stop
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signal**. As a defensive ceiling against a misbehaving upstream that never
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sends an empty page, we also stop once we have yielded strictly more rows
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than the declared ``total`` (strict ``>`` so an honest source yields
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exactly ``total`` rows).
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``total`` is parsed lazily from the first response and may be ``None`` if
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the envelope does not carry it — in that case only the empty-page signal
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terminates the loop.
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``rate_limiter`` is an optional :class:`RateLimiter`; when supplied, it is
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acquired before every upstream call.
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"""
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page_num = 1
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total: int | None = None
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yielded = 0
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while True:
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if rate_limiter is not None:
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await rate_limiter.acquire()
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body = build_body(page_num, page_size, **extra)
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resp = await client.post(path, json=body)
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# Read the declared total once from the first response. The yunke
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# envelopes keep it on every page, but reading it once is enough for
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# the over-fetch ceiling and avoids trusting stale updates.
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if total is None:
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total = parse_total(resp)
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rows = parse_rows(resp)
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if not rows:
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# Empty page == the upstream's "no more rows" signal. This is the
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# normal, primary termination path.
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return
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for row in rows:
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yield row
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yielded += 1
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# Over-fetch safety: a well-behaved source sends an empty page next,
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# but if it never does (or sends duplicates), cap at the declared total.
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# Strict ``>`` so we yield exactly ``total`` when the count is honest.
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if total is not None and yielded > total:
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return
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page_num += 1
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class RateLimiter:
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"""Minimal asyncio limiter enforcing a minimum interval between calls.
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Call ``await limiter.acquire()`` before each upstream request. The first
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call never waits. Successive calls wait just long enough that the gap
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between the previous call's dispatch and this one is at least
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``min_interval`` seconds.
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This is deliberately tiny: no tokens, no concurrency cap, no skew handling
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— just a floor on inter-call spacing, which is all the yunke scrapers need
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to stay polite to the CRM. If you need a semaphore or token bucket, that
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belongs in a future helper, not here.
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"""
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def __init__(self, min_interval: float = 0.0) -> None:
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self._min_interval = float(min_interval)
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self._last: float = 0.0
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async def acquire(self) -> None:
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"""Block until at least ``min_interval`` has elapsed since the last call."""
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if self._min_interval <= 0:
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self._last = time.monotonic()
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return
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now = time.monotonic()
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wait = self._min_interval - (now - self._last)
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if wait > 0:
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await asyncio.sleep(wait)
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self._last = time.monotonic()
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"""WeChat friend-list scraper.
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Wraps ``POST /wechatweb/wxFriends/friend_list/es`` and yields normalized dicts
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ready to be upserted into :class:`app.db.models.Customer` (persistence is a
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LATER task — Task 1.7). Each dict carries:
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* snake_case keys matching the ``Customer`` columns (see :func:`_normalize`),
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* ``channel == "wechat"``,
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* ``raw_json`` — the original upstream record, verbatim, so nothing captured
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is lost even when a column has no target field.
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Field names are mapped from the real capture (see Task 1.5 spec). The mapping
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is a straight ``camelCase -> snake_case`` translation with a couple of
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disambiguations where the source has two fields for one column:
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* ``phone`` <- ``phone``
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* ``wechat_phone`` <- ``wechatPhone``
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* ``dept_name`` <- ``deptName`` (falls back to ``deptRouteName``)
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* ``head_image_url`` <- ``friendHeadImageUrl`` (falls back to ``headImg``)
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"""
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from __future__ import annotations
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from collections.abc import AsyncIterator
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from typing import Any
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from app.scraper.base import paginate_by_page
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from app.session.yunke_client import YunkeClient
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__all__ = ["scrape_wechat_friends"]
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FRIEND_LIST_PATH = "/wechatweb/wxFriends/friend_list/es"
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def _parse_total(resp: Any) -> int | None:
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"""Read the declared row count from the friend_list envelope.
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Shape: ``data.basicResult.total`` (an int). Returns ``None`` if the path
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is absent so the paginator falls back to the empty-page stop signal.
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"""
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try:
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body = resp.json()
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except (AttributeError, ValueError):
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return None
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data = body.get("data") if isinstance(body, dict) else None
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if not isinstance(data, dict):
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return None
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basic = data.get("basicResult")
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if not isinstance(basic, dict):
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return None
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total = basic.get("total")
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return int(total) if isinstance(total, (int, float)) else None
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def _parse_rows(resp: Any) -> list[dict[str, Any]]:
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"""Extract the list of friend records from the envelope.
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Shape: ``data.basicResult.data`` (a list of records). Missing/non-list
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values collapse to an empty list so the paginator sees "empty page".
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"""
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try:
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body = resp.json()
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except (AttributeError, ValueError):
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return []
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data = body.get("data") if isinstance(body, dict) else None
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if not isinstance(data, dict):
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return []
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basic = data.get("basicResult")
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if not isinstance(basic, dict):
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return []
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rows = basic.get("data")
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return rows if isinstance(rows, list) else []
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def _build_body(
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page_num: int,
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page_size: int,
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*,
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department_id: str = "",
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user_id: str = "",
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) -> dict[str, Any]:
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"""Build the friend_list request body for a given page.
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The real client sends ``departmentId`` / ``userId`` filters; we accept
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them as optional kwargs (default empty) so per-staff / per-department
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scrapes are a drop-in without changing the paginator contract.
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"""
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body: dict[str, Any] = {"pageNum": page_num, "pageSize": page_size}
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if department_id:
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body["departmentId"] = department_id
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if user_id:
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body["userId"] = user_id
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return body
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def _normalize(record: dict[str, Any]) -> dict[str, Any]:
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"""Map one upstream friend record to the ``Customer`` column shape.
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Adds ``channel="wechat"`` and preserves the original record under
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``raw_json``. ``None``-safe: missing fields become ``None`` rather than
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raising, so partial payloads do not break the whole scrape.
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"""
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return {
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"friend_id": record.get("friendWxId"),
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"channel": "wechat",
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"owner_account_id": record.get("wxId"),
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"friend_nickname": record.get("friendWxNickname"),
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"friend_remark": record.get("friendWxRemark"),
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"real_name": record.get("realName"),
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"phone": record.get("phone"),
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"wechat_phone": record.get("wechatPhone"),
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"gender": record.get("gender"),
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"region": record.get("region"),
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"description": record.get("description"),
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"sale_name": record.get("saleName"),
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"user_id": record.get("userId"),
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"dept_route": record.get("deptRoute"),
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# Prefer the canonical deptName; fall back to the route-display name.
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"dept_name": record.get("deptName") or record.get("deptRouteName"),
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# Prefer friendHeadImageUrl; fall back to the legacy headImg field.
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"head_image_url": record.get("friendHeadImageUrl") or record.get("headImg"),
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"last_chat_time": record.get("lastChatTime"),
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"send_num": record.get("sendNum"),
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"receive_num": record.get("receiveNum"),
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"message_count": record.get("messageCount"),
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"delete_flag": record.get("deleteFlag"),
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"is_block": record.get("isBlock"),
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"friend_state": record.get("friendState"),
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"version": record.get("version"),
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"raw_json": record,
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}
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async def scrape_wechat_friends(
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client: YunkeClient,
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*,
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department_id: str = "",
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user_id: str = "",
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page_size: int = 50,
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) -> AsyncIterator[dict[str, Any]]:
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"""Yield normalized WeChat friend records from the CRM.
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Walks ``POST /wechatweb/wxFriends/friend_list/es`` page by page until the
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upstream reports no more rows, mapping each record to the ``Customer``
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column shape (snake_case) plus a verbatim ``raw_json`` copy.
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Parameters
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----------
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client:
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Authenticated :class:`YunkeClient`. Auth headers / 401 re-login are
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handled by the client; this scraper only concerns itself with the
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friend-list endpoint contract.
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department_id, user_id:
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Optional upstream filters (passed through to the request body as
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``departmentId`` / ``userId``). Empty by default — scrape everything
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the logged-in account can see.
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page_size:
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Page size to request. Defaults to 50 (a sane middle ground between
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request count and per-response payload size for this endpoint).
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"""
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async for record in paginate_by_page(
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client,
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FRIEND_LIST_PATH,
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page_size=page_size,
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parse_total=_parse_total,
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parse_rows=_parse_rows,
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build_body=_build_body,
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department_id=department_id,
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user_id=user_id,
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):
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yield _normalize(record)
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