feat(automation): 新增「账号资料定时补全」作业 —— 分批慢跑,不撞风控

## 为什么不能一次性跑全量

生产约 **8,000 个**「CK 有效但没查过」的账号。一次性发起 ≈ **8 万次斗鱼请求**,
很容易触发风控 —— 而风控一旦触发是**所有账号一起受影响**。试水 200 个时
0.65 秒/账号看着很香(全量 86 分钟),但那正是危险的地方:**跑得越快越容易被封**。

## 新作业 `account_overview_refresh`

照「自动巡检」(`ck_health`)那套做,并复用它的两道保护。

| 项 | 默认 | 说明 |
| --- | --- | --- |
| `interval_seconds` | 30 分钟 | 多久一轮 |
| `batch_size` | 30 | 每轮查多少(约 20 秒跑完)|
| `concurrency` | 3 | 并发 |
| `refresh_days` | 7(config 可调)| 查过的多久后再查 |
| `enabled` | **False** | 默认关,由运维手动开 |

按默认值:8,000 个约 **3 天**补完,全程不打满斗鱼接口。

## 两类账号**分开**(用户明确要求)

- **没查过的**(`overview_queried_at IS NULL`)**优先**
- 查过的只在超过 `refresh_days` 后重新入选

否则"周期性刷新老账号"会永远挤掉"从没查过的新账号"。
MySQL 没有 `NULLS FIRST`,用 `ORDER BY overview_queried_at IS NULL DESC` 等价实现。

## 只查有效 CK

`ck_check_status == 'valid'`。失效的查了也是白查(只会多一条失败记录),
交给「CK 检测与重登」处理。另外沿用 `cookie_operable_filter()`(有 CK 且无在途尝试)、
排除人工状态(停用/归档)与「不参与自动化」的账号。

## 风控熔断(沿用巡检口径)

一轮里失败率 > 50%(且样本 ≥ 10)就**自己把自己关掉**,交给人确认。
消息里写明可能原因,否则运维只看到"失败率高"会一头雾水:

    失败率过高,已自动关闭作业(大面积失败通常是**被风控**或接口抖动,请先确认再重开)

样本 < 10 不熔断 —— 1 个失败就是 100%,比例没意义。

## 查询记录

每轮都建真实的 `douyu_tasks` 行(payload 标 `source=scheduled_refresh`),
「哪个账号、什么时候、查出来什么」都有据可查,也能在任务列表里
区分「定时巡检」与「人工点查询」。账号上的 `overview_queried_at`
则是"下次该不该再查"的依据。

## 验证

- **镜像库实测**:`本轮查 3 个:成功 3 / 失败 0(剩 7784 个待查)`
- 本地 `TZ=Asia/Shanghai` **632 passed / 6 skipped**;ruff 全绿
- 新增 11 条用例:选择口径(只查有效 CK、没查过优先、refresh_days 可调、
  人工状态排除、batch_size 限流)+ 熔断(高失败率关闭、正常不关、小样本不熔断)
  + 一条回归:计数不能走带 LIMIT 的查询(作业第一版就是这么挂的)
This commit is contained in:
yml2213
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"""定时补全账号资料的作业(`account_overview_refresh`)。
**为什么不能一次性跑全量**:生产约 8,000 个待查账号,一次性发起 ≈ 8 万次斗鱼请求,
很容易触发风控 —— 而风控的代价是所有账号一起受影响。所以做成定时分批,
并复用「自动巡检」的两道保护(`cookie_operable_filter` + 错误率熔断)。
"""
from __future__ import annotations
from datetime import UTC, datetime, timedelta
from tests.support.db import get_test_engine, make_test_session
from web.backend.models import Account, AutomationJob, User
from web.backend.services.automation.jobs import account_overview_refresh as job
class _Base:
def setup_method(self):
self.engine = get_test_engine()
self.session = make_test_session(self.engine)
self.admin = User(username="ovr-admin", password_hash="h", role="super_admin")
self.session.add(self.admin)
self.session.flush()
self.job = AutomationJob(
key=job.JOB_KEY,
title="账号资料定时补全",
interval_seconds=1800,
batch_size=10,
concurrency=3,
enabled=False,
config={"refresh_days": 7},
)
self.session.add(self.job)
self.session.commit()
def teardown_method(self):
self.session.close()
def account(
self,
name: str,
*,
ck: str = "valid",
queried_days_ago: int | None = None,
auto_managed: bool = True,
status: str = "active",
) -> Account:
acc = Account(
username=name,
password="p",
email=f"{name}@e.com",
email_password="ep",
cookie="acf_uid=1; acf_ccn=c",
ck_check_status=ck,
auto_managed=auto_managed,
status=status,
)
if queried_days_ago is not None:
acc.overview_queried_at = datetime.now(UTC) - timedelta(
days=queried_days_ago
)
self.session.add(acc)
self.session.commit()
return acc
def selected(self) -> list[Account]:
return job.build_select_query(self.session, self.job, datetime.now(UTC)).all()
class TestSelection(_Base):
def test_only_valid_ck_is_selected(self):
"""只查有效 CK —— 失效的查了也是白查,只会多一条失败记录。"""
self.account("ovr-valid", ck="valid")
self.account("ovr-invalid", ck="invalid")
self.account("ovr-error", ck="error")
names = [a.username for a in self.selected()]
assert "ovr-valid" in names
assert "ovr-invalid" not in names
assert "ovr-error" not in names
def test_never_queried_comes_first(self):
"""**没查过的优先** —— 否则周期性刷新会永远挤掉从没查过的新账号。"""
self.account("ovr-old", queried_days_ago=30)
self.account("ovr-never")
assert self.selected()[0].username == "ovr-never"
def test_recently_queried_is_skipped(self):
"""刚查过的要跳过(`refresh_days` 之内不再查)。"""
self.account("ovr-fresh", queried_days_ago=1)
names = [a.username for a in self.selected()]
assert "ovr-fresh" not in names
def test_stale_is_selected_again(self):
self.account("ovr-stale", queried_days_ago=30)
assert "ovr-stale" in [a.username for a in self.selected()]
def test_refresh_days_is_configurable(self):
self.job.config = {"refresh_days": 100}
self.session.commit()
self.account("ovr-30d", queried_days_ago=30)
assert "ovr-30d" not in [a.username for a in self.selected()]
def test_manual_and_unmanaged_accounts_are_excluded(self):
"""人工状态(停用/归档)与「不参与自动化」的账号不该被自动碰。"""
self.account("ovr-disabled", status="disabled")
self.account("ovr-archived", status="archived")
self.account("ovr-unmanaged", auto_managed=False)
names = [a.username for a in self.selected()]
for bad in ("ovr-disabled", "ovr-archived", "ovr-unmanaged"):
assert bad not in names
def test_batch_size_limits_the_round(self):
for i in range(5):
self.account(f"ovr-batch-{i}")
self.job.batch_size = 2
self.session.commit()
assert len(self.selected()) == 2
def test_remaining_count_works_with_limit_applied(self):
"""回归:计数不能走 `build_select_query`。
那个查询已经 `LIMIT` 了,再 `order_by(None)` 会被 SQLAlchemy 拒绝:
"order_by() being called on a Query which already has LIMIT"。
(真踩过 —— 作业第一版就是这么挂的。)
"""
for i in range(4):
self.account(f"ovr-count-{i}")
self.job.batch_size = 1
self.session.commit()
assert job.count_remaining(self.session, self.job, datetime.now(UTC)) >= 4
class TestCircuitBreaker(_Base):
"""失败率过高就**自己把自己关掉**(风控保护)。
与「自动巡检」同口径。大面积失败通常意味着被风控或斗鱼接口抖动 ——
这时候继续跑只会把更多账号写坏,停手交给人确认才是对的。
"""
def _run_with(self, total: int, failed: int):
"""打桩执行器,只关心失败率熔断的逻辑。"""
from web.backend.models import DouyuTask
for i in range(total):
self.account(f"ovr-cb-{i}")
def fake_create(db, ids, task_type, scope, created_by, payload=None):
batch_id = "cb-batch"
for account_id in ids:
self.session.add(
DouyuTask(
batch_id=batch_id,
account_id=account_id,
task_type=task_type,
handbook_scope=scope,
status="planned",
created_by=created_by,
)
)
self.session.commit()
return batch_id, len(ids)
session = self.session # 闭包捕获:下面 _FakeRunner 里的 self 是 runner
class _FakeRunner:
def __init__(self, *a, **k):
pass
def run(self):
# 把前 `failed` 个标成失败,其余成功
rows = (
session.query(DouyuTask)
.filter(DouyuTask.batch_id == "cb-batch")
.order_by(DouyuTask.id.asc())
.all()
)
for index, row in enumerate(rows):
row.status = "failed" if index < failed else "success"
session.commit()
import web.backend.services.automation.jobs.account_overview_refresh as mod
original_create = mod.create_douyu_planned_tasks
original_runner = mod.DouyuBatchRunner
mod.create_douyu_planned_tasks = fake_create
mod.DouyuBatchRunner = _FakeRunner
try:
return job.run_account_overview_refresh(self.session, self.job)
finally:
mod.create_douyu_planned_tasks = original_create
mod.DouyuBatchRunner = original_runner
def test_high_failure_ratio_disables_the_job(self):
out = self._run_with(total=20, failed=15) # 75% 失败
self.session.refresh(self.job)
assert out["paused"] is True
assert self.job.enabled is False, "失败率过高应自动关闭作业"
assert "风控" in out["message"]
def test_normal_failure_ratio_keeps_job_running(self):
out = self._run_with(total=20, failed=1) # 5% 失败(真实的 CK 失效率)
self.session.refresh(self.job)
assert out["paused"] is False
assert "风控" not in out["message"]
def test_small_sample_does_not_trigger_breaker(self):
"""样本太少时比例没有意义(1 个失败就是 100%),不该熔断。"""
out = self._run_with(total=3, failed=3)
self.session.refresh(self.job)
assert out["paused"] is False, "样本不足时不该熔断"
@@ -6,6 +6,12 @@
from __future__ import annotations
from .jobs.account_overview_refresh import (
JOB_KEY as ACCOUNT_OVERVIEW_REFRESH_KEY,
)
from .jobs.account_overview_refresh import (
run_account_overview_refresh,
)
from .jobs.ck_health import JOB_KEY as CK_HEALTH_KEY
from .jobs.ck_health import run_ck_health
from .jobs.ck_relogin import JOB_KEY as CK_RELOGIN_KEY
@@ -33,6 +39,7 @@ from .scheduler import (
)
__all__ = [
"ACCOUNT_OVERVIEW_REFRESH_KEY",
"CK_HEALTH_KEY",
"CK_RELOGIN_KEY",
"DOUYU_TASKS_RETENTION_KEY",
@@ -44,6 +51,7 @@ __all__ = [
"register_job",
"registered_jobs",
"reset_registry",
"run_account_overview_refresh",
"run_ck_health",
"run_ck_relogin",
"run_douyu_tasks_retention",
@@ -92,6 +100,18 @@ def register_default_jobs() -> None:
run=run_ck_relogin,
)
)
register_job(
JobSpec(
key=ACCOUNT_OVERVIEW_REFRESH_KEY,
title="账号资料定时补全",
# 默认每 30 分钟一轮、每轮 30 个 —— 约 20 秒跑完,慢而稳。
# 8,000 个待查按这个速度约 3 天补完,全程不打满斗鱼接口。
interval_seconds=30 * 60,
batch_size=30,
concurrency=3,
run=run_account_overview_refresh,
)
)
register_job(
JobSpec(
key=CK_HEALTH_KEY,
@@ -0,0 +1,213 @@
"""作业:**定时分批**补全账号基础资料(一键查询的内容)。
## 为什么不能一次性跑全量
生产有约 8,000 个「CK 有效但没查过」的账号。一次性发起等于
**~8 万次斗鱼请求**,很容易触发风控 —— 而风控的代价是所有账号一起受影响。
所以做成**定时分批**:每轮只取 `batch_size` 个(默认 30),
跑完就结束,下一轮再来。慢一点没关系,**稳**最重要。
口径与「自动巡检」(`ck_health`)一致,并复用它的两道保护:
- `cookie_operable_filter()`:账号有 CK 且没有在途尝试
- **错误率熔断**:一轮里失败比例过高(通常是风控或接口抖动)就
**自己把自己关掉**,不再继续污染账号
## 两类账号分开
| 类型 | 条件 | 优先级 |
| --- | --- | --- |
| **没查过的** | `overview_queried_at IS NULL` | **优先**(补历史欠账)|
| 查过但过期了 | `overview_queried_at < now - refresh_days` | 其次(周期性刷新)|
用户明确要求这两类分开 —— 否则"周期性刷新老账号"会永远挤掉"从没查过的新账号"。
## 查询记录
每次都会建真实的 `douyu_tasks` 行(`query_account_overview`),
所以「哪个账号、什么时候、查出来什么」都有据可查;
账号上的 `overview_queried_at` 则是"下次该不该再查"的依据。
## 只查有效 CK
`ck_check_status == 'valid'`。CK 失效的账号查了也是白查(只会多一条失败记录),
交给「CK 检测与重登」去处理。
"""
from __future__ import annotations
import json
from datetime import UTC, datetime, timedelta
from typing import Any
from loguru import logger
from sqlalchemy import or_
from sqlalchemy.orm import Session
from ....models import Account, AutomationJob
from ...account_lifecycle import MANUAL_STATES
from ...douyu_runner import DouyuBatchRunner
from ...douyu_service import cookie_operable_filter, create_douyu_planned_tasks
JOB_KEY = "account_overview_refresh"
#: 默认多久刷新一次已查过的账号(天)
DEFAULT_REFRESH_DAYS = 7
#: 触发熔断的最小样本量:样本太少时比例没有意义(1 个失败就是 100%)
ERROR_PAUSE_MIN_SCANNED = 10
#: 失败比例超过这个值就熔断(与 ck_health 同口径)
ERROR_PAUSE_RATIO = 0.5
def _positive_int(value: Any, default: int) -> int:
try:
parsed = int(value)
except (TypeError, ValueError):
return default
return parsed if parsed > 0 else default
def _load_config(job: AutomationJob) -> dict[str, Any]:
config = job.config
if isinstance(config, str):
try:
config = json.loads(config)
except ValueError:
config = {}
return dict(config) if isinstance(config, dict) else {}
def build_select_query(db: Session, job: AutomationJob, now: datetime):
"""选出本轮要查的账号。
- 只要 **CK 有效**(`ck_check_status == 'valid'`)—— 失效的查了也是白查
- **没查过的优先**:`overview_queried_at IS NULL` 排在最前
(MySQL 没有 `NULLS FIRST`,用 `IS NULL` 的布尔值降序等价实现)
- 查过的只在超过 `refresh_days` 后才重新入选
"""
refresh_days = _positive_int(
_load_config(job).get("refresh_days"), DEFAULT_REFRESH_DAYS
)
cutoff = now - timedelta(days=refresh_days)
batch = _positive_int(job.batch_size, 30)
batch = _positive_int(job.batch_size, 30)
return (
_base_query(db, job, now)
# 没查过的(IS NULL = 1)排最前 —— MySQL 没有 NULLS FIRST,
# 用 `IS NULL` 的布尔值降序等价实现
.order_by(Account.overview_queried_at.is_(None).desc(), Account.id.asc())
.limit(batch)
)
def _base_query(db: Session, job: AutomationJob, now: datetime):
"""**不带排序和 LIMIT** 的基础查询。
单独抽出来是因为计数不能再走 `build_select_query`:
SQLAlchemy 不允许在已 `LIMIT` 的查询上再 `order_by(None)`
(抛 "order_by() being called on a Query which already has LIMIT")。
"""
refresh_days = _positive_int(
_load_config(job).get("refresh_days"), DEFAULT_REFRESH_DAYS
)
cutoff = now - timedelta(days=refresh_days)
return db.query(Account).filter(
cookie_operable_filter(),
Account.auto_managed.is_(True),
Account.status.notin_(MANUAL_STATES),
Account.ck_check_status == "valid",
or_(
Account.overview_queried_at.is_(None),
Account.overview_queried_at < cutoff,
),
)
def count_remaining(db: Session, job: AutomationJob, now: datetime) -> int:
"""还剩多少待查(只用于提示,不参与调度)。"""
return _base_query(db, job, now).count()
def _system_user_id(db: Session) -> int:
"""任务行的 created_by —— 定时任务不是某个人的操作,记在超管名下。"""
from ....models import User
user = (
db.query(User)
.filter(User.role == "super_admin")
.order_by(User.id.asc())
.first()
)
if user is None:
raise RuntimeError("库中没有超管用户,无法为定时任务提供 created_by")
return int(user.id)
def run_account_overview_refresh(db: Session, job: AutomationJob) -> dict[str, Any]:
"""本轮:选一批 → 建任务 → 就地跑完 → 看失败率决定要不要熔断。"""
now = datetime.now(UTC)
accounts = build_select_query(db, job, now).all()
if not accounts:
return {"scanned": 0, "succeeded": 0, "failed": 0, "message": "没有待查账号"}
account_ids = [a.id for a in accounts]
batch_id, count = create_douyu_planned_tasks(
db,
account_ids,
"query_account_overview",
"elite",
_system_user_id(db),
# 标上来源,便于在任务列表里区分「定时巡检」与「人工点查询」
{"source": "scheduled_refresh"},
)
if count == 0:
return {"scanned": 0, "succeeded": 0, "failed": 0, "message": "账号都不可查"}
# 复用现有执行器:并发、代理、进度、失败处理都是现成的
runner = DouyuBatchRunner(
db,
batch_id,
"query_account_overview",
concurrency=max(1, min(int(job.concurrency or 1), 10)),
)
runner.run()
db.commit()
from ....models import DouyuTask
rows = db.query(DouyuTask).filter(DouyuTask.batch_id == batch_id).all()
succeeded = sum(1 for t in rows if t.status == "success")
failed = sum(1 for t in rows if t.status == "failed")
error_ratio = failed / len(rows) if rows else 0.0
paused = False
if len(rows) >= ERROR_PAUSE_MIN_SCANNED and error_ratio > ERROR_PAUSE_RATIO:
# 大面积失败通常是风控或斗鱼接口抖动。继续跑只会把更多账号写坏,
# 所以**自己把自己关掉**,交给人来确认(与 ck_health 同口径)。
job.enabled = False
db.commit()
paused = True
logger.warning(
f"[overview] 失败率 {error_ratio:.0%} 过高,已自动关闭作业"
f"(batch={batch_id},failed={failed}/{len(rows)})—— 请确认是否被风控"
)
message = (
f"本轮查 {len(rows)} 个:成功 {succeeded} / 失败 {failed}"
f"(剩 {count_remaining(db, job, now)} 个待查)"
)
if paused:
# 把**可能的原因**写进消息里:运维看作业历史时才知道该去查什么,
# 否则只看到"失败率高"会一头雾水。
message += ";失败率过高,已自动关闭作业(大面积失败通常是**被风控**或接口抖动,请先确认再重开)"
logger.info(f"[overview] {message}")
return {
"scanned": len(rows),
"succeeded": succeeded,
"failed": failed,
"batch_id": batch_id,
"paused": paused,
"message": message,
}