Files
MediaCrawler/api/monitor/models.py
T
butubb b9aa590814
Deploy VitePress site to Pages / build (push) Canceled after 0s
Deploy VitePress site to Pages / Deploy (push) Canceled after 0s
feat(monitor): 作品标签 —— 词表在设置里维护,作品上贴
和「作品备注」刻意并存,不是一回事:备注是一句话的自由文字,标签是**从一份固定
词表里选的分类**。分类必须封闭,否则「重点 / 重要 / 优先」各写各的,筛就没法用了。

* `monitor_tag`:词表,全局一套(不按平台分)—— 「重点」是给人自己用的心智,不该在
  小红书和抖音各定义一遍。颜色存的是**调色板里的名字**,不是色值:Tailwind 的类名是
  静态提取的,拼出来的 `text-${color}` 它看不见,线上会静默变无色。
* `monitor_note_tag`:作品↔标签,**多对多**。一条作品可以既是重点又是竞品;只能贴一个
  的话人就会跑去备注里写自由文字,这份词表就白建了。全部替换式提交,不是逐个增删。
* 删除标签时**显式删关联**,不靠外键级联 —— 测试跑 SQLite,它默认不开外键约束。
* 组头上的筛选做成平铺开关片,多选是「或」。

顺带:/monitor/notes 现在支持按 tag_id 筛。
2026-10-11 09:16:17 +08:00

533 lines
26 KiB
Python
Raw Blame History

This file contains ambiguous Unicode characters
This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.
# -*- coding: utf-8 -*-
# Copyright (c) 2025 [email protected]
#
# This file is part of MediaCrawler project.
# Repository: https://github.com/NanmiCoder/MediaCrawler/blob/main/api/monitor/models.py
# GitHub: https://github.com/NanmiCoder
# Licensed under NON-COMMERCIAL LEARNING LICENSE 1.1
#
# 声明:本代码仅供学习和研究目的使用。使用者应遵守以下原则:
# 1. 不得用于任何商业用途。
# 2. 使用时应遵守目标平台的使用条款和robots.txt规则。
# 3. 不得进行大规模爬取或对平台造成运营干扰。
# 4. 应合理控制请求频率,避免给目标平台带来不必要的负担。
# 5. 不得用于任何非法或不当的用途。
#
# 详细许可条款请参阅项目根目录下的LICENSE文件。
# 使用本代码即表示您同意遵守上述原则和LICENSE中的所有条款。
"""Monitoring layer data model.
Lives in its own SQLite database (``data/monitor.db``) with its own declarative
Base, deliberately separate from the crawler's ``database/models.py``. The
crawler's DB store overwrites ``liked_count`` and friends in place on every
re-crawl, so it cannot answer "how did this note change?". These tables keep the
history the crawler throws away.
All timestamps are epoch **milliseconds** (BigInteger), matching the project's
own ``tools.time_util.get_current_timestamp()`` convention. Using ints
throughout avoids naive/aware datetime mixing bugs.
"""
from typing import Optional
from sqlalchemy import (
BigInteger,
Boolean,
ForeignKey,
Integer,
String,
Text,
UniqueConstraint,
)
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column, relationship
class MonitorBase(DeclarativeBase):
"""Declarative base for the monitoring database."""
# Run statuses
RUN_PENDING = "pending"
RUN_RUNNING = "running"
RUN_SUCCESS = "success"
RUN_PARTIAL = "partial"
RUN_FAILED = "failed"
RUN_TIMEOUT = "timeout"
RUN_INTERRUPTED = "interrupted"
# Event types
EVENT_NEW_NOTE = "new_note"
EVENT_NEW_COMMENT_POSTED = "new_comment_posted"
EVENT_NEW_COMMENT_SEEN = "new_comment_seen"
EVENT_METRIC_DELTA = "metric_delta"
EVENT_RUN_FAILED = "run_failed"
EVENT_AUTH_FAILURE = "suspected_auth_failure"
# A run that completed cleanly yet fetched nothing, where the login is provably
# fine because another task just succeeded with it. The target, not the cookie,
# is what needs looking at.
EVENT_NO_DATA = "no_data_found"
# Task modes. One subprocess handles exactly one crawler type, so a task is
# either creator-driven or note-driven -- never both.
MODE_CREATOR = "creator"
MODE_NOTE = "note"
class MonitorTask(MonitorBase):
"""One monitored schedule: a set of targets, plus when to run them."""
__tablename__ = "monitor_task"
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
name: Mapped[str] = mapped_column(String(200), nullable=False)
platform: Mapped[str] = mapped_column(String(32), nullable=False, default="xhs")
mode: Mapped[str] = mapped_column(String(16), nullable=False)
enabled: Mapped[bool] = mapped_column(Boolean, nullable=False, default=True)
interval_minutes: Mapped[int] = mapped_column(Integer, nullable=False, default=360)
# How the task is scheduled. `interval` is the original "every N minutes" and
# stays the default; `daily` and `weekly` fire at chosen clock times instead
# (the arithmetic lives in schedule.py).
#
# The clock fields are comma-separated text rather than a child table: they
# are a handful of small integers, always read as a whole, and a table would
# buy nothing but joins.
schedule_mode: Mapped[str] = mapped_column(String(16), nullable=False, default="interval")
# 0-23, e.g. "9,12,18". Empty in interval mode.
schedule_hours: Mapped[str] = mapped_column(String(96), nullable=False, default="")
# 0-6 with Monday = 0, matching Python's date.weekday(). Weekly mode only.
schedule_days: Mapped[str] = mapped_column(String(32), nullable=False, default="")
# Minute past the hour, shared by every time in the schedule.
schedule_minute: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
# Crawl window knobs, mirrored onto each run's CLI flags.
max_notes_count: Mapped[int] = mapped_column(Integer, nullable=False, default=20)
enable_comments: Mapped[bool] = mapped_column(Boolean, nullable=False, default=True)
max_comments_count: Mapped[int] = mapped_column(Integer, nullable=False, default=50)
run_timeout_seconds: Mapped[int] = mapped_column(Integer, nullable=False, default=3600)
# 通知分成两类,因为它们的性质完全不同:
#
# * `notify_enabled` —— **推送新作品**。可能每轮都有,一条任务列表都推到同一个群
# 会很快变吵,所以默认关。(列名是历史遗留:它早先是唯一的通知开关。)
# * `notify_failures` —— **推送异常**(登录失效 / 运行失败 / 没抓到数据)。频率低,
# 而且一旦发生就意味着这个任务从此**默默采不到任何东西**,你会一直不知道,
# 直到某天发现数据停在几周前。这正是最该被告知的情况,所以默认**开**。
notify_enabled: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
notify_failures: Mapped[bool] = mapped_column(Boolean, nullable=False, default=True)
# Scheduler state. Persisted so the schedule survives an API restart.
next_run_at: Mapped[Optional[int]] = mapped_column(BigInteger, index=True)
last_run_at: Mapped[Optional[int]] = mapped_column(BigInteger)
last_status: Mapped[str] = mapped_column(String(32), nullable=False, default="idle")
last_error: Mapped[Optional[str]] = mapped_column(Text)
# Lets the UI answer "why did I not get a push for this run?".
last_notified_at: Mapped[Optional[int]] = mapped_column(BigInteger)
created_at: Mapped[int] = mapped_column(BigInteger, nullable=False)
updated_at: Mapped[int] = mapped_column(BigInteger, nullable=False)
targets: Mapped[list["MonitorTarget"]] = relationship(
back_populates="task",
cascade="all, delete-orphan",
lazy="selectin",
)
class MonitorTarget(MonitorBase):
"""One watched creator or note belonging to a task.
``external_id`` is the stable identity (XHS user_id / note_id). It is kept
separate from ``xsec_token`` on purpose: tokens expire within weeks, so
treating a tokenised URL as the primary key would make every long-running
task fail eventually.
"""
__tablename__ = "monitor_target"
__table_args__ = (
UniqueConstraint("task_id", "kind", "external_id", name="uq_monitor_target"),
)
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
task_id: Mapped[int] = mapped_column(
ForeignKey("monitor_task.id", ondelete="CASCADE"), nullable=False, index=True
)
kind: Mapped[str] = mapped_column(String(16), nullable=False)
external_id: Mapped[str] = mapped_column(String(128), nullable=False)
xsec_token: Mapped[str] = mapped_column(String(512), nullable=False, default="")
xsec_source: Mapped[str] = mapped_column(String(64), nullable=False, default="")
raw_value: Mapped[str] = mapped_column(Text, nullable=False, default="")
label: Mapped[str] = mapped_column(String(200), nullable=False, default="")
enabled: Mapped[bool] = mapped_column(Boolean, nullable=False, default=True)
created_at: Mapped[int] = mapped_column(BigInteger, nullable=False)
task: Mapped["MonitorTask"] = relationship(back_populates="targets")
class MonitorRun(MonitorBase):
"""One subprocess execution. The run history in the UI is this table."""
__tablename__ = "monitor_run"
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
task_id: Mapped[int] = mapped_column(
ForeignKey("monitor_task.id", ondelete="CASCADE"), nullable=False, index=True
)
trigger: Mapped[str] = mapped_column(String(16), nullable=False, default="scheduled")
status: Mapped[str] = mapped_column(String(16), nullable=False, default=RUN_PENDING, index=True)
phase: Mapped[str] = mapped_column(String(16), nullable=False)
# Where this run's jsonl landed. Each run gets its own directory because the
# crawler's file writer names output by date only.
save_data_path: Mapped[str] = mapped_column(Text, nullable=False, default="")
queued_at: Mapped[int] = mapped_column(BigInteger, nullable=False)
not_before: Mapped[int] = mapped_column(BigInteger, nullable=False, default=0)
started_at: Mapped[Optional[int]] = mapped_column(BigInteger)
finished_at: Mapped[Optional[int]] = mapped_column(BigInteger)
# BigInteger, not Integer: Windows reports failures as unsigned 32-bit
# NTSTATUS values (0xC0000142 = 3221225794), which overflow MySQL's signed
# INT. SQLite's dynamic typing hid this until the data was migrated.
exit_code: Mapped[Optional[int]] = mapped_column(BigInteger)
notes_fetched: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
comments_fetched: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
new_notes: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
new_comments: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
# The very first successful run of a task establishes the baseline: every
# note is "new" at that point, so emitting events would be pure noise.
is_baseline: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
# Window actually used, so the UI can be honest that comments are the top N
# in the platform's own ordering rather than a complete set.
max_comments_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
error_message: Mapped[Optional[str]] = mapped_column(Text)
class MonitorNote(MonitorBase):
"""A note ever seen by a task, plus when it was first/last seen.
Grain is (task, note) so the same note tracked by two tasks stays independent.
"""
__tablename__ = "monitor_note"
__table_args__ = (
UniqueConstraint("task_id", "note_id", name="uq_monitor_note"),
)
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
task_id: Mapped[int] = mapped_column(
ForeignKey("monitor_task.id", ondelete="CASCADE"), nullable=False, index=True
)
note_id: Mapped[str] = mapped_column(String(128), nullable=False, index=True)
title: Mapped[str] = mapped_column(Text, nullable=False, default="")
note_url: Mapped[str] = mapped_column(Text, nullable=False, default="")
cover: Mapped[str] = mapped_column(Text, nullable=False, default="")
# 创作者匿名哈希。爬虫刻意不落原始 user_id(见 tools/user_hash.py),
# 所以这是唯一稳定的创作者标识 —— 按博主分组就靠它。
creator_hash: Mapped[str] = mapped_column(String(64), nullable=False, default="")
# 创作者昵称,**已由爬虫脱敏**(张***三 这种)。存的是脱敏后的值,与项目一贯的
# 匿名化姿态一致;不存的话分组只能显示一串哈希,根本认不出是谁。
creator_name: Mapped[str] = mapped_column(String(200), nullable=False, default="")
source_kind: Mapped[str] = mapped_column(String(16), nullable=False, default="")
published_at: Mapped[Optional[int]] = mapped_column(BigInteger)
first_seen_run_id: Mapped[Optional[int]] = mapped_column(Integer)
first_seen_at: Mapped[int] = mapped_column(BigInteger, nullable=False)
last_seen_run_id: Mapped[Optional[int]] = mapped_column(Integer)
last_seen_at: Mapped[int] = mapped_column(BigInteger, nullable=False)
class MonitorNoteMetric(MonitorBase):
"""One metric snapshot per (task, note, run) -- the time series.
Raw strings are kept alongside the parsed integers so a mis-parsed "1.2万"
can always be audited after the fact.
"""
__tablename__ = "monitor_note_metric"
__table_args__ = (
UniqueConstraint("task_id", "note_id", "run_id", name="uq_note_metric"),
)
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
task_id: Mapped[int] = mapped_column(Integer, nullable=False, index=True)
note_id: Mapped[str] = mapped_column(String(128), nullable=False, index=True)
run_id: Mapped[int] = mapped_column(Integer, nullable=False, index=True)
captured_at: Mapped[int] = mapped_column(BigInteger, nullable=False)
# NULL (not 0) when the platform value could not be parsed: storing 0 would
# forge a large negative delta on the next comparison.
liked_count: Mapped[Optional[int]] = mapped_column(Integer)
comment_count: Mapped[Optional[int]] = mapped_column(Integer)
collected_count: Mapped[Optional[int]] = mapped_column(Integer)
share_count: Mapped[Optional[int]] = mapped_column(Integer)
raw_liked_count: Mapped[str] = mapped_column(String(64), nullable=False, default="")
raw_comment_count: Mapped[str] = mapped_column(String(64), nullable=False, default="")
raw_collected_count: Mapped[str] = mapped_column(String(64), nullable=False, default="")
raw_share_count: Mapped[str] = mapped_column(String(64), nullable=False, default="")
class MonitorComment(MonitorBase):
"""A comment ever seen by a task.
The (task, note, comment) uniqueness gives idempotent dedup across runs for
free -- re-running the same crawl cannot double-count.
"""
__tablename__ = "monitor_comment"
__table_args__ = (
UniqueConstraint("task_id", "note_id", "comment_id", name="uq_monitor_comment"),
)
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
task_id: Mapped[int] = mapped_column(Integer, nullable=False, index=True)
note_id: Mapped[str] = mapped_column(String(128), nullable=False, index=True)
comment_id: Mapped[str] = mapped_column(String(128), nullable=False)
content: Mapped[str] = mapped_column(Text, nullable=False, default="")
nickname: Mapped[str] = mapped_column(String(200), nullable=False, default="")
creator_hash: Mapped[str] = mapped_column(String(64), nullable=False, default="")
# Platform-stated publish time. Used to distinguish a genuinely new comment
# from one that merely entered the visible top-N window this run.
create_time: Mapped[Optional[int]] = mapped_column(BigInteger)
like_count: Mapped[Optional[int]] = mapped_column(Integer)
sub_comment_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
parent_comment_id: Mapped[str] = mapped_column(String(128), nullable=False, default="")
first_seen_run_id: Mapped[Optional[int]] = mapped_column(Integer)
first_seen_at: Mapped[int] = mapped_column(BigInteger, nullable=False)
class MonitorEvent(MonitorBase):
"""Append-only change feed. This is what the dashboard reads."""
__tablename__ = "monitor_event"
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
task_id: Mapped[int] = mapped_column(Integer, nullable=False, index=True)
run_id: Mapped[Optional[int]] = mapped_column(Integer, index=True)
type: Mapped[str] = mapped_column(String(32), nullable=False, index=True)
severity: Mapped[str] = mapped_column(String(16), nullable=False, default="info")
target_kind: Mapped[str] = mapped_column(String(16), nullable=False, default="")
target_id: Mapped[str] = mapped_column(String(128), nullable=False, default="")
title: Mapped[str] = mapped_column(Text, nullable=False, default="")
payload_json: Mapped[str] = mapped_column(Text, nullable=False, default="{}")
created_at: Mapped[int] = mapped_column(BigInteger, nullable=False, index=True)
is_read: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
class MonitorCreatorAlias(MonitorBase):
"""给博主起的备注。
作品栏和评论栏都按 ``creator_hash`` 把作品归到博主名下,可那是个哈希;
``creator_name`` 是平台上的昵称(而且粉丝少的号常常没有)。两样都认不出"这是谁"。
备注是**人自己起的名字**(「竞品A」「自家号-3」),用来把账号对上人。
键取 ``(platform, creator_hash)``:哈希对同一个 uid 是稳定的,所以同一个博主出现在
多个任务里时备注也是同一个,不用每个任务各填一遍。
"""
__tablename__ = "monitor_creator_alias"
__table_args__ = (
UniqueConstraint("platform", "creator_hash", name="uq_creator_alias"),
)
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
platform: Mapped[str] = mapped_column(String(16), nullable=False, index=True)
creator_hash: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
alias: Mapped[str] = mapped_column(String(128), nullable=False, default="")
updated_at: Mapped[int] = mapped_column(BigInteger, nullable=False)
class MonitorCreatorStat(MonitorBase):
"""博主的**账号级**快照:粉丝数 / 总获赞 / 作品数 / 关注数。
这是作品列表给不了的东西:作品级指标说"这一条视频涨了多少赞",账号级说"这个人
整个账号的粉丝是在涨还是在掉"。两者不互相替代。
粒度取 ``(任务, 博主, 轮次)``,和作品指标一样的形状 —— 于是趋势、差分、报表那套
现成的逻辑换个表就能用。
目前**只有抖音**会写它:小红书那条走的是爬虫子进程,而它的 ``save_creator()`` 在
教学版里是空函数,根本没落过创作者资料。所以表里只有抖音的博主。
"""
__tablename__ = "monitor_creator_stat"
__table_args__ = (
UniqueConstraint(
"task_id", "creator_hash", "run_id", name="uq_creator_stat"
),
)
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
task_id: Mapped[int] = mapped_column(
ForeignKey("monitor_task.id", ondelete="CASCADE"), nullable=False, index=True
)
run_id: Mapped[int] = mapped_column(Integer, nullable=False, index=True)
creator_hash: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
nickname: Mapped[str] = mapped_column(String(128), nullable=False, default="")
# 平台上的**主页 id**(抖音是 sec_uid),用来拼博主主页的跳转链接。
# creator_hash 是单向的,拼不出地址 —— 所以这个必须单独存。
# 拿不到的地方(小红书那条路不落创作者资料)留空,界面就不画那个按钮。
creator_id: Mapped[str] = mapped_column(String(128), nullable=False, default="")
# 都可能为 None:平台没给就留空,**不要伪造成 0** —— 0 是"掉到零",和"不知道"
# 在趋势图上是完全不同的两回事。
fans: Mapped[Optional[int]] = mapped_column(BigInteger)
total_favorited: Mapped[Optional[int]] = mapped_column(BigInteger)
works_count: Mapped[Optional[int]] = mapped_column(BigInteger)
following: Mapped[Optional[int]] = mapped_column(BigInteger)
captured_at: Mapped[int] = mapped_column(BigInteger, nullable=False, index=True)
class MonitorNoteAlias(MonitorBase):
"""给**作品**起的备注。
和 ``MonitorCreatorAlias`` 是一对:博主那条回答"这是谁",这条回答"这条我要盯着"。
键取 ``(platform, note_id)`` —— 作品 id 本身就带平台语义,但显式带上 platform 才能和
博主备注用同一套查询形状。
"""
__tablename__ = "monitor_note_alias"
__table_args__ = (
UniqueConstraint("platform", "note_id", name="uq_note_alias"),
)
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
platform: Mapped[str] = mapped_column(String(16), nullable=False, index=True)
note_id: Mapped[str] = mapped_column(String(128), nullable=False, index=True)
alias: Mapped[str] = mapped_column(String(128), nullable=False, default="")
updated_at: Mapped[int] = mapped_column(BigInteger, nullable=False)
class MonitorTag(MonitorBase):
"""作品标签的**词表** —— 在设置里维护,贴标签时从这里选。
刻意做成一张表而不是一个设置项:设置里那个注册表存的是标量(一个数、一段文字),
而这是一组能增能删能改名的条目。
**全局一套,不按平台分。** 「重点」「竞品」这种分类是给人自己用的心智,不该在小红书
和抖音各定义一遍;而且同一个词在两个平台上含义不同的话,反而不好比。
"""
__tablename__ = "monitor_tag"
__table_args__ = (UniqueConstraint("name", name="uq_tag_name"),)
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
name: Mapped[str] = mapped_column(String(32), nullable=False)
# 一个**调色板里的名字**(cyan/pink/green/…),不是颜色值。Tailwind 的类名是静态
# 提取的,拼不出 `text-${color}` 那种动态类,所以这里存的是查表用的键。
color: Mapped[str] = mapped_column(String(16), nullable=False, default="")
sort_order: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
created_at: Mapped[int] = mapped_column(BigInteger, nullable=False)
class MonitorNoteTag(MonitorBase):
"""作品 ↔ 标签。
键取 ``(platform, note_id)``,和作品备注同一个口径:作品 id 本身带平台语义,但显式
带上 platform 才能和别处用同一套查询形状。
**多对多**:一条作品可以既是「重点」又是「竞品」—— 标签本来就是可以叠加的分类,
一个不够用的话人就会去备注里写自由文字,那这个功能就白做了。
"""
__tablename__ = "monitor_note_tag"
__table_args__ = (
UniqueConstraint("platform", "note_id", "tag_id", name="uq_note_tag"),
)
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
platform: Mapped[str] = mapped_column(String(16), nullable=False, index=True)
note_id: Mapped[str] = mapped_column(String(128), nullable=False, index=True)
tag_id: Mapped[int] = mapped_column(Integer, nullable=False, index=True)
created_at: Mapped[int] = mapped_column(BigInteger, nullable=False)
class MonitorSetting(MonitorBase):
"""Key/value store. Holds the XHS cookie for unattended runs."""
__tablename__ = "monitor_setting"
key: Mapped[str] = mapped_column(String(64), primary_key=True)
value: Mapped[str] = mapped_column(Text, nullable=False, default="")
updated_at: Mapped[int] = mapped_column(BigInteger, nullable=False)
class AuthSession(MonitorBase):
"""A WebUI login session.
Only the SHA-256 of the token is stored, never the token itself -- a leaked
database therefore does not hand over live sessions. This mirrors the
existing posture of never returning the XHS cookie or webhook value.
A stateful table (rather than a signed stateless token) is what makes "log
out" and "password changed" take effect immediately.
"""
__tablename__ = "auth_session"
token_hash: Mapped[str] = mapped_column(String(64), primary_key=True)
created_at: Mapped[int] = mapped_column(BigInteger, nullable=False)
expires_at: Mapped[int] = mapped_column(BigInteger, nullable=False, index=True)
last_seen_at: Mapped[int] = mapped_column(BigInteger, nullable=False)
SETTING_AUTH_PASSWORD_HASH = "auth_password_hash"
SETTING_AUTH_PASSWORD_UPDATED_AT = "auth_password_updated_at"
# Settings are namespaced by scope: `platform.<p>.<name>` for values each
# platform keeps its own copy of, `system.<name>` for values shared across all of
# them. Key builders live in settings.py.
SETTING_WECOM_WEBHOOK = "system.wecom_webhook"
# 上游更新检查的两条状态。都不是给用户编辑的设置项,所以不在 app_settings 的注册表里
# (那张表只列可编辑项,因此也不会被设置接口读出来)。
#
# 最近一次检查的结果整体存成一条 JSON:它总是被整体读写,拆成多个 key 只会带来
# 另一半没写完的不一致。
SETTING_UPSTREAM_STATE = "system.upstream_check_state"
# 已经推送过通知的那个上游 tip。换 tip 才再推 —— 否则每个检查周期都会把同样的
# 更新推一遍,直到有人去合并为止;而上游真又动了的时候应该再推一次。
SETTING_UPSTREAM_NOTIFIED_TIP = "system.upstream_notified_tip"
# Pre-namespacing keys, kept only so the startup migration can find and move
# them. Nothing should read these directly.
LEGACY_SETTING_KEY_RENAMES = {
# Pre-batch-2 flat keys.
"xhs_cookie": "platform.xhs.cookie",
"xhs_cookie_updated_at": "platform.xhs.cookie_updated_at",
"xhs_cookie_last_ok_at": "platform.xhs.cookie_last_ok_at",
"wecom_webhook": "system.wecom_webhook",
# Batch-2 keys, before settings gained a scope. Those values belonged to
# Xiaohongshu because it was the only platform, so they migrate to its scope;
# the two scheduling keys were always instance-wide.
"collect.default_interval_minutes": "platform.xhs.default_interval_minutes",
"collect.default_max_notes": "platform.xhs.default_max_notes",
"collect.default_max_comments": "platform.xhs.default_max_comments",
"collect.enable_sub_comments": "platform.xhs.enable_sub_comments",
"collect.crawl_sleep_sec": "platform.xhs.crawl_sleep_sec",
"collect.active_hours_start": "system.active_hours_start",
"collect.active_hours_end": "system.active_hours_end",
"proxy.enable_ip_proxy": "platform.xhs.enable_ip_proxy",
"proxy.provider": "platform.xhs.proxy_provider",
"proxy.pool_count": "platform.xhs.proxy_pool_count",
"proxy.static_proxy_url": "platform.xhs.static_proxy_url",
}
# utf8mb4 is forced on every table rather than left to the schema default: this
# deployment's MySQL server *and* the target database both default to latin1,
# which would mangle or reject Chinese text. Setting it per table means it holds
# regardless of what the schema default happens to be.
#
# Must run after every model is declared, hence the end of the module.
for _table in MonitorBase.metadata.tables.values():
_table.kwargs["mysql_charset"] = "utf8mb4"
_table.kwargs["mysql_collate"] = "utf8mb4_unicode_ci"