zhenxun_bot/zhenxun/services/scheduler/engine.py
Rumio 70bde00757
feat(core): 增强定时任务与群组标签管理,重构调度核心 (#2068)
*  feat(core): 更新群组信息、Markdown 样式与 Pydantic 兼容层

- 【group】添加更新所有群组信息指令,并同步群组控制台数据
- 【markdown】支持合并 Markdown 的 CSS 来源
- 【pydantic-compat】提供 model_validate 兼容函数

*  feat(core): 增强定时任务与群组标签管理,重构调度核心

 新功能

* **标签 (tags)**: 引入群组标签服务。
    * 支持静态标签和动态标签 (基于 Alconna 规则自动匹配群信息)。
    * 支持黑名单模式及 `@all` 特殊标签。
    * 提供 `tag_manage` 超级用户插件 (list, create, edit, delete 等)。
    * 群成员变动时自动失效动态标签缓存。
* **调度 (scheduler)**: 增强定时任务。
    * 重构 `ScheduledJob` 模型,支持 `TAG`, `ALL_GROUPS` 等多种目标类型。
    * 新增任务别名 (`name`)、创建者、权限、来源等字段。
    * 支持一次性任务 (`schedule_once`) 和 Alconna 命令行参数 (`--params-cli`)。
    * 新增执行选项 (`jitter`, `spread`) 和并发策略 (`ALLOW`, `SKIP`, `QUEUE`)。
    * 支持批量获取任务状态。

♻️ 重构优化

* **调度器核心**:
    * 拆分 `service.py` 为 `manager.py` (API) 和 `types.py` (模型)。
    * 合并 `adapter.py` / `job.py` 至 `engine.py` (统一调度引擎)。
    * 引入 `targeting.py` 模块管理任务目标解析。
* **调度器插件 (scheduler_admin)**:
    * 迁移命令参数校验逻辑至 `ArparmaBehavior`。
    * 引入 `dependencies.py` 和 `data_source.py` 解耦业务逻辑与依赖注入。
    * 适配新的任务目标类型展示。

* 🐛 fix(tag): 修复黑名单标签解析逻辑并优化标签详情展示

*  feat(scheduler): 为多目标定时任务添加固定间隔串行执行选项

*  feat(schedulerAdmin): 允许定时任务删除、暂停、恢复命令支持多ID操作

* 🚨 auto fix by pre-commit hooks

---------

Co-authored-by: webjoin111 <455457521@qq.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
2025-11-03 10:53:40 +08:00

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"""
引擎适配层 (Adapter) 与 任务执行逻辑 (Job)
封装所有对具体调度器引擎 (APScheduler) 的操作,
以及被 APScheduler 实际调度的函数。
"""
import asyncio
from collections.abc import Callable
from datetime import datetime
from functools import partial
import random
import nonebot
from nonebot.adapters import Bot
from nonebot.dependencies import Dependent
from nonebot.exception import FinishedException, PausedException, SkippedException
from nonebot.matcher import Matcher
from nonebot.typing import T_State
from nonebot_plugin_apscheduler import scheduler
from pydantic import BaseModel
from zhenxun.configs.config import Config
from zhenxun.models.scheduled_job import ScheduledJob
from zhenxun.services.log import logger
from zhenxun.utils.common_utils import CommonUtils
from zhenxun.utils.decorator.retry import Retry
from zhenxun.utils.pydantic_compat import parse_as
from .repository import ScheduleRepository
from .types import ExecutionPolicy, ScheduleContext
JOB_PREFIX = "zhenxun_schedule_"
SCHEDULE_CONCURRENCY_KEY = "all_groups_concurrency_limit"
class APSchedulerAdapter:
"""封装对 APScheduler 的操作"""
@staticmethod
def _get_job_id(schedule_id: int) -> str:
"""
生成 APScheduler 的 Job ID
参数:
schedule_id: 定时任务的ID。
返回:
str: APScheduler 使用的 Job ID。
"""
return f"{JOB_PREFIX}{schedule_id}"
@staticmethod
def add_or_reschedule_job(schedule: ScheduledJob):
"""
根据 ScheduledJob 添加或重新调度一个 APScheduler 任务
参数:
schedule: 定时任务对象,包含任务的所有配置信息。
"""
job_id = APSchedulerAdapter._get_job_id(schedule.id)
try:
scheduler.remove_job(job_id)
except Exception:
pass
if not isinstance(schedule.trigger_config, dict):
logger.error(
f"任务 {schedule.id} 的 trigger_config 不是字典类型: "
f"{type(schedule.trigger_config)}"
)
return
trigger_params = schedule.trigger_config.copy()
execution_options = (
schedule.execution_options
if isinstance(schedule.execution_options, dict)
else {}
)
if jitter := execution_options.get("jitter"):
if isinstance(jitter, int) and jitter > 0:
trigger_params["jitter"] = jitter
concurrency_policy = execution_options.get("concurrency_policy", "ALLOW")
job_params = {
"id": job_id,
"misfire_grace_time": 300,
"args": [schedule.id],
}
if concurrency_policy == "SKIP":
job_params["max_instances"] = 1
job_params["coalesce"] = True
elif concurrency_policy == "QUEUE":
job_params["max_instances"] = 1
job_params["coalesce"] = False
scheduler.add_job(
_execute_job,
trigger=schedule.trigger_type,
**job_params,
**trigger_params,
)
logger.debug(
f"已添加或更新APScheduler任务: {job_id} | 并发策略: {concurrency_policy}, "
f"抖动: {trigger_params.get('jitter', '')}"
)
@staticmethod
def remove_job(schedule_id: int):
"""
移除一个 APScheduler 任务
参数:
schedule_id: 要移除的定时任务ID。
"""
job_id = APSchedulerAdapter._get_job_id(schedule_id)
try:
scheduler.remove_job(job_id)
logger.debug(f"已从APScheduler中移除任务: {job_id}")
except Exception:
pass
@staticmethod
def pause_job(schedule_id: int):
"""
暂停一个 APScheduler 任务
参数:
schedule_id: 要暂停的定时任务ID。
"""
job_id = APSchedulerAdapter._get_job_id(schedule_id)
try:
scheduler.pause_job(job_id)
except Exception:
pass
@staticmethod
def resume_job(schedule_id: int):
"""
恢复一个 APScheduler 任务
参数:
schedule_id: 要恢复的定时任务ID。
"""
job_id = APSchedulerAdapter._get_job_id(schedule_id)
try:
scheduler.resume_job(job_id)
except Exception:
import asyncio
async def _re_add_job():
schedule = await ScheduleRepository.get_by_id(schedule_id)
if schedule:
APSchedulerAdapter.add_or_reschedule_job(schedule)
asyncio.create_task(_re_add_job()) # noqa: RUF006
@staticmethod
def get_job_status(schedule_id: int) -> dict:
"""
获取 APScheduler Job 的状态
参数:
schedule_id: 定时任务的ID。
返回:
dict: 包含任务状态信息的字典包含next_run_time等字段。
"""
job_id = APSchedulerAdapter._get_job_id(schedule_id)
job = scheduler.get_job(job_id)
return {
"next_run_time": job.next_run_time.strftime("%Y-%m-%d %H:%M:%S")
if job and job.next_run_time
else "N/A",
"is_paused_in_scheduler": not bool(job.next_run_time) if job else "N/A",
}
@staticmethod
def add_ephemeral_job(
job_id: str,
func: Callable,
trigger_type: str,
trigger_config: dict,
context: ScheduleContext,
):
"""
直接向 APScheduler 添加一个临时的、非持久化的任务
参数:
job_id: 临时任务的唯一ID。
func: 要执行的函数。
trigger_type: 触发器类型。
trigger_config: 触发器配置字典。
context: 任务执行上下文。
"""
job = scheduler.get_job(job_id)
if job:
logger.warning(f"尝试添加一个已存在的临时任务ID: {job_id},操作被忽略。")
return
scheduler.add_job(
_execute_job,
trigger=trigger_type,
id=job_id,
misfire_grace_time=60,
args=[None],
kwargs={"context_override": context},
**trigger_config,
)
logger.debug(f"已添加新的临时APScheduler任务: {job_id}")
async def _execute_single_job_instance(
schedule: ScheduledJob, bot, group_id: str | None = None
):
"""
负责执行一个具体目标的任务实例。
"""
from .manager import scheduler_manager
plugin_name = schedule.plugin_name
if group_id is None and schedule.target_type == "GROUP":
group_id = schedule.target_identifier
task_meta = scheduler_manager._registered_tasks.get(plugin_name)
if not task_meta:
logger.error(f"无法执行任务:插件 '{plugin_name}' 在执行期间变得不可用。")
return
is_blocked = await CommonUtils.task_is_block(bot, plugin_name, group_id)
if is_blocked:
target_desc = f"{group_id}" if group_id else "全局"
logger.info(
f"插件 '{plugin_name}' 的定时任务在目标 [{target_desc}] "
f"因功能被禁用而跳过执行。"
)
return
context = ScheduleContext(
schedule_id=schedule.id,
plugin_name=plugin_name,
bot_id=bot.self_id,
group_id=group_id,
job_kwargs=schedule.job_kwargs if isinstance(schedule.job_kwargs, dict) else {},
)
state: T_State = {ScheduleContext: context}
policy_data = context.job_kwargs.pop("execution_policy", {})
policy = ExecutionPolicy(**policy_data)
async def task_execution_coro():
injected_params = {"context": context}
params_model = task_meta.get("model")
if params_model and isinstance(context.job_kwargs, dict):
try:
if isinstance(params_model, type) and issubclass(
params_model, BaseModel
):
params_instance = parse_as(params_model, context.job_kwargs)
injected_params["params"] = params_instance # type: ignore
except Exception as e:
logger.error(
f"任务 {schedule.id} (目标: {group_id}) 参数验证失败: {e}", e=e
)
raise
async def wrapper(bot: Bot):
return await task_meta["func"](bot=bot, **injected_params) # type: ignore
dependent = Dependent.parse(
call=wrapper,
allow_types=Matcher.HANDLER_PARAM_TYPES,
)
return await dependent(bot=bot, state=state)
try:
if policy.retries > 0:
on_success_handler = None
if policy.on_success_callback:
on_success_handler = partial(policy.on_success_callback, context)
on_failure_handler = None
if policy.on_failure_callback:
on_failure_handler = partial(policy.on_failure_callback, context)
retry_exceptions = tuple(policy.retry_on_exceptions or [])
retry_decorator = Retry.api(
stop_max_attempt=policy.retries + 1,
strategy="exponential" if policy.retry_backoff else "fixed",
wait_fixed_seconds=policy.retry_delay_seconds,
exception=retry_exceptions,
on_success=on_success_handler,
on_failure=on_failure_handler,
log_name=f"ScheduledJob-{schedule.id}-{group_id or 'global'}",
)
decorated_executor = retry_decorator(task_execution_coro)
await decorated_executor()
else:
logger.info(
f"插件 '{plugin_name}' 开始为目标 [{group_id or '全局'}] "
f"执行定时任务 (ID: {schedule.id})。"
)
await task_execution_coro()
except (PausedException, FinishedException, SkippedException) as e:
logger.warning(
f"定时任务 {schedule.id} (目标: {group_id}) 被中断: {type(e).__name__}"
)
except Exception as e:
logger.error(
f"执行定时任务 {schedule.id} (目标: {group_id}) "
f"时发生未被策略处理的最终错误",
e=e,
)
async def _execute_job(
schedule_id: int | None,
force: bool = False,
context_override: ScheduleContext | None = None,
):
"""
APScheduler 调度的入口函数,现在作为分发器。
"""
from .manager import scheduler_manager
schedule = None
if context_override:
plugin_name = context_override.plugin_name
task_meta = scheduler_manager._registered_tasks.get(plugin_name)
if not task_meta or not task_meta["func"]:
logger.error(f"无法执行临时任务:函数 '{plugin_name}' 未注册。")
return
try:
bot = nonebot.get_bot()
logger.info(f"开始执行临时任务: {plugin_name}")
injected_params = {"context": context_override}
state: T_State = {ScheduleContext: context_override}
async def wrapper(bot: Bot):
return await task_meta["func"](bot=bot, **injected_params) # type: ignore
dependent = Dependent.parse(
call=wrapper,
allow_types=Matcher.HANDLER_PARAM_TYPES,
)
await dependent(bot=bot, state=state)
logger.info(f"临时任务 '{plugin_name}' 执行完成。")
except Exception as e:
logger.error(f"执行临时任务 '{plugin_name}' 时发生错误", e=e)
return
if schedule_id is None:
logger.error("执行持久化任务时 schedule_id 不能为空。")
return
scheduler_manager._running_tasks.add(schedule_id)
try:
schedule = await ScheduleRepository.get_by_id(schedule_id)
if not schedule or (not schedule.is_enabled and not force):
logger.warning(f"定时任务 {schedule_id} 不存在或已禁用,跳过执行。")
return
try:
bot = (
nonebot.get_bot(schedule.bot_id)
if schedule.bot_id
else nonebot.get_bot()
)
except (KeyError, ValueError):
logger.warning(
f"任务 {schedule_id} 需要的 Bot {schedule.bot_id} "
f"不在线,本次执行跳过。"
)
raise
resolver = scheduler_manager._target_resolvers.get(schedule.target_type)
if not resolver:
logger.error(
f"任务 {schedule.id} 的目标类型 '{schedule.target_type}' "
f"没有注册解析器,执行跳过。"
)
raise ValueError(f"未知的目标类型: {schedule.target_type}")
try:
resolved_targets = await resolver(schedule.target_identifier, bot)
except Exception as e:
logger.error(f"为任务 {schedule.id} 解析目标失败", e=e)
raise
logger.info(
f"任务 {schedule.id} ({schedule.name or schedule.plugin_name}) 开始执行, "
f"目标类型: {schedule.target_type}, "
f"解析出 {len(resolved_targets)} 个目标"
)
concurrency_limit = Config.get_config(
"SchedulerManager", SCHEDULE_CONCURRENCY_KEY, 5
)
semaphore = asyncio.Semaphore(concurrency_limit if concurrency_limit > 0 else 5)
spread_config = (
schedule.execution_options
if isinstance(schedule.execution_options, dict)
else {}
)
interval_seconds = spread_config.get("interval")
if interval_seconds is not None and interval_seconds > 0:
logger.debug(
f"任务 {schedule.id}: 使用串行模式执行 {len(resolved_targets)} "
f"个目标,固定间隔 {interval_seconds} 秒。"
)
for i, target_id in enumerate(resolved_targets):
if i > 0:
logger.debug(
f"任务 {schedule.id} 目标 [{target_id or '全局'}]: "
f"等待 {interval_seconds} 秒后执行。"
)
await asyncio.sleep(interval_seconds)
await _execute_single_job_instance(schedule, bot, group_id=target_id)
else:
spread_seconds = spread_config.get("spread", 1.0)
logger.debug(
f"任务 {schedule.id}: 将在 {spread_seconds:.2f} 秒内分散执行 "
f"{len(resolved_targets)} 个目标。"
)
async def worker(target_id: str | None):
delay = random.uniform(0.1, spread_seconds)
logger.debug(
f"任务 {schedule.id} 目标 [{target_id or '全局'}]: "
f"随机延迟 {delay:.2f} 秒后执行。"
)
await asyncio.sleep(delay)
async with semaphore:
await _execute_single_job_instance(
schedule, bot, group_id=target_id
)
tasks_to_run = [worker(target_id) for target_id in resolved_targets]
if tasks_to_run:
await asyncio.gather(*tasks_to_run, return_exceptions=True)
schedule.last_run_at = datetime.now()
schedule.last_run_status = "SUCCESS"
schedule.consecutive_failures = 0
await schedule.save(
update_fields=["last_run_at", "last_run_status", "consecutive_failures"]
)
if schedule.is_one_off:
logger.info(f"一次性任务 {schedule.id} 执行成功,将被删除。")
await ScheduledJob.filter(id=schedule.id).delete()
APSchedulerAdapter.remove_job(schedule.id)
if schedule.plugin_name.startswith("runtime_one_off__"):
scheduler_manager._registered_tasks.pop(schedule.plugin_name, None)
logger.debug(f"已注销一次性运行时任务: {schedule.plugin_name}")
except Exception as e:
logger.error(f"执行任务 {schedule_id} 期间发生严重错误", e=e)
if schedule:
schedule.last_run_at = datetime.now()
schedule.last_run_status = "FAILURE"
schedule.consecutive_failures = (schedule.consecutive_failures or 0) + 1
await schedule.save(
update_fields=["last_run_at", "last_run_status", "consecutive_failures"]
)
finally:
if schedule_id is not None:
scheduler_manager._running_tasks.discard(schedule_id)