初始化项目

2026-06-02 17:46:38 +08:00
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+"""
+待办工单附件数据上传。
+
+对应文档接口：7、推送附件信息
+"""
+import asyncio
+import json
+from typing import Optional, Union
+
+import pandas as pd
+from sqlalchemy import select, desc
+from tornado.httpclient import HTTPResponse, HTTPRequest
+
+import dock
+import models
+from dock.oa import oa_api_request
+from models.dcm_push_status import DcmPushStatus
+from models.dcm_task import DcmTask
+from models.dcm_task_attachment import DcmTaskAttachment
+from models.dcm_task_file_upload import DcmTaskFileUpload
+from paste.core.logging import echo_log
+from paste.util import udict
+from paste.web import requests
+
+DcmTaskAttachmentMapping = {
+    DcmTaskAttachment.id.key: 'id',
+    DcmTaskFileUpload.oa_media_id.key: 'mediaId',
+    DcmTaskAttachment.media_usage.key: 'mediaUsage',
+    DcmTaskAttachment.act_def_name.key: 'actDefName',
+    DcmTaskAttachment.upload_time.key: 'uploadCreateTime',
+}
+"""
+附件数据推送映射关系。
+"""
+
+
+async def after_push_attachment_request(response: HTTPResponse, retry_queue: asyncio.Queue[HTTPRequest]):
+    """
+    工单推送请求响应后的处理程序。
+
+    :param response: 响应对象
+    :param retry_queue: 重试队列
+    """
+    body = response.body.decode()
+    echo_log(body)
+    body_data = json.loads(body)
+    code = udict.get_by_path(body_data, 'code')
+    message = udict.get_by_path(body_data, 'msg')
+    if code==200:
+        dcm_task_id = getattr(response.request, "dcm_task_id")
+        await DcmPushStatus.set_push_task_attachment_status(dcm_task_id)
+        echo_log(f"推送企业待办附件成功.")
+    else:
+        echo_log(f"推送企业待办附件失败：{message}")
+
+    if retry_queue:
+        echo_log(f"企业待办附件重试队列中有：{retry_queue.qsize()} 个请求在等待.")
+
+
+async def push_attachment(fetch_size: int = 50,
+                          task_id: Optional[Union[str, int, list[Union[str, int]]]] = None):
+    """
+    推送待办附件数据及其数据。
+
+    :param fetch_size: 本次推送数量
+    :param task_id: 待办任务 ID 可选
+    """
+    # 根据条件获取目标任务 ID 列表（支持指定 task_id 或分页获取）
+    task_query = select(DcmTask.id).order_by(desc(DcmTask.act_id))
+    if task_id:
+        if isinstance(task_id, list):
+            task_query = task_query.where(DcmTask.id.in_(task_id))
+            echo_log(f"本次推送待办列表：{task_id} 的附件数据...")
+        else:
+            task_query = task_query.where(DcmTask.id == task_id)
+            echo_log(f"本次推送待办：{task_id} 的附件数据...")
+    else:
+        task_query = task_query.limit(fetch_size)
+        echo_log(f"本次推送前 {fetch_size} 条待办附件数据...")
+
+    dcm_task_df = await DcmTask.query_as_df(task_query)
+    # 格式化为字符串
+    dcm_task_df[DcmTask.id.key] = dcm_task_df[DcmTask.id.key].astype(str)
+
+    # 预处理数据方法
+    def preprocess(df: pd.DataFrame):
+        # 更名，并仅保留需要的列
+        df = df.rename(columns=DcmTaskAttachmentMapping)
+        df = df[list(DcmTaskAttachmentMapping.values()) + [DcmTaskAttachment.dcm_task_id.key]]
+        return df
+
+    # 填充附件数据
+    await DcmTaskAttachment.fill_attachment(dcm_task_df, column_name='attachmentList', preprocessing=preprocess)
+
+    # 处理无附件待办状态
+    empty_dcm_task_df = dcm_task_df[dcm_task_df['attachmentList'].apply(lambda x: len(x) == 0)]
+    empty_dcm_task_df[DcmPushStatus.dcm_task_id.key] = empty_dcm_task_df[DcmTask.id.key]
+    empty_dcm_task_df[DcmPushStatus.push_task_attachment_status.key] = 1
+    empty_dcm_task_df = empty_dcm_task_df[[DcmPushStatus.dcm_task_id.key, DcmPushStatus.push_task_attachment_status.key]]
+    await DcmPushStatus.save_batch(empty_dcm_task_df)
+
+    # 过滤空数组
+    full_dcm_task_df = dcm_task_df[dcm_task_df['attachmentList'].apply(lambda x: len(x) > 0)]
+    # 删除 DcmTaskAttachment.dcm_task_id.key 字段
+    def remove_dcm_task_id(attachment_list):
+        for item in attachment_list:
+            if isinstance(item, dict) and DcmTaskAttachment.dcm_task_id.key in item:
+                del item[DcmTaskAttachment.dcm_task_id.key]
+        return attachment_list
+    # 执行替换
+    full_dcm_task_df['attachmentList'] = full_dcm_task_df['attachmentList'].apply(remove_dcm_task_id)
+
+    # 处理数据映射，适应接口推送
+    mapped_df = full_dcm_task_df.rename(columns={DcmTask.id.key: 'gdId'})
+    # 这里把空数据都换成 None，以便存入数据库时是 null
+    mapped_df.replace(models.EmptyInDF + models.EmptyDatetimeInDF, '', inplace=True)
+
+    echo_log(f"正在准备请求队列...")
+    # 构建请求队列
+    dcm_push_queue = asyncio.Queue()
+
+    # 向队列中填充请求对象
+    for _h, row in mapped_df.iterrows():
+        push_request = await oa_api_request.get_push_attachment_request(**row.to_dict())
+        setattr(push_request, "dcm_task_id", row.get('gdId'))
+        await dcm_push_queue.put(push_request)
+
+    # 并发提交推送请求
+    echo_log(f"开始推送待办附件数据...")
+    await requests.async_concurrency(
+        dcm_push_queue, con_count=dock.CONCURRENCY_COUNT, retry=dock.MAX_RETRY_COUNT,
+        after_request=after_push_attachment_request
+    )
+    echo_log(f"待办附件数据推送已经完成...")
+
+
+if __name__ == "__main__":
+    from paste.core import aio_pool
+    _runner = aio_pool.get_aio_runner()
+    _runner(push_attachment(task_id=2054174091237265408))