443 lines
19 KiB
Python
443 lines
19 KiB
Python
import json
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import logging
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import os
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import tempfile
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import time
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from collections import defaultdict
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from time import sleep
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import cv2
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import jieba
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import requests
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from rapidfuzz import process, fuzz
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from sqlalchemy import update
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from db import MysqlSession
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from db.mysql import BdYljg, BdYlks, ZxIeResult, ZxIeCost, ZxIeDischarge, ZxIeSettlement, ZxPhhd, ZxPhrec
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from doc_dewarp import dewarp
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from paddle_detection import detector
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from photo_review import PATIENT_NAME, ADMISSION_DATE, DISCHARGE_DATE, MEDICAL_EXPENSES, PERSONAL_CASH_PAYMENT, \
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PERSONAL_ACCOUNT_PAYMENT, PERSONAL_FUNDED_AMOUNT, MEDICAL_INSURANCE_TYPE, HOSPITAL, DEPARTMENT, DOCTOR, \
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ADMISSION_ID, SETTLEMENT_ID, AGE, OCR, SETTLEMENT_IE, DISCHARGE_IE, COST_IE, PHHD_BATCH_SIZE, SLEEP_MINUTES, \
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UPPERCASE_MEDICAL_EXPENSES, HOSTNAME, HOSPITAL_ALIAS, HOSPITAL_FILTER, DEPARTMENT_ALIAS, DEPARTMENT_FILTER
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from ucloud import ufile
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from util import image_util, util
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from util.data_util import handle_date, handle_decimal, parse_department, handle_name, \
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handle_insurance_type, handle_original_data, handle_hospital, handle_department, handle_id, handle_age, parse_money, \
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parse_hospital
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# 合并信息抽取结果
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def merge_result(result1, result2):
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for key in result2:
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result1[key] = result1.get(key, []) + result2[key]
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return result1
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def ie_temp_image(ie, ocr, image):
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with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as temp_file:
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cv2.imwrite(temp_file.name, image)
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ie_result = []
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try:
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layout = util.get_ocr_layout(ocr, temp_file.name)
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if not layout:
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# 无识别结果
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ie_result = []
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else:
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ie_result = ie({"doc": temp_file.name, "layout": layout})[0]
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except Exception as e:
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logging.error("信息抽取时出错", exc_info=e)
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finally:
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try:
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os.remove(temp_file.name)
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except Exception as e:
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logging.info(f"删除临时文件 {temp_file.name} 时出错", exc_info=e)
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return ie_result
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# 关键信息提取
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def request_ie_result(task_enum, phrecs):
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url = task_enum.request_url()
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identity = int(time.time())
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images = []
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for phrec in phrecs:
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images.append({"name": phrec.cfjaddress, "pk": phrec.pk_phrec})
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payload = {"images": images, "schema": task_enum.schema(), "pk_phhd": phrecs[0].pk_phhd, "identity": identity}
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response = requests.post(url, json=payload)
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if response.status_code == 200:
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return response.json()["data"]
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else:
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raise Exception(f"请求信息抽取结果失败，状态码：{response.status_code}")
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# 关键信息提取
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def information_extraction(ie, phrecs, identity):
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result = {}
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for phrec in phrecs:
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img_path = ufile.get_private_url(phrec.cfjaddress)
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if not img_path:
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continue
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image = image_util.read(img_path)
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target_images = []
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det_time = time.time()
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target_images += detector.get_book_areas(image) # 识别文档区域并裁剪
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logging.info(f"det耗时：{time.time() - det_time}")
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if not target_images:
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target_images.append(image) # 识别失败
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angle_count = defaultdict(int, {"0": 0}) # 分割后图片的最优角度统计
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for target_image in target_images:
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dewarp_time = time.time()
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dewarped_image = dewarp.dewarp_image(target_image) # 去扭曲
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logging.info(f"dewarp耗时：{time.time() - dewarp_time}")
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angles = image_util.parse_rotation_angles(dewarped_image)
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zx_ie_results = []
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split_results = image_util.split(dewarped_image)
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for split_result in split_results:
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rotated_img = image_util.rotate(split_result["img"], int(angles[0]))
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ie_results = [{"result": ie_temp_image(ie, OCR, rotated_img), "angle": angles[0]}]
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if not ie_results[0]["result"] or len(ie_results[0]["result"]) < len(ie.kwargs.get("schema")):
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rotated_img = image_util.rotate(split_result["img"], int(angles[1]))
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ie_results.append({"result": ie_temp_image(ie, OCR, rotated_img), "angle": angles[1]})
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now = util.get_default_datetime()
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best_angle = ["0", 0]
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for ie_result in ie_results:
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if not ie_result["result"]:
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continue
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result_json = json.dumps(ie_result["result"], ensure_ascii=False)
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if len(result_json) > 5000:
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result_json = result_json[:5000]
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zx_ie_results.append(ZxIeResult(pk_phhd=phrec.pk_phhd, pk_phrec=phrec.pk_phrec, id=identity,
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cfjaddress=phrec.cfjaddress, content=result_json,
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rotation_angle=int(ie_result["angle"]),
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x_offset=split_result["x_offset"],
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y_offset=split_result["y_offset"], create_time=now,
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creator=HOSTNAME, update_time=now, updater=HOSTNAME))
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result = merge_result(result, ie_result["result"])
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if len(ie_result["result"]) > best_angle[1]:
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best_angle = [ie_result["angle"], len(ie_result["result"])]
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angle_count[best_angle[0]] += 1
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img_angle = max(angle_count, key=angle_count.get)
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if img_angle != "0":
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image = image_util.rotate(image, int(img_angle))
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with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as temp_file:
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cv2.imwrite(temp_file.name, image)
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try:
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ufile.upload_file(phrec.cfjaddress, temp_file.name)
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# 修正旋转角度
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for zx_ie_result in zx_ie_results:
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zx_ie_result.rotation_angle -= int(img_angle)
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except Exception as e:
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logging.error(f"上传图片({phrec.cfjaddress})失败", exc_info=e)
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finally:
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util.delete_temp_file(temp_file.name)
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session = MysqlSession()
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session.add_all(zx_ie_results)
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session.commit()
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session.close()
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return result
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# 从keys中获取准确率最高的value
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def get_best_value_in_keys(source, keys):
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# 最终结果
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result = None
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# 最大可能性
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best_probability = 0
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for key in keys:
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values = source.get(key)
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if values:
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for value in values:
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text = value.get("text")
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probability = value.get("probability")
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if text and probability > best_probability:
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result = text
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best_probability = probability
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return result
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# 从keys中获取所有value组成list
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def get_values_of_keys(source, keys):
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result = []
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for key in keys:
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value = source.get(key)
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if value:
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for v in value:
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v = v.get("text")
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if v:
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result.append(v)
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# 去重
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return list(set(result))
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def save_or_update_ie(table, pk_phhd, data):
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data = {k: v for k, v in data.items() if v is not None and v != ""}
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obj = table(**data)
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session = MysqlSession()
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db_data = session.query(table).filter_by(pk_phhd=pk_phhd).one_or_none()
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now = util.get_default_datetime()
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if db_data:
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# 更新
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db_data.update_time = now
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db_data.creator = HOSTNAME
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for k, v in data.items():
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setattr(db_data, k, v)
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else:
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# 新增
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obj.create_time = now
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obj.creator = HOSTNAME
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obj.update_time = now
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obj.updater = HOSTNAME
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session.add(obj)
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session.commit()
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session.close()
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def search_hospital(hospital):
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def _filter_search_keywords(keywords):
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keywords = [x for x in keywords if x not in HOSPITAL_FILTER and len(x) > 1]
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result1 = ""
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result2 = ""
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for keyword in keywords:
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if "医院" in keyword:
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break
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result2 = result1
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result1 = keyword
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result = [result1]
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if result2:
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result.append(result2)
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return result
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cut_list = jieba.lcut(hospital, HMM=False)
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session = MysqlSession()
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yljg = session.query(BdYljg.pk_yljg, BdYljg.name).filter(BdYljg.name.like(f"%{'%'.join(cut_list)}%")).all()
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if not yljg:
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filter_keywords = _filter_search_keywords(cut_list)
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for filter_keyword in filter_keywords:
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yljg = session.query(BdYljg.pk_yljg, BdYljg.name).filter(BdYljg.name.like(f"%{filter_keyword}%")).all()
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if yljg:
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break
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session.close()
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yljg = {row.pk_yljg: row.name for row in yljg}
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best_match = process.extractOne(hospital, yljg, scorer=fuzz.partial_token_set_ratio)
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return best_match
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def search_department(department):
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def _filter_search_keywords(keywords):
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keywords = [x for x in keywords if x not in DEPARTMENT_FILTER]
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return keywords
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cut_list = jieba.lcut(department, HMM=False)
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session = MysqlSession()
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cut_list = _filter_search_keywords(cut_list)
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if not cut_list:
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return None
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ylks = session.query(BdYlks.pk_ylks, BdYlks.name).filter(BdYlks.name.like(f"%{'%'.join(cut_list)}%")).all()
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if not ylks:
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filter_keywords = cut_list
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for filter_keyword in filter_keywords:
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ylks = session.query(BdYlks.pk_ylks, BdYlks.name).filter(BdYlks.name.like(f"%{filter_keyword}%")).all()
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if ylks:
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break
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session.close()
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ylks = {row.pk_ylks: row.name for row in ylks}
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best_match = process.extractOne(department, ylks, scorer=fuzz.token_ratio)
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if best_match and best_match[0] in ["内科", "外科"]:
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# 降低内科、外科的优先级
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best_match = list(best_match)
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best_match[1] -= 100
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return best_match
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def settlement_task(pk_phhd, settlement_list, identity):
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settlement_list_ie_result = information_extraction(SETTLEMENT_IE, settlement_list, identity)
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settlement_data = {
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"pk_phhd": pk_phhd,
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"name": handle_name(get_best_value_in_keys(settlement_list_ie_result, PATIENT_NAME)),
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"admission_date_str": handle_original_data(get_best_value_in_keys(settlement_list_ie_result, ADMISSION_DATE)),
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"discharge_date_str": handle_original_data(get_best_value_in_keys(settlement_list_ie_result, DISCHARGE_DATE)),
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"personal_cash_payment_str": handle_original_data(
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get_best_value_in_keys(settlement_list_ie_result, PERSONAL_CASH_PAYMENT)),
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"personal_account_payment_str": handle_original_data(
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get_best_value_in_keys(settlement_list_ie_result, PERSONAL_ACCOUNT_PAYMENT)),
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"personal_funded_amount_str": handle_original_data(
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get_best_value_in_keys(settlement_list_ie_result, PERSONAL_FUNDED_AMOUNT)),
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"medical_insurance_type_str": handle_original_data(
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get_best_value_in_keys(settlement_list_ie_result, MEDICAL_INSURANCE_TYPE)),
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"admission_id": handle_id(get_best_value_in_keys(settlement_list_ie_result, ADMISSION_ID)),
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"settlement_id": handle_id(get_best_value_in_keys(settlement_list_ie_result, SETTLEMENT_ID)),
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}
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settlement_data["admission_date"] = handle_date(settlement_data["admission_date_str"])
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settlement_data["admission_date"] = handle_date(settlement_data["admission_date_str"])
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settlement_data["discharge_date"] = handle_date(settlement_data["discharge_date_str"])
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settlement_data["personal_cash_payment"] = handle_decimal(settlement_data["personal_cash_payment_str"])
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settlement_data["personal_account_payment"] = handle_decimal(settlement_data["personal_account_payment_str"])
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settlement_data["personal_funded_amount"] = handle_decimal(settlement_data["personal_funded_amount_str"])
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settlement_data["medical_insurance_type"] = handle_insurance_type(settlement_data["medical_insurance_type_str"])
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parse_money_result = parse_money(get_best_value_in_keys(settlement_list_ie_result, UPPERCASE_MEDICAL_EXPENSES),
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get_best_value_in_keys(settlement_list_ie_result, MEDICAL_EXPENSES))
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settlement_data["medical_expenses_str"] = handle_original_data(parse_money_result[0])
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settlement_data["medical_expenses"] = parse_money_result[1]
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save_or_update_ie(ZxIeSettlement, pk_phhd, settlement_data)
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def discharge_task(pk_phhd, discharge_record, identity):
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discharge_record_ie_result = information_extraction(DISCHARGE_IE, discharge_record, identity)
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hospitals = get_values_of_keys(discharge_record_ie_result, HOSPITAL)
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departments = get_values_of_keys(discharge_record_ie_result, DEPARTMENT)
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discharge_data = {
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"pk_phhd": pk_phhd,
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"hospital": handle_hospital(",".join(hospitals)),
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"department": handle_department(",".join(departments)),
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"name": handle_name(get_best_value_in_keys(discharge_record_ie_result, PATIENT_NAME)),
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"admission_date_str": handle_original_data(get_best_value_in_keys(discharge_record_ie_result, ADMISSION_DATE)),
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"discharge_date_str": handle_original_data(get_best_value_in_keys(discharge_record_ie_result, DISCHARGE_DATE)),
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"doctor": handle_name(get_best_value_in_keys(discharge_record_ie_result, DOCTOR)),
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"admission_id": handle_id(get_best_value_in_keys(discharge_record_ie_result, ADMISSION_ID)),
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"age": handle_age(get_best_value_in_keys(discharge_record_ie_result, AGE)),
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}
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discharge_data["admission_date"] = handle_date(discharge_data["admission_date_str"])
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discharge_data["discharge_date"] = handle_date(discharge_data["discharge_date_str"])
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if hospitals:
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match_hospitals = []
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for hospital in hospitals:
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parsed_hospitals = parse_hospital(hospital)
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for parsed_hospital in parsed_hospitals:
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search_result = search_hospital(parsed_hospital)
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match_hospitals.append(search_result)
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if search_result and search_result[1] == 100:
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break
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for hospital_alias_key in HOSPITAL_ALIAS.keys():
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if hospital_alias_key in parsed_hospital:
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for hospital_alias in HOSPITAL_ALIAS[hospital_alias_key]:
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new_hospital = parsed_hospital.replace(hospital_alias_key, hospital_alias)
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match_hospitals.append(search_hospital(new_hospital))
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break
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best_match = None
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best_score = 0
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for match_hospital in match_hospitals:
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if match_hospital and match_hospital[1] > best_score:
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best_match = match_hospital
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best_score = match_hospital[1]
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if best_score == 100:
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break
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if best_match:
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discharge_data["pk_yljg"] = best_match[2]
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if departments:
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match_departments = []
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for department in departments:
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parsed_departments = parse_department(department)
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for parsed_department in parsed_departments:
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search_result = search_department(parsed_department)
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match_departments.append(search_result)
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if search_result and search_result[1] == 100:
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break
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for department_alias_key in DEPARTMENT_ALIAS.keys():
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if department_alias_key in parsed_department:
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for department_alias in DEPARTMENT_ALIAS[department_alias_key]:
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new_department = parsed_department.replace(department_alias_key, department_alias)
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match_departments.append(search_department(new_department))
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break
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best_match = None
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best_score = -1000
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for match_department in match_departments:
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if match_department and match_department[1] > best_score:
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best_match = match_department
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best_score = match_department[1]
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if best_score == 100:
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break
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if best_match:
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discharge_data["pk_ylks"] = best_match[2]
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save_or_update_ie(ZxIeDischarge, pk_phhd, discharge_data)
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def cost_task(pk_phhd, cost_list, identity):
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cost_list_ie_result = information_extraction(COST_IE, cost_list, identity)
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cost_data = {
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"pk_phhd": pk_phhd,
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"name": handle_name(get_best_value_in_keys(cost_list_ie_result, PATIENT_NAME)),
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"admission_date_str": handle_original_data(get_best_value_in_keys(cost_list_ie_result, ADMISSION_DATE)),
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"discharge_date_str": handle_original_data(get_best_value_in_keys(cost_list_ie_result, DISCHARGE_DATE)),
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"medical_expenses_str": handle_original_data(get_best_value_in_keys(cost_list_ie_result, MEDICAL_EXPENSES))
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}
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cost_data["admission_date"] = handle_date(cost_data["admission_date_str"])
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cost_data["discharge_date"] = handle_date(cost_data["discharge_date_str"])
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cost_data["medical_expenses"] = handle_decimal(cost_data["medical_expenses_str"])
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save_or_update_ie(ZxIeCost, pk_phhd, cost_data)
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def photo_review(pk_phhd):
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settlement_list = []
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discharge_record = []
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cost_list = []
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session = MysqlSession()
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phrecs = session.query(ZxPhrec.pk_phrec, ZxPhrec.pk_phhd, ZxPhrec.cRectype, ZxPhrec.cfjaddress).filter(
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ZxPhrec.pk_phhd == pk_phhd
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).all()
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session.close()
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for phrec in phrecs:
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if phrec.cRectype == "1":
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settlement_list.append(phrec)
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elif phrec.cRectype == "3":
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discharge_record.append(phrec)
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elif phrec.cRectype == "4":
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cost_list.append(phrec)
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# 同一批图的标识
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identity = int(time.time())
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settlement_task(pk_phhd, settlement_list, identity)
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discharge_task(pk_phhd, discharge_record, identity)
|
||
cost_task(pk_phhd, cost_list, identity)
|
||
|
||
|
||
def main():
|
||
while 1:
|
||
session = MysqlSession()
|
||
phhds = (session.query(ZxPhhd.pk_phhd)
|
||
.join(ZxPhrec, ZxPhhd.pk_phhd == ZxPhrec.pk_phhd, isouter=True)
|
||
.filter(ZxPhhd.exsuccess_flag == "1")
|
||
.filter(ZxPhrec.pk_phrec.isnot(None))
|
||
.distinct().limit(PHHD_BATCH_SIZE).all())
|
||
# 将状态改为正在识别中
|
||
pk_phhd_values = [phhd.pk_phhd for phhd in phhds]
|
||
update_flag = (update(ZxPhhd).where(ZxPhhd.pk_phhd.in_(pk_phhd_values)).values(exsuccess_flag="2"))
|
||
session.execute(update_flag)
|
||
session.commit()
|
||
session.close()
|
||
if phhds:
|
||
for phhd in phhds:
|
||
pk_phhd = phhd.pk_phhd
|
||
logging.info(f"开始识别：{pk_phhd}")
|
||
start_time = time.time()
|
||
photo_review(pk_phhd)
|
||
|
||
# 识别完成更新标识
|
||
session = MysqlSession()
|
||
update_flag = (update(ZxPhhd).where(ZxPhhd.pk_phhd == pk_phhd).values(
|
||
exsuccess_flag="8",
|
||
ref_id1=HOSTNAME,
|
||
checktime=util.get_default_datetime(),
|
||
fFSYLFY=time.time() - start_time))
|
||
session.execute(update_flag)
|
||
session.commit()
|
||
session.close()
|
||
else:
|
||
# 没有查询到新案子，等待一段时间后再查
|
||
logging.info(f"暂未查询到需要识别的案子，等待{SLEEP_MINUTES}分钟...")
|
||
sleep(SLEEP_MINUTES * 60)
|