435 lines
12 KiB
Plaintext
435 lines
12 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "ae533fe9-e20e-4e44-b9bb-030c4fa4e714",
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"metadata": {},
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"source": [
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"## 体测人员导入"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"id": "1144aaac-92a0-4bcf-aba7-096f7dd3ad3b",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2022-11-03T11:59:47.933493Z",
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"iopub.status.busy": "2022-11-03T11:59:47.932972Z",
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"iopub.status.idle": "2022-11-03T11:59:49.278241Z",
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"shell.execute_reply": "2022-11-03T11:59:49.276741Z",
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"shell.execute_reply.started": "2022-11-03T11:59:47.933444Z"
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},
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"ok\n"
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]
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}
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],
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"source": [
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"import openpyxl\n",
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"import json\n",
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"\n",
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"\n",
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"wb = openpyxl.load_workbook('data/天津石化员工检测花名册 （20221014）.xlsx')\n",
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"sheet = wb.active\n",
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"# sheets = wb.sheetnames\n",
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"person = {}\n",
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"\n",
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"for n in range(2, sheet.max_row+1):\n",
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" code = int(sheet.cell(n, 6).value)\n",
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" person.setdefault(code, {})\n",
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" dict1 = {}\n",
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" dict1['name'] = sheet.cell(n, 3).value\n",
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" dict1['sex'] = sheet.cell(n, 4).value\n",
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" dict1['unit'] = sheet.cell(n, 1).value\n",
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" dict1['sub_unit'] = sheet.cell(n, 2).value\n",
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" if sheet.cell(n,5).value is not None:\n",
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" dict1['id_num'] = sheet.cell(n,5).value\n",
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" person[code] = dict1\n",
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"filename = 'data/天津石化人员名单.json'\n",
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"with open(filename, 'w') as fl:\n",
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" json.dump(person, fl, ensure_ascii=False)\n",
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"print('ok')"
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]
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},
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{
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"cell_type": "markdown",
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"id": "5e648b69-40bf-4494-9079-e4e2b6ab8866",
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"metadata": {},
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"source": [
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"## 获取人员测试成绩"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"id": "a57ebb22-543c-4804-8d44-89984058ec1d",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2022-11-03T12:04:25.033604Z",
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"iopub.status.busy": "2022-11-03T12:04:25.033082Z",
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"iopub.status.idle": "2022-11-03T12:04:25.402569Z",
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"shell.execute_reply": "2022-11-03T12:04:25.401118Z",
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"shell.execute_reply.started": "2022-11-03T12:04:25.033556Z"
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},
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"ok\n"
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]
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}
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],
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"source": [
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"import json\n",
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"import time\n",
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"import csv\n",
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"\n",
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"filename = '../item.json'\n",
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"item = {}\n",
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"unit = {}\n",
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"with open(filename,'r') as fl:\n",
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" dict1 = json.load(fl) \n",
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"for k,v in dict1.items():\n",
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" item[k] = v\n",
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"#SQL语句为：\n",
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"# SELECT a.item_id,a.performance,a.score,a.date AS DATE1,a.avatar_id,b.unit,b.name FROM places_result AS a,_zgshhgxs AS b WHERE a.place_id=135 AND a.avatar_id=b.id AND a.avatar_id < 4999\n",
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"\n",
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"re_ta = {}\n",
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"dict1 = {}\n",
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"list1 = []\n",
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"#print(\"\\n运动项目信息：\")\n",
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"filename = 'data/134_2210.csv'\n",
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"with open(filename,'r',newline='') as csv_file:\n",
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" fl = csv.reader(csv_file,delimiter=',')\n",
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" header = next(fl) \n",
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" for line in fl:\n",
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" #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n",
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" list1.append(line)\n",
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"#print(list1)\n",
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"for result in list1:\n",
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" user = str(result[4])\n",
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" m_item = str(result[0]) \n",
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" re_ta.setdefault(user,{}) \n",
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" re_ta[user]['name'] = str(result[6])\n",
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" re_ta[user]['unit'] = str(result[5]) \n",
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" item_name = item[m_item]['name']\n",
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" re_ta[user].setdefault(item_name,{}) \n",
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" score = int(result[1])/item[m_item]['divisor'] \n",
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" re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n",
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" re_ta[user][item_name]['得分'] =result[2]\n",
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"filename = 'data/result_天津.json'\n",
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"with open(filename,'w') as fl:\n",
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" json.dump(re_ta, fl) \n",
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"print('ok')"
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]
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},
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{
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"cell_type": "markdown",
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"id": "55d961e5-a512-44b2-808e-7c55d7000d52",
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"metadata": {},
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"source": [
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"## 导出测试成绩"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"id": "38397ad4-2bb3-4b5e-8ece-9ea11e801890",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2022-11-03T12:04:34.987311Z",
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"iopub.status.busy": "2022-11-03T12:04:34.986720Z",
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"iopub.status.idle": "2022-11-03T12:04:36.000903Z",
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"shell.execute_reply": "2022-11-03T12:04:35.999784Z",
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"shell.execute_reply.started": "2022-11-03T12:04:34.987262Z"
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},
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"tags": []
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},
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"outputs": [],
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"source": [
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"import json\n",
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"import openpyxl\n",
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"\n",
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"items = ['身高','体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
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"title = ['编号','姓名','性别','单位/部门','车间/科室','身高','体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
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"filename = 'data/result_天津.json'\n",
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"with open(filename,'r') as fl:\n",
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" dict1 = json.load(fl)\n",
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"\n",
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"filename = 'data/天津石化人员名单.json'\n",
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"with open(filename,'r') as fl:\n",
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" dict2 = json.load(fl)\n",
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" \n",
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"list1 = []\n",
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"for k, v in dict1.items():\n",
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" list2 = []\n",
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" list2.append(str(k).rjust(8,'0'))\n",
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" list2.append(v['name']) \n",
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" list2.append(dict2[k]['sex'])\n",
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" list2.append(dict2[k]['unit'])\n",
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" list2.append(dict2[k]['sub_unit'])\n",
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" \n",
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" for item in items:\n",
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" if item in v.keys():\n",
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" list2.append(v[item]['成绩'])\n",
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" \n",
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" elif item =='name':\n",
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" list2.append(v[item])\n",
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" else:\n",
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" list2.append('') \n",
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" \n",
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" list1.append(list2)\n",
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"filename = 'data/天津石化体测情况表（截至20221103）.xlsx'\n",
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"wb = openpyxl.Workbook()\n",
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"sheet = wb.active\n",
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"sheet.append(title)\n",
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"for row in list1:\n",
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" sheet.append(row)\n",
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" \n",
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"wb.save(filename)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "1c7b219f-43cd-4bf0-971f-2c398f8db8ed",
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"metadata": {},
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"source": [
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"## 按照日期进行报告分类"
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]
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},
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{
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"cell_type": "markdown",
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"id": "3d57ff66-69c3-4c13-811b-f1e13b404077",
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"metadata": {},
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"source": [
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"### 按照体测明细分类"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "29c0f15b-1345-4b46-ac1d-b45ddede9641",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"import json\n",
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"import time\n",
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"import csv\n",
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"import os,sys,shutil\n",
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"import glob\n",
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"\n",
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"dict1 = {}\n",
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"list1 = []\n",
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"filename = 'data/134_2210.csv'\n",
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"with open(filename,'r',newline='') as csv_file:\n",
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" fl = csv.reader(csv_file,delimiter=',')\n",
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" header = next(fl) \n",
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" for line in fl:\n",
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" #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n",
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" list1.append(line)\n",
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"for result in list1:\n",
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" user = str(result[4])\n",
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" dict1.setdefault(user,'2022-10-01')\n",
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" m_date = result[7]\n",
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" if m_date> dict1[user]:\n",
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" dict1[user] = m_date\n",
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"rq = set() \n",
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"for k, v in dict1.items():\n",
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" rq.add(str(v).split(' ')[0].replace('-', '', 2))\n",
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"# 创建目录\n",
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"m_path = 'file/134'\n",
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"for pn in rq:\n",
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" if not os.path.exists(m_path + '/' + pn):\n",
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" os.mkdir(m_path + '/' + pn)\n",
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"fls = glob.glob(f'file/*.pdf')\n",
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"for fn in fls:\n",
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" #old = os.path.basename(fn).split('.')[0].rjust(8,'0') \n",
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" old = os.path.basename(fn).split('.')[0]\n",
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" mrq = str(dict1[old]).split(' ')[0].replace('-', '', 2)\n",
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" n_name = f'{m_path}/{mrq}/{str(old).rjust(8,\"0\")}_{mrq}.pdf'\n",
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" if not os.path.exists(n_name):\n",
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" shutil.copyfile(fn,n_name)\n",
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"print('ok!')"
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]
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},
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{
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"cell_type": "markdown",
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"id": "ae2b17bd-38b9-4809-affb-01441a5581eb",
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"metadata": {},
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"source": [
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"### 按照报告生成日期分类"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "eb24c1be-b5d3-4e61-a432-854a887746d4",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"import json\n",
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"import time\n",
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"import csv\n",
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"import os,sys,shutil\n",
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"import glob\n",
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"\n",
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"dict1 = {}\n",
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"list1 = []\n",
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"\n",
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"m_path = 'file/134'\n",
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"mrq = '20221028'\n",
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"if not os.path.exists(m_path + '/' + mrq):\n",
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" os.mkdir(m_path + '/' + mrq)\n",
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"fls = glob.glob(f'file/new/*.pdf')\n",
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"for fn in fls:\n",
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" #old = os.path.basename(fn).split('.')[0].rjust(8,'0') \n",
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" old = os.path.basename(fn).split('.')[0] \n",
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" n_name = f'{m_path}/{mrq}/{str(old).rjust(8,\"0\")}_{mrq}.pdf'\n",
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" if not os.path.exists(n_name):\n",
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" shutil.copyfile(fn,n_name)\n",
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"print('ok!')"
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]
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},
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{
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"cell_type": "markdown",
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"id": "838ec7d3-137c-4ccd-9f16-7b6312d1ffa6",
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"metadata": {},
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"source": [
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"### PDF文件压缩"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "a6ab0943-b018-4dd6-9176-85a762f9f60c",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"import fitz\n",
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"from pdf2image import convert_from_path, convert_from_bytes\n",
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"import os,sys\n",
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"import tempfile\n",
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"from pdf2image.exceptions import (\n",
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" PDFInfoNotInstalledError,\n",
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" PDFPageCountError,\n",
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" PDFSyntaxError\n",
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")\n",
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"import img2pdf \n",
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"import glob\n",
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"import shutil\n",
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"\n",
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"def covert2pic(old_fn):\n",
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" if os.path.exists('.pdf'): # 临时文件，需为空\n",
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" shutil.rmtree('.pdf')\n",
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" os.mkdir('.pdf')\n",
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" with tempfile.TemporaryDirectory() as path:\n",
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" images_from_path = convert_from_path(old_fn, dpi=100,fmt='jpg', output_folder='.pdf')\n",
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"\n",
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"def pic2pdf(new_fn):\n",
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" fl1=glob.glob('.pdf/*.jpg')\n",
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" fl1.sort()\n",
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" a4inpt = (img2pdf.mm_to_pt(210),img2pdf.mm_to_pt(297))\n",
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" layout_fun = img2pdf.get_layout_fun(a4inpt)\n",
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" with open(new_fn,\"wb\") as f:\n",
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" f.write(img2pdf.convert(fl1,layout_fun=layout_fun))\n",
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" print(f'{new_fn}转换成功！')\n",
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" \n",
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"\n",
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"\n",
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"def pdfz(sor, obj, zoom): \n",
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" covert2pic(zoom)\n",
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" pic2pdf(obj)\n",
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" \n",
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"fi_path = 'file/134/20221028/'\n",
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"fl = glob.glob(f'{fi_path}*.pdf')\n",
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"\n",
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"for fn in fl:\n",
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" new_fn = fi_path+'new/'+os.path.basename(fn)\n",
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" covert2pic(fn)\n",
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" pic2pdf(new_fn)\n",
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" shutil.rmtree('.pdf')\n",
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"\n",
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"\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "72c693e1-dd7c-40fa-8948-4fd6fbea8ddc",
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"metadata": {},
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"source": [
|
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"### 区分新文件"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "9d06d4f0-364b-438c-844b-7d5badaf3496",
|
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"metadata": {
|
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"tags": []
|
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},
|
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"outputs": [],
|
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"source": [
|
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"import os,sys,shutil\n",
|
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"import glob\n",
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"import time\n",
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"\n",
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"fi_path = 'file/'\n",
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"fls = glob.glob(f'{fi_path}*.pdf')\n",
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"m_date = time.strptime('2022-10-28','%Y-%m-%d')\n",
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"for fn in fls:\n",
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" c_time = time.gmtime(os.path.getctime(fn))\n",
|
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" if c_time > m_date:\n",
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" n_name = f'{fi_path}new/{os.path.basename(fn)}'\n",
|
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" if not os.path.exists(n_name):\n",
|
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" shutil.copyfile(fn,n_name)\n",
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" print(n_name)\n"
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]
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},
|
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{
|
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"cell_type": "code",
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"execution_count": null,
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"id": "32b61559-4495-4fbe-8eb6-2614e6225b5c",
|
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"metadata": {},
|
||
"outputs": [],
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"source": []
|
||
}
|
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],
|
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"metadata": {
|
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"kernelspec": {
|
||
"display_name": "Python 3",
|
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"language": "python",
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"name": "python3"
|
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},
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"language_info": {
|
||
"codemirror_mode": {
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"name": "ipython",
|
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"version": 3
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},
|
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"file_extension": ".py",
|
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"mimetype": "text/x-python",
|
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"name": "python",
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"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.8.10"
|
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}
|
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},
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"nbformat": 4,
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"nbformat_minor": 5
|
||
}
|