{ "cells": [ { "cell_type": "markdown", "id": "19280f5c-8e34-4a64-8dfb-6353cbf597d2", "metadata": {}, "source": [ "# 体质检测数据处理" ] }, { "cell_type": "markdown", "id": "112d80f4-607b-41f9-bb30-ac2eb8f52ee2", "metadata": {}, "source": [ "## 基础数据管理" ] }, { "cell_type": "markdown", "id": "b7dfd50f-a614-497d-8f0a-fa1e4c89168a", "metadata": {}, "source": [ "### 体测项目标准导入" ] }, { "cell_type": "code", "execution_count": null, "id": "8cd73044-56a8-409b-a873-085feb63af17", "metadata": { "tags": [] }, "outputs": [], "source": [ "import openpyxl\n", "import json\n", "\n", "tcbz ={\n", " 'HeightWeigh':'身高体重',\n", " 'StepExperiment':'台阶指数',\n", " 'Lung':'肺活量',\n", " 'Proneness':'坐位体前屈',\n", " 'PowerfullGrip':'握力',\n", " 'OneMinutePushUp':'一分钟仰卧起坐',\n", " 'PushUp':'俯卧撑',\n", " 'VerticalJump':'纵跳',\n", " 'ReactionTime':'选择反应时',\n", " 'FootStand':'单脚站立'\n", "}\n", "wb = openpyxl.load_workbook('data/体质检测标准.xlsx')\n", "sheet = wb.active\n", "# sheets = wb.sheetnames\n", "dict1 = {}\n", "dict3 = {}\n", "for k, v in tcbz.items():\n", " dict3[v] = k\n", "sheet = wb.active\n", "data1 =list(sheet.values)\n", "del data1[0]\n", "for item in data1:\n", " sex = item[0][6:]\n", " if sex =='男':\n", " age_sex = 'M'+item[0][:5]\n", " else:\n", " age_sex = 'F'+item[0][:5]\n", " dict1.setdefault(age_sex,{})\n", " if item[1] in dict3.keys():\n", " xm = dict3[item[1]]\n", " dict1[age_sex].setdefault(xm,[])\n", " dict1[age_sex][xm].append(item[3]/item[4])\n", "dict2 = {}\n", "#print(dict1)\n", "for k, v in dict1.items():\n", " i1 = int(k[1:3])\n", " i2 = int(k[-2:])\n", " m_sex = k[:1]\n", " for i in range(i1,i2+1):\n", " dict2[m_sex+str(i)] = k\n", "dict3 = {}\n", "dict3['person'] = dict2\n", "dict3['criteria'] = dict1\n", "filename = 'data/体质检测标准.json'\n", "with open(filename, 'w') as fl:\n", " json.dump(dict3, fl, ensure_ascii=False)\n", "print('ok')" ] }, { "cell_type": "markdown", "id": "c36641d8-c54b-43d2-ad9d-ff4cb72deba9", "metadata": {}, "source": [ "### 身高标准导入" ] }, { "cell_type": "code", "execution_count": null, "id": "2ca52d7b-d77e-452f-98f6-95072a5a1934", "metadata": { "tags": [] }, "outputs": [], "source": [ "import openpyxl\n", "import json\n", "\n", "tcbz ={\n", " 'HeightWeigh':'身高体重',\n", " 'StepExperiment':'台阶指数',\n", " 'Lung':'肺活量',\n", " 'Proneness':'坐位体前屈',\n", " 'PowerfullGrip':'握力',\n", " 'OneMinutePushUp':'一分钟仰卧起坐',\n", " 'PushUp':'俯卧撑',\n", " 'VerticalJump':'纵跳',\n", " 'ReactionTime':'选择反应时',\n", " 'FootStand':'单脚站立'\n", "}\n", "wb = openpyxl.load_workbook('data/体质检测标准_BMI.xlsx')\n", "sheet = wb.active\n", "# sheets = wb.sheetnames\n", "dict1 = {}\n", "dict3 = {}\n", "for k, v in tcbz.items():\n", " dict3[v] = k\n", "sheet = wb.active\n", "data1 =list(sheet.values)\n", "del data1[0]\n", "for item in data1:\n", " min_age = int(item[1]/12)\n", " max_age = int((item[2]+1)/12) - 1\n", " sex = item[0]\n", " height = int(item[3])\n", " if sex ==0:\n", " age_sex = 'M'+str(min_age)+'~'+str(max_age)\n", " else:\n", " age_sex = 'F'+str(min_age)+'~'+str(max_age)\n", " dict1.setdefault(age_sex,{})\n", " \n", " dict1[age_sex].setdefault(height,[])\n", " dict1[age_sex][height].append(item[5]/1000)\n", "dict2 = {}\n", "#print(dict1)\n", "for k, v in dict1.items():\n", " i1 = int(k[1:3])\n", " i2 = int(k[-2:])\n", " m_sex = k[:1]\n", " for i in range(i1,i2+1):\n", " dict2[m_sex+str(i)] = k\n", "dict3 = {}\n", "dict3['person'] = dict2\n", "dict3['criteria'] = dict1\n", "filename = 'data/体质检测标准_BMI.json'\n", "with open(filename, 'w') as fl:\n", " json.dump(dict3, fl, ensure_ascii=False)\n", "print('ok')" ] }, { "cell_type": "markdown", "id": "59f5708d-c2d0-4470-b2f4-b9face431865", "metadata": {}, "source": [ "### 计算分数" ] }, { "cell_type": "code", "execution_count": 14, "id": "f32b266a-7e46-4703-ab61-7cbbc81b5ab1", "metadata": { "execution": { "iopub.execute_input": "2023-06-09T03:17:48.044584Z", "iopub.status.busy": "2023-06-09T03:17:48.044175Z", "iopub.status.idle": "2023-06-09T03:17:48.054183Z", "shell.execute_reply": "2023-06-09T03:17:48.053116Z", "shell.execute_reply.started": "2023-06-09T03:17:48.044557Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[41.3, 46.2, 52.3, 58.8, 68.2]\n", "46.2\n", "1\n" ] } ], "source": [ "import json\n", "import time\n", "import csv\n", "\n", "filename = 'data/体质检测标准.json'\n", "item = {}\n", "unit = {}\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "person = dict1['person']\n", "criteria = dict1['criteria']\n", "data = {'name':'张三','sex':'M','age':37,'item':'StepExperiment','result':46}\n", "info = data['sex']+str(data['age'])\n", "bz = person[info]\n", "mx = criteria[bz][data['item']]\n", "result = data['result']\n", "score = -1\n", "print(mx)\n", "for bz1 in mx:\n", " if result < bz1:\n", " print(bz1)\n", " score = mx.index(bz1,0)\n", " break\n", " else:\n", " score = 5\n", "#if score == -1:\n", " # score = 5\n", "print(score)" ] }, { "cell_type": "markdown", "id": "755f8b66-c71c-4138-bd12-dff24e85e36a", "metadata": {}, "source": [ "### 计算BMI分数" ] }, { "cell_type": "code", "execution_count": 6, "id": "b32fbbdd-eb0a-4f0d-8901-e39a727c3ff8", "metadata": { "execution": { "iopub.execute_input": "2023-06-09T03:07:07.558861Z", "iopub.status.busy": "2023-06-09T03:07:07.557966Z", "iopub.status.idle": "2023-06-09T03:07:07.572751Z", "shell.execute_reply": "2023-06-09T03:07:07.571714Z", "shell.execute_reply.started": "2023-06-09T03:07:07.558820Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "M30~39\n", "177.7,97.0\n", "1\n" ] } ], "source": [ "import json\n", "import time\n", "import csv\n", "\n", "filename = 'data/体质检测标准_BMI.json'\n", "item = {}\n", "unit = {}\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "person = dict1['person']\n", "criteria = dict1['criteria']\n", "data = {'name':'张三','sex':'M','age':37,'item':'HeightWeight','result':'177.7,97.0'}\n", "info = data['sex']+str(data['age'])\n", "\n", "bz = person[info]\n", "print(bz)\n", "result = data['result']\n", "print(result)\n", "height = int(float(result.split(',')[0]))\n", "weight = float(result.split(',')[1])\n", "mx = criteria[bz][str(height)]\n", "if weight < mx[0]:\n", " score = 1\n", "elif weight < mx[1]:\n", " score = 3\n", "elif weight < mx[2]:\n", " score = 5 \n", "elif weight <= mx[3]:\n", " score = 3 \n", "elif weight > mx[3]:\n", " score = 1\n", "print(score)" ] }, { "cell_type": "markdown", "id": "732161bb-98f2-4861-ab66-7a374678bcd8", "metadata": {}, "source": [ "# 体质检测数据管理" ] }, { "cell_type": "markdown", "id": "bb2db5e8-5dc6-4366-a39c-a3600ee5007c", "metadata": {}, "source": [ "## 数据导入Mycrm" ] }, { "cell_type": "markdown", "id": "bc98d772-5841-41a3-ad8f-f7d1ff3b5fde", "metadata": {}, "source": [ "### 导入系统人员信息" ] }, { "cell_type": "code", "execution_count": null, "id": "2cd93f45-6613-4a3f-97e4-5236068e1860", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import time\n", "import csv\n", "\n", "list1 = []\n", "filename = 'data/person_134.csv'\n", "with open(filename,'r',newline='') as csv_file:\n", " fl = csv.reader(csv_file,delimiter=',')\n", " header = next(fl) \n", " for line in fl:\n", " #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n", " list1.append(line)\n", "#print(list1)\n", "dict1 = {}\n", "for result in list1:\n", " code = str(result[4])\n", " if int(result[1]) == 0:\n", " sex = '男'\n", " else:\n", " sex = '女'\n", " \n", " m_item = str(result[3]) \n", " dict1.setdefault(code,{}) \n", " dict1[code]['name'] = result[0]\n", " dict1[code]['sex'] = sex\n", " dict1[code]['birth'] = result[2]\n", "filename = 'data/天津石化人员清单.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl, ensure_ascii=False) \n", "print(len(dict1)) " ] }, { "cell_type": "markdown", "id": "2eb50f19-c15f-4a36-87b7-cd02551d248d", "metadata": {}, "source": [ "### 导入测试项目item" ] }, { "cell_type": "code", "execution_count": null, "id": "0eb37435-9c15-40ef-bd4c-2dffc026f59e", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import psycopg2\n", "from psycopg2 import extras as ex\n", "\n", "filename = '../item.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "data_list = []\n", "for k, v in dict1.items():\n", " data_list.append((int(k),v['name'])) \n", "conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n", "cursor = conn.cursor()\n", "sql = 'insert into shijiazhuang_item (id,name) values %s'\n", "ex.execute_values(cursor, sql, data_list, page_size=10000)\n", "#conn.commit()\n", "cursor.close()\n", "conn.close()\n", "print('ok!')" ] }, { "cell_type": "markdown", "id": "2ba97298-1e7e-4192-8d69-ea59f98e071a", "metadata": {}, "source": [ "### 导入一级部门" ] }, { "cell_type": "code", "execution_count": null, "id": "9f7ed380-95f3-47d4-9eb5-74937af7811f", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import psycopg2\n", "from psycopg2 import extras as ex\n", "\n", "conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n", "cursor = conn.cursor()\n", "filename = 'data/result_石家庄.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "unit = set()\n", "for k, v in dict1.items():\n", " #if 'sub_unit' not in v.keys():\n", " # print(k,v['name'])\n", " unit.add(v['unit'])\n", "print(unit) \n", "i = 1\n", "dict2 = {}\n", "for item in unit:\n", " dict2[item] = i\n", " i+=1\n", "data_list = []\n", "for k, v in dict2.items():\n", " data_list.append((v,k)) \n", " \n", "sql = 'insert into shijiazhuang_unit (id,name) values %s'\n", "ex.execute_values(cursor, sql, data_list, page_size=10000)\n", "#conn.commit()\n", "cursor.close()\n", "conn.close()\n", "print('ok!')" ] }, { "cell_type": "markdown", "id": "b8a1fa7f-08ff-49bb-8052-9f86b1f2ac18", "metadata": {}, "source": [ "### 导入二级部门" ] }, { "cell_type": "code", "execution_count": null, "id": "a13e81f2-467f-42c7-bb46-b547ef7bdd6c", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import psycopg2\n", "from psycopg2 import extras as ex\n", "\n", "conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n", "cursor = conn.cursor()\n", "filename = 'data/天津石化人员名单.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "unit = set()\n", "for k, v in dict1.items():\n", " #if 'sub_unit' not in v.keys():\n", " # print(k,v['name'])\n", " unit.add(v['unit'])\n", "print(unit) \n", "i = 1\n", "dict2 = {}\n", "for item in unit:\n", " dict2[item] = i\n", " i+=1\n", "data_list = []\n", "dict3 = {}\n", "for k, v in dict1.items():\n", " dict3.setdefault(v['unit'],set())\n", " dict3[v['unit']].add(v['sub_unit'])\n", "i = 1 \n", "for k, v in dict3.items():\n", " unit_id = dict2[k]\n", " for item in v:\n", " data_list.append((i,item,unit_id))\n", " i+=1\n", "sql = 'insert into tianjin_sub_unit (id,name,unit_id) values %s'\n", "ex.execute_values(cursor, sql, data_list, page_size=10000)\n", "#conn.commit()\n", "cursor.close()\n", "conn.close()\n", "print('ok!')" ] }, { "cell_type": "markdown", "id": "12917000-59e0-4f8a-beee-929c6d7b60a0", "metadata": {}, "source": [ "### 生成部门JSON文件" ] }, { "cell_type": "code", "execution_count": null, "id": "5446269c-d324-4a16-b10e-f24d87178d77", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import csv\n", "\n", "dict1 = {}\n", "filename = 'data/shijiazhuang_unit_20230517.csv'\n", "with open(filename,'r',newline='') as csv_file:\n", " fl = csv.reader(csv_file,delimiter=',')\n", " header = next(fl)\n", " list1 = []\n", " for line in fl:\n", " #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n", " list1.append({'id':int(line[0]),'name':line[1]})\n", "dict1['unit'] = list1\n", "\n", "filename = 'data/sub_unit_134.csv'\n", "with open(filename,'r',newline='') as csv_file:\n", " fl = csv.reader(csv_file,delimiter=',')\n", " header = next(fl)\n", " list1 = []\n", " for line in fl:\n", " #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n", " list1.append({'id':int(line[0]),'name':line[1],'unit_id':int(line[2])})\n", "dict1['sub_unit'] = list1\n", "print(dict1)\n", "\n", "filename = 'data/天津石化部门.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl, ensure_ascii=False) \n", "print(len(dict1)) " ] }, { "cell_type": "code", "execution_count": null, "id": "5e57329d-a0ef-47b2-9866-fe2a911ff01d", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import csv\n", "\n", "dict1 = {}\n", "filename = 'data/shijiazhuang_unit_20230517.csv'\n", "with open(filename,'r',newline='') as csv_file:\n", " fl = csv.reader(csv_file,delimiter=',')\n", " header = next(fl)\n", " list1 = []\n", " for line in fl:\n", " #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n", " list1.append({'id':int(line[0]),'name':line[1]})\n", " dict1[int(line[0])] = line[1]\n", "\n", "\n", "filename = 'data/石家庄石化部门.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl, ensure_ascii=False) \n", "print(len(dict1)) " ] }, { "cell_type": "markdown", "id": "53bf98fe-0ae9-402f-b8d8-495e8f31df3d", "metadata": {}, "source": [ "### 导入人员信息" ] }, { "cell_type": "code", "execution_count": null, "id": "6af82fd2-b1d6-44b7-8b13-58883b58f8b0", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import psycopg2\n", "from psycopg2 import extras as ex\n", "\n", "conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n", "cursor = conn.cursor()\n", "filename = 'data/天津石化人员清单.json'\n", "with open(filename,'r') as fl:\n", " person = json.load(fl)\n", " \n", "filename = 'data/石家庄石化部门.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "i = 1\n", "dict2 = {}\n", "for item in unit:\n", " dict2[item] = i\n", " i+=1\n", "data_list = []\n", "dict3 = {}\n", "dict4 = {}\n", "for k, v in dict1.items():\n", " dict3.setdefault(v['unit'],set())\n", " dict3[v['unit']].add(v['sub_unit']) \n", "i = 1 \n", "for k, v in dict3.items():\n", " unit_id = dict2[k]\n", " for item in v:\n", " data_list.append((i,item,unit_id))\n", " i+=1\n", "for item in data_list:\n", " sub_id = item[0]\n", " dict4[sub_id] = {'name':item[1],'unit':item[2]}\n", "dict5 = {}\n", "for k, v in dict1.items():\n", " id_unit = dict2[v['unit']]\n", " sub_name = v['sub_unit']\n", " id_sub = 0\n", " for k1, v1 in dict4.items():\n", " if v1['name'] == sub_name and v1['unit'] == id_unit:\n", " id_sub = int(k1)\n", " if id_sub >0:\n", " dict5[k] = {'unit':id_unit,'sub_unit':id_sub}\n", " else:\n", " print(k,'not fund')\n", "data_list = []\n", "for k, v in dict5.items():\n", " id = int(k)\n", " name = person[k]['name']\n", " sex = person[k]['sex']\n", " birth = person[k]['birth']\n", " phone = ''\n", " note = ''\n", " unit = v['sub_unit']\n", " data_list.append((id,name,sex,birth,unit))\n", "sql = 'insert into tianjin_person (id,name,sex,birth,unit_id) values %s'\n", "ex.execute_values(cursor, sql, data_list, page_size=10000)\n", "#conn.commit()\n", "cursor.close()\n", "conn.close()\n", "print('ok!') \n", " " ] }, { "cell_type": "code", "execution_count": null, "id": "c2007c46-38c8-4a20-9917-b0b8743fe2a9", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import psycopg2\n", "from psycopg2 import extras as ex\n", "\n", "conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n", "cursor = conn.cursor()\n", " \n", "filename = 'data/石家庄石化部门.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "dict3 = {}\n", "for k,v in dict1.items():\n", " dict3[v] = int(k)\n", "filename = 'data/result_石家庄.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl)\n", "data_list = []\n", "for k, v in dict2.items():\n", " id = int(k)\n", " name = dict2[k]['name']\n", " sex = dict2[k]['sex']\n", " birth = dict2[k]['birth'] \n", " unit = dict3[dict2[k]['unit']]\n", " data_list.append((id,name,sex,birth,unit))\n", "sql = 'insert into shijiazhuang_person (id,name,sex,birth,unit_id) values %s'\n", "ex.execute_values(cursor, sql, data_list, page_size=10000)\n", "#conn.commit()\n", "cursor.close()\n", "conn.close()\n", "print('ok!') " ] }, { "cell_type": "markdown", "id": "fd95a45a-c6df-47c3-9941-2d0579b2c5d9", "metadata": {}, "source": [ "### 导入测试成绩及得分" ] }, { "cell_type": "markdown", "id": "c989de3f-a8ab-47dc-9662-544e4b6a0e2f", "metadata": { "tags": [] }, "source": [ "#### 二级部门导入" ] }, { "cell_type": "code", "execution_count": null, "id": "360e61e9-7895-484b-a9d6-333bdefa1a86", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import psycopg2\n", "from psycopg2 import extras as ex\n", "\n", "filename = '../item.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "dict2 = {}\n", "for k, v in dict1.items():\n", " dict2[v['name']] = int(k)\n", "\n", "filename = 'data/天津石化部门.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "unit = {}\n", "for item in dict1['unit']:\n", " unit[item['name']] = item['id']\n", "\n", "sub_unit = {}\n", "for item in dict1['sub_unit']:\n", " sub_unit.setdefault(item['unit_id'],[])\n", " sub_unit[item['unit_id']].append({'id':item['id'],'name':item['name']})\n", " \n", "filename = 'data/天津石化人员名单.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "person = {}\n", "for k, v in dict1.items():\n", " person[k] = {'unit':v['unit'],'sub_unit':v['sub_unit']}\n", "\n", " \n", "conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n", "cursor = conn.cursor()\n", "data_list = []\n", "filename = 'data/result_天津.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "for k, v in dict1.items():\n", " for item in v.keys():\n", " if item in dict2.keys():\n", " item_id = dict2[item]\n", " if v[item]['得分'] == '\\\\N':\n", " score = None\n", " else:\n", " score = int(v[item]['得分'])\n", " unit_name = person[k]['unit'] \n", " sub_unit_name = person[k]['sub_unit']\n", " unit_id = unit[unit_name]\n", " for items in sub_unit[unit_id]:\n", " if items['name'] ==sub_unit_name:\n", " sub_id = items['id'] \n", " data_list.append((v[item]['成绩'],score,int(k),item_id,unit_id,sub_id))\n", " \n", "sql = 'insert into tianjin_records (performance,score,avatar_id_id,item_id_id,unit_id_id,sub_unit_id_id) values %s'\n", "ex.execute_values(cursor, sql, data_list, page_size=10000)\n", "#conn.commit()\n", "cursor.close()\n", "conn.close()\n", "print('ok!') \n", " " ] }, { "cell_type": "markdown", "id": "4aeabbbc-5b51-4dd0-b428-83e2012e63c4", "metadata": {}, "source": [ "#### 一级部门导入" ] }, { "cell_type": "code", "execution_count": null, "id": "cb747368-d3ac-4b29-ae4f-ce207d5fcd43", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import psycopg2\n", "from psycopg2 import extras as ex\n", "\n", "filename = '../item.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "dict2 = {}\n", "for k, v in dict1.items():\n", " dict2[v['name']] = int(k)\n", "\n", "filename = 'data/石家庄石化部门.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "dict3 = {}\n", "for k,v in dict1.items():\n", " dict3[v] = int(k)\n", " \n", "\n", "conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n", "cursor = conn.cursor()\n", "data_list = []\n", "filename = 'data/result_石家庄.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "for k, v in dict1.items():\n", " for item in v.keys():\n", " if item in dict2.keys():\n", " item_id = dict2[item] \n", " if v[item]['得分'] == '':\n", " score = None\n", " else:\n", " score = int(v[item]['得分'])\n", " unit_name = v['unit']\n", " unit_id = dict3[unit_name]\n", " data_list.append((v[item]['成绩'],score,int(k),item_id,unit_id))\n", "sql = 'insert into shijiazhuang_records (performance,score,avatar_id_id,item_id_id,unit_id_id) values %s'\n", "ex.execute_values(cursor, sql, data_list, page_size=10000)\n", "#conn.commit()\n", "cursor.close()\n", "conn.close()\n", "print('ok!')" ] }, { "cell_type": "code", "execution_count": null, "id": "51dc35a5-dc07-40a4-9ea7-375ca7f983c3", "metadata": {}, "outputs": [], "source": [ "import json\n", "import psycopg2\n", "from psycopg2 import extras as ex\n", "\n", "filename = '../item.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "dict2 = {}\n", "for k, v in dict1.items():\n", " dict2[v['name']] = int(k)\n", "\n", "filename = 'data/天津石化部门.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "unit = {}\n", "for item in dict1['unit']:\n", " unit[item['name']] = item['id']\n", "print(unit)" ] }, { "cell_type": "markdown", "id": "bdb81e20-32ec-4e0e-b2ac-13dac2060068", "metadata": { "tags": [] }, "source": [ "# 体质报告在线管理" ] }, { "cell_type": "markdown", "id": "1485fc89-4fc2-437d-a29e-b4a0aab12aa0", "metadata": {}, "source": [ "## 新增体测单位" ] }, { "cell_type": "code", "execution_count": 2, "id": "cf345bf0-f11b-459e-9b69-b2843836f6f3", "metadata": { "execution": { "iopub.execute_input": "2023-05-19T08:30:41.861658Z", "iopub.status.busy": "2023-05-19T08:30:41.860765Z", "iopub.status.idle": "2023-05-19T08:30:42.006745Z", "shell.execute_reply": "2023-05-19T08:30:42.006220Z", "shell.execute_reply.started": "2023-05-19T08:30:41.861616Z" }, "tags": [] }, "outputs": [], "source": [ "import pymongo\n", "\n", "myclient = pymongo.MongoClient('mongodb://localhost:27017/')\n", "mydb = myclient[\"baogao\"]\n", "mycol = mydb[\"place\"]\n", "\n", "mydict = { \"id\": \"714309\",\"name\": \"中国石化石家庄炼化公司\", }\n", " \n", "x = mycol.insert_one(mydict) " ] }, { "cell_type": "markdown", "id": "df2d18e2-d2e4-499e-876a-59d8550a8201", "metadata": {}, "source": [ "## 新增报告信息" ] }, { "cell_type": "code", "execution_count": 3, "id": "1acaf159-637e-4101-9881-f6bb79400136", "metadata": { "execution": { "iopub.execute_input": "2023-05-19T09:08:35.287714Z", "iopub.status.busy": "2023-05-19T09:08:35.286693Z", "iopub.status.idle": "2023-05-19T09:08:35.304177Z", "shell.execute_reply": "2023-05-19T09:08:35.303461Z", "shell.execute_reply.started": "2023-05-19T09:08:35.287667Z" }, "tags": [] }, "outputs": [], "source": [ "import pymongo\n", "\n", "myclient = pymongo.MongoClient('mongodb://localhost:27017/')\n", "mydb = myclient[\"baogao\"]\n", "mycol = mydb[\"pdf\"]\n", "\n", "mydict = { \"place\": \"714309\",\"code\":\"4\",\"name\": \"朱维\", }\n", " \n", "x = mycol.insert_one(mydict) " ] }, { "cell_type": "code", "execution_count": 5, "id": "ad3078ac-ae53-4bb4-95bd-387631092bf1", "metadata": { "execution": { "iopub.execute_input": "2023-05-20T04:06:02.667541Z", "iopub.status.busy": "2023-05-20T04:06:02.667013Z", "iopub.status.idle": "2023-05-20T04:06:02.681377Z", "shell.execute_reply": "2023-05-20T04:06:02.680428Z", "shell.execute_reply.started": "2023-05-20T04:06:02.667502Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'_id': ObjectId('64673c9319e8481e9c0ad1a3'), 'place': '714309', 'code': '4', 'name': '朱维'}\n" ] } ], "source": [ "import pymongo\n", "\n", "myclient = pymongo.MongoClient('mongodb://localhost:27017/')\n", "mydb = myclient[\"baogao\"]\n", "mycol = mydb[\"pdf\"]\n", "\n", "mydict = { \"place\": \"714309\",\"code\":\"4\",\"name\": \"朱维\", }\n", " \n", "x = mycol.find_one(mydict) \n", "print(x)" ] }, { "cell_type": "code", "execution_count": null, "id": "cc0571b6-1da5-4bcc-96ad-5613cd1198e3", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.6" } }, "nbformat": 4, "nbformat_minor": 5 }