This commit is contained in:
512song committed 2023-09-16 17:20:48 +08:00
1 parent 398d997b2e
commit 01614b040a
2 files changed
+99 -281

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+77 -30
View File
@@ -59,12 +59,27 @@
},
{
"cell_type": "code",
"execution_count": null,
"id": "b68302b4-8fc1-4060-a10d-7f059f006f3c",
"execution_count": 23,
"id": "63a87059-0a0d-43d3-8b89-0cad64d95ff3",
"metadata": {
"execution": {
"iopub.execute_input": "2023-09-16T08:19:06.600529Z",
"iopub.status.busy": "2023-09-16T08:19:06.600315Z",
"iopub.status.idle": "2023-09-16T08:19:06.626704Z",
"shell.execute_reply": "2023-09-16T08:19:06.626070Z",
"shell.execute_reply.started": "2023-09-16T08:19:06.600513Z"
},
"tags": []
},
"outputs": [],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ok\n"
]
}
],
"source": [
"import openpyxl\n",
"import os,sys,shutil\n",
@@ -79,12 +94,15 @@
"mydb = myclient[\"baogao\"]\n",
"\n",
"\n",
"wb = openpyxl.load_workbook('data/北京石油分公司报告明细.xlsx')\n",
"place_id = 419309\n",
"place_code = '01'\n",
"dw_name = '北京石油分公司'\n",
"fi_path = 'file/2023-06-15'\n",
"fls = glob.glob(f'{fi_path}/*.pdf')\n",
"filename = 'data/北京农行人员名单all.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"\n",
"place_id = 309118\n",
"place_code = '03'\n",
"dw_name = '中国农业银行股份有限公司北京市分行'\n",
"fi_path = '/home/songyi/python/mycrm/flask/pdf/files'\n",
"fls = glob.glob(f'{fi_path}/{str(place_id)}/*.pdf')\n",
"\n",
"code_list = []\n",
"for i in range(10): # 0~9\n",
@@ -93,49 +111,78 @@
"list1 = []\n",
"i = 0\n",
"while i < len(fls):\n",
" code = random.sample(code_list,6) #随机取6位数\n",
" code = random.sample(code_list,5) #随机取6位数\n",
" code_num = ''.join(code) \n",
" if code_num not in list1:\n",
" list1.append(place_code+code_num)\n",
" i +=1\n",
"print(len(list1))\n",
"sheet = wb.active\n",
"# sheets = wb.sheetnames\n",
"list2 = []\n",
"i = 0\n",
"list2= []\n",
"for fn in fls:\n",
" dict2 = {}\n",
"for n in range(2, sheet.max_row+1):\n",
" if sheet.cell(n,1).value is not None:\n",
" dict1 = {}\n",
" phone = str(sheet.cell(n, 3).value)\n",
" code = int(sheet.cell(n, 1).value)\n",
" yzm = list1[i]\n",
" fi_name =Path(fn).stem.split('-')[0]\n",
" code = int(fi_name)\n",
" dxm = list1[i]\n",
" dict2 = {'place_id':place_id,'code':dxm,'fn':Path(fn).name}\n",
" list2.append(dict2)\n",
" i +=1\n",
" dict1 = {'place_id':place_id,'code':yzm,'fn':str(code)+'.pdf'}\n",
" list2.append(dict1)\n",
" dict2[code]={'phone':phone,'code':yzm}\n",
"mycol = mydb[\"pdf\"]\n",
"x = mycol.insert_many(list2)\n",
"filename = 'data/01.json'\n",
"with open(filename, 'w') as fl:\n",
" json.dump(dict2, fl, ensure_ascii=False)\n",
"print('ok') \n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "63a87059-0a0d-43d3-8b89-0cad64d95ff3",
"id": "767cdc9b-310e-4922-8b7d-3581a328cf45",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 34,
"id": "5f665c0f-8d30-4759-b7f8-fb7e13b98efa",
"metadata": {
"execution": {
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},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{375: {'phone': '15910307259', 'code': '0379208'}, 73: {'phone': '18611301540', 'code': '0302967'}, 145: {'phone': '13701207035', 'code': '0364802'}, 355: {'phone': '13901053648', 'code': '0378150'}, 2: {'phone': '13681550603', 'code': '0374538'}, 632: {'phone': '13811150911', 'code': '0379240'}, 491: {'phone': '19883837917', 'code': '0371356'}, 608: {'phone': '1531155192', 'code': '0360195'}, 458: {'phone': '15201200818', 'code': '0362015'}, 403: {'phone': '13811308649', 'code': '0306485'}, 346: {'phone': '18811088287', 'code': '0346502'}, 70: {'phone': '13521913639', 'code': '0331789'}, 610: {'phone': '15010171499', 'code': '0380976'}, 159: {'phone': '13810905776', 'code': '0313498'}, 393: {'phone': '13311165101', 'code': '0350972'}, 341: {'phone': '13718561781', 'code': '0338904'}, 48: {'phone': '18811520206', 'code': '0360952'}, 472: {'phone': '15011393285', 'code': '0396812'}, 482: {'phone': '18232050833', 'code': '0302847'}, 149: {'phone': '13701387037', 'code': '0398520'}, 398: {'phone': '13811310093', 'code': '0358149'}, 371: {'phone': '18600196043', 'code': '0351097'}, 509: {'phone': '18800102596', 'code': '0316705'}, 80: {'phone': '18611785822', 'code': '0312590'}, 152: {'phone': '18611729348', 'code': '0340358'}, 33: {'phone': '13522494577', 'code': '0385063'}, 430: {'phone': '13810964375', 'code': '0375681'}, 417: {'phone': '13611195117', 'code': '0359764'}, 35: {'phone': '13661000573', 'code': '0324057'}, 554: {'phone': '13401005611', 'code': '0337502'}, 275: {'phone': '15801378850', 'code': '0398567'}, 109: {'phone': '18031929396', 'code': '0330478'}, 631: {'phone': '18612263001', 'code': '0369850'}, 568: {'phone': '15210147173', 'code': '0370913'}, 280: {'phone': '13810571305', 'code': '0376841'}, 423: {'phone': '13661337053', 'code': '0392671'}, 538: {'phone': '15711335018', 'code': '0350436'}, 419: {'phone': '13520702450', 'code': '0346218'}, 53: {'phone': '13810347086', 'code': '0317908'}, 288: {'phone': '15901266232', 'code': '0320471'}, 284: {'phone': '13601318622', 'code': '0317402'}, 368: {'phone': '15810525561', 'code': '0312580'}, 223: {'phone': '13717637763', 'code': '0350173'}, 392: {'phone': '13611327008', 'code': '0315783'}, 362: {'phone': '13718160787', 'code': '0326840'}, 68: {'phone': '15811121155', 'code': '0396301'}, 411: {'phone': '13810789285', 'code': '0364853'}, 161: {'phone': '13621363036', 'code': '0330267'}, 621: {'phone': '15600122986', 'code': '0369381'}, 312: {'phone': '18600969778', 'code': '0362943'}, 292: {'phone': '15210931992', 'code': '0354302'}, 211: {'phone': '13810711846', 'code': '0340325'}, 522: {'phone': '18600105035', 'code': '0367091'}, 528: {'phone': '18618112086', 'code': '0309814'}, 503: {'phone': '13439769978', 'code': '0386421'}, 148: {'phone': '13718105338', 'code': '0301397'}, 586: {'phone': '18611153739', 'code': '0342358'}, 91: {'phone': '13581739016', 'code': '0376201'}, 511: {'phone': '13911291987', 'code': '0312986'}, 94: {'phone': '13522105719', 'code': '0393514'}, 210: {'phone': '13439992552', 'code': '0325938'}, 553: {'phone': '18701369469', 'code': '0384692'}, 527: {'phone': '13466579237', 'code': '0342387'}, 218: {'phone': '15101188612', 'code': '0347390'}, 24: {'phone': '13263182038', 'code': '0361428'}, 242: {'phone': '13042462119', 'code': '0309253'}, 451: {'phone': '13641339621', 'code': '0346831'}, 470: {'phone': '13801276364', 'code': '0302568'}, 373: {'phone': '18601330789', 'code': '0341782'}, 252: {'phone': '15210359017', 'code': '0394520'}, 446: {'phone': '13522035153', 'code': '0331275'}, 545: {'phone': '13683272714', 'code': '0372318'}, 432: {'phone': '13810157405', 'code': '0347059'}, 8: {'phone': '18611567979', 'code': '0390851'}, 515: {'phone': '13661162501', 'code': '0354913'}, 405: {'phone': '15011368769', 'code': '0308916'}, 316: {'phone': '13466784879', 'code': '0365908'}, 130: {'phone': '13436888995', 'code': '0331896'}, 54: {'phone': '15646599033', 'code': '0331952'}, 590: {'phone': '13269498662', 'code': '0352137'}, 454: {'phone': '18611596667', 'code': '0346583'}, 296: {'phone': '13716708310', 'code': '0376802'}, 427: {'phone': '13716785016', 'code': '0346732'}, 402: {'phone': '18710017488', 'code': '0341970'}, 450: {'phone': '18500190588', 'code': '0334975'}, 45: {'phone': '13910057186', 'code': '0332490'}, 386: {'phone': '15609831889', 'code': '0371962'}, 229: {'phone': '18910751910', 'code': '0381603'}, 584: {'phone': '13681478000', 'code': '0360718'}, 216: {'phone': '13581913037', 'code': '0361739'}, 241: {'phone': '18310618336', 'code': '0364179'}, 77: {'phone': '15910221201', 'code': '0398730'}, 479: {'phone': '13269568290', 'code': '0330184'}, 473: {'phone': '17720168592', 'code': '0336784'}, 399: {'phone': '18511578360', 'code': '0331805'}, 212: {'phone': '18610310486', 'code': '0308752'}, 609: {'phone': '18500238720', 'code': '0394710'}, 281: {'phone': '13488822979', 'code': '0369842'}, 108: {'phone': '13811425728', 'code': '0301874'}, 618: {'phone': '13521616239', 'code': '0338296'}, 6: {'phoneLine truncated
]
}
],
"source": [
"import json\n",
"import pymongo\n",
"\n",
"myclient = pymongo.MongoClient('mongodb://localhost:27017/')\n",
"mydb = myclient[\"baogao\"]\n",
"place_id = 469849\n",
"mycol = mydb[\"pdf\"]\n",
"\n",
"x = \n"
"filename = 'data/北京农行人员名单all.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"dict2 = {}\n",
"place_id = 309118\n",
"myquery = { \"place_id\": place_id }\n",
"for x in mycol.find(myquery,{ \"_id\": 0, \"place_id\": 0}):\n",
" code = int(x['fn'].split('-')[0])\n",
" if str(code) in dict1.keys():\n",
" dict2[code] = {'phone':str(dict1[str(code)]['phone']),'code':x['code']}\n",
" else:\n",
" print('no phone')\n",
"print(dict2)"
]
},
{
@@ -183,7 +230,7 @@
" req.SmsSdkAppId = \"1400140089\"\n",
" req.SignName = \"坤铭教育\"\n",
" req.TemplateId = \"1875765\" \n",
" req.TemplateParamSet = [\"北京石油分公司体测者\",yzm]\n",
" req.TemplateParamSet = [\"农行北京市分行体测者\",yzm]\n",
" req.PhoneNumberSet = [phone]\n",
" req.SessionContext = \"\"\n",
" req.ExtendCode = \"\"\n",
+22 -251
View File
@@ -4,6 +4,7 @@
"cell_type": "markdown",
"id": "e764be85-0ddf-4055-abd6-de2990e75db8",
"metadata": {
"jp-MarkdownHeadingCollapsed": true,
"tags": [],
"toc-hr-collapsed": true
},
@@ -23,27 +24,12 @@
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": null,
"id": "1144aaac-92a0-4bcf-aba7-096f7dd3ad3b",
"metadata": {
"execution": {
"iopub.execute_input": "2023-04-28T08:05:05.494533Z",
"iopub.status.busy": "2023-04-28T08:05:05.494066Z",
"iopub.status.idle": "2023-04-28T08:05:06.489698Z",
"shell.execute_reply": "2023-04-28T08:05:06.488731Z",
"shell.execute_reply.started": "2023-04-28T08:05:05.494503Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ok\n"
]
}
],
"outputs": [],
"source": [
"import openpyxl\n",
"import json\n",
@@ -81,27 +67,12 @@
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": null,
"id": "d5171966-95ae-47ae-a75e-db08de772348",
"metadata": {
"execution": {
"iopub.execute_input": "2023-04-28T08:30:24.695022Z",
"iopub.status.busy": "2023-04-28T08:30:24.694269Z",
"iopub.status.idle": "2023-04-28T08:30:24.860969Z",
"shell.execute_reply": "2023-04-28T08:30:24.859964Z",
"shell.execute_reply.started": "2023-04-28T08:30:24.694992Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ok\n"
]
}
],
"outputs": [],
"source": [
"import json\n",
"filename = 'data/天津石化人员名单.json'\n",
@@ -140,15 +111,7 @@
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ok\n"
]
}
],
"outputs": [],
"source": [
"import json\n",
"import time\n",
@@ -262,27 +225,12 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": null,
"id": "27529013-f3de-4e23-980d-f62203e4df88",
"metadata": {
"execution": {
"iopub.execute_input": "2023-04-30T01:28:04.696517Z",
"iopub.status.busy": "2023-04-30T01:28:04.695670Z",
"iopub.status.idle": "2023-04-30T01:28:06.723602Z",
"shell.execute_reply": "2023-04-30T01:28:06.722564Z",
"shell.execute_reply.started": "2023-04-30T01:28:04.696475Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ok\n"
]
}
],
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
@@ -927,97 +875,12 @@
},
{
"cell_type": "code",
"execution_count": 25,
"execution_count": null,
"id": "83f02525-fd26-41ba-8b6a-c3cd584825e6",
"metadata": {
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},
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},
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{
"name": "stdout",
"output_type": "stream",
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"30333332313739300000000000000000 bfb5b7b2000000000000000000000000\n",
"ok!\n"
]
}
],
"outputs": [],
"source": [
"import binascii\n",
"import openpyxl\n",
@@ -1348,27 +1211,12 @@
},
{
"cell_type": "code",
"execution_count": 183,
"execution_count": null,
"id": "695b4933-b8c3-4be6-a024-742a982f0abb",
"metadata": {
"execution": {
"iopub.execute_input": "2023-01-14T08:57:36.572541Z",
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},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{2: {'男': {'num': 700, 'score': 1913.639999999998, 'zhongyi': 91, 'pianpo': 73}, '女': {'num': 550, 'score': 1736.5499999999988, 'zhongyi': 47, 'pianpo': 43}}, 1: {'男': {'num': 465, 'score': 1291.3899999999994, 'zhongyi': 153, 'pianpo': 119}, '女': {'num': 265, 'score': 846.3700000000005, 'zhongyi': 47, 'pianpo': 45}}, 3: {'男': {'num': 1161, 'score': 3063.0399999999995, 'zhongyi': 144, 'pianpo': 109}, '女': {'num': 279, 'score': 865.81, 'zhongyi': 39, 'pianpo': 34}}, 4: {'男': {'num': 163, 'score': 406.15000000000003, 'zhongyi': 23, 'pianpo': 19}}, 0: {'女': {'num': 405, 'score': 1218.0100000000002, 'zhongyi': 40, 'pianpo': 27}, '男': {'num': 737, 'score': 1971.2600000000007, 'zhongyi': 87, 'pianpo': 44}}, 5: {'男': {'num': 1, 'score': 2.57, 'zhongyi': 0, 'pianpo': 0}}}\n"
]
}
],
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
@@ -1419,28 +1267,12 @@
},
{
"cell_type": "code",
"execution_count": 188,
"execution_count": null,
"id": "181ff60b-3372-441a-8cd7-29e8de66ceb8",
"metadata": {
"execution": {
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"iopub.status.idle": "2023-01-14T09:14:36.136340Z",
"shell.execute_reply": "2023-01-14T09:14:36.135039Z",
"shell.execute_reply.started": "2023-01-14T09:14:36.031320Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{2: {'num': 1250, 'score': 3650.189999999998, 'zhongyi': 138, 'pianpo': 116}, 1: {'num': 730, 'score': 2137.7599999999993, 'zhongyi': 200, 'pianpo': 164}, 3: {'num': 1440, 'score': 3928.850000000005, 'zhongyi': 183, 'pianpo': 143}, 4: {'num': 163, 'score': 406.15000000000003, 'zhongyi': 23, 'pianpo': 19}, 0: {'num': 1142, 'score': 3189.270000000001, 'zhongyi': 127, 'pianpo': 71}, 5: {'num': 1, 'score': 2.57, 'zhongyi': 0, 'pianpo': 0}}\n",
"ok!\n"
]
}
],
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
@@ -1512,27 +1344,12 @@
},
{
"cell_type": "code",
"execution_count": 192,
"execution_count": null,
"id": "d5ab1a99-cb3e-4905-8c05-a6122ea09913",
"metadata": {
"execution": {
"iopub.execute_input": "2023-01-14T09:22:28.467869Z",
"iopub.status.busy": "2023-01-14T09:22:28.467341Z",
"iopub.status.idle": "2023-01-14T09:22:28.568909Z",
"shell.execute_reply": "2023-01-14T09:22:28.567550Z",
"shell.execute_reply.started": "2023-01-14T09:22:28.467822Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ok!\n"
]
}
],
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
@@ -1603,28 +1420,12 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": null,
"id": "255b5649-fb85-424d-9fad-0f3e1dff2be3",
"metadata": {
"execution": {
"iopub.execute_input": "2023-02-14T14:30:30.331426Z",
"iopub.status.busy": "2023-02-14T14:30:30.330830Z",
"iopub.status.idle": "2023-02-14T14:30:30.441098Z",
"shell.execute_reply": "2023-02-14T14:30:30.440041Z",
"shell.execute_reply.started": "2023-02-14T14:30:30.331376Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{2: {'num': 571, 'score': 1619.279999999999, 'zhongyi': 55, 'pianpo': 44}, 3: {'num': 665, 'score': 1730.73, 'zhongyi': 76, 'pianpo': 62}, 1: {'num': 129, 'score': 358.9600000000001, 'zhongyi': 23, 'pianpo': 19}, 0: {'num': 706, 'score': 1963.300000000001, 'zhongyi': 70, 'pianpo': 32}, 4: {'num': 81, 'score': 194.23999999999992, 'zhongyi': 17, 'pianpo': 14}}\n",
"ok!\n"
]
}
],
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
@@ -1705,27 +1506,12 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": null,
"id": "25283932-c03a-4a34-a59d-314fc64d8fbd",
"metadata": {
"execution": {
"iopub.execute_input": "2023-09-15T15:46:52.763943Z",
"iopub.status.busy": "2023-09-15T15:46:52.763438Z",
"iopub.status.idle": "2023-09-15T15:46:53.519617Z",
"shell.execute_reply": "2023-09-15T15:46:53.519093Z",
"shell.execute_reply.started": "2023-09-15T15:46:52.763906Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ok\n"
]
}
],
"outputs": [],
"source": [
"import openpyxl\n",
"import json\n",
@@ -1762,27 +1548,12 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": null,
"id": "c908e5e7-c014-4b8d-a583-a8c2f7115a96",
"metadata": {
"execution": {
"iopub.execute_input": "2023-09-15T15:46:56.254396Z",
"iopub.status.busy": "2023-09-15T15:46:56.254184Z",
"iopub.status.idle": "2023-09-15T15:46:56.297483Z",
"shell.execute_reply": "2023-09-15T15:46:56.296945Z",
"shell.execute_reply.started": "2023-09-15T15:46:56.254373Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ok\n"
]
}
],
"outputs": [],
"source": [
"import json\n",
"\n",