#!/usr/bin/python3
import os
import sys
import re
import pymysql
import time
import logging
import pandas as pd
import requests
from clickhouse_driver import Client
from pathlib import Path
"""
统计佛山市所有卡口的港澳过车总数,识别率
"""
if __name__ == '__main__':
logging.basicConfig(filename=os.path.dirname(os.path.abspath(__file__)) + "/pn_recognize_fail.log",level=logging.DEBUG)
try:
cursor = Client(host='68.109.211.36', port=9001, password='Yisa_fs_2021')
except:
logging.info("lighting连接失败!")
sys.exit(1)
ct = "2022-07-12 08:00:00"
et = "2022-07-12 21:00:00"
sql = "select license_plate2,location_id from yisa_oe.vehicle_all where plate_type_id2 in (19,20) and license_plate2 != '未识别' and toDateTime(capture_time) >= '{}' and toDateTime(capture_time) < '{}'".format(ct,et)
try:
results = cursor.execute(sql)
except:
logging.error("lighting语句执行错误!")
sys.exit(1)
try:
mysql_db = pymysql.connect(host='68.109.211.67',user='yisa_oe',password='Yisa_fs_2021',database='yisa_oe')
except:
logging.info("mysql连接失败!")
sys.exit(1)
pn_list = [] # 元素是列表,0:卡口名称,1:卡口id,2:香港内地牌,3:香港本地牌,4:澳门内地牌,5:澳门本地牌,6:香港识别率,7:澳门识别率
pn_list = [] # 元素是列表,0:卡口名称,1:卡口id,2:二次识别总量,3:二次识别错误
am_recognize = 0
for row in results:
row_list = list(row)
tmp_list = ['','',1,0]
if len(row_list[0]) != 7:
tmp_list[3] = 1
localtion_id = int(row_list[1])
cursor = mysql_db.cursor()
try:
sql = "select pointname,PROVIDER from location where id = {};".format(localtion_id)
print(sql)
cursor.execute(sql)
result = cursor.fetchall()
if result:
pn = result[0][0]
tmp_list[0] = pn
tmp_list[1] = result[0][1]
else:
pn = '缺失点位'
continue
except:
logging.error("mysql语句执行错误!")
sys.exit(1)
if pn_list:
flag = 0
for i in range(len(pn_list)):
if tmp_list[0] in pn_list[i]:
pn_list[i][2] = tmp_list[2] + pn_list[i][2]
pn_list[i][3] = tmp_list[3] + pn_list[i][3]
flag = 1
if flag == 0: #pn_list没有这个卡口
pn_list.append(tmp_list)
else:
pn_list.append(tmp_list)
sort_pn_list = sorted(pn_list,key=(lambda x:x[2]),reverse=True)
df = pd.DataFrame(sort_pn_list,columns=['卡口名称','卡口ID','二次总量','二次识别错误'])
df.to_csv('pn_recognize_xny_0712.csv',index=False)
print(df.head())