标签:exec 连接 div print mit gecko create session processes
先上个图看下网页版数据、mysql结构化数据
通过Python读写mysql执行时间为:1477s,而通过Pandas读写mysql执行时间为:47s,方法2速度几乎是方法1的30倍。在于IO读写上,Python多线程显得非常鸡肋,具体分析可参考:https://cuiqingcai.com/3325.html
1、Python读写Mysql
# -*- coding: utf-8 -*- import pandas as pd import tushare as ts import pymysql import time import requests import json from multiprocessing import Pool import traceback # ====================东方财富个股盘口异动数据抓取============================================================================================================ def EMydSpider(param_list): # 抓取东财个股盘口异动数据:http://quote.eastmoney.com/changes # 创建计数器 success, fail = 0, 0 # 获取当天日期 cur_date = time.strftime("%Y%m%d", time.localtime()) # 创建MySQL连接对象 conn_mysql = pymysql.connect(user=‘root‘, password=‘123456‘, database=‘stock‘, charset=‘utf8‘) cursor = conn_mysql.cursor() header = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (Khtml, like Gecko) Chrome/70.0.3538.25 Safari/537.36 Core/1.70.3676.400 QQBrowser/10.5.3738.400"} url = "http://push2ex.eastmoney.com/getAllStockChanges?type=8201,8202,8193,4,32,64,8207,8209,8211,8213,8215,8204,8203,8194,8,16,128,8208,8210,8212,8214,8216" session = requests.Session() for param in param_list: try: html = json.loads(session.get(url=url, params=param, headers=header).text) allstock = html[‘data‘][‘allstock‘] for stock in allstock: stk_code = stock[‘c‘] # 股票代码,无后缀 stk_name = stock[‘n‘] # 股票名称 chg_time = stock[‘tm‘] # 异动时间 chg_type = stock[‘t‘] # 异动类型 chg_value = stock[‘i‘] # 异动值 try: sql = ‘‘‘insert into stock_yd_list(stk_code,trade_date,chg_time,chg_type,chg_value) values(‘%s‘,‘%s‘,‘%s‘,‘%s‘,‘%s‘)‘‘‘ % (stk_code, cur_date, chg_time, chg_type, chg_value) cursor.execute(sql) conn_mysql.commit() success += 1 print("东方财富盘口异动,第%d条数据存储完成......" % success) except: conn_mysql.rollback() fail += 1 traceback.print_exc() print("东方财富盘口异动,第%d条数据存储失败......" % fail) except: traceback.print_exc() exit() cursor.close() conn_mysql.close() print(‘当天个股盘口异动数据获取完毕,新入库数据:%d条‘ % success) print(‘当天个股盘口异动数据获取完毕,入库失败数据:%d条‘ % fail) # ====================主函数==================================================================================================================================== if __name__==‘__main__‘: print("东财异动程序开始执行") start = time.time() # 定义空列表 param_list = [] for page in range(0,300): param = {"pageindex": page, "pagesize": ‘64‘, "ut": ‘7eea3edcaed734bea9cbfc24409ed989‘, "dpt": ‘wzchanges‘} param_list.append(param) # 创建多进程 pool = Pool(processes=4) # 开启多进程爬取东财异动数据 try: pool.map(EMydSpider, (param_list,)) except: print("多进程执行error") traceback.print_exc() end = time.time() print(‘东财异动程序共执行%0.2f秒.‘ % ((end - start)))
执行时间:
2、Pandas读写Mysql
# -*- coding: utf-8 -*- import pandas as pd import tushare as ts import time import requests import json from sqlalchemy import create_engine from multiprocessing import Pool from requests.packages.urllib3.exceptions import InsecureRequestWarning import traceback # ====================东方财富个股盘口异动数据抓取============================================================================================================ def EMydSpider(param_list): # 抓取东财个股盘口异动数据:http://quote.eastmoney.com/changes # 获取当天日期 cur_date = time.strftime("%Y%m%d", time.localtime()) # 创建空列表 html_list = [] header = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (Khtml, like Gecko) Chrome/70.0.3538.25 Safari/537.36 Core/1.70.3676.400 QQBrowser/10.5.3738.400"} url = "http://push2ex.eastmoney.com/getAllStockChanges?type=8201,8202,8193,4,32,64,8207,8209,8211,8213,8215,8204,8203,8194,8,16,128,8208,8210,8212,8214,8216" session = requests.Session() for param in param_list: try: html = json.loads(session.get(url=url, params=param, headers=header).text) html_list.append(html) except: break # 创建用于存储异动数据的空Dataframe stock_yd = pd.DataFrame(columns=(‘symbol‘, ‘trade_date‘, ‘chg_time‘,‘chg_type‘,‘chg_value‘)) for html in html_list: try: allstock = html[‘data‘][‘allstock‘] for stock in allstock: code = stock[‘c‘] # 股票代码,无后缀 stk_name = stock[‘n‘] # 股票名称 chg_time = stock[‘tm‘] # 异动时间 chg_type = stock[‘t‘] # 异动类型 chg_value = stock[‘i‘] # 异动值 stock_yd = stock_yd.append({‘symbol‘:code, ‘trade_date‘: cur_date, ‘chg_time‘: chg_time,‘chg_type‘:chg_type,‘chg_value‘:chg_value}, ignore_index=True) except: pass # 创建Pandas读写数据库引擎 engine_mysql = create_engine(‘mysql://root:123456@127.0.0.1/stock?charset=utf8‘) # Pandas数据存储 stock_yd.to_sql(‘stock_yd_list‘, engine_mysql, index=False, if_exists=‘append‘) print("新入库数据%s条" % stock_yd.shape[0]) # ====================主函数==================================================================================================================================== if __name__==‘__main__‘: print("东财异动程序开始执行") start = time.time() # 定义空列表 param_list = [] for page in range(0,300): param = {"pageindex": page, "pagesize": ‘64‘, "ut": ‘7eea3edcaed734bea9cbfc24409ed989‘, "dpt": ‘wzchanges‘} param_list.append(param) # 创建多进程 pool = Pool(processes=4) # 开启多进程爬取东财异动数据 try: pool.map(EMydSpider, (param_list,)) except: print("多进程执行error") traceback.print_exc() end = time.time() print(‘东财异动程序共执行%0.2f秒.‘ % ((end - start)))
执行时间:
Python多进程爬虫东方财富盘口异动数据+Python读写Mysql与Pandas读写Mysql效率对比
标签:exec 连接 div print mit gecko create session processes
原文地址:https://www.cnblogs.com/Iceredtea/p/12164152.html