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

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:[email protected]/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：