Python实现爬虫爬取NBA数据功能示例
本文实例讲述了Python实现爬虫爬取NBA数据功能。分享给大家供大家参考,具体如下:
爬取的网站为:stat-nba.com,这里爬取的是NBA2016-2017赛季常规赛至2017年1月7日的数据
改变url_header和url_tail即可爬取特定的其他数据。
源代码如下:
#coding=utf-8 import sys reload(sys) sys.setdefaultencoding('utf-8') import requests import time import urllib from bs4 import BeautifulSoup import re from pyExcelerator import * def getURLLists(url_header,url_tail,pages): """ 获取所有页面的URL列表 """ url_lists = [] url_0 = url_header+'0'+url_tail print url_0 url_lists.append(url_0) for i in range(1,pages+1): url_temp = url_header+str(i)+url_tail url_lists.append(url_temp) return url_lists def getNBAAllData(url_lists): """ 获取所有2017赛季NBA常规赛数据 """ datasets = [''] for item in url_lists: data1 = getNBASingleData(item) datasets.extend(data1) #去掉数据里的空元素 for item in datasets[:]: if len(item) == 0: datasets.remove(item) return datasets def getNBASingleData(url): """ 获取1个页面NBA常规赛数据 """ # url = 'http://stat-nba.com/query_team.php?QueryType=game&order=1&crtcol=date_out&GameType=season&PageNum=3000&Season0=2016&Season1=2017' # html = requests.get(url).text html = urllib.urlopen(url).read() # print html soup = BeautifulSoup(html) data = soup.html.body.find('tbody').text list_data = data.split('\n') # with open('nba_data.txt','a') as fp: # fp.write(data) # for item in list_data[:]: # if len(item) == 0: # list_data.remove(item) return list_data def saveDataToExcel(datasets,sheetname,filename): book = Workbook() sheet = book.add_sheet(sheetname) sheet.write(0,0,u'序号') sheet.write(0,1,u'球队') sheet.write(0,2,u'时间') sheet.write(0,3,u'结果') sheet.write(0,4,u'主客') sheet.write(0,5,u'比赛') sheet.write(0,6,u'投篮命中率') sheet.write(0,7,u'命中数') sheet.write(0,8,u'出手数') sheet.write(0,9,u'三分命中率') sheet.write(0,10,u'三分命中数') sheet.write(0,11,u'三分出手数') sheet.write(0,12,u'罚球命中率') sheet.write(0,13,u'罚球命中数') sheet.write(0,14,u'罚球出手数') sheet.write(0,15,u'篮板') sheet.write(0,16,u'前场篮板') sheet.write(0,17,u'后场篮板') sheet.write(0,18,u'助攻') sheet.write(0,19,u'抢断') sheet.write(0,20,u'盖帽') sheet.write(0,21,u'失误') sheet.write(0,22,u'犯规') sheet.write(0,23,u'得分') num = 24 row_cnt = 0 data_cnt = 0 data_len = len(datasets) print 'data_len:',data_len while(data_cnt< data_len): row_cnt += 1 print '序号:',row_cnt for col in range(num): # print col sheet.write(row_cnt,col,datasets[data_cnt]) data_cnt += 1 book.save(filename) def writeDataToTxt(datasets): fp = open('nba_data.txt','w') line_cnt = 1 for i in range(len(datasets)-1): #球队名称对齐的操作:如果球队名字过短或者为76人队是 球队名字后面加两个table 否则加1个table if line_cnt % 24 == 2 and len(datasets[i]) < 5 or datasets[i] == u'费城76人': fp.write(datasets[i]+'\t\t') else: fp.write(datasets[i]+'\t') line_cnt += 1 if line_cnt % 24 == 1: fp.write('\n') fp.close() if __name__ == "__main__": pages = int(1132/150) url_header = 'http://stat-nba.com/query_team.php?page=' url_tail = '&QueryType=game&order=1&crtcol=date_out&GameType=season&PageNum=3000&Season0=2016&Season1=2017#label_show_result' url_lists = getURLLists(url_header,url_tail,pages) datasets = getNBAAllData(url_lists) writeDataToTxt(datasets) sheetname = 'nba normal data 2016-2017' str_time = time.strftime('%Y-%m-%d',time.localtime(time.time())) filename = 'nba_normal_data'+str_time+'.xls' saveDataToExcel(datasets,sheetname,filename)
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