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-8import sysreload(sys)sys.setdefaultencoding('utf-8')import requestsimport timeimport urllibfrom bs4 import BeautifulSoupimport refrom 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_listsdef 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 datasetsdef 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_datadef 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)