当前位置: 移动技术网 > IT编程>脚本编程>Python > Python实现爬虫爬取NBA数据功能示例

Python实现爬虫爬取NBA数据功能示例

2018年08月21日  | 移动技术网IT编程  | 我要评论

中国营销论坛,ca1569,monisa-za

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)

更多关于python相关内容可查看本站专题:《python socket编程技巧总结》、《python正则表达式用法总结》、《python数据结构与算法教程》、《python函数使用技巧总结》、《python字符串操作技巧汇总》、《python入门与进阶经典教程》及《python文件与目录操作技巧汇总

希望本文所述对大家python程序设计有所帮助。

如对本文有疑问,请在下面进行留言讨论,广大热心网友会与你互动!! 点击进行留言回复

相关文章:

验证码:
移动技术网