python爬网站数据实例-利用Python爬虫爬取NBA数据功能实例分享

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(' ')

# 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]+' ')

else:

fp.write(datasets[i]+' ')

line_cnt += 1

if line_cnt % 24 == 1:

fp.write(' ')

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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