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【Python数据分析】Python3操作Excel(二) 一些问题的解决与优化

    继上一篇【Python数据分析】Python3操作Excel-以豆瓣图书Top250为例 对豆瓣图书Top250进行爬取以后,鉴于还有一些问题没有解决,所以进行了进一步的交流讨论,这期间得到了一只尼玛的帮助与启发,十分感谢!

    上次存在的问题如下:

    1.写入不能继续的问题

    2.在Python IDLE中明明输出正确的结果,写到excel中就乱码了。

    上述两个问题促使我改换excel处理模块,因为据说xlwt只支持到Excel 2003,很有可能会出问题。

    虽然“一只尼玛”给了一个Validate函数,可是那是针对去除Windows下文件名中非法字符的函数,跟写入excel乱码没有关系,所以还是考虑更换模块。

更换xlsxwriter模块

    这次我改成xlsxwriter这个模块,https://pypi.python.org/pypi/XlsxWriter. 同样可以pip3 install xlsxwriter,自动下载安装,简便易行。一些用法样例:

import xlsxwriter

# Create an new Excel file and add a worksheet.
workbook = xlsxwriter.Workbook('demo.xlsx')
worksheet = workbook.add_worksheet()

# Widen the first column to make the text clearer.
worksheet.set_column('A:A', 20)

# Add a bold format to use to highlight cells.
bold = workbook.add_format({'bold': True})

# Write some simple text.
worksheet.write('A1', 'Hello')

# Text with formatting.
worksheet.write('A2', 'World', bold)

# Write some numbers, with row/column notation.
worksheet.write(2, 0, 123)
worksheet.write(3, 0, 123.456)

# Insert an image.
worksheet.insert_image('B5', 'logo.png')

workbook.close()

果断更换写入excel的代码。效果如下:

果然鼻子是鼻子脸是脸,该是链接就是链接,不管什么字符都能写,毕竟unicode。

所以说,选对模块很重要选对模块很重要选对模块很重要!(重说三)

如果要爬的内容不是很公正标准的字符串或数字的话,我是不会用xlwt啦。

这里有4中Python写入excel的模块对比:http://ju.outofmemory.cn/entry/56671

我截了一个对比图如下,具体可以看上面那篇文章,非常详细!

顺藤摸瓜

这个既然如此顺畅,还可以写入图片,那我们何不试试看呢?

目标:把图片链接那一列的内容换成真正的图片!

其实很简单,因为我们之前已经有了图片的存储路径,把它插入到里面就可以了。

    the_img = "I:\\douban\\image\\"+bookName+".jpg"
    writelist=[i+j,bookName,nickname,rating,nums,the_img,bookurl,notion,tag]
    for k in range(0,9):
        if k == 5:
            worksheet.insert_image(i+j,k,the_img)
        else:
            worksheet.write(i+j,k,writelist[k])

出来是这样的效果,显然不美观,那我们应该适当调整一些每行的高度,以及让他们居中试试看:

查阅xlsxwriter文档可知,可以这么设置行列宽度和居中:(当然,这些操作在excel中可以直接做,而且可能会比写代码更快,但是我倒是想更多试试这个模块)

format = workbookx.add_format()
format.set_align('justify')
format.set_align('center')
format.set_align('vjustify')
format.set_align('vcenter')
format.set_text_wrap()

worksheet.set_row(0,12,format)
for i in range(1,251):
    worksheet.set_row(i,70)
worksheet.set_column('A:A',3,format)
worksheet.set_column('B:C',17,format)
worksheet.set_column('D:D',4,format)
worksheet.set_column('E:E',7,format)
worksheet.set_column('F:F',10,format)
worksheet.set_column('G:G',19,format)
worksheet.set_column('H:I',40,format)

至此完成了excel的写入,只不过设置格式这块实在繁杂,得不断调试距离,大小,所以在excel里面做会简单些。

最终代码:

# -*- coding:utf-8 -*-
import requests
import re
import xlwt
import xlsxwriter
from bs4 import BeautifulSoup
from datetime import datetime
import codecs

now = datetime.now()             #开始计时
print(now)

def validate(title):                        #from nima
    rstr = r"[\/\\\:\*\?\"\<\>\|]"          # '/\:*?"<>|-'
    new_title = re.sub(rstr, "", title)
    return new_title

txtfile = codecs.open("top2501.txt",'w','utf-8')
url = "http://book.douban.com/top250?"

header = { "User-Agent": "Mozilla/5.0 (Windows NT 6.3; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/49.0.2623.13 Safari/537.36",
           "Referer": "http://book.douban.com/"
           }

image_dir = "I:\\douban\\image\\"
#下载图片
def download_img(imageurl,imageName = "xxx.jpg"):
    rsp = requests.get(imageurl, stream=True)
    image = rsp.content
    path = image_dir + imageName +'.jpg'
    #print(path)
    with open(path,'wb') as file:
        file.write(image)

#建立Excel
workbookx = xlsxwriter.Workbook('I:\\douban\\btop250.xlsx')
worksheet = workbookx.add_worksheet()
format = workbookx.add_format()
format.set_align('justify')
format.set_align('center')
format.set_align('vjustify')
format.set_align('vcenter')
format.set_text_wrap()

worksheet.set_row(0,12,format)
for i in range(1,251):
    worksheet.set_row(i,70)
worksheet.set_column('A:A',3,format)
worksheet.set_column('B:C',17,format)
worksheet.set_column('D:D',4,format)
worksheet.set_column('E:E',7,format)
worksheet.set_column('F:F',10,format)
worksheet.set_column('G:G',19,format)
worksheet.set_column('H:I',40,format)

item = ['书名','别称','评分','评价人数','封面','图书链接','出版信息','标签']
for i in range(1,9):
    worksheet.write(0,i,item[i-1])
        
s = requests.Session()      #建立会话
s.get(url,headers=header)

for i in range(0,250,25):  
    geturl = url + "/start=" + str(i)                     #要获取的页面地址
    print("Now to get " + geturl)
    postData = {"start":i}                                #post数据
    res = s.post(url,data = postData,headers = header)    #post
    soup = BeautifulSoup(res.content.decode(),"html.parser")       #BeautifulSoup解析
    table = soup.findAll('table',{"width":"100%"})        #找到所有图书信息的table
    sz = len(table)                                       #sz = 25,每页列出25篇文章
    for j in range(1,sz+1):                               #j = 1~25
        sp = BeautifulSoup(str(table[j-1]),"html.parser") #解析每本图书的信息

        imageurl = sp.img['src']                          #找图片链接
        bookurl = sp.a['href']                            #找图书链接
        bookName = sp.div.a['title']
        nickname = sp.div.span                            #找别名
        if(nickname):                                     #如果有别名则存储别名否则存’无‘
            nickname = nickname.string.strip()
        else:
            nickname = ""
        
        notion = str(sp.find('p',{"class":"pl"}).string)   #抓取出版信息,注意里面的.string还不是真的str类型
        rating = str(sp.find('span',{"class":"rating_nums"}).string)    #抓取平分数据
        nums = sp.find('span',{"class":"pl"}).string                    #抓取评分人数
        nums = nums.replace('(','').replace(')','').replace('\n','').strip()
        nums = re.findall('(\d+)人评价',nums)[0]
        download_img(imageurl,bookName)                     #下载图片
        book = requests.get(bookurl)                        #打开该图书的网页
        sp3 = BeautifulSoup(book.content,"html.parser")     #解析
        taglist = sp3.find_all('a',{"class":"  tag"})       #找标签信息
        tag = ""
        lis = []
        for tagurl in taglist:
            sp4 = BeautifulSoup(str(tagurl),"html.parser")  #解析每个标签
            lis.append(str(sp4.a.string))
        
        tag = ','.join(lis)        #加逗号
        the_img = "I:\\douban\\image\\"+bookName+".jpg"
        writelist=[i+j,bookName,nickname,rating,nums,the_img,bookurl,notion,tag]
        for k in range(0,9):
            if k == 5:
                worksheet.insert_image(i+j,k,the_img)
            else:
                worksheet.write(i+j,k,writelist[k])
            txtfile.write(str(writelist[k]))
            txtfile.write('\t')
        txtfile.write(u'\r\n')

end = datetime.now()    #结束计时
print(end)
print("程序耗时: " + str(end-now))
txtfile.close()
workbookx.close()
View Code

运行结果如下:

2016-03-28 11:40:50.525635
Now to get http://book.douban.com/top250?/start=0
Now to get http://book.douban.com/top250?/start=25
Now to get http://book.douban.com/top250?/start=50
Now to get http://book.douban.com/top250?/start=75
Now to get http://book.douban.com/top250?/start=100
Now to get http://book.douban.com/top250?/start=125
Now to get http://book.douban.com/top250?/start=150
Now to get http://book.douban.com/top250?/start=175
Now to get http://book.douban.com/top250?/start=200
Now to get http://book.douban.com/top250?/start=225
2016-03-28 11:48:14.946184
程序耗时: 0:07:24.420549

顺利爬完250本书。此次爬取行动就正确性来说已告完成!

本次耗时7分24秒,还是显得太慢了。下一步就应该是如何在提高效率上面下功夫了。

posted @ 2016-03-28 16:55 whatbeg 阅读(...) 评论(...) 编辑 收藏