TypeError:需要一个类似字节的对象，而不是 python 和 CSV 中的“str"

2022-01-31 00:00:00 python python-3.x beautifulsoup csv html-table

问题描述

TypeError: 需要一个类似字节的对象，而不是 'str'

TypeError: a bytes-like object is required, not 'str'

在执行以下 python 代码以将 HTML 表数据保存在 Csv 文件中时出现上述错误.不知道怎么搭车.请帮帮我.

getting above error while Executing below python code to save the HTML table data in Csv file. don't know how to get rideup.pls help me.

import csv
import requests
from bs4 import BeautifulSoup

url='http://www.mapsofindia.com/districts-india/'
response=requests.get(url)
html=response.content

soup=BeautifulSoup(html,'html.parser')
table=soup.find('table', attrs={'class':'tableizer-table'})
list_of_rows=[]
for row in table.findAll('tr')[1:]:
    list_of_cells=[]
    for cell in row.findAll('td'):
        list_of_cells.append(cell.text)
    list_of_rows.append(list_of_cells)
outfile=open('./immates.csv','wb')
writer=csv.writer(outfile)
writer.writerow(["SNo", "States", "Dist", "Population"])
writer.writerows(list_of_rows)

在最后一行的上方.

解决方案

您使用的是 Python 2 方法而不是 Python 3.

You are using Python 2 methodology instead of Python 3.

变化:

outfile=open('./immates.csv','wb')

收件人:

outfile=open('./immates.csv','w')

你会得到一个带有以下输出的文件:

and you will get a file with the following output:

SNo,States,Dist,Population
1,Andhra Pradesh,13,49378776
2,Arunachal Pradesh,16,1382611
3,Assam,27,31169272
4,Bihar,38,103804637
5,Chhattisgarh,19,25540196
6,Goa,2,1457723
7,Gujarat,26,60383628
.....

在 Python 3 中，csv 采用文本模式输入，而在 Python 2 中采用二进制模式.

In Python 3 csv takes the input in text mode, whereas in Python 2 it took it in binary mode.

编辑添加

这是我运行的代码:

url='http://www.mapsofindia.com/districts-india/'
html = urllib.request.urlopen(url).read()
soup = BeautifulSoup(html)
table=soup.find('table', attrs={'class':'tableizer-table'})
list_of_rows=[]
for row in table.findAll('tr')[1:]:
    list_of_cells=[]
    for cell in row.findAll('td'):
        list_of_cells.append(cell.text)
    list_of_rows.append(list_of_cells)
outfile = open('./immates.csv','w')
writer=csv.writer(outfile)
writer.writerow(['SNo', 'States', 'Dist', 'Population'])
writer.writerows(list_of_rows)

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