【基础】【Python网络爬虫】【6.数据持久化】Excel、Json、Csv 数据保存(附大量案例代码)(建议收藏)
2024-01-01 06:24:05
Python网络爬虫基础
数据持久化(数据保存)
1. Excel
创建数据表
import openpyxl # 第三方模块, pip install openpyxl
# 1.创建一个工作簿对象
work_book = openpyxl.Workbook()
# 2.创建表对象
sheet1 = work_book.create_sheet('表1')
# 如果使用默认的表操作数据, 需要调用工作簿对象的active属性
sheet1 = work_book.active
# 3.操作表中单元格写入数据
sheet1['A1'] = 'A1'
sheet1['B7'] = 'B7'
# cell --> 单元格对象, row表示行, column表示列
sheet1.cell(row=1, column=1).value = '111111'
sheet1.cell(row=2, column=2).value = '222222'
data1 = (1, 2, 3, 4, 5)
# data2 = '45678'
# sheet1.append(序列数据) 整行添加数据到表格中去, 括号内部传递序列数据(列表/元祖)
# 通过数据的第一次和第二次数据提取, 会提取到一条一条的数据
sheet1.append(data1)
# sheet1.append(data2)
# 4.保存
work_book.save('实例.xlsx')
批量数据写入
import openpyxl
work = openpyxl.Workbook()
sheet1 = work.active
for i in range(1, 10):
for j in range(1, i + 1):
print(f'{j} x {i} = {j * i}', end='\t')
sheet1.cell(row=i, column=j).value = f'{j} x {i} = {j * i}'
print()
work.save('实例.xlsx')
读取表格数据
import openpyxl
workbook = openpyxl.load_workbook('实例.xlsx')
print(workbook.sheetnames)
sheet = workbook['Sheet'] # 指定表读取
print(sheet.max_row) # 最大行
print(sheet.max_column) # 最大列
# 读取第一行
for i in range(1, sheet.max_column + 1):
print(sheet.cell(row=1, column=i).value) # 单元格为空就返回None
# 读取第一列
for j in range(1, sheet.max_row + 1):
print(sheet.cell(row=j, column=1).value) # 单元格为空就返回None
for i in range(1, sheet.max_column + 1):
for j in range(1, sheet.max_row + 1):
print(sheet.cell(row=i, column=j).value)
案例 - 豆瓣保存 Excel
import parsel
import requests
import openpyxl
# 3.操作表中单元格写入数据
# 4.保存
# 1.创建一个工作簿对象
work = openpyxl.Workbook()
# 2.创建表对象
sheet1 = work.active
# 写表头? √
sheet1.append(['标题', '简介', '评分', '评价人数'])
for page in range(0, 226, 25):
url = f'https://movie.douban.com/top250?start={page}&filter='
headers = {
'Cookie': 'll="118267"; bid=VrC8tT1GWz8; __yadk_uid=iHqVKZD4ZHIVREbOrlu9k4uWFSsAdZtO; _pk_id.100001.4cf6=b39d476add4f5658.1683638062.; __utmz=30149280.1687782730.8.7.utmcsr=baidu|utmccn=(organic)|utmcmd=organic; __utmz=223695111.1687782730.4.4.utmcsr=baidu|utmccn=(organic)|utmcmd=organic; _pk_ref.100001.4cf6=%5B%22%22%2C%22%22%2C1687952054%2C%22https%3A%2F%2Fwww.baidu.com%2Flink%3Furl%3DqdlD_RZvrHI0sXUZ08wSSKbkKLAWA_R84aALUkbWwp__yA2hUL-2C_Ej15saTpe7%26wd%3D%26eqid%3Dfdfaeaeb0001b3f60000000664998548%22%5D; _pk_ses.100001.4cf6=1; ap_v=0,6.0; __utma=30149280.1169382564.1682168622.1687782730.1687952054.9; __utmb=30149280.0.10.1687952054; __utmc=30149280; __utma=223695111.1640817040.1683638062.1687782730.1687952054.5; __utmb=223695111.0.10.1687952054; __utmc=223695111; __gads=ID=744f53c3cb2ebb52-22841ef3a4e00021:T=1683638065:RT=1687952056:S=ALNI_MZhRKuML1OBDnNRafe3qd6-ndhaiQ; __gpi=UID=00000c03bafcda5c:T=1683638065:RT=1687952056:S=ALNI_MbkLLsUm467wiS6ZZ6Mn2ohKIWBZw',
'Host': 'movie.douban.com',
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36',
}
response = requests.get(url=url, headers=headers)
html_data = response.text
# print(html_data)
"""解析数据"""
# 转对象
selector = parsel.Selector(html_data)
# 第一次提取
lis = selector.css('.grid_view>li')
# 二次提取
for li in lis:
title = li.css('.hd>a>span:nth-child(1)::text').get()
info = li.css('.bd>p:nth-child(1)::text').getall()
info = '//'.join([i.strip() for i in info])
score = li.css('.rating_num::text').get()
follow = li.css('.star>span:nth-child(4)::text').get()
print(title, info, score, follow)
# 调用append方法写入每一条数据
# 写表头? x
sheet1.append([title, info, score, follow])
print('=' * 100 + '\n')
# 写表头? x
work.save('douban.xlsx')
# 编码
# office软件中Excel文件使用的编码是gbk
# wps软件使用的编码是 utf-8
案例 - 网易新闻Excel保存
"""
目标站点:https://news.163.com/
往下翻有 "要闻" 这个新闻类目, 找不到可以 Ctrl + F 搜索下
需求:
爬取网易新闻 "要闻" 类目第一页数据,将数据保存为 Excel 表格
保存字段需要以下内容
title
channelname
docurl
imgurl
source
tlink
"""
import json
import re
import requests
import openpyxl
url = 'https://news.163.com/special/cm_yaowen20200213/?callback=data_callback'
response = requests.get(url=url)
json_data = response.text
# print(json_data)
result = re.findall('data_callback\((.*?)\)', json_data, re.S)
# print(result)
item_json = json.loads(result[0])
# print(item_json)
# print(type(item_json))
work = openpyxl.Workbook()
sheet1 = work.active
sheet1.append(['title', 'channelname', 'docurl', 'imgurl', 'source', 'tlink'])
for item in item_json:
title = item['title']
channelname = item['channelname']
docurl = item['docurl']
imgurl = item['imgurl']
source = item['source']
tlink = item['tlink']
print(title, channelname, docurl, imgurl, source, tlink, sep=' | ')
sheet1.append([title, channelname, docurl, imgurl, source, tlink])
work.save('网易新闻.xlsx')
2. Json
数据序列化和反序列化
import json # 内置
# [] {}
data = {
'name': 'ACME',
'shares': 100,
'price': 542.23
}
"""
json序列化: 将对象转化成json字符串
dumps() 序列化json字符串
"""
json_str = json.dumps(data)
print(json_str)
print(type(json_str))
"""
json反序列化: 将json字符串转化成对象
dumps() 序列化json字符串
"""
json_obj = json.loads(json_str)
print(json_obj)
print(type(json_obj))
中文指定
import json
data = {
'name': '青灯',
'shares': 100,
'price': 542.23
}
# json字符串默认使用unicode编码, 无法显示中文
# ensure_ascii=False 不适用默认编码
json_str = json.dumps(data, ensure_ascii=False)
with open('data.json', mode='w', encoding='utf-8') as f:
f.write(json_str)
案例 - 豆瓣保存Json
import json
import parsel
import requests
import openpyxl
data = [] # 定义一个空列表, 用于收集每一条数据
for page in range(0, 226, 25):
url = f'https://movie.douban.com/top250?start={page}&filter='
headers = {
'Cookie': 'll="118267"; bid=VrC8tT1GWz8; __yadk_uid=iHqVKZD4ZHIVREbOrlu9k4uWFSsAdZtO; _pk_id.100001.4cf6=b39d476add4f5658.1683638062.; __utmz=30149280.1687782730.8.7.utmcsr=baidu|utmccn=(organic)|utmcmd=organic; __utmz=223695111.1687782730.4.4.utmcsr=baidu|utmccn=(organic)|utmcmd=organic; _pk_ref.100001.4cf6=%5B%22%22%2C%22%22%2C1687952054%2C%22https%3A%2F%2Fwww.baidu.com%2Flink%3Furl%3DqdlD_RZvrHI0sXUZ08wSSKbkKLAWA_R84aALUkbWwp__yA2hUL-2C_Ej15saTpe7%26wd%3D%26eqid%3Dfdfaeaeb0001b3f60000000664998548%22%5D; _pk_ses.100001.4cf6=1; ap_v=0,6.0; __utma=30149280.1169382564.1682168622.1687782730.1687952054.9; __utmb=30149280.0.10.1687952054; __utmc=30149280; __utma=223695111.1640817040.1683638062.1687782730.1687952054.5; __utmb=223695111.0.10.1687952054; __utmc=223695111; __gads=ID=744f53c3cb2ebb52-22841ef3a4e00021:T=1683638065:RT=1687952056:S=ALNI_MZhRKuML1OBDnNRafe3qd6-ndhaiQ; __gpi=UID=00000c03bafcda5c:T=1683638065:RT=1687952056:S=ALNI_MbkLLsUm467wiS6ZZ6Mn2ohKIWBZw',
'Host': 'movie.douban.com',
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36',
}
response = requests.get(url=url, headers=headers)
html_data = response.text
# print(html_data)
"""解析数据"""
# 转对象
selector = parsel.Selector(html_data)
# 第一次提取
lis = selector.css('.grid_view>li')
# 二次提取
for li in lis:
title = li.css('.hd>a>span:nth-child(1)::text').get()
info = li.css('.bd>p:nth-child(1)::text').getall()
info = '//'.join([i.strip() for i in info])
score = li.css('.rating_num::text').get()
follow = li.css('.star>span:nth-child(4)::text').get()
# print(title, info, score, follow)
d = {'title': title, 'info': info, 'score': score, 'follow': follow}
data.append(d)
# print('=' * 100 + '\n')
print(data)
# json数据的序列化
json_str = json.dumps(data, ensure_ascii=False)
with open('douban.json', mode='w', encoding='utf-8') as f:
f.write(json_str)
# [{}, {}, {}......]
案例 - Json保存
"""
目标网址:https://www.ku6.com/video/feed?pageNo=0&pageSize=40&subjectId=76
请求方式: GET
要求:
1、请求上述网址的数据
2、把获取到的数据保存到json文件中
文件命名: data.json
需要在文件中看到json字符串
请在下方编写代码
"""
import requests
url = 'https://www.ku6.com/video/feed?pageNo=0&pageSize=40&subjectId=76'
response = requests.get(url=url)
json_data = response.text
print(json_data)
with open('data.json', mode='w', encoding='utf-8') as f:
f.write(json_data)
# json序列化-
3. Csv
写入csv列表数据
"""
csv数据格式:
每一行是一条数据
每一行中每个数据字段有分隔符号, 默认为逗号
"""
import csv # 内置
data = [
[1, 2, 3, 4],
[1, 2, 3, 4],
[5, 6, 7, 8],
[5, 6, 7, 8]
]
with open('data.csv', mode='a', encoding='utf-8', newline='') as f:
# newline='' 指定数据新行是一个空字符串, 不然保存会有数据空行
# csv.writer(f) 实例化一个csv数据的写入对象, 括号内部传递文件对象
csv_write = csv.writer(f)
for i in data:
# writerow(i) 把数据一行一行<一条一条>写入, 传入(列表/元组)
csv_write.writerow(i)
案例 - 豆瓣列表保存Csv
import csv
import json
import parsel
import requests
import openpyxl
# 上下文管理器
with open('douban-list.csv', mode='a', encoding='utf-8', newline='') as f:
csv_write = csv.writer(f)
# csv_write.writerow(['标题', '简介', '平分', '评论人数'])
f.write('标题,简介,平分,评论人数\n')
for page in range(0, 226, 25):
url = f'https://movie.douban.com/top250?start={page}&filter='
headers = {
'Cookie': 'll="118267"; bid=VrC8tT1GWz8; __yadk_uid=iHqVKZD4ZHIVREbOrlu9k4uWFSsAdZtO; _pk_id.100001.4cf6=b39d476add4f5658.1683638062.; __utmz=30149280.1687782730.8.7.utmcsr=baidu|utmccn=(organic)|utmcmd=organic; __utmz=223695111.1687782730.4.4.utmcsr=baidu|utmccn=(organic)|utmcmd=organic; _pk_ref.100001.4cf6=%5B%22%22%2C%22%22%2C1687952054%2C%22https%3A%2F%2Fwww.baidu.com%2Flink%3Furl%3DqdlD_RZvrHI0sXUZ08wSSKbkKLAWA_R84aALUkbWwp__yA2hUL-2C_Ej15saTpe7%26wd%3D%26eqid%3Dfdfaeaeb0001b3f60000000664998548%22%5D; _pk_ses.100001.4cf6=1; ap_v=0,6.0; __utma=30149280.1169382564.1682168622.1687782730.1687952054.9; __utmb=30149280.0.10.1687952054; __utmc=30149280; __utma=223695111.1640817040.1683638062.1687782730.1687952054.5; __utmb=223695111.0.10.1687952054; __utmc=223695111; __gads=ID=744f53c3cb2ebb52-22841ef3a4e00021:T=1683638065:RT=1687952056:S=ALNI_MZhRKuML1OBDnNRafe3qd6-ndhaiQ; __gpi=UID=00000c03bafcda5c:T=1683638065:RT=1687952056:S=ALNI_MbkLLsUm467wiS6ZZ6Mn2ohKIWBZw',
'Host': 'movie.douban.com',
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36',
}
response = requests.get(url=url, headers=headers)
html_data = response.text
# print(html_data)
"""解析数据"""
# 转对象
selector = parsel.Selector(html_data)
# 第一次提取
lis = selector.css('.grid_view>li')
# 二次提取
for li in lis:
title = li.css('.hd>a>span:nth-child(1)::text').get()
info = li.css('.bd>p:nth-child(1)::text').getall()
info = '//'.join([i.strip() for i in info])
score = li.css('.rating_num::text').get()
follow = li.css('.star>span:nth-child(4)::text').get()
print(title, info, score, follow)
# 循环写入数据
csv_write.writerow([title, info, score, follow])
print('=' * 100 + '\n')
写入csv字典数据
"""
csv数据格式:
每一行是一条数据
每一行中每个数据字段有分隔符号, 默认为逗号
"""
import csv # 内置
list_dict = [{'first_name': 'Baked', 'last_name': 'Beans'},
{'first_name': 'Lovely'},
{'first_name': 'Wonderful', 'last_name': 'Spam'}]
with open('data.csv', mode='a', encoding='utf-8', newline='') as f:
# 创建一个字典数据写入对象, 第一个参数是文件对象, 第二个参数是字典中的键
# fieldnames 指定字典的键, 不能多不能少不能错
csv_write = csv.DictWriter(f, fieldnames=['first_name', 'last_name'])
# 字典数据会有专门写表头的方法
csv_write.writeheader()
for i in list_dict:
csv_write.writerow(i)
案例 - 豆瓣字典保存csv
import csv
import json
import parsel
import requests
import openpyxl
with open('douban-dict.csv', mode='a', encoding='utf-8', newline='') as f:
csv_write = csv.DictWriter(f, fieldnames=['title', 'info', 'score', 'follow'])
csv_write.writeheader() # 写表头, 只有字典数据有写表头的方法,列表没有方法写表头
for page in range(0, 226, 25):
url = f'https://movie.douban.com/top250?start={page}&filter='
headers = {
'Cookie': 'll="118267"; bid=VrC8tT1GWz8; __yadk_uid=iHqVKZD4ZHIVREbOrlu9k4uWFSsAdZtO; _pk_id.100001.4cf6=b39d476add4f5658.1683638062.; __utmz=30149280.1687782730.8.7.utmcsr=baidu|utmccn=(organic)|utmcmd=organic; __utmz=223695111.1687782730.4.4.utmcsr=baidu|utmccn=(organic)|utmcmd=organic; _pk_ref.100001.4cf6=%5B%22%22%2C%22%22%2C1687952054%2C%22https%3A%2F%2Fwww.baidu.com%2Flink%3Furl%3DqdlD_RZvrHI0sXUZ08wSSKbkKLAWA_R84aALUkbWwp__yA2hUL-2C_Ej15saTpe7%26wd%3D%26eqid%3Dfdfaeaeb0001b3f60000000664998548%22%5D; _pk_ses.100001.4cf6=1; ap_v=0,6.0; __utma=30149280.1169382564.1682168622.1687782730.1687952054.9; __utmb=30149280.0.10.1687952054; __utmc=30149280; __utma=223695111.1640817040.1683638062.1687782730.1687952054.5; __utmb=223695111.0.10.1687952054; __utmc=223695111; __gads=ID=744f53c3cb2ebb52-22841ef3a4e00021:T=1683638065:RT=1687952056:S=ALNI_MZhRKuML1OBDnNRafe3qd6-ndhaiQ; __gpi=UID=00000c03bafcda5c:T=1683638065:RT=1687952056:S=ALNI_MbkLLsUm467wiS6ZZ6Mn2ohKIWBZw',
'Host': 'movie.douban.com',
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36',
}
response = requests.get(url=url, headers=headers)
html_data = response.text
# print(html_data)
"""解析数据"""
# 转对象
selector = parsel.Selector(html_data)
# 第一次提取
lis = selector.css('.grid_view>li')
# 二次提取
for li in lis:
title = li.css('.hd>a>span:nth-child(1)::text').get()
info = li.css('.bd>p:nth-child(1)::text').getall()
info = '//'.join([i.strip() for i in info])
score = li.css('.rating_num::text').get()
follow = li.css('.star>span:nth-child(4)::text').get()
print(title, info, score, follow)
d = {'title': title, 'info': info, 'score': score, 'follow': follow}
csv_write.writerow(d)
print('=' * 100 + '\n')
读取csv数据
import csv
"""基于字符串文件类型直接读取"""
# with open('data.csv', mode='r', encoding='utf-8') as f:
# print(f.read())
"""读取返回列表"""
# with open('douban-list.csv', mode='r', encoding='utf-8') as f:
# csv_read = csv.reader(f)
# print(csv_read)
# for i in csv_read:
# print(i)
"""读取返回字典对象的方法"""
with open('douban-list.csv', mode='r', encoding='utf-8') as f:
csv_read = csv.DictReader(f)
print(csv_read)
for i in csv_read:
print(i)
案例 - 网易新闻csv
"""
目标站点:https://news.163.com/
往下翻有 要闻 这个新闻类目
需求:
爬取网易新闻 要闻 类目第一页数据,将数据保存为csv格式
保存字段需要以下内容
title
channelname
docurl
imgurl
source
tlink
"""
import csv
import json
import re
import requests
import openpyxl
url = 'https://news.163.com/special/cm_yaowen20200213/?callback=data_callback'
response = requests.get(url=url)
json_data = response.text
result = re.findall('data_callback\((.*?)\)', json_data, re.S)
item_json = json.loads(result[0])
with open('网易新闻.csv', mode='a', encoding='utf-8', newline='') as f:
write = csv.writer(f)
write.writerow(['title', 'channelname', 'docurl', 'imgurl', 'source', 'tlink'])
for item in item_json:
title = item['title']
channelname = item['channelname']
docurl = item['docurl']
imgurl = item['imgurl']
source = item['source']
tlink = item['tlink']
print(title, channelname, docurl, imgurl, source, tlink, sep=' | ')
write.writerow([title, channelname, docurl, imgurl, source, tlink])
文章来源:https://blog.csdn.net/weixin_43612602/article/details/135316636
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本文来自互联网用户投稿,该文观点仅代表作者本人,不代表本站立场。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。 如若内容造成侵权/违法违规/事实不符,请联系我的编程经验分享网邮箱:veading@qq.com进行投诉反馈,一经查实,立即删除!