c = csv.writer(f) c.writerow(i['content'],i['id'])
时间: 2024-05-15 17:13:17 浏览: 11
这段代码的意思是将变量 `i` 中的 `content` 和 `id` 作为一行写入到一个 csv 文件(在此之前必须以写入模式打开文件对象 `f`)。`csv.writer()` 是一个用于写入 csv 文件的类,而 `writerow()` 方法则用于写入一行数据。在这里,`i['content']` 是第一个参数,表示这一行中的第一个数据,然后使用逗号分隔,接着是 `i['id']`,表示这一行中的第二个数据。最终写入的结果应该是这样子的:
```
content1,id1
content2,id2
content3,id3
...
```
相关问题
with open(csv_file, "w", newline="", encoding="utf-8-sig") as f: writer = csv.writer(f) writer.writerow(["Talk ID", "Time", "Sender ID", "Receive ID", "Talk Type", "Content", "File Name"])
根据你的代码,你想使用CSV写入器(`csv.writer`)将行标题写入CSV文件。以下是修改后的代码示例:
```python
import os
from bs4 import BeautifulSoup
import re
import csv
# 指定文件夹路径
folder_path = "C:/Users/test/Desktop/DIDItest"
# 正则表达式模式
pattern = r'<body>(.*?)<\/body>'
# 打开原有的CSV文件路径
csv_file = "output.csv"
# 打开CSV文件进行写入
with open(csv_file, "w", newline="", encoding="utf-8-sig") as f:
writer = csv.writer(f)
# 写入行标题
writer.writerow(["Talk ID", "Time", "Sender ID", "Receive ID", "Talk Type", "Content", "File Name"])
# 遍历文件夹中的所有文件
for root, dirs, files in os.walk(folder_path):
for file in files:
# 读取html文件
file_path = os.path.join(root, file)
with open(file_path, "r", encoding="utf-8-sig") as f:
html_code = f.read()
# 创建BeautifulSoup对象
soup = BeautifulSoup(html_code, 'html.parser')
# 使用正则表达式匹配<body>标签内的数据
body_data = re.findall(pattern, html_code, re.DOTALL)
# 剔除<p>和()</p>
body_data = body_data[0].replace("<p>", "").replace("()</p>", "")
# 使用正则表达式提取talk_id、时间、发送者ID和接收者ID
matches2 = re.findall(r'(?:中发言|发送)\s*(.*?)\s*(?:音频 :|图片 :)?(?:\[([^\]]+)\])?', body_data)
for match in matches2:
# 提取链接地址
file_text = match[1]
matches = re.findall(r'"([^"]*)"', file_text)
if matches:
file_name = matches[0]
else:
file_name = "No matches found."
# 替换字符
file_name = file_name.replace('No matches found.', '')
# 将提取的数据写入CSV文件
writer.writerow(["", "", "", "", "", "", file_name])
print("数据已成功写入CSV文件")
```
在上面的代码中,我使用了`csv.writer`将行标题写入到CSV文件中。然后,遍历文件夹中的所有文件,并将提取的文件名数据写入CSV文件中。
请确保提供正确的文件夹路径和CSV文件路径,并根据需要调整代码。
import csv import requests from lxml import etree #定义主程序入口 if name == "main": # 定义要爬取的网页链接 url = 'https://jn.lianjia.com/zufang/pg%d' # 请求头 header = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/113.0.0.0 Safari/537.36 Edg/113.0.1774.57' } # 爬取源码数据 # 定义要爬取的数据字段 headers = ["区域", "小区名称", "户型", "面积(㎡)", "价格(元/月)"] path = "链家济南租房数据.csv" #打开CSV文件,使用csv.writer()函数创建一个csv.writer对象,用于写入CSV文件 with open(path, 'w', newline='') as f: csv_write = csv.writer(f) csv_head = ["区域", "小区名称", "户型", "面积(㎡)", "价格(元/月)"] csv_write.writerow(csv_head) # 用于循环爬取多个网页,其中range(85,101)表示需要爬取85-100页的租房信息 for num in range(85,101): # 使用字符串的format()方法将%d占位符替换成实际的页码num new_url = url.format(num) # 用request库获取网页源码数据 page_num1 = requests.get(url=new_url, headers=header) page_num1.encoding = ('utf-8') page_num = page_num1.text tree = etree.HTML(page_num) # # 使用xpath语法获取所有租房信息的父级标签对象 div_list = tree.xpath('//*[@id="content"]/div[1]/div[1]/div') with open(path, 'a', newline='') as f: # 循环处理每个租房信息的标签对象 csv_write = csv.writer(f) for div in div_list: quyu = div.xpath('./div/p[2]/a[1]//text()')[0] name = div.xpath('./div/p[2]/a[3]//text()')[0] area_text = div.xpath('./div/p[2]/text()')[4] #用来解决.split()出错 area = area_text.split()[0] if len(area_text.split()) > 0 else "" type = div.xpath('./div/p[2]/text()')[6].split()[0] place = div.xpath('./div//span/em/text()')[0] data_row = [quyu, name, type, area, place] csv_write.writerow(data_row) print("完成")改成先获取网页数爬网页数据
要先获取网页数,可以通过访问链家网站的租房列表页面,获取页面中的总页数信息,然后再根据总页数进行循环爬取每一页的租房信息。具体实现可以参考以下代码:
```python
import csv
import requests
from lxml import etree
# 定义要爬取的网页链接
url = 'https://jn.lianjia.com/zufang/pg{}'
# 请求头
header = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/113.0.0.0 Safari/537.36 Edg/113.0.1774.57'
}
# 获取总页数
page_num1 = requests.get(url=url.format(1), headers=header)
page_num1.encoding = ('utf-8')
page_num = page_num1.text
tree = etree.HTML(page_num)
total_page = int(tree.xpath('//*[@id="content"]/div[1]/div[2]/div/@data-totalpage')[0])
# 定义要爬取的数据字段
headers = ["区域", "小区名称", "户型", "面积(㎡)", "价格(元/月)"]
path = "链家济南租房数据.csv"
# 打开CSV文件,使用csv.writer()函数创建一个csv.writer对象,用于写入CSV文件
with open(path, 'w', newline='') as f:
csv_write = csv.writer(f)
csv_head = ["区域", "小区名称", "户型", "面积(㎡)", "价格(元/月)"]
csv_write.writerow(csv_head)
# 循环爬取每一页的租房信息
for num in range(1, total_page+1):
new_url = url.format(num)
page_num1 = requests.get(url=new_url, headers=header)
page_num1.encoding = ('utf-8')
page_num = page_num1.text
tree = etree.HTML(page_num)
div_list = tree.xpath('//*[@id="content"]/div[1]/div[1]/div')
with open(path, 'a', newline='') as f:
csv_write = csv.writer(f)
for div in div_list:
quyu = div.xpath('./div/p[2]/a[1]//text()')[0]
name = div.xpath('./div/p[2]/a[3]//text()')[0]
area_text = div.xpath('./div/p[2]/text()')[4]
area = area_text.split()[0] if len(area_text.split()) > 0 else ""
type = div.xpath('./div/p[2]/text()')[6].split()[0]
place = div.xpath('./div//span/em/text()')[0]
data_row = [quyu, name, type, area, place]
csv_write.writerow(data_row)
print("第{}页完成".format(num))
print("全部完成")
```
这样就可以先获取总页数,再循环爬取每一页的租房信息,将数据写入到CSV文件中。
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from bs4 import BeautifulSoup import csv import os import re # 设置文件夹路径 folder_path = 'C:/Users/test/Desktop/DIDItest' # 创建CSV文件 csv_file = open('output.csv', 'w', newline='') csv_writer = csv.writer(csv_file) csv_writer.writerow(['ID', '时间', '发送号码', '接收号码', '发送内容']) # 遍历文件夹下的所有文件 for root, dirs, files in os.walk(folder_path): for file in files: if file.endswith('.html'): file_path = os.path.join(root, file) # 打开文件并解析HTML源代码 with open(file_path, 'r', encoding='utf-8') as f: soup = BeautifulSoup(f, 'html.parser') # 提取talkid、时间、发送号码、接收号码、信息类型和消息内容的正则表达式模式 pattern = r'\[talkid:(\d+)\](.*?) 向 (.*?) 发送 (.*?):\[(.*?)\]' matches = re.findall(pattern, soup) # 遍历匹配结果并输出 for match in matches: talkid = match[0] time = match[1].strip() sender = match[2].strip() receiver = match[3].strip() type = match[4].strip() content = re.findall(r'', match[5])[0] if type in ['音频', '图片'] else match[5] # 写入CSV文件 csv_writer.writerow([talkid, time, sender, receiver, content]) # 关闭CSV文件 csv_file.close() print("数据已成功写入CSV文件。")
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