python爬取牛客网站招聘信息1000条id包含：编号、公司名称、学历要求、工作类型、工作名称、薪资、发布时间、截止时间、城市编码、公司规模、福利、岗位职责、地区、工作经验等信息，并以表格形式写入文本

好的，这是一个比较复杂的爬虫任务，需要用到多个Python库和技术。下面是一个可能的实现方式：

import requests
from bs4 import BeautifulSoup
import csv

# 定义一个函数，用于爬取一页的招聘信息
def scrape_page(page_num):
    url = f'https://www.nowcoder.com/recommend/intern?skillType=0&city=0&jobType=0&page={page_num}'
    headers = {
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3'}
    response = requests.get(url, headers=headers)
    soup = BeautifulSoup(response.content, 'html.parser')
    job_list = soup.find_all('li', class_='recommend-intern-item')

    # 定义一个列表，用于保存所有招聘信息
    job_info_list = []

    # 遍历每一个招聘信息，提取所需的信息
    for job in job_list:
        job_id = job.get('data-recommend-id')
        company_name = job.find('a', class_='company-name').text.strip()
        education = job.find('span', class_='education').text.strip()
        job_type = job.find('span', class_='job-type').text.strip()
        job_name = job.find('a', class_='job-name').text.strip()
        salary = job.find('span', class_='salary').text.strip()
        publish_time = job.find('span', class_='publish-time').text.strip()
        end_time = job.find('span', class_='end-time').text.strip()
        city_code = job.find('span', class_='city-code').text.strip()
        company_scale = job.find('span', class_='company-scale').text.strip()
        welfare = job.find('span', class_='welfare').text.strip()
        job_responsibility = job.find('div', class_='job-responsibility').text.strip()
        area = job.find('span', class_='area').text.strip()
        work_experience = job.find('span', class_='work-experience').text.strip()

        # 将所提取的信息保存到一个字典中
        job_info = {
            'job_id': job_id,
            'company_name': company_name,
            'education': education,
            'job_type': job_type,
            'job_name': job_name,
            'salary': salary,
            'publish_time': publish_time,
            'end_time': end_time,
            'city_code': city_code,
            'company_scale': company_scale,
            'welfare': welfare,
            'job_responsibility': job_responsibility,
            'area': area,
            'work_experience': work_experience
        }

        # 将该字典添加到job_info_list中
        job_info_list.append(job_info)

    return job_info_list

# 爬取前100页的招聘信息
all_job_info = []
for page_num in range(1, 101):
    job_info = scrape_page(page_num)
    all_job_info.extend(job_info)

# 将所有招聘信息写入csv文件
with open('jobs.csv', 'w', encoding='utf-8', newline='') as f:
    writer = csv.writer(f)
    writer.writerow(all_job_info[0].keys()) # 写入表头
    for job_info in all_job_info:
        writer.writerow(job_info.values())

这段代码使用了requests和BeautifulSoup库来爬取牛客网的招聘信息。首先定义了一个`scrape_page`函数，用于爬取一页的招聘信息，返回一个包含多个字典的列表。然后在主程序中循环调用该函数，将所有招聘信息保存到一个`all_job_info`列表中。最后使用csv库将所有招聘信息写入到一个csv文件中。