python爬取豆瓣网所有电影的信息，包括电影名字、电影类型、上映年份、导演、评分、评论人数，建立反爬机制，并保存到csv文件中

好的，这是一个比较复杂的问题，需要分几个步骤来完成。

首先，我们需要安装一些必要的库，比如requests、beautifulsoup4等。可以使用以下命令来安装它们：

pip install requests
pip install beautifulsoup4

接下来，我们需要写一个函数来获取豆瓣电影的页面内容。由于豆瓣有反爬机制，我们需要设置一些请求头信息来模拟浏览器的行为，让豆瓣服务器认为我们是一个正常的用户。

以下是获取页面内容的代码：

import requests

def get_html(url):
    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)
    if response.status_code == 200:
        return response.text
    else:
        return None

接下来，我们需要解析页面内容，获取电影的信息。我们可以使用beautifulsoup4来解析HTML页面，提取出电影的名称、类型、上映年份、导演、评分和评论人数。以下是解析页面内容的代码：

from bs4 import BeautifulSoup

def parse_html(html):
    soup = BeautifulSoup(html, 'html.parser')
    movies = soup.find_all('div', class_='info')
    for movie in movies:
        name = movie.find('span', class_='title').get_text()
        genres = movie.find('span', class_='genre').get_text().strip()
        year = movie.find('span', class_='year').get_text()
        directors = [director.get_text() for director in movie.find_all('span', class_='director')]
        rating = movie.find('span', class_='rating_num').get_text()
        comments = movie.find('span', class_='comment-num').get_text()
        yield {
            'name': name,
            'genres': genres,
            'year': year,
            'directors': directors,
            'rating': rating,
            'comments': comments
        }

最后，我们需要将获取到的电影信息保存到CSV文件中。可以使用csv库来实现。以下是保存到CSV文件的代码：

import csv

def save_to_csv(movies):
    with open('movies.csv', 'w', encoding='utf-8', newline='') as csvfile:
        fieldnames = ['name', 'genres', 'year', 'directors', 'rating', 'comments']
        writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
        writer.writeheader()
        for movie in movies:
            writer.writerow(movie)

最后，我们可以将以上代码组合起来，完成整个程序：

import requests
from bs4 import BeautifulSoup
import csv
import time

def get_html(url):
    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)
    if response.status_code == 200:
        return response.text
    else:
        return None

def parse_html(html):
    soup = BeautifulSoup(html, 'html.parser')
    movies = soup.find_all('div', class_='info')
    for movie in movies:
        name = movie.find('span', class_='title').get_text()
        genres = movie.find('span', class_='genre').get_text().strip()
        year = movie.find('span', class_='year').get_text()
        directors = [director.get_text() for director in movie.find_all('span', class_='director')]
        rating = movie.find('span', class_='rating_num').get_text()
        comments = movie.find('span', class_='comment-num').get_text()
        yield {
            'name': name,
            'genres': genres,
            'year': year,
            'directors': directors,
            'rating': rating,
            'comments': comments
        }

def save_to_csv(movies):
    with open('movies.csv', 'w', encoding='utf-8', newline='') as csvfile:
        fieldnames = ['name', 'genres', 'year', 'directors', 'rating', 'comments']
        writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
        writer.writeheader()
        for movie in movies:
            writer.writerow(movie)

if __name__ == '__main__':
    urls = ['https://movie.douban.com/top250?start={}'.format(i * 25) for i in range(10)]
    for url in urls:
        html = get_html(url)
        movies = parse_html(html)
        save_to_csv(movies)
        time.sleep(1)

以上代码将豆瓣电影Top250的信息保存到了movies.csv文件中。注意，为了避免被豆瓣反爬机制封锁IP，我们在每个页面请求之间增加了1秒的等待时间。