爬取豆瓣电影数据并保存至本地csv文件并将数据导入MySQL数据库

抱歉，作为AI语言模型，我无法执行爬虫操作和访问本地文件系统。但您可以参考以下步骤来完成该任务：

1. 安装Python的爬虫框架Scrapy和MySQL数据库连接库pymysql：

pip install scrapy
pip install pymysql

2. 创建一个Scrapy项目：

scrapy startproject douban_movie

3. 编写爬虫代码。在douban_movie/spiders目录下创建一个名为douban_spider.py的文件，实现对豆瓣电影top250页面的爬取，并将结果保存至本地csv文件：

import scrapy
import csv

class DoubanSpider(scrapy.Spider):
    name = 'douban'
    start_urls = ['https://movie.douban.com/top250']

    def parse(self, response):
        for movie in response.css('.item'):
            yield {
                'title': movie.css('.title::text').get(),
                'rating': movie.css('.rating_num::text').get(),
                'comment': movie.css('.quote span::text').get()
            }

        next_page = response.css('.next a::attr(href)').get()
        if next_page is not None:
            yield response.follow(next_page, self.parse)

        # 保存至本地csv文件
        with open('douban_movie.csv', mode='a', newline='', encoding='utf-8') as file:
            writer = csv.writer(file)
            for movie in response.css('.item'):
                writer.writerow([
                    movie.css('.title::text').get(),
                    movie.css('.rating_num::text').get(),
                    movie.css('.quote span::text').get()
                ])

4. 运行爬虫并将结果导入MySQL数据库。在douban_movie目录下创建一个名为mysql_pipeline.py的文件，实现将csv文件中的数据导入MySQL数据库：

import csv
import pymysql

class MysqlPipeline:
    def __init__(self):
        self.conn = pymysql.connect(
            host='localhost',
            port=3306,
            user='root',
            password='password',
            db='douban_movie',
            charset='utf8mb4'
        )
        self.cursor = self.conn.cursor()

    def process_item(self, item, spider):
        self.cursor.execute(
            "INSERT INTO movie(title, rating, comment) VALUES (%s, %s, %s)",
            (item['title'], item['rating'], item['comment'])
        )
        self.conn.commit()
        return item

    def close_spider(self, spider):
        self.cursor.close()
        self.conn.close()

if __name__ == '__main__':
    with open('douban_movie.csv', mode='r', encoding='utf-8') as file:
        reader = csv.reader(file)
        next(reader)  # 跳过表头
        for row in reader:
            pipeline = MysqlPipeline()
            pipeline.process_item({
                'title': row[0],
                'rating': row[1],
                'comment': row[2]
            }, None)

5. 运行爬虫并导入数据：

scrapy crawl douban
python mysql_pipeline.py

注意：在运行mysql_pipeline.py文件之前，需要先创建MySQL数据库和movie表。可以使用以下SQL语句：

CREATE DATABASE douban_movie CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci;
USE douban_movie;
CREATE TABLE movie (
    id INT(11) NOT NULL AUTO_INCREMENT,
    title VARCHAR(255) NOT NULL,
    rating FLOAT NOT NULL,
    comment VARCHAR(255),
    PRIMARY KEY (id)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;