用python抓取豆瓣电影top250，写入数据库，并实现可视化

好的，以下是抓取豆瓣电影Top250并写入数据库的Python代码：

import requests
from bs4 import BeautifulSoup
import sqlite3

url = 'https://movie.douban.com/top250'
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'}
movies = []

for i in range(0, 250, 25):
    params = {'start': str(i), 'filter': ''}
    response = requests.get(url, headers=headers, params=params)
    soup = BeautifulSoup(response.text, 'html.parser')
    movie_list = soup.find('ol', class_='grid_view').find_all('li')
    for movie in movie_list:
        title = movie.find('span', class_='title').text
        rating_num = movie.find('span', class_='rating_num').text
        quote = movie.find('span', class_='inq').text if movie.find('span', class_='inq') else ''
        movies.append({'title': title, 'rating_num': rating_num, 'quote': quote})

conn = sqlite3.connect('movies.db')
cursor = conn.cursor()
cursor.execute('CREATE TABLE IF NOT EXISTS top250 (title TEXT, rating_num REAL, quote TEXT)')
for movie in movies:
    cursor.execute('INSERT INTO top250 (title, rating_num, quote) VALUES (?, ?, ?)', (movie['title'], movie['rating_num'], movie['quote']))
conn.commit()
conn.close()

这段代码会使用 requests 库向豆瓣电影Top250的网站发送请求，然后使用 BeautifulSoup 库对网页进行解析，最后把电影的标题、评分和引用语存储到 SQLite 数据库中。

接下来是实现可视化的Python代码，使用了 Matplotlib 库：

import sqlite3
import matplotlib.pyplot as plt

conn = sqlite3.connect('movies.db')
cursor = conn.cursor()
cursor.execute('SELECT rating_num, COUNT(*) FROM top250 GROUP BY rating_num')
data = cursor.fetchall()
conn.close()

x = [d[0] for d in data]
y = [d[1] for d in data]

plt.bar(x, y)
plt.xlabel('Rating')
plt.ylabel('Count')
plt.title('Top 250 Movies on Douban')
plt.show()

这段代码会从 SQLite 数据库中读取每个评分的电影数量，然后使用 Matplotlib 库绘制条形图来展示。运行后会弹出一个可视化窗口，展示所有评分的电影数量。