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如何保存爬虫获取商品评论的数据？

news 2025/7/1 17:38:56

保存爬取的评论数据是爬虫项目中的一个重要环节。根据需求，你可以选择将数据保存为本地文件（如CSV、JSON、TXT），或者存储到数据库（如MySQL、MongoDB等）。以下是几种常见的数据保存方式及其示例代码。

1. 保存为CSV文件

CSV（逗号分隔值）文件是一种常用的文本文件格式，适合存储表格数据。你可以使用Python的csv模块将评论数据保存为CSV文件。

示例代码：

import csv

def save_to_csv(reviews, filename="amazon_reviews.csv"):
    with open(filename, mode='w', newline='', encoding='utf-8') as file:
        writer = csv.writer(file)
        writer.writerow(["标题", "内容", "评分", "有用次数"])  # 写入表头
        for review in reviews:
            writer.writerow([review['title'], review['content'], review['rating'], review['helpful_count']])
    print(f"数据已保存到 {filename}")

# 示例：保存评论数据
reviews = [
    {"title": "很好用", "content": "这个产品真的很好用！", "rating": "5星", "helpful_count": "12人觉得有用"},
    {"title": "一般般", "content": "感觉一般般，没有想象中好。", "rating": "3星", "helpful_count": "5人觉得有用"}
]

save_to_csv(reviews)

2. 保存为JSON文件

JSON格式是一种轻量级的数据交换格式，适合存储结构化数据。你可以使用Python的json模块将评论数据保存为JSON文件。

示例代码：

import json

def save_to_json(reviews, filename="amazon_reviews.json"):
    with open(filename, mode='w', encoding='utf-8') as file:
        json.dump(reviews, file, ensure_ascii=False, indent=4)
    print(f"数据已保存到 {filename}")

# 示例：保存评论数据
reviews = [
    {"title": "很好用", "content": "这个产品真的很好用！", "rating": "5星", "helpful_count": "12人觉得有用"},
    {"title": "一般般", "content": "感觉一般般，没有想象中好。", "rating": "3星", "helpful_count": "5人觉得有用"}
]

save_to_json(reviews)

3. 保存到MySQL数据库

MySQL是一种关系型数据库管理系统，适合存储结构化数据。你可以使用Python的mysql-connector-python库将评论数据保存到MySQL数据库。

示例代码：

import mysql.connector

def save_to_mysql(reviews, db_config):
    conn = mysql.connector.connect(**db_config)
    cursor = conn.cursor()
    cursor.execute("""
        CREATE TABLE IF NOT EXISTS amazon_reviews (
            id INT AUTO_INCREMENT PRIMARY KEY,
            title VARCHAR(255),
            content TEXT,
            rating VARCHAR(10),
            helpful_count VARCHAR(50)
        )
    """)
    for review in reviews:
        cursor.execute("""
            INSERT INTO amazon_reviews (title, content, rating, helpful_count)
            VALUES (%s, %s, %s, %s)
        """, (review['title'], review['content'], review['rating'], review['helpful_count']))
    conn.commit()
    cursor.close()
    conn.close()
    print("数据已保存到MySQL数据库")

# 示例：保存评论数据
reviews = [
    {"title": "很好用", "content": "这个产品真的很好用！", "rating": "5星", "helpful_count": "12人觉得有用"},
    {"title": "一般般", "content": "感觉一般般，没有想象中好。", "rating": "3星", "helpful_count": "5人觉得有用"}
]

db_config = {
    "host": "localhost",
    "user": "root",
    "password": "your_password",
    "database": "your_database"
}

save_to_mysql(reviews, db_config)

4. 保存到MongoDB数据库

MongoDB是一种非关系型数据库，适合存储非结构化或半结构化数据。你可以使用Python的pymongo库将评论数据保存到MongoDB数据库。

示例代码：

from pymongo import MongoClient

def save_to_mongodb(reviews, db_config):
    client = MongoClient(db_config['host'], db_config['port'])
    db = client[db_config['database']]
    collection = db['amazon_reviews']
    collection.insert_many(reviews)
    print("数据已保存到MongoDB数据库")

# 示例：保存评论数据
reviews = [
    {"title": "很好用", "content": "这个产品真的很好用！", "rating": "5星", "helpful_count": "12人觉得有用"},
    {"title": "一般般", "content": "感觉一般般，没有想象中好。", "rating": "3星", "helpful_count": "5人觉得有用"}
]

db_config = {
    "host": "localhost",
    "port": 27017,
    "database": "your_database"
}

save_to_mongodb(reviews, db_config)

5. 保存为TXT文件

如果你只需要简单地保存原始文本数据，可以将评论保存为TXT文件。

示例代码：

def save_to_txt(reviews, filename="amazon_reviews.txt"):
    with open(filename, mode='w', encoding='utf-8') as file:
        for review in reviews:
            file.write(f"标题: {review['title']}\n")
            file.write(f"内容: {review['content']}\n")
            file.write(f"评分: {review['rating']}\n")
            file.write(f"有用次数: {review['helpful_count']}\n")
            file.write("-" * 50 + "\n")
    print(f"数据已保存到 {filename}")

# 示例：保存评论数据
reviews = [
    {"title": "很好用", "content": "这个产品真的很好用！", "rating": "5星", "helpful_count": "12人觉得有用"},
    {"title": "一般般", "content": "感觉一般般，没有想象中好。", "rating": "3星", "helpful_count": "5人觉得有用"}
]

save_to_txt(reviews)