AI网络爬虫：用deepseek批量提取coze扣子的智能体数据_爬虫智能体

动态加载页面，返回json数据：

翻页规律：

https://www.coze.cn/api/marketplace/product/list?entity_type=1&keyword=&page_num=17&page_size=24&sort_type=1&source=1&msToken=8_renFdIfix-XVFJAqAj8F_gSPv1V5A8NX_iL2teO45SBxvZye4AXZv4JiFygZVTPs2LVqZg0CowxYQ9sdwwkxHC3lR41AkwQGefhQr32f7YVvrrl1PS9L1SC_ftRvg%3D&a_bogus=EyW0%2FR8DdEVTvfg655KLfY3qVVa3Y0Ia0SVkMDhe5n3Rtg39HMOv9exYKs0vMDjjNs%2FDIeEjy4hbYpcQrQcnM1wf7Wsx%2F2CZmyh0t-P2so0j53intL6mE0hN-Jj3SFlm5XNAEOJ0y75aKY00W9oamhK4bfebY7Y6i6trIE%3D%3D

https://www.coze.cn/api/marketplace/product/list?entity_type=1&keyword=&page_num=16&page_size=24&sort_type=1&source=1&msToken=8_renFdIfix-XVFJAqAj8F_gSPv1V5A8NX_iL2teO45SBxvZye4AXZv4JiFygZVTPs2LVqZg0CowxYQ9sdwwkxHC3lR41AkwQGefhQr32f7YVvrrl1PS9L1SC_ftRvg%3D&a_bogus=x7Rh%2FQgXmDIpvfLh55KLfY3qV4a3Y0Iy0SVkMDheeV3Rdg39HMO19exYKsJvjk6jNs%2FDIeEjy4hbYpcQrQcnM1wf7Wsx%2F2CZmyh0t-P2so0j53intL6mE0hN-Jj3SFlm5XNAEOJ0y75aKY00W9oamhK4bfebY7Y6i6trRj%3D%3D

这两个URL在多个方面有所不同，主要差异如下：

1. **查询参数（Query Parameters）**:
   - 第一个URL的查询参数包括：
   - `entity_type=1`
   - `keyword=`（空值）
   - `page_num=16`
   - `page_size=24`
   - `sort_type=1`
   - `source=1`
   - `msToken=8_renFdIfix-XVFJAqAj8F_gSPv1V5A8NX_iL2teO45SBxvZye4AXZv4JiFygZVTPs2LVqZg0CowxYQ9sdwwkxHC3lR41AkwQGefhQr32f7YVvrrl1PS9L1SC_ftRvg%3D`
   - `a_bogus=x7Rh%2FQgXmDIpvfLh55KLfY3qV4a3Y0Iy0SVkMDheeV3Rdg39HMO19exYKsJvjk6jNs%2FDIeEjy4hbYpcQrQcnM1wf7Wsx%2F2CZmyh0t-P2so0j53intL6mE0hN-Jj3SFlm5XNAEOJ0y75aKY00W9oamhK4bfebY7Y6i6trRj%3D%3D`
   - 第二个URL的查询参数包括：
   - `entity_type=1`
   - `keyword=`（空值）
   - `page_num=1`
   - `page_size=24`
   - `sort_type=1`
   - `source=1`
   - `msToken=8_renFdIfix-XVFJAqAj8F_gSPv1V5A8NX_iL2teO45SBxvZye4AXZv4JiFygZVTPs2LVqZg0CowxYQ9sdwwkxHC3lR41AkwQGefhQr32f7YVvrrl1PS9L1SC_ftRvg%3D`
   - `a_bogus=x7Rh%2FQgXmDIpvfLh55KLfY3qV4a3Y0Iy0SVkMDheeV3Rdg39HMO19exYKsJvjk6jNs%2FDIeEjy4hbYpcQrQcnM1wf7Wsx%2F2CZmyh0t-P2so0j53intL6mE0hN-Jj3SFlm5XNAEOJ0y75aKY00W9oamhK4bfebY7Y6i6trRj%3D%3D`
   主要区别在于`page_num`参数，第一个URL中`page_num=16`，而第二个URL中`page_num=1`。这意味着第一个URL请求的是第16页的数据，而第二个URL请求的是第1页的数据。
2. **URL编码**:

- 两个URL中的查询参数值都是经过URL编码的，以确保特殊字符（如空格、%、&等）能够正确传输。

总结来说，这两个URL的主要区别在于请求的数据页数不同，第一个URL请求第16页的数据，而第二个URL请求第1页的数据。其他参数如`entity_type`, `keyword`, `page_size`, `sort_type`, `source`, `msToken`, 和 `a_bogus` 在两个URL中都是相同的。

返回的json数据如下：

{

"code": 0,

"data": {

"has_more": false,

"products": [

{

"bot_extra": {

"chat_conversation_count": "145",

"config": {

"models": [

{

"icon_url": "https://lf-coze-web-cdn.coze.cn/obj/coze-web-cn/MODEL_ICON/doubao.png",

"name": "豆包·Function call模型"

}

],

"total_knowledges_count": 1,

"total_plugins_count": 0,

"total_workflows_count": 0

},

"publish_mode": 2,

"publish_platforms": [

{

"icon_url": "https://lf26-appstore-sign.oceancloudapi.com/ocean-cloud-tos/FileBizType.BIZ_BOT_ICON/4383119973291048_1700223103089819298.jpeg?lk3s=60aae199\u0026x-expires=1718792155\u0026x-signature=FlRwUZl%2FOoBKUwJHWskM5skN4xs%3D",

"id": "482431",

"name": "豆包",

"url": "https://www.doubao.com/share?botId=7356440225838841908"

}

],

"user_count": 46

},

"meta_info": {

"category": {

"active_icon_url": "",

"count": 0,

"icon_url": "",

"id": "7338033313162051635",

"index": 0,

"name": "角色"

},

"description": "非遗小贴士是一名资深的非物质文化遗产研究学者，能够为用户提供目录查询、详细信息查询以及相关的文化历史背景介绍。通过使用工具搜索相关信息，去除冗余信息并以通俗易懂的方式回答用户问题，让用户更好地了解中国各地的非物质文化遗产。",

"entity_id": "7356440225838841908",

"entity_type": 1,

"entity_version": "1712825279218",

"favorite_count": 7,

"heat": 0,

"icon_url": "https://p26-flow-product-sign.byteimg.com/tos-cn-i-13w3uml6bg/9a23cfb384944811aafa4bee236071c3~tplv-13w3uml6bg-resize:128:128.image?rk3s=2e2596fd\u0026x-expires=1721380555\u0026x-signature=Rpy50nvNyEe2WZIN6NY2Apen5XQ%3D",

"id": "7356526186891149324",

"is_favorited": false,

"is_free": true,

"labels": [],

"listed_at": "1712825280",

"medium_icon_url": "",

"name": "非遗小贴士",

"readme": "",

"seller": {

"avatar_url": "https://p9-passport.byteacctimg.com/img/mosaic-legacy/3796/2975850990~300x300.image",

"id": "0",

"name": "dingansich"

},

"status": 1,

"user_info": {

"avatar_url": "https://p9-passport.byteacctimg.com/img/mosaic-legacy/3796/2975850990~300x300.image",

"name": "用户514055857025",

"user_id": "0",

"user_name": "dingansich"

}

}

},

在deepseek中输入提示词：

你是一个Python编程专家，完成一个Python脚本编写的任务，具体步骤如下：

在F盘新建一个Excel文件：cozeaiagent20240619.xlsx

请求网址:

https://www.coze.cn/api/marketplace/product/list?entity_type=1&keyword=&page_num={pagennumber}&page_size=24&sort_type=1&source=1&msToken=8_renFdIfix-XVFJAqAj8F_gSPv1V5A8NX_iL2teO45SBxvZye4AXZv4JiFygZVTPs2LVqZg0CowxYQ9sdwwkxHC3lR41AkwQGefhQr32f7YVvrrl1PS9L1SC_ftRvg%3D&a_bogus=Oym0QfzDdidpDfL655KLfY3qVVa3Y0Ia0SVkMDhe5n3Rt639HMY79exYKs0vM-WjNs%2FDIeEjy4hbYpcQrQcnM1wf7Wsx%2F2CZmyh0t-P2so0j53intL6mE0hN-Jj3SFlm5XNAEOJ0y75aKY00W9oamhK4bfebY7Y6i6trvf%3D%3D

请求方法:

GET

状态代码:

200 OK

{pagenumber}的值从1开始，以1递增，到17结束；

获取网页的响应，这是一个嵌套的json数据；

获取json数据中"data"键的值，然后获取其中"products"键的值，这是一个json数据；

提取这个json数据中 "bot_extra"键的值，然后获取其中"chat_conversation_count"键的值，作为chat_conversation_coun，写入Excel文件的第1列；

提取这个json数据中"meta_info"键的值，这是一个json数据，提取这个json数据中所有的键写入Excel文件的标头（从第2列开始），提取这个json数据中所有键对应的值写入Excel文件的列（从第2列开始）；

保存Excel文件；

注意：每一步都输出信息到屏幕；

每爬取1页数据后暂停5-9秒；

需要对 JSON 数据进行预处理，将嵌套的字典和列表转换成适合写入 Excel 的格式，比如将嵌套的字典转换为字符串；

在较新的Pandas版本中，append方法已被弃用。我们应该使用pd.concat来代替。

要设置请求标头：

请求标头：

Accept:

application/json, text/plain, */*

Accept-Encoding:

gzip, deflate, br, zstd

Accept-Language:

zh-CN,zh;q=0.9,en;q=0.8

Agw-Js-Conv:

str

Priority:

u=1, i

Referer:

https://www.coze.cn/store/bot

Sec-Ch-Ua:

"Google Chrome";v="125", "Chromium";v="125", "Not.A/Brand";v="24"

Sec-Ch-Ua-Mobile:

?0

Sec-Ch-Ua-Platform:

"Windows"

Sec-Fetch-Dest:

empty

Sec-Fetch-Mode:

cors

Sec-Fetch-Site:

same-origin

Traceparent:

03-8de266a364bfbd7d249c9595eec2c7ac-007656cd2d801cbd-01

User-Agent:

Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36

X-Requested-With:

XMLHttpRequest

程序运行，数据爬取下来了，但是有些问题，没有正确写入Excel列，让deepseek修正：

程序把"meta_info"这个json数据中所有的内容写入Excel第2行的，我希望的是把"meta_info"这个json数据中所有的键写入第2行、第3行等的表头，所有键的值写入第2行、第3行。。。

import requests

import pandas as pd

import time

import json

# 请求URL模板

url_template = "https://www.coze.cn/api/marketplace/product/list?entity_type=1&keyword=&page_num={}&page_size=24&sort_type=1&source=1&msToken=8_renFdIfix-XVFJAqAj8F_gSPv1V5A8NX_iL2teO45SBxvZye4AXZv4JiFygZVTPs2LVqZg0CowxYQ9sdwwkxHC3lR41AkwQGefhQr32f7YVvrrl1PS9L1SC_ftRvg%3D&a_bogus=Oym0QfzDdidpDfL655KLfY3qVVa3Y0Ia0SVkMDhe5n3Rt639HMY79exYKs0vM-WjNs%2FDIeEjy4hbYpcQrQcnM1wf7Wsx%2F2CZmyh0t-P2so0j53intL6mE0hN-Jj3SFlm5XNAEOJ0y75aKY00W9oamhK4bfebY7Y6i6trvf%3D%3D"

# 请求头

headers = {

"Accept": "application/json, text/plain, */*",

"Accept-Encoding": "gzip, deflate, br, zstd",

"Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8",

"Agw-Js-Conv": "str",

"Priority": "u=1, i",

"Referer": "https://www.coze.cn/store/bot",

"Sec-Ch-Ua": "\"Google Chrome\";v=\"125\", \"Chromium\";v=\"125\", \"Not.A/Brand\";v=\"24\"",

"Sec-Ch-Ua-Mobile": "?0",

"Sec-Ch-Ua-Platform": "\"Windows\"",

"Sec-Fetch-Dest": "empty",

"Sec-Fetch-Mode": "cors",

"Sec-Fetch-Site": "same-origin",

"Traceparent": "03-8de266a364bfbd7d249c9595eec2c7ac-007656cd2d801cbd-01",

"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36",

"X-Requested-With": "XMLHttpRequest"

}

# 创建Excel文件

file_path = "F:/cozeaiagent20240619.xlsx"

df = pd.DataFrame(columns=["chat_conversation_count"])

# 遍历页码

for page_number in range(1, 18):

url = url_template.format(page_number)

response = requests.get(url, headers=headers)

if response.status_code == 200:

data = response.json()

products = data['data']['products']

for product in products:

chat_conversation_count = product['bot_extra']['chat_conversation_count']

meta_info = product['meta_info']

meta_info_keys = list(meta_info.keys())

meta_info_values = list(meta_info.values())

new_data = pd.DataFrame({

"chat_conversation_count": [chat_conversation_count],

})

for key, value in zip(meta_info_keys, meta_info_values):

new_data[key] = [value]

df = pd.concat([df, new_data], ignore_index=True)

print(f"Page {page_number} processed.")

else:

print(f"Failed to retrieve data from page {page_number}. Status code: {response.status_code}")

# 暂停5-9秒

time.sleep(5 + (page_number % 5))

# 保存Excel文件

df.to_excel(file_path, index=False)

print(f"Data saved to {file_path}")