Dianping API#

Zero-dependency HTTP API for dianping.com (大众点评). No browser engine, no pip install — only curl (pre-installed on macOS/Linux).

Prerequisites#

• Python 3.6+
• curl (系统自带，无需安装)

Authentication (only 2 cookies needed)#

Only dper and dplet cookies are required. Stored in ~/.dianping/cookies.json.

bash

# Set cookies
python3 dianping-api/scripts/dianping_login.py --set-cookies "dper=xxx; dplet=yyy"

# Check login status
python3 dianping-api/scripts/dianping_login.py --status

# Cookie expired? Guided renewal:
python3 dianping-api/scripts/dianping_login.py --renew

API Reference — dianping_api.py#

All commands output JSON to stdout, ready for AI parsing.

1. Search Shops#

bash

python3 dianping-api/scripts/dianping_api.py search <keyword> [--city_id N]

• keyword: 大众点评搜索框，支持自由组合。示例：

  • 菜系: "川菜", "日料", "淮扬菜", "火锅", "西餐"
  • 地点+菜系: "外滩 日料", "陆家嘴 火锅", "世纪大道 淮扬菜"
  • 景点+场景: "迪士尼 亲子餐厅", "故宫 烤鸭", "西湖 本帮菜"
  • 特殊需求: "有包厢", "宝宝餐", "人均100", "深夜食堂"
  • 综合: "陆家嘴 亲子 好评", "南京路 网红甜品"

• city_id: 城市编号（见下方城市表），默认 1=上海

Response:

json

{
  "keyword": "世纪大道淮扬菜",
  "city_id": 1,
  "count": 11,
  "shops": [
    {
      "shop_id": "l7UgWvw6yZ7ytaly",
      "name": "九厨·淮扬(陆家嘴紫金山店)",
      "rating": 4.5,
      "review_count": "455",
      "avg_price": 155
    }
  ]
}

2. Shop Details#

bash

python3 dianping-api/scripts/dianping_api.py shop <shop_id>

Response:

json

{
  "shop_id": "l7UgWvw6yZ7ytaly",
  "name": "九厨·淮扬(陆家嘴紫金山店)",
  "score_text": "口味:4.7 环境:4.8 服务:4.7",
  "avg_price": "155",
  "review_count": "455条",
  "category": "淮扬菜",
  "region": "世纪大道",
  "address": "东方路778号金陵紫金山大酒店2楼",
  "route": "距地铁世纪大道站12口步行400m",
  "phone": "65******",
  "recommended_dishes": ["九厨桂花香酥烤鸭", "淮安特色一品狮子头", "..."],
  "scores": {"taste": 4.7, "environment": 4.8, "service": 4.7}
}

3. Deals / Coupons#

bash

python3 dianping-api/scripts/dianping_api.py deals <shop_id>

Response:

json

{
  "shop_id": "l7UgWvw6yZ7ytaly",
  "name": "九厨·淮扬(陆家嘴紫金山店)",
  "deals": [
    {"title": "【午市专享】100元代金券", "price": 79.0, "original_price": 100.0},
    {"title": "九厨淮扬精选宝宝餐", "price": 0.1, "original_price": 29.9},
    {"title": "招牌烤鸭+醉沼虾+牛肉粒2-3人餐", "price": 279.0, "original_price": 500.0}
  ],
  "services": [],
  "tags": []
}

Python Import Usage#

python

import sys; sys.path.insert(0, "dianping-api/scripts")
from dianping_api import api_search, api_shop, api_deals

# Search
results = api_search("陆家嘴火锅", city_id=1)
for s in results["shops"]:
    print(s["shop_id"], s["name"], s.get("rating"))

# Shop detail
info = api_shop("l7UgWvw6yZ7ytaly")
print(info["scores"], info["recommended_dishes"])

# Deals
deals = api_deals("l7UgWvw6yZ7ytaly")
for d in deals["deals"]:
    print(d["title"], d.get("price"), d.get("original_price"))

Typical AI Workflow#

text

1. 根据用户意图组合 keyword（地点+菜系+场景），选对 city_id
   例: 用户说"北京故宫附近吃烤鸭" → search("故宫 烤鸭", city_id=2)
   例: 用户说"上海迪士尼带娃吃饭" → search("迪士尼 亲子餐厅", city_id=1)
   例: 用户说"杭州西湖附近日料"   → search("西湖 日料", city_id=5)

2. api_search(keyword, city_id) → 拿到 shop_id 列表
3. api_shop(shop_id)            → 评分、推荐菜、地址、交通
4. api_deals(shop_id)           → 优惠券、套餐、价格
5. 整理推荐给用户（含评分、人均、推荐菜、优惠信息）

City IDs#

城市ID城市ID城市ID城市ID上海1北京2大连3广州4杭州5苏州6深圳7成都8南京9天津10沈阳11武汉12哈尔滨13长沙14厦门15郑州16西安17青岛18重庆19昆明20

Error Handling#

All errors return {"error": "..."}. Common:

• "请求失败或需要重新登录" → Run dianping_login.py --renew

Architecture#

• Backend: Pure HTTP via curl subprocess (no Playwright/browser, no pip dependencies)
• Auth: dper + dplet cookies in ~/.dianping/cookies.json
• Scripts: dianping_login.py (auth管理) + dianping_api.py (数据API)