以下是为远距离恋爱情侣设计的智能见面地点匹配方案，结合地理信息处理与数据筛选技术实现：
方案架构图 graph TD A[获取双方位置] --> B[计算地理中点] B --> C[周边场所搜索] C --> D[多维度筛选] D --> E[智能排序推荐] E --> F[生成可视化报告] 技术实现步骤
- 地理中点计算 from geopy.distance import distance from geopy.point import Point
def calculate_midpoint(lat1, lon1, lat2, lon2): """使用球面几何计算地理中点""" d = distance((lat1, lon1), (lat2, lon2)).km brng = 90 # 方位角设为正东方向 mid_lat = (lat1 + lat2) / 2 mid_lon = lon1 + (d/(111.32 * math.cos(math.radians(mid_lat)))) * math.sin(math.radians(brng)) return (mid_lat, mid_lon) 2. 场所搜索与筛选 import requests
def search_venues(lat, lon, category='cafe', radius=1000): """调用高德地图POI搜索API""" url = "restapi.amap.com/v3/place/ar…" params = { 'key': 'YOUR_API_KEY', 'location': f"{lon},{lat}", 'radius': radius, 'types': category, 'sortrule': 1 # 按评分排序 } response = requests.get(url, params=params) return response.json()['pois']
筛选条件示例
def filter_venues(venues, min_rating=4.0, price_range=[20, 80]):
filtered = []
for v in venues:
if float(v['rating']) >= min_rating and
(price_range[0] <= float(v['biz_ext']['avgPrice']) <= price_range[1]):
filtered.append(v)
return filtered
3. 智能排序算法
import pandas as pd
def rank_venues(filtered_venues):
df = pd.DataFrame(filtered_venues)
# 加权评分模型（可根据偏好调整权重）
df['score'] = 0.4 * df['rating'].astype(float) +
0.3 * (1 / df['distance'].astype(float)) +
0.2 * df['biz_ext'].apply(lambda x: x['commentNum']) +
0.1 * (df['type'].str.contains('网红|特色').astype(int))
return df.sort_values('score', ascending=False).head(5)
4. 可视化输出
import folium
def generate_map(midpoint, ranked_venues):
m = folium.Map(location=midpoint, zoom_start=15)
# 标记中点
folium.Marker(
midpoint,
icon=folium.Icon(color='red', icon='bullseye'),
popup='中点'
).add_to(m)
# 标记推荐场所
for idx, row in ranked_venues.iterrows():
folium.Marker(
[row['latitude'], row['longitude']],
icon=folium.Icon(color='blue', icon='coffee'),
popup=f"{row['name']}
评分：{row['rating']}
人均：{row['biz_ext']['avgPrice']}"
).add_to(m)
return m.save('meeting_point.html')
系统增强功能
1. 交通优化
def get_transit_info(venue_lat, venue_lon): """查询地铁/公交站点距离""" transit_url = "restapi.amap.com/v3/place/te…" params = { 'key': 'YOUR_API_KEY', 'keywords': '地铁站|公交站', 'location': f"{venue_lon},{venue_lat}", 'radius': 500 } response = requests.get(transit_url, params=params) return len(response.json()['pois']) > 0 # 附近有交通站点返回True 2. 时间成本计算 def calculate_time_cost(lat1, lon1, lat2, lon2, venue_lat, venue_lon): """计算双方到达时间""" def get_duration(origin, destination): url = "restapi.amap.com/v3/directio…" params = {'key': 'YOUR_API_KEY', 'origin': origin, 'destination': destination} return requests.get(url, params).json()['route']['paths'][0]['duration']
time1 = get_duration(f"{lat1},{lon1}", f"{venue_lat},{venue_lon}")
time2 = get_duration(f"{lat2},{lon2}", f"{venue_lat},{venue_lon}")
return (time1, time2)
3. 实时天气感知
def get_weather(lat, lon): """查询场所周边天气""" weather_url = "restapi.amap.com/v3/weather/…" params = {'key': 'YOUR_API_KEY', 'city': '上海', 'location': f"{lon},{lat}"} return requests.get(weather_url, params).json()['forecasts'][0]['casts'][0] 部署建议
1. 技术栈选型
◦ 前端：React + Leaflet（实现交互地图）
◦ 后端：Django + Redis（缓存高频查询）
◦ 数据库：PostGIS（存储地理信息）
2. 扩展功能
◦ 支持多地点选择（如双方各选3个偏好区域）
◦ 集成电影票/餐厅预订API
◦ 开发微信小程序实现实时位置共享
3. 数据安全
◦ 使用HTTPS传输位置信息
◦ 对API密钥进行加密存储
◦ 设置IP白名单限制访问
示例输出 { "midpoint": { "latitude": 31.2304, "longitude": 121.4737 }, "recommendations": [ { "name": "梧桐树下咖啡", "rating": 4.8, "price": 58, "distance": 320, "transit": true, "time_cost": ("32min", "28min") }, { "name": "云端书屋咖啡", "rating": 4.6, "price": 65, "distance": 180, "transit": false, "time_cost": ("25min", "35min") } ] } 通过这个系统，情侣不仅能找到地理中点，还能综合考虑场所质量、交通便利性、双方时间成本等因素，让见面更高效浪漫~ 需要具体实现某个模块的代码细节可以告诉我哦！
