#!/bin/python #coding: utf-8 # +------------------------------------------------------------------- # | system: django-vue-lyadmin # +------------------------------------------------------------------- # | Author: lybbn # +------------------------------------------------------------------- # | QQ: 1042594286 # +------------------------------------------------------------------- # ------------------------------ # 经纬度工具类封装 # ------------------------------ from urllib import parse import hashlib import json import math from urllib.request import urlopen import requests from math import radians, cos, sin, asin, sqrt, degrees, atan2 from django.db.models.expressions import RawSQL # ================================================= # # ******************** 根据经度纬度匹配最近的点 ******************** # # ================================================= # def validate_point(lat,lon): assert -90 <= lat <= 90, "bad latitude" assert -180 <= lon <= 180, "bad longitude" # original formula from http://www.movable-type.co.uk/scripts/latlong.html def distance_haversine(lat1, lon1, lat2, lon2): """ Calculate the great circle distance between two points on the earth (specified in decimal degrees) Haversine formula: a = sin²(Δφ/2) + cos φ1 ⋅ cos φ2 ⋅ sin²(Δλ/2) _ ____ c = 2 ⋅ atan2( √a, √(1−a) ) d = R ⋅ c where φ is latitude, λ is longitude, R is earth’s radius (mean radius = 6,371km); note that angles need to be in radians to pass to trig functions! """ validate_point(lat1, lon1) validate_point(lat2, lon2) R = 6371 # km - earths's radius # convert decimal degrees to radians lat1, lon1, lat2, lon2 = map(radians, [lat1, lon1, lat2, lon2]) # haversine formula dlon = lon2 - lon1 dlat = lat2 - lat1 a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2 c = 2 * asin(sqrt(a)) # 2 * atan2(sqrt(a), sqrt(1-a)) d = R * c return d #根据经纬度匹配最近的商家，按distance距离排序 def get_locations_nearby_queryset(queryset,latitude, longitude, max_distance=None): """ Return objects sorted by distance to specified coordinates which distance is less than max_distance given in kilometers queryset 要查询的商家的查询集 latitude 纬度 longitude 经度 max_distance 自定义的最大查询距离：自带单位km """ # Great circle distance formula gcd_formula = "6371 * acos(least(greatest(\ cos(radians(%s)) * cos(radians(latitude)) \ * cos(radians(longitude) - radians(%s)) + \ sin(radians(%s)) * sin(radians(latitude)) \ , -1), 1))" distance_raw_sql = RawSQL( gcd_formula, (latitude, longitude, latitude) ) qs = queryset.annotate(distance=distance_raw_sql).order_by('distance') if max_distance is not None: qs = qs.filter(distance__lt=max_distance) return qs # ================================================= # # ******************** 百度地图详细地址解析成经纬度 ******************** # # ================================================= # ak = 'LYGmcld2pgHXuocf4bqsyHABEfT9lf1B' sk = 'gAaECvBKFjeuLzlwVKNp5r80MRA7zMMe' # 百度地图根据详细地址获取经纬度 def getbaidulnglat(address): # 以get请求为例http://api.map.baidu.com/geocoder/v2/?address=百度大厦&output=json&ak=你的ak queryStr = '/geocoding/v3/?address=%s&output=json&ak=%s' % (address,ak) # 对queryStr进行转码，safe内的保留字符不转换 encodedStr = parse.quote(queryStr, safe="/:=&?#+!$,;'@()*[]") # 在最后直接追加上yoursk rawStr = encodedStr + sk # 计算sn sn = (hashlib.md5(parse.quote_plus(rawStr).encode("utf8")).hexdigest()) # 由于URL里面含有中文，所以需要用parse.quote进行处理，然后返回最终可调用的url uri = parse.quote("http://api.map.baidu.com" +queryStr +"&sn=" +sn, safe="/:=&?#+!$,;'@()*[]") # print(uri) try: req = urlopen(uri) res = req.read().decode() temp = json.loads(res) # print(temp) # 纬度 lat = temp['result']['location']['lat'] # 经度 lng = temp['result']['location']['lng'] # 地址查找失败 if math.isclose(lat, 39.910925, rel_tol=1e-5): lat = None if math.isclose(lng, 116.413384, rel_tol=1e-5): lng = None except Exception as e: # print(e) lng = None lat = None return {'lng':lng,'lat':lat} def computeMD5(message): m = hashlib.md5() m.update(message.encode(encoding='utf-8')) return m.hexdigest() # ================================================================= # # ******************** 腾讯地图详细地址解析成经纬度 ******************** # # =================================================================# #限制 10,000 次/日 #限制 并发 5 次/秒 key = "M4NBZ-STTK5-OARIA-Q7T4R-YO5OQ-MTB7O" secretkey='uCUAQVJKvx5OgvHuOYK5uFzI0CdisBvm' def gettecentlnglat(address): # url = 'https://apis.map.qq.com/ws/geocoder/v1/?address='+address+'&key='+key queryStr1 = '/ws/geocoder/v1/' queryStr2 = 'address='+address+'&key='+key # 计算sig sig = computeMD5(queryStr1+'?'+queryStr2+secretkey) url = 'https://apis.map.qq.com'+queryStr1+'?'+queryStr2+'&sig='+sig try: response = requests.get(url) res = response.json() # print(res) # 纬度 lat = res['result']['location']['lat'] # 经度 lng = res['result']['location']['lng'] except Exception as e: lng = None lat = None return {'lng': lng, 'lat': lat} # { # "status": 0, # "message": "query ok", # "result": { # "title": "海淀西大街74号", # "location": { # "lng": 116.307015, # "lat": 39.982915 # }, # "ad_info": { # "adcode": "110108" # }, # "address_components": { # "province": "北京市", # "city": "北京市", # "district": "海淀区", # "street": "海淀西大街", # "street_number": "74" # }, # "similarity": 0.8, # "deviation": 1000, # "reliability": 7, # "level": 9 # } # } # ========================================================================= # # ******************** 腾讯地图逆地址解析-经纬度解析成地址信息 ******************** # # =========================================================================# def gettecentaddress(location): """ location=lat<纬度>,lng<经度> 例如：location= 39.984154,116.307490 """ # url = 'https://apis.map.qq.com/ws/geocoder/v1/?address='+address+'&key='+key queryStr1 = '/ws/geocoder/v1/' queryStr2 = 'key='+key+'&location='+location # 计算sig sig = computeMD5(queryStr1+'?'+queryStr2+secretkey) url = 'https://apis.map.qq.com'+queryStr1+'?'+queryStr2+'&sig='+sig try: response = requests.get(url) res = response.json() # print(res) except Exception as e: res=None return res