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