python获取向上两级路径_【第三弹】python|获取web自行车路径规划数据

import pandas as pd
import requests
import time
import shapefile
import math
#坐标转换&＃xff0c;高德转WGS84
x_pi &＃61; 3.14159265358979324 * 3000.0 / 180.0
pi &＃61; 3.1415926535897932384626 # π
a &＃61; 6378245.0 # 长半轴
ee &＃61; 0.00669342162296594323 # 偏心率平方def gcj02_to_wgs84(lng, lat):"""GCJ02(火星坐标系)转GPS84:param lng:火星坐标系的经度:param lat:火星坐标系纬度:return:"""if out_of_china(lng, lat):return [lng, lat]dlat &＃61; _transformlat(lng - 105.0, lat - 35.0)dlng &＃61; _transformlng(lng - 105.0, lat - 35.0)radlat &＃61; lat / 180.0 * pimagic &＃61; math.sin(radlat)magic &＃61; 1 - ee * magic * magicsqrtmagic &＃61; math.sqrt(magic)dlat &＃61; (dlat * 180.0) / ((a * (1 - ee)) / (magic * sqrtmagic) * pi)dlng &＃61; (dlng * 180.0) / (a / sqrtmagic * math.cos(radlat) * pi)mglat &＃61; lat &＃43; dlatmglng &＃61; lng &＃43; dlngreturn [lng * 2 - mglng, lat * 2 - mglat]def _transformlat(lng, lat):ret &＃61; -100.0 &＃43; 2.0 * lng &＃43; 3.0 * lat &＃43; 0.2 * lat * lat &＃43; 0.1 * lng * lat &＃43; 0.2 * math.sqrt(math.fabs(lng))ret &＃43;&＃61; (20.0 * math.sin(6.0 * lng * pi) &＃43; 20.0 *math.sin(2.0 * lng * pi)) * 2.0 / 3.0ret &＃43;&＃61; (20.0 * math.sin(lat * pi) &＃43; 40.0 *math.sin(lat / 3.0 * pi)) * 2.0 / 3.0ret &＃43;&＃61; (160.0 * math.sin(lat / 12.0 * pi) &＃43; 320 *math.sin(lat * pi / 30.0)) * 2.0 / 3.0return retdef _transformlng(lng, lat):ret &＃61; 300.0 &＃43; lng &＃43; 2.0 * lat &＃43; 0.1 * lng * lng &＃43; 0.1 * lng * lat &＃43; 0.1 * math.sqrt(math.fabs(lng))ret &＃43;&＃61; (20.0 * math.sin(6.0 * lng * pi) &＃43; 20.0 *math.sin(2.0 * lng * pi)) * 2.0 / 3.0ret &＃43;&＃61; (20.0 * math.sin(lng * pi) &＃43; 40.0 *math.sin(lng / 3.0 * pi)) * 2.0 / 3.0ret &＃43;&＃61; (150.0 * math.sin(lng / 12.0 * pi) &＃43; 300.0 *math.sin(lng / 30.0 * pi)) * 2.0 / 3.0return ret
#读取数据
def read_csv(path):file &＃61; pd.read_excel(path,index_col&＃61;[0],encoding&＃61;"utf_8_sig",date_parser&＃61;[1,2,3])file &＃61; pd.DataFrame(file)print(file)return file#提取输入数据
def extract_data(file):#提取输入数据,赋值每个变量origin_lng &＃61; file["ori_lng"]origin_lat &＃61; file["ori_lat"]destination_lng &＃61; file["des_lng"]destination_lat &＃61; file["des_lat"]return origin_lng,origin_lat,destination_lng,destination_lat#发送请求解析数据
def mapping(origin_lng,origin_lat,destination_lng,destination_lat,my_key):l &＃61; []key &＃61; my_keyn &＃61; 0for i in range (len(origin_lat)):n &＃43;&＃61; 1print("已经成功匹配{}条数据".format(n))#构造urlurl &＃61;"https://restapi.amap.com/v4/direction/bicycling?origin&＃61;{},{}&destination&＃61;{},{}&key&＃61;{}"u &＃61; url.format(origin_lng.values[i],origin_lat.values[i],destination_lng.values[i],destination_lat.values[i],key)#发送请求time.sleep(0.2)r &＃61; requests.get(u).json()try:#解析返回返回数据#距离origin &＃61; r["data"].get("origin")o_lnglat &＃61; origin.split(",")destination &＃61; r["data"].get("destination")d_lnglat &＃61; destination.split(",")distance &＃61; r["data"]["paths"][0].get("distance")#耗时duration &＃61; r["data"]["paths"][0]["duration"]step &＃61; r["data"]["paths"][0]["steps"]for j in range (len(step)):#第i条记录&＃xff0c;第j个路段的起始坐标print(step[j])p &＃61; step[j]["polyline"]p1 &＃61; p.split(";")for k in range(len(p1)):p2 &＃61; p1[k].split(",")#添加数据到列表l.append([i,distance,duration,float(p2[0]),float(p2[1]),float(o_lnglat[0]),float(o_lnglat[1]),float(d_lnglat[0]),float(d_lnglat[1])])except:with open(r"./error.txt","a") as f:f.write("{},{},{},{}错误n".format(origin_lng.values[i],origin_lat.values[i],destination_lng.values[i],destination_lat.values[i]))continueresult &＃61; pd.DataFrame(l,columns&＃61;["record","distance","time","lng","lat","origin_lng","origin_lat","destination_lng","destination_lat"])# 转化坐标result["lng84"] &＃61; 0.00result["lat84"] &＃61; 0.00for i in range(len(result)):result["lng84"][i] &＃61; gcj02_to_wgs84(float(result["lng"][i]), float(result["lat"][i]))[0]result["lat84"][i] &＃61; gcj02_to_wgs84(float(result["lng"][i]), float(result["lat"][i]))[1]return result
#储存数据
def save_data(result):result.to_csv(r"./bike_trip.csv",encoding&＃61;"utf-8_sig")print("已完成")def main():path &＃61; r"./OD_bike.xlsx"key &＃61; &＃39;你的key值&＃39;file &＃61; read_csv(path)o_lng,o_lat,d_lng,d_lat &＃61; extract_data(file)print(o_lat.values)result &＃61; mapping(o_lng,o_lat,d_lng,d_lat,key)save_data(result)if __name__ &＃61;&＃61; "__main__":main()