Question

我很难通过Google Maps Geocoder每秒增加请求量。我使用的是付费帐户（费用为$ .50 / 1000），因此根据Google Geocoder API，我每秒最多可以提出50个请求。

我有一个15k地址列表，我正在尝试获取GPS坐标。我将它们存储为Pandas Dataframe并循环遍历它们。为了确保这不是由于慢速循环，我测试了它在所有15k上的循环速度，并且它只花了1.5秒。但我每秒只能做少于1个请求。我意识到这可能是由于我的互联网连接速度缓慢，所以我发布了一个具有明显快速互联网的Windows Google Cloud VM。我能够将请求加速到大约1.5个请求/秒，但仍然比理论上慢。

我认为这可能是因为使用了python库Geocoder，所以我尝试使用python请求直接发出请求，但这并没有加快速度。

这是否与我不使用服务器的事实有关？我认为这不重要，因为我使用的是Google Cloud VM。另外，我知道这与多线程没有关系，因为它已经可以使用1个核心以极快的速度迭代循环。提前感谢任何想法。

import geocoder
import pandas as pd
import time
import requests


startTime = time.time()
#Read File Name with all transactions up to October 4th
input_filename = "C:/Users/username/Downloads/transaction-export 10-04-2017.csv"
df = pd.read_csv(input_filename, header=0, error_bad_lines=False)
#Only look at customer addresses
df = df['Customer Address']
#Drop duplicates and NAs
df = df.drop_duplicates(keep='first')
df = df.dropna()
#convert dataframe to string
addresses = df.tolist()
#Google Api Key
api_key = 'my_api_key'
#create empty array
address_gps = []
#google api address
url = 'https://maps.googleapis.com/maps/api/geocode/json'
#For each address return its geocoded latlng coordinates
for int, val in enumerate(addresses):
    ''' Direct way to make call without geocoder
    params = {'sensor': 'false', 'address': address, 'key': api_key}
    r = requests.get(url, params=params)
    results = r.json()['results']
    location = results[0]['geometry']['location']
    print location['lat'], location['lng']
    num_address = num_address+1;
    '''
    endTime = time.time()
    g = geocoder.google(val, key=api_key,  exactly_one=True)
    print "Address,", (val), "Number,", int, "Total,", len(addresses), "Time,", endTime-startTime

    if g.ok:
        address_gps.append(g.latlng)
        print g.latlng
    else:
        address_gps.append(0)
        print("Error")
    #save every 100 iterations
    if int%100==0:
        # save as csv
        df1 = pd.DataFrame({'Address GPS': address_gps})
        df1.to_csv('C:/Users/username/Downloads/AllCustomerAddressAsGPS.csv')


# save as csv
df1 = pd.DataFrame({'Address GPS': address_gps})
df1.to_csv('C:/Users/username/Downloads/AllCustomerAddressAsGPS.csv')

Answer 1

提高速度的一种方法是维持与Google的请求会话，而不是为每个请求创建一个新会话。这在geocoder documentation中得到了建议。

您修改后的代码将为：

import requests

#Google Api Key
api_key = 'my_api_key'
#create empty array
address_gps = []
#google api address
url = 'https://maps.googleapis.com/maps/api/geocode/json'
#For each address return its geocoded latlng coordinates
with requests.Session() as session:
    for int, val in enumerate(addresses):
        ''' Direct way to make call without geocoder
        params = {'sensor': 'false', 'address': address, 'key': api_key}
        r = requests.get(url, params=params)
        results = r.json()['results']
        location = results[0]['geometry']['location']
        print location['lat'], location['lng']
        num_address = num_address+1;
        '''
        endTime = time.time()
        g = geocoder.google(val, key=api_key,  exactly_one=True, session=session)
        print "Address,", (val), "Number,", int, "Total,", len(addresses), "Time,", endTime-startTime

        if g.ok:
            address_gps.append(g.latlng)
            print g.latlng
        else:
            address_gps.append(0)
            print("Error")
        #save every 100 iterations
        if int%100==0:
            # save as csv
            df1 = pd.DataFrame({'Address GPS': address_gps})
            df1.to_csv('C:/Users/username/Downloads/AllCustomerAddressAsGPS.csv')

# save as csv
df1 = pd.DataFrame({'Address GPS': address_gps})
df1.to_csv('C:/Users/username/Downloads/AllCustomerAddressAsGPS.csv')

增加请求/第二个Python Google Maps Geocoder

1 个答案: