python - 将 Census Bulk Geocoder 与 python 请求库一起使用

Question

我正在试验人口普查批量地理编码 API文档

以下 curl 命令有效：

curl --form addressFile=@Addresses.csv --form benchmark=9 http://geocoding.geo.census.gov/geocoder/locations/addressbatch --output geocoderesult.csv

但是当我尝试将其移植到 python 请求时：

url = 'http://geocoding.geo.census.gov/geocoder/geographies/addressbatch'
payload = {'benchmark':9}
files = {'addressFile': ('Addresses.csv', open('Addresses.csv', 'rb'), 'text/csv')}
r = requests.post(url, files=files, data = payload)
print r.text

我显然没有发送格式正确的请求，而只是收到“出现内部错误”作为响应。知道我在形成这个请求时做错了什么吗？

Answer 1

知道了！事实证明，地理请求类型需要一些位置类型不需要的参数。工作解决方案：

url = 'http://geocoding.geo.census.gov/geocoder/geographies/addressbatch'
payload = {'benchmark':'Public_AR_Current','vintage':'ACS2013_Current'}
files = {'addressFile': ('Addresses.csv', open('Addresses.csv', 'rb'), 'text/csv')}
r = requests.post(url, files=files, data = payload)
print r.text

Answer 2

可能这是做同样事情的更简单的方法。

您将在 pandas 数据框中获得干净的输出:)

# pip install censusgeocode    

import censusgeocode
import pandas as pd

cg = censusgeocode.CensusGeocode(benchmark='Public_AR_Census2010',vintage='Census2010_Census2010')
k = cg.addressbatch('D:\WORK\Addresses.csv')

# Bonus
# Get clean output in Dataframe

df = pd.DataFrame(k, columns=k[0].keys())

# PS: I tried with 9990 records in single batch

---

参考：

https://pypi.org/project/censusgeocode/

https://geocoding.geo.census.gov/geocoder/benchmarks

https://geocoding.geo.census.gov/geocoder/vintages?form

https://geocoding.geo.census.gov/geocoder/geographies/addressbatch?form

Answer 3

效果很好。今天我只是使用了下面显示的代码。

url = 'https://geocoding.geo.census.gov/geocoder/locations/addressbatch'
payload = {'benchmark':'Public_AR_Current','vintage':'ACS2013_Current'}
files = {'addressFile': ('19067.csv', open('19067.csv', 'rb'), 'text/csv')}
r = requests.post(url, files=files, data = payload)