如何使用 Python 保存对 csv 的 API 响应
How to save API response to csv with Python
我正在以这种形式从 API 获取面部检测数据:
{"id":1,"ageMin":0,"ageMax":100,"faceConfidence":66.72220611572266,"emotion":"ANGRY","emotionConfidence":50.0'
b'2540969848633,"eyeglasses":false,"eyeglassesConfidence":50.38102722167969,"eyesOpen":true,"eyesOpenConfidence":50.20328140258789'
b',"gender":"Male","genderConfidence":50.462989807128906,"smile":false,"smileConfidence":50.15522384643555,"sunglasses":false,"sun'
b'glassesConfidence":50.446510314941406}]'
我想将其保存到这样的 csv 文件中:
id ageMin ageMax faceConfidence
1 0 100 66
...等等。
我试过这样做:
response = requests.get(url, headers=headers)
with open('detections.csv', 'w') as f:
writer = csv.writer(f)
for item in response:
writer.writerow(str(item))
这会将每个字符放在自己的单元格中。我也尝试过使用 item.id
,但出现错误:AttributeError: 'bytes' object has no attribute 'id'
.
有人能给我指出正确的方向吗?
您可以使用 pandas 和 json 库相对轻松地完成此操作。
import pandas as pd
import json
response = """{
"id": 1,
"ageMin": 0,
"ageMax": 100,
"faceConfidence": 66.72220611572266,
"emotion": "ANGRY",
"emotionConfidence": 50.0,
"eyeglasses": false,
"eyeglassesConfidence": 50.38102722167969,
"eyesOpen": true,
"eyesOpenConfidence": 50.20328140258789,
"gender": "Male",
"genderConfidence": 50.462989807128906,
"smile": false,
"smileConfidence": 50.15522384643555,
"sunglasses": false,
"glassesConfidence":50.446510314941406
}"""
file = json.loads(doc)
json = pd.DataFrame({"data": file})
json.to_csv("response.csv")
这是格式为 csv 的响应。
,data
ageMax,100
ageMin,0
emotion,ANGRY
emotionConfidence,50.0
eyeglasses,False
eyeglassesConfidence,50.38102722167969
eyesOpen,True
eyesOpenConfidence,50.20328140258789
faceConfidence,66.72220611572266
gender,Male
genderConfidence,50.462989807128906
glassesConfidence,50.446510314941406
id,1
smile,False
smileConfidence,50.15522384643555
sunglasses,False
对于小任务来说可能有点矫枉过正,但您可以执行以下操作:
将JSON响应(不要忘记检查异常等)转换为python字典
dic = response.json()
创建数据框,例如使用 pandas:
df = pandas.DataFrame(dic)
保存到 csv 省略索引:
df.to_csv('detections.csv', index=False, sep="\t")
我正在以这种形式从 API 获取面部检测数据:
{"id":1,"ageMin":0,"ageMax":100,"faceConfidence":66.72220611572266,"emotion":"ANGRY","emotionConfidence":50.0'
b'2540969848633,"eyeglasses":false,"eyeglassesConfidence":50.38102722167969,"eyesOpen":true,"eyesOpenConfidence":50.20328140258789'
b',"gender":"Male","genderConfidence":50.462989807128906,"smile":false,"smileConfidence":50.15522384643555,"sunglasses":false,"sun'
b'glassesConfidence":50.446510314941406}]'
我想将其保存到这样的 csv 文件中:
id ageMin ageMax faceConfidence
1 0 100 66
...等等。 我试过这样做:
response = requests.get(url, headers=headers)
with open('detections.csv', 'w') as f:
writer = csv.writer(f)
for item in response:
writer.writerow(str(item))
这会将每个字符放在自己的单元格中。我也尝试过使用 item.id
,但出现错误:AttributeError: 'bytes' object has no attribute 'id'
.
有人能给我指出正确的方向吗?
您可以使用 pandas 和 json 库相对轻松地完成此操作。
import pandas as pd
import json
response = """{
"id": 1,
"ageMin": 0,
"ageMax": 100,
"faceConfidence": 66.72220611572266,
"emotion": "ANGRY",
"emotionConfidence": 50.0,
"eyeglasses": false,
"eyeglassesConfidence": 50.38102722167969,
"eyesOpen": true,
"eyesOpenConfidence": 50.20328140258789,
"gender": "Male",
"genderConfidence": 50.462989807128906,
"smile": false,
"smileConfidence": 50.15522384643555,
"sunglasses": false,
"glassesConfidence":50.446510314941406
}"""
file = json.loads(doc)
json = pd.DataFrame({"data": file})
json.to_csv("response.csv")
这是格式为 csv 的响应。
,data
ageMax,100
ageMin,0
emotion,ANGRY
emotionConfidence,50.0
eyeglasses,False
eyeglassesConfidence,50.38102722167969
eyesOpen,True
eyesOpenConfidence,50.20328140258789
faceConfidence,66.72220611572266
gender,Male
genderConfidence,50.462989807128906
glassesConfidence,50.446510314941406
id,1
smile,False
smileConfidence,50.15522384643555
sunglasses,False
对于小任务来说可能有点矫枉过正,但您可以执行以下操作:
将JSON响应(不要忘记检查异常等)转换为python字典
dic = response.json()
创建数据框,例如使用 pandas:
df = pandas.DataFrame(dic)
保存到 csv 省略索引:
df.to_csv('detections.csv', index=False, sep="\t")