'Efficient way to calculate metrics from nested JSON, via python?
What is the most efficient way to calculate metrics from nested JSON, via python?
Given the JSON blob below, how can I calculate the user (ie profileId) with the most events - without using the pandas library and not having multiple nested for loops? I am having trouble writing the code the would not rely on O(N2).
{
"kind":"admin#reports#activities",
"etag":"\"5g8\"",
"nextPageToken":"A:1651795128914034:-4002873813067783265:151219070090:C02f6wppb",
"items":[
{
"kind":"admin#reports#activity",
"id":{
"time":"2022-05-05T23:59:39.421Z",
"uniqueQualifier":"5526793068617678141",
"applicationName":"token",
"customerId":"cds"
},
"etag":"\"jkYcURYoi8\"",
"actor":{
"email":"[email protected]",
"profileId":"1323"
},
"ipAddress":"107.178.193.87",
"events":[
{
"type":"auth",
"name":"activity",
"parameters":[
{
"name":"api_name",
"value":"admin"
},
{
"name":"method_name",
"value":"directory.users.list"
},
{
"name":"client_id",
"value":"722230783769-dsta4bi9fkom72qcu0t34aj3qpcoqloq.apps.googleusercontent.com"
},
{
"name":"num_response_bytes",
"intValue":"7158"
},
{
"name":"product_bucket",
"value":"GSUITE_ADMIN"
},
{
"name":"app_name",
"value":"Untitled project"
},
{
"name":"client_type",
"value":"WEB"
}
]
}
]
},
{
"kind":"admin#reports#activity",
"id":{
"time":"2022-05-05T23:58:48.914Z",
"uniqueQualifier":"-4002873813067783265",
"applicationName":"token",
"customerId":"df"
},
"etag":"\"5T53xK7dpLei95RNoKZd9uz5Xb8LJpBJb72fi2HaNYM/9DTdB8t7uixvUbjo4LUEg53_gf0\"",
"actor":{
"email":"[email protected]",
"profileId":"1324"
},
"ipAddress":"54.80.168.30",
"events":[
{
"type":"auth",
"name":"activity",
"parameters":[
{
"name":"api_name",
"value":"gmail"
},
{
"name":"method_name",
"value":"gmail.users.messages.list"
},
{
"name":"client_id",
"value":"927538837578.apps.googleusercontent.com"
},
{
"name":"num_response_bytes",
"intValue":"2"
},
{
"name":"product_bucket",
"value":"GMAIL"
},
{
"name":"app_name",
"value":"Zapier"
},
{
"name":"client_type",
"value":"WEB"
}
]
}
]
}
]
}
Solution 1:[1]
This would be a good place to start:
data = # your dict.
ids = [x['actor']['profileId'] for x in data['items']]
print(ids)
Output:
['1323', '1324']
Sources
This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.
Source: Stack Overflow
| Solution | Source |
|---|---|
| Solution 1 | BeRT2me |