Extracting average time series

Question

I have this JSON code that I got from a get request with Azure API. Everything works how I want it but it doesn't look good. There must be an easier way to parse the data.

import json
#GET REQUEST code here, it works now the code below is grabbing the result and loading it.
formatted_response = {'cost': 0, 'timespan': '2020-07-07T03:00:00Z/2020-07-07T03:15:00Z', 'interval': 'TM', 'value': [{'id': '/subscriptions/hjhkjhjljkjknlkjjlkj/Groups/jhkjhjkhjs/providers/Micro/virtualMachines/jhjkhkjhjkhkhljkl/providers/MicInsights/metrics/Percentage CPU', 'type': 'Microsoft.Insights/metrics', 'name': {'value': 'Percentage CPU', 'localizedValue': 'Percentage CPU'}, 'displayDescription': 'The percentage of allocated compute units that are currently in use by the Virtual Machine(s)', 'unit': 'Percent', 'timeseries': [{'metadatavalues': [], 'data': [{'timeStamp': '2020-07-07T03:00:00Z', 'average': 2.4659375}, {'timeStamp': '2020-07-07T03:01:00Z', 'average': 2.974375}, {'timeStamp': '2020-07-07T03:02:00Z', 'average': 2.90265625}, {'timeStamp': '2020-07-07T03:03:00Z', 'average': 1.72484375}, {'timeStamp': '2020-07-07T03:04:00Z', 'average': 1.1275}, {'timeStamp': '2020-07-07T03:05:00Z', 'average': 0.05640625}, {'timeStamp': '2020-07-07T03:06:00Z', 'average': 0.05515625}, {'timeStamp': '2020-07-07T03:07:00Z', 'average': 0.055}, {'timeStamp': '2020-07-07T03:08:00Z', 'average': 0.28765625}, {'timeStamp': '2020-07-07T03:09:00Z', 'average': 0.0546875}, {'timeStamp': '2020-07-07T03:10:00Z', 'average': 0.054375}, {'timeStamp': '2020-07-07T03:11:00Z', 'average': 0.05734375}, {'timeStamp': '2020-07-07T03:12:00Z', 'average': 0.0553125}, {'timeStamp': '2020-07-07T03:13:00Z', 'average': 0.05609375}, {'timeStamp': '2020-07-07T03:14:00Z', 'average': 0.0528125}]}], 'errorCode': 'Success'}], 'namespace': 'Microsoft/virtualMachines', 'resourceregion': 'eastus8'}
p = formatted_response['value']
for i in p:
 for j in i:
 if j == 'timeseries':
 q = i[j]
for l in q:
 for u in l:
 if u =="data":
 g=l['data']
for r in g:
 for s in r:
 if s == "average":
 print(r[s])

$ python testapi.py
2.4659375
2.974375
2.90265625
1.72484375
1.1275
0.05640625
0.05515625
0.055
0.28765625
0.0546875
0.054375
0.05734375
0.0553125
0.05609375
0.0528125

• Colorful Codes: @Peilonrayz Added the output of formatted response above the picture so the code could be tested that way, but now I just put it up top instead so you can run the whole snippet. I just ran it in my terminal and it gave me the output.
• Peilonrayz: Ok so formatted_response was the value not formatted_response['value'] like you had originally said. Yes this outputs the same.

Answer 1

Json should be put in a separate file.

myfile.json

{ "cost":0,
 "timespan":"2020年07月07日T03:00:00Z/2020-07-07T03:15:00Z",
 "interval":"TM",
 "value":[ { "id":"/subscriptions/hjhkjhjljkjknlkjjlkj/Groups/jhkjhjkhjs/providers/Micro/virtualMachines/jhjkhkjhjkhkhljkl/providers/MicInsights/metrics/Percentage CPU",
 "type":"Microsoft.Insights/metrics",
 "name":{
 "value":"Percentage CPU",
 "localizedValue":"Percentage CPU"
 
},
 "displayDescription":"The percentage of allocated compute units that are currently in use by the Virtual Machine(s)",
 "unit":"Percent",
 "timeseries":[ { "metadatavalues":[
 
],
 "data":[ {
 "timeStamp":"2020年07月07日T03:00:00Z",
 "average":2.4659375
 
},
 {
 "timeStamp":"2020年07月07日T03:01:00Z",
 "average":2.974375
 
},
 {
 "timeStamp":"2020年07月07日T03:02:00Z",
 "average":2.90265625
 
},
 {
 "timeStamp":"2020年07月07日T03:03:00Z",
 "average":1.72484375
 
},
 {
 "timeStamp":"2020年07月07日T03:04:00Z",
 "average":1.1275
 
},
 {
 "timeStamp":"2020年07月07日T03:05:00Z",
 "average":0.05640625
 
},
 {
 "timeStamp":"2020年07月07日T03:06:00Z",
 "average":0.05515625
 
},
 {
 "timeStamp":"2020年07月07日T03:07:00Z",
 "average":0.055
 
},
 {
 "timeStamp":"2020年07月07日T03:08:00Z",
 "average":0.28765625
 
},
 {
 "timeStamp":"2020年07月07日T03:09:00Z",
 "average":0.0546875
 
},
 {
 "timeStamp":"2020年07月07日T03:10:00Z",
 "average":0.054375
 
},
 {
 "timeStamp":"2020年07月07日T03:11:00Z",
 "average":0.05734375
 
},
 {
 "timeStamp":"2020年07月07日T03:12:00Z",
 "average":0.0553125
 
},
 {
 "timeStamp":"2020年07月07日T03:13:00Z",
 "average":0.05609375
 
},
 {
 "timeStamp":"2020年07月07日T03:14:00Z",
 "average":0.0528125
 
}
 
]
 
}
 
],
 "errorCode":"Success"
 
}
 
],
 "namespace":"Microsoft/virtualMachines",
 "resourceregion":"eastus8"
}

myfile.py

with open("myfile.json") as file_obj:
 formatted_response = json.load(file_obj)

Use descriptive identifiers for variables.

formatted_response_value = formatted_response['value']

Unnecessary double for loop

formatted_response_value = formatted_response['value']
timeseries = formatted_response_value[0]["timeseries"] #please name something descriptive at all places. 
data = q[0]["data"]
average = list(map(lambda x:x["average"], g))[-1] #or [entry["average"] for entry in g][-1]

• Colorful Codes: Is there a way I can avoid the for loops? it seems excessive.
• Vishesh Mangla: Yep, I was thinking of nested filters. But I 'm trying to understand your code
• Vishesh Mangla: Ask me if you got any confusion without any hesitation.
• Vishesh Mangla: Please upvote the answer if you like it.
• Vishesh Mangla: Thanks:) . Use of map, filter can cut down your loops.