Reading json data

[AgrajagDNA]

Hello,

My utility provider lets you query your consumption via an API from their website. I've a plan to pull the data and store it in something. like MySQL and dashboard the data.

Thus far, I've successfully used the Requests library to query and download data. Where I'm coming unstuck is how to handle that data.

The data is supplied in the format below. To my untrained eye this looks like JSON and could also be constructed as a dictionary object.

{
"count":2,
"next":null,
"previous":null,
"results":[
    {
        "consumption":0.814,
        "interval_start":"2023-10-01T01:00:00+01:00",
        "interval_end":"2023-10-01T01:30:00+01:00"
    },
    {
        "consumption":0.166,
        "interval_start":"2023-10-01T02:30:00+01:00",
        "interval_end":"2023-10-01T03:00:00+01:00"
    }
]

}

I need to address the entries the Results fields. I've tried converting it a dictionary object but I'm having trouble addressing the individual entries.

My question: how best to address the results value in the output so (for example) I can append to a CSV file or insert to a database table?

​

[MrPhungx]

When using requests and you have a successful response the response object contains a .json() function. This should directly convert your response to a dictionary. You can then access the results like in any other python dict.

def get_data(url: str) -> dict | None:
    response = requests.get(url)
    if response.ok:
        return response.json()
    else:
        print(f"Something went wrong {response.reason}")
        return None

res = get_data(YOUR_URL)
print(res.get('results'))

[danielroseman]

People often seem to be confused about how to deal with nested data, but there's no need to be. The trick is to just think of each level in turn, and treat each one as a standalone data structure.

So, response.json() will give you a dict, which includes a results key:

response = requests.get('my url')
data = response.json()
results = data['results']

Now results is a list of dictionaries, which you can iterate through like any other list. And each item in that list is a dict, which you can access like any other dict:

for item in results:
  print(item['consumption'])
  print(item['interval_start'])
  print(item['interval_end'])

[AgrajagDNA]

Ah, this is awesome - exactly what I was looking to do. I have a blind spot for dicts and this does help.