json_normalize a nested database

I'm trying to flatten a json database into pandas dataframe and as it's the first time I'm dealing with json format, I can't do what I want. The database is located here https://mtgjson.com/downloads/all-files/#allprices and according to the model, the structure is like this :

{
  "0120a941-9cfb-50b5-b5e4-4e0c7bd32410": {
    "mtgo": {
      "cardhoarder": {
        "currency": "USD",
        "retail": {
          "foil": {
            ..., // more rows
            "2020-04-21": 0.02
          },
          "normal": {
            ..., // more rows
            "2020-04-21": 0.02
          }
        }
      },
    },
    "paper": {
      "cardkingdom" : {
        "buylist": {
          "foil": {
            ..., // more rows
            "2020-04-21": 0.6
          },
          "normal": {
            ..., // more rows
            "2020-04-21": 0.01
          }
        },
        "currency": "USD",
        "retail": {
          "foil": {
            ..., // more rows
            "2020-04-21": 0.12
          },
          "normal": {
            ..., // more rows
            "2020-04-21": 0.02
          }
        }
      },
      "cardmarket": {
        "currency": "EUR",
        "retail": {
          "foil": {
            ..., // more rows
            "2020-04-21": 0.12
          },
          "normal": {
            ..., // more rows
            "2020-04-21": 0.02
          }
        }
      },
      "tcgplayer": {
        "currency": "USD",
        "retail": {
          "foil": {
            ..., // more rows
            "2020-04-21": 0.12
          },
          "normal": {
            ..., // more rows
            "2020-04-21": 0.02
          }
        }
      }
    }
  }
}

When I look into the json file I have this :

{"meta": {"date": "2021-11-07", "version": "5.1.0+20211107"}, "data": {"00010d56-fe38-5e35-8aed-518019aa36a5": {"paper": {"cardkingdom": {"buylist": {"foil.....

When I do the basic pd.read_json('AllPrices.json') I got this

So I did some research and found the json_normalize and wrote this piece of code :

with open('AllPrices.json','r') as f:
    data = json.loads(f.read())
pd.json_normalize(data, errors='ignore')

This did the job by flattening the json database but I ended with one row and 31 millions columns. What I want is only one information in this database that is the uuid and the cardmarket price of a normal paper card on the date I want like this :

I played with the record_path = parameter and the meta = parameter but the best I did was not my expected table. I tried record_path = ['data'] that give me only the uuid in one column.

Thanks for your help