如何使用 python 中的分组键将 OrderedDict 列表转换为嵌套 json

Question

I'm working on a project where I need to convert a set of data rows from database into list of OrderedDict for other purpose and use this list of OrderedDict to convert into a nested JSON format in python . I'm starting to learn python. I was able convert the query response from database which is a list of lists to list of OrderedDict .

I have the list of OrderedDict as below:

    {
'OUTBOUND': [
OrderedDict([('Leg', 1), ('SessionID', 'W12231fwfegwcaa2'),('FeeCode', 'ATO'),('SeatGroup', '2'),
               ('Currency', 'MXN'),('Modality', 'VB'),('BookingClass', 'A'),('Price', 145.0),('Num_Pax', 1),('Channel', 'Web')]),
  OrderedDict([('Leg', 1),('SessionID', 'W12231fwfegwcaa2'),('FeeCode', 'ATO'),('SeatGroup', '4'),
               ('Currency', 'MXN'),('Modality', 'VB'),('BookingClass', 'A'),('Price', 111.0),('Num_Pax', 1),('Channel', 'Web')]),
  OrderedDict([('Leg', 1),('SessionID', 'W12231fwfegwcaa2'),('FeeCode', 'BDM'),('SeatGroup', 'null'),
               ('Currency', 'MXN'),('Modality', 'VB'),('BookingClass', 'A'),('Price', 111.0),('Num_Pax', 1),('Channel', 'Web')]),
  OrderedDict([('Leg', 2),('SessionID', 'W12231fwfegwcaa2'),('FeeCode', 'ATO'),('SeatGroup', '1'),
                ('Currency', 'MXN'),('Modality', 'VB'),('BookingClass', 'U'),('Price', 180.0),('Num_Pax', 1),('Channel', 'Web'))]),
  OrderedDict([('Leg', 2),('SessionID', 'W12231fwfegwcaa2'),('FeeCode', 'ATO'),('SeatGroup', '4'),
                ('Currency', 'MXN'),('Modality', 'VB'),('BookingClass', 'U'),('Price', 97.0),('Num_Pax', 1),('Channel', 'Web')]),
  OrderedDict([('Leg', 2),('SessionID', 'W12231fwfegwcaa2'),('FeeCode', 'BDM'),('SeatGroup', 'null'),
                ('Currency', 'MXN'),('Modality', 'VB'),('BookingClass', 'U'),('Price', 97.0),('Num_Pax', 1),('Channel', 'Web')])
            ]
}

And I needed the nested format like below:

{
"OUTBOUND": [
    {
      "Leg": 1,
      "SessionID": "W12231fwfegwcaa2",
      "Modality": "VB",
      "BookingClass": "A",
      "FeeCodes":[
                    {
                        "FeeCode": "ATO",
                        "Prices":
                        [
                            {
                                "SeatGroup": "2",
                                "Price": 145.0,
                                "Currency": "MXN"
                            },
                            {
                                "SeatGroup": "4",
                                "Price": 111.0,
                                "Currency": "MXN"
                            }
                        ]
                    },
                    {
                        "FeeCode": "VBABDM",                
                        "Prices":
                        [ 
                            {
                                "SeatGroup": "null",
                                "Price": 111.0,
                                "Currency": "MXN"                   
                            }
                        ]
                    }
                ],
      "Num_Pax": 1,
      "Channel": "Web"
    },
    {
      "Leg": 2,
      "SessionID": "W12231fwfegwcaa2",
      "Modality": "VB",
      "BookingClass": "U",
      "FeeCodes":[
                    {
                        "FeeCode": "ATO",
                        "Prices":
                        [
                            {
                                "SeatGroup": "1",
                                "Price": 180.0,
                                "Currency": "MXN"
                            },
                            {
                                "SeatGroup": "4",
                                "price": 97.0,
                                "Currency": "MXN"
                            }
                        ]
                    },
                    {
                        "FeeCode": "VBABDM",                
                        "Prices":
                        [ 
                            {
                                "SeatGroup": "null",
                                "price": 97.0,
                                "Currency": "MXN"                   
                            }
                        ]
                    }
                ],
      "Num_Pax": 1,
      "Channel": "Web"
    }
    ]
}

If I'm not wrong, I need to group by Leg , SessionID , Modality , BookingClass , NumPax and Channel and group the FeeCode , SeatGroup , Price and Currency into nested format as above but unable to move ahead with how to loop and group for nesting.

It would be great if I could get some help. Thanks

Answer 1

I was able to write a python code to get the format as I needed using simple looping with a couple of changes in the output like the fields SessionID, Num_Pax and Channel is taken outside then the OUTBOUND field and fields within are generated.

Instead of OrderedDict, I used a list of lists as input which I convert into Pandas DataFrame and work with the DataFrame to get the nested format.

Below is the code I used:

outbound_df = pd.DataFrame(response_outbound,columns=All_columns)
Common_columns = ['Leg', 'Modality', 'BookingClass']

### Taking SessionID, AirlineCode,Num_Pax and Channel outside OUTBOUND part as they are common for all the leg level data
response_data['SessionID'] = outbound_df['SessionID'].unique()[0]   
response_data['Num_Pax'] = int(outbound_df['Num_Pax'].unique()[0])
response_data['Channel'] = outbound_df['Channel'].unique()[0]

temp_data = []
Legs = outbound_df['Leg'].unique()

for i in Legs:
    subdata = outbound_df[outbound_df['Leg']==i]
    
    ### Initializing leg_data dict
    leg_data = collections.OrderedDict()
        
    ### Populating common fields of the leg (Leg, Modality,BookingClass)
    for j in Common_columns: 
        if(j=='Leg'):
            leg_data[j] = int(subdata[j].unique()[0])
        else:
            leg_data[j] = subdata[j].unique()[0]
    
    leg_data['FeeCodes'] = []
    FeeCodes = subdata['FeeCode'].unique()
    
    for fc in FeeCodes:
        subdata_fees = subdata[subdata['FeeCode']==fc]
        
        Prices = {'FeeCode':fc, "Prices":[]}
        
        for _,rows in subdata_fees.iterrows():
            data = {}
            data['SeatGroup'] = rows['SeatGroup']
            data['Price'] = float(rows['Price'])
            data['Currency'] = rows['Currency']
            
            Prices["Prices"].append(data)
        
        leg_data["FeeCodes"].append(Prices)
    temp_data.append(leg_data)

response_data["OUTBOUND"] = temp_data

I can just do json.dumps on response_data to get json format which will be sent to the next steps.

Below is the output format I get:

{
   "SessionID":"W12231fwfegwcaa2",
   "Num_Pax":1,
   "Channel":"Web",
   "OUTBOUND":[
      {
         "Leg":1,
         "Modality":"VB",
         "BookingClass":"A",
         "FeeCodes":[
            {
               "FeeCode":"ATO",
               "Prices":[
                  {
                     "SeatGroup":"2",
                     "Price":145.0,
                     "Currency":"MXN"
                  },
                  {
                     "SeatGroup":"4",
                     "Price":111.0,
                     "Currency":"MXN"
                  }
               ]
            },
            {
               "FeeCode":"VBABDM",
               "Prices":[
                  {
                     "SeatGroup":"null",
                     "Price":111.0,
                     "Currency":"MXN"
                  }
               ]
            }
         ]
      },
      {
         "Leg":2,
         "Modality":"VB",
         "BookingClass":"U",
         "FeeCodes":[
            {
               "FeeCode":"ATO",
               "Prices":[
                  {
                     "SeatGroup":"1",
                     "Price":180.0,
                     "Currency":"MXN"
                  },
                  {
                     "SeatGroup":"4",
                     "price":97.0,
                     "Currency":"MXN"
                  }
               ]
            },
            {
               "FeeCode":"VBABDM",
               "Prices":[
                  {
                     "SeatGroup":"null",
                     "price":97.0,
                     "Currency":"MXN"
                  }
               ]
            }
         ]
      }
   ]
}

Please let me know if we can shorten the code in terms of lengthy iterations or any other changes. Thanks. PS: Sorry for my editing mistakes

Answer 2

Assuming that you stored the dictionary to some variable foo , you can do:

import json

json.dumps(foo)

And be careful, you added extra bracket in the 4th element OUTBOUND list