Error while converting json file to a csv file

I have many json files (example below), I am interested in converting these json to a table version in the csv file format [example below] with the help of python script from jupyter notebook provided my one of my collaborator [example below]. The notebook works on extracting one gene_name along with summary, and scores, but I am looking to extract two gene_name columns. Primarily, from the json file, I am interested in extracting the "gene_name" field, and make it as two separate columns such as gene_name_A, and gene_name_B, Summary_Gene_A, and Summary_Gene_B from "brief_summary" field, and scores for all the 6 statements in json file (well_characterized, "biology", cancer", tumor, drug_targets, clinical_marker).

Error:

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Cell In[4], line 76
     74     print (k)
     75     q1 = json.load(open(k,'r'))
---> 76     tmpDF = get_qScore(q1,mainkey_qFLU, subkey=subkey_name)
     77     q1_DF = pd.concat([q1_DF,tmpDF],axis=0)
     79 print (q1_DF.shape)

Cell In[4], line 60, in get_qScore(q, question_dict, subkey)
     58 q_scores = []
     59 for gname in q.keys():
---> 60     for model in q[gname].keys():
     61         kx = convert_stringtodict(q[gname][model],question_dict)
     62         kx.update({'gene_name':gname,
     63                     'runID':model,
     64                     "model_version":model.lstrip("datasvc-openai-paluckalab-poc-").split("_")[0],
     65                     "subjectKey":subkey,})

AttributeError: 'int' object has no attribute 'keys'

Example json file:

{
    "KAT2A": {
        "official_gene_symbol": "KAT2A",
        "brief_summary": "KAT2A, also known as GCN5, is a histone acetyltransferase that plays a key role."
    },
    "E2F1": {
        "official_gene_symbol": "E2F1",
        "brief_summary": "E2F1 is a member of the E2F family of transcription factors."
    },
    "The genes encode molecules that are well characterized protein-protein pairs": 7,
    "The protein-protein pair is relevant to biology": 8,
    "The protein-protein pair is relevant to cancer": 3,
    "The protein-protein pair is relevant to interactions between tumor": 4,
    "One or both of the genes are known drug targets": 5,
    "One or both of the genes are known clinical marker": 6
}

Example expected csv file:

#>   gene_name_A gene_name_B               Summary_Gene_A
#> 1       KAT2A        E2F1   KAT2A, also known as GCN5.
#> 2       KRT30       KRT31 Keratin 30 is a cytokeratin.
#>                                         Summary_Gene_B well_characterized
#> 1 E2F1 is a member of the E2F family of transcription.                  7
#> 2                         Keratin 31 is a cytokeratin.                  7
#>   Biology Cancer Tumor drug_targets clinical_biomarkers
#> 1       8      3     4            5                   6
#> 2       8      2     3            1                   5

Jupyter notebook

# test azure
import sys, time, json
# from openai import OpenAI
import pandas as pd
import re
from glob import glob
# define key dictionary for each question for concrete formatting

mainkey_qFLU = {'summary':'Summary',
                'well characterized':'well_characterized',
                'biology':'Biology',
                'cancer':'Cancer',
                'tumor':'tumor',
                'drug targets':'drug_targets',
                'clinical markers':'clinical_markers'
               }


def find_keyword(sline, keyLib):
    for mk in keyLib.keys():

        # Regular expression pattern to find all combinations of the letters in 'gene'
        pattern = r'{}'.format(mk)

        # Finding all matches in the sample text
        matches = re.findall(pattern, sline, re.IGNORECASE)
        if matches:
            return keyLib[mk]
        else:
            next
    return False



def convert_stringtodict(lines, keylib):
    dict_line = {}
    for k in lines:
        ksplit = k.split(":")

        if len(ksplit) ==2:
            key_tmp = find_keyword(ksplit[0].strip("'|"|', |").strip(), keylib)
            val_tmp = ksplit[1].strip("'|"|',|{|} ").strip()
            if key_tmp and val_tmp:
                if key_tmp == "Summary":
                    dict_line[key_tmp] = val_tmp
                else:
                    try:
                        dict_line[key_tmp] = float(val_tmp)
                    except:
                        dict_line[key_tmp] = 0
            else:
                next
                # print ("error in ", ksplit)

    return dict_line

def get_qScore(q, question_dict, subkey):
    q_scores = []
    for gname in q.keys():
        for model in q[gname].keys():
            kx = convert_stringtodict(q[gname][model],question_dict)
            kx.update({'gene_name':gname,
                        'runID':model,
                        "model_version":model.lstrip("datasvc-openai-testinglab-poc-").split("_")[0],
                        "subjectKey":subkey,})
            q_scores.append(kx)
    print (len(q_scores))
    return pd.DataFrame(q_scores)


q1_DF = pd.DataFrame()
for k in glob("/Users/Documents/Projects/json_files/*.json"):
    subkey_name = "-".join(k.split("/")[-1].split("_")[1:3])
    print (k)
    q1 = json.load(open(k,'r'))
    tmpDF = get_qScore(q1,mainkey_qFLU, subkey=subkey_name)
    q1_DF = pd.concat([q1_DF,tmpDF],axis=0)

print (q1_DF.shape)

q1_DF.to_csv("./Score_parse_1_2.csv")

``





I tried using the jupyter notebook [code mentioned above] that works on extracting one gene_name along with summary, and scores, but I am looking to extract two gene_name columns.