Python: request json gets error - If using all scalar values, you must pass an index

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When attempting to request a json file from API, i have an error after get the first result.

Does anyone have any idea why is requested an index from a list ?

Best regards :)

import requests
import json
import pandas as pd
import time
import datetime

### OCs List ids
OCs = ['1003473-1116-SE21','1003473-1128-AG21','1031866-12-CC21','1057440-3184-AG21','1070620-1832-CM21', '1070620-2219-SE21', '1070620-2499-CM21']

for i in OCs:
    link ="http://api.mercadopublico.cl/servicios/v1/publico/ordenesdecompra.json?codigo="+ str(i) +"&ticket=F8537A18-6766-4DEF-9E59-426B4FEE2844"
    response = requests.get(link, [])
    data = response.json()
    
    df = pd.DataFrame.from_dict(data) 
    
    ### remove unnecessary columns
    df.drop(df.columns[[0,1,2]],axis=1, inplace=True)
         
    ### flat json to pandas dataframe
    df_detail = pd.json_normalize(df['Listado'])



ValueError: If using all scalar values, you must pass an index
python-requests pandas python-3.x list json
1 Answers

The server detects too many requests and sends error response (and then your script throws an error). Solution is to wait for correct response, for example:

import requests
import json
import pandas as pd
import time
import datetime

### OCs List ids
OCs = [
    "1003473-1116-SE21",
    "1003473-1128-AG21",
    "1031866-12-CC21",
    "1057440-3184-AG21",
    "1070620-1832-CM21",
    "1070620-2219-SE21",
    "1070620-2499-CM21",
]

for i in OCs:
    link = (
        "http://api.mercadopublico.cl/servicios/v1/publico/ordenesdecompra.json?codigo="
        + str(i)
        + "&ticket=F8537A18-6766-4DEF-9E59-426B4FEE2844"
    )

    while True:   # <--- repeat until we get correct response
        print(link)
        response = requests.get(link, [])
        data = response.json()

        if "Listado" in data:
            break

        time.sleep(3)   # <--- wait 3 seconds and try again

    df = pd.DataFrame.from_dict(data)

    ### remove unnecessary columns
    df.drop(df.columns[[0, 1, 2]], axis=1, inplace=True)

    ### flat json to pandas dataframe
    df_detail = pd.json_normalize(df["Listado"])

    # ...
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