Using the groundwork of knackpy to combine the fields and the headers, I have added some sorting and date formatting ability in the below script.
(I'm very new to python so any suggestions are gratefully accepted)
## https://github.com/cityofaustin/knackpy from knackpy import Knack import json import pandas as pd from pandas.io.json import json_normalize# download data from Knack
# will fetch records in chunks of 1000 until all records have been downloaded
# optionally pass a rows_per_page and/or page_limit parameter to limit record count
kn = Knack(
obj=‘object_XX’,
app_id=‘REDACTED’,
api_key=‘REDACTED’,
tzinfo=‘Europe/London’,
page_limit=10, # this is the default
rows_per_page=1000 # this is the default
)#Set file paths
offline_filepath = ‘C:/Directory Name/Folder Name/Save Location/’
filename = ‘KNACK_filename here with no ext’#Save the raw JSON file to Drive Backup
with open(offline_filepath+filename+’.json’, ‘w’) as outfile:
json.dump(kn.data, outfile)#Flatten the data
data_df = json_normalize(kn.data,sep="_")#Order the columns
#data_df = data_df[[‘Field ID’,‘Employee’,‘Department’,‘Date of Birth’,‘id’]]
#data_df.sort_values(by=[‘Field ID’], inplace=True)#Convert the date formats from UNIX to Date
#data_df[‘Date of Birth’] = pd.to_datetime(data_df[‘Date of Birth’],unit=‘ms’)
#Convert and export to CSV
#Save to Drive Backup
data_df.to_csv(offline_filepath+filename+’.csv’,index=False,date_format="%Y-%m-%d")