Hi Team, First of all i have review all past thread related to this issue but didn'f found solution. I have created app and also purchase the credit and same has been added in app. then i am trying to fetch historical data for HCLTECH but it gives me permission issue. I have also check after regenerating secret key and access tocken but it still gives me the error. Please find below error code and could u please let me know what is the issue and how we can over come it.
Traceback (most recent call last): File "C:\Users\ci\Desktop\Zerodha\python code\fetch intraday data.py", line 21, in data = kite.historical_data( ^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\ci\AppData\Local\Programs\Python\Python312\Lib\site-packages\kiteconnect\connect.py", line 632, in historical_data data = self._get("market.historical", ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\ci\AppData\Local\Programs\Python\Python312\Lib\site-packages\kiteconnect\connect.py", line 861, in _get return self._request(route, "GET", url_args=url_args, params=params, is_json=is_json) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\ci\AppData\Local\Programs\Python\Python312\Lib\site-packages\kiteconnect\connect.py", line 937, in _request raise exp(data["message"], code=r.status_code) kiteconnect.exceptions.PermissionException: Insufficient permission for that call.
I am using below code..API key and access tocken is set as reference and not actual due to open forum
from kiteconnect import KiteConnect import pandas as pd from datetime import datetime
# Initialize KiteConnect with your API key and access token api_key = "dsfsdfsdfsdfgertgfh" access_token = "sdfsdfsfsd" # Create an instance of KiteConnect and set the access token kite = KiteConnect(api_key=api_key) kite.set_access_token(access_token)
# Define the instrument token for HCL Tech (replace with your actual token) instrument_token = 1850625
# Define the date range for the data from_date = "2024-05-01" # Start date (set to about 2 months ago) to_date = datetime.today().strftime('%Y-%m-%d') # End date (today's date)
# Fetch 5-minute intraday data data = kite.historical_data( instrument_token=instrument_token, from_date=from_date, to_date=to_date, interval="5minute" # 5-minute intervals )
# Convert the data into a DataFrame for easier analysis df = pd.DataFrame(data)
# Display the first few rows to verify the data print(df.head())
# Save to a CSV file for future use df.to_csv("hcltech_intraday_data.csv", index=False)
from kiteconnect import KiteConnect
import pandas as pd
from datetime import datetime
# Initialize KiteConnect with your API key and access token
api_key = "dsfsdfsdfsdfgertgfh"
access_token = "sdfsdfsfsd"
# Create an instance of KiteConnect and set the access token
kite = KiteConnect(api_key=api_key)
kite.set_access_token(access_token)
# Define the instrument token for HCL Tech (replace with your actual token)
instrument_token = 1850625
# Define the date range for the data
from_date = "2024-05-01" # Start date (set to about 2 months ago)
to_date = datetime.today().strftime('%Y-%m-%d') # End date (today's date)
# Fetch 5-minute intraday data
data = kite.historical_data(
instrument_token=instrument_token,
from_date=from_date,
to_date=to_date,
interval="5minute" # 5-minute intervals
)
# Convert the data into a DataFrame for easier analysis
df = pd.DataFrame(data)
# Display the first few rows to verify the data
print(df.head())
# Save to a CSV file for future use
df.to_csv("hcltech_intraday_data.csv", index=False)