yes sir same problem occurs v{'success': False, 'message': 'Invalid Token', 'errorCode': 'AG8001', 'data': ''} please resolve this so we can fetch it using Functions Like SmartAPI.xyz
Prasanna.k
@Prasanna.k
Best posts made by Prasanna.k
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RE: Getting Invalid API Key for Top Gainers API
Latest posts made by Prasanna.k
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RE: Getting Invalid API Key for Top Gainers API
yes sir same problem occurs v{'success': False, 'message': 'Invalid Token', 'errorCode': 'AG8001', 'data': ''} please resolve this so we can fetch it using Functions Like SmartAPI.xyz
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RE: getLtpData Rate limit changed?
@admin123 @admin still getting this error on connection time out
num_threads = 2
delay_between_requests = 0.1 which sends 4 requests but still gets connection time out of my strategy which completes its ops in 90 sec at present it takes more than 280 sec (5 min approx). please resolve this. -
how can i fetch strike price of futures stock
url = "https://margincalculator.angelbroking.com/OpenAPI_File/files/OpenAPIScripMaster.json"
Read the JSON file and store it as a DataFrame
df = pd.read_json(url)
df1 = df[df['exch_seg'] == 'NFO']# retrieve only nfo segmentprint (df1)
df1.to_csv('NFO.csv', index=True)
df2 = df1[(df1['instrumenttype'] == 'FUTSTK') & (df1['expiry'] == '27JUL2023')]#retrive only option stock
df2.to_csv('NFOOPTSTK.csv', index=False)
print (df2)
df2.loc['expiry'] = pd.to_datetime(df2['expiry'] ) #to sort according to expiry
expdt = df2.sort_values('expiry') #to sort according to expiry
print (expdt)
expdt.to_csv('sortedexp.csv', index=False)
Filter the DataFrame based on the condition
assingn_value = df2[(df2['instrumenttype'] == 'FUTSTK')]
tokens = assingn_value['token'].tolist()
symbols = assingn_value['symbol'].tolist()
names = assingn_value['name'].tolist()
instrument_types = assingn_value['instrumenttype'].tolist()
exch_types = assingn_value['exch_seg'].tolist()
lot_size = assingn_value['lotsize'].tolist()print(names, lot_size, symbols)
combined_data = list(zip(tokens, symbols, names, instrument_types, exch_types, lot_size))
print("Combined Data:", combined_data) # Check if combined_data has any data
for row in combined_data:
print(*row)
for one stock or symbol
try:
ltp = smartApi.ltpData('NFO', symbols[1], tokens[1])
print(ltp)
except Exception as e:
print("Error fetching LTP data:", e)
for multiple stock using DF
ltp_data_list = []
try:
for i in range(len(symbols)):
# Assuming the JSON data is returned by smartApi.ltpData function
ltp_data = smartApi.ltpData('NFO', symbols[i], tokens[i])# Extract relevant data from the JSON exchange = ltp_data['data']['exchange'] tradingsymbol = ltp_data['data']['tradingsymbol'] symboltoken = ltp_data['data']['symboltoken'] open_price = ltp_data['data']['open'] high_price = ltp_data['data']['high'] low_price = ltp_data['data']['low'] close_price = ltp_data['data']['close'] ltp = ltp_data['data']['ltp'] lotsize = lot_size[i] # Append data to the list ltp_data_list.append({ 'Exchange': exchange, 'symbol': tradingsymbol, 'Exchange' : exchange, 'token': symboltoken, 'Open': open_price, 'High': high_price, 'Low': low_price, 'Close': close_price, 'LTP': ltp, 'lotsize' :lot_size[i] }) # Optional: print each symbol and LTP # print("Symbol: {} | LTP: {}".format(symbols[i], ltp))
except Exception as e:
print("Error fetching LTP data:", e)Create a DataFrame
ltp_df = pd.DataFrame(ltp_data_list)
print(ltp_df)
ltp_df.to_csv ('ltp.csv', index= False )
filtered_stocks = ltp_df[I will write condition ] I want to fetch strike price of stock how can i