error

swathi priya

from SmartApi import SmartConnect
import os
import urllib
import json
import pandas as pd
import time
from pyotp import TOTP

key_path = r"C:\Users\kswat\angelone"
os.chdir(key_path)

key_secret = open("angeloneapi.txt","r").read().split()
obj=SmartConnect(api_key=key_secret[0])
data = obj.generateSession(key_secret[2],key_secret[3],TOTP(key_secret[4]).now())

instrument_url = "https://margincalculator.angelbroking.com/OpenAPI_File/files/OpenAPIScripMaster.json"
response = urllib.request.urlopen(instrument_url)
instrument_list = json.loads(response.read())

tickers = ["WIPRO","ULTRACEMCO","UPL","TITAN","TECHM","TATASTEEL","TATAMOTORS",
"TATACONSUM","TCS","SUNPHARMA","SBIN","SBILIFE","RELIANCE","POWERGRID",
"ONGC","NESTLEIND","NTPC","MARUTI","M&M","LT","KOTAKBANK","JSWSTEEL",
"INFY","INDUSINDBK","ITC","ICICIBANK","HINDUNILVR","HINDALCO",
"HEROMOTOCO","HDFCLIFE","HDFCBANK","HCLTECH","GRASIM","EICHERMOT",
"DRREDDY","DIVISLAB","COALINDIA","CIPLA","BRITANNIA","BHARTIARTL",
"BPCL","BAJAJFINSV","BAJFINANCE","BAJAJ-AUTO","AXISBANK","ASIANPAINT",
"APOLLOHOSP","ADANIPORTS","ADANIENT"]

bktst_start_dt = "2021-06-01 09:15"
bktst_end_dt = "2022-10-21 15:30"

def token_lookup(ticker, instrument_list, exchange="NSE"):
for instrument in instrument_list:
if instrument["name"] == ticker and instrument["exch_seg"] == exchange and instrument["symbol"].split('-')[-1] == "EQ":
return instrument["token"]

def symbol_lookup(token, instrument_list, exchange="NSE"):
for instrument in instrument_list:
if instrument["token"] == token and instrument["exch_seg"] == exchange and instrument["symbol"].split('-')[-1] == "EQ":
return instrument["name"]

def hist_data_daily(tickers,instrument_list,exchange="NSE"):
hist_data_tickers = {}
for ticker in tickers:
time.sleep(0.3)
params = {
"exchange": exchange,
"symboltoken": token_lookup(ticker,instrument_list),
"interval": "ONE_DAY",
"fromdate": bktst_start_dt,
"todate": bktst_end_dt
}
hist_data = obj.getCandleData(params)
df_data = pd.DataFrame(hist_data["data"],
columns = ["date","open","high","low","close","volume"])
df_data.set_index("date",inplace=True)
df_data.index = pd.to_datetime(df_data.index)
df_data.index = df_data.index.tz_localize(None)
df_data["gap"] = ((df_data["open"]/df_data["close"].shift(1))-1)*100
df_data["avvol"] = df_data["volume"].rolling(10).mean().shift(1)
hist_data_tickers[ticker] = df_data
return hist_data_tickers

def hist_data_intraday(ticker,datestamp,interval,instrument_list,exchange="NSE"):
params = {
"exchange": exchange,
"symboltoken": token_lookup(ticker,instrument_list),
"interval": interval,
"fromdate": datestamp.strftime("%Y-%m-%d")+ " 09:15",
"todate": datestamp.strftime("%Y-%m-%d") + " 15:30"
}
hist_data = obj.getCandleData(params)
df_data = pd.DataFrame(hist_data["data"],
columns = ["date","open","high","low","close","volume"])
df_data.set_index("date",inplace=True)
df_data.index = pd.to_datetime(df_data.index)
df_data.index = df_data.index.tz_localize(None)
return df_data

candle_data = hist_data_daily(tickers, instrument_list)

def topGap(data):
top_gap_by_date = {}
dates = data[tickers[0]].index.to_list()
for date in dates:
temp = pd.Series()
for ticker in data:
try:
temp.loc[ticker] = data[ticker].loc[date,"gap"]
except:
pass
top_gap_by_date[date] = (abs(temp[abs(temp)>1.5])).sort_values(ascending=False)[:5].index.to_list()
print("top 5 gap stocks on {}".format(date))
print((abs(temp[abs(temp)>1.5])).sort_values(ascending=False)[:5])

return top_gap_by_date

top_gap_by_date = topGap(candle_data)

def backtest(top_gap_by_date, candle_data):
date_stats = {}
for date in top_gap_by_date:
date_orgnl = date.strftime("%Y-%m-%d %H:%M")
date_stats[date] = {}
for ticker in top_gap_by_date[date]:
try:
intraday_df = hist_data_intraday(ticker,date,'FIVE_MINUTE',instrument_list)
hi_price = intraday_df.iloc[0]['high']
lo_price = intraday_df.iloc[0]['low']
open_price = ''
direction = ''
date_stats[date][ticker] = 0
for i in range(1,len(intraday_df[1:])):
if intraday_df.iloc[i]["volume"] > 2*(candle_data[ticker].loc[date_orgnl,"avvol"])/75
and intraday_df.iloc[i]["high"] > hi_price
and open_price == '':
open_price = 0.8intraday_df.iloc[i+1]["open"] + 0.2intraday_df.iloc[i+1]["high"] #factoring in slippage
direction = 'long'
elif intraday_df.iloc[i]["volume"] > 2*(candle_data[ticker].loc[date_orgnl,"avvol"])/75
and intraday_df.iloc[i]["low"] < lo_price
and open_price == '':
open_price = 0.8intraday_df.iloc[i+1]["open"] + 0.2intraday_df.iloc[i+1]["low"] #factoring in slippage
direction = 'short'

                if open_price != '' and direction == 'long':
                    if intraday_df.iloc[i]["high"] > hi_price*1.05:
                        ticker_return = ((hi_price*1.05)/open_price)-1
                        date_stats[date][ticker] = ticker_return
                        break
                    elif intraday_df.iloc[i]["low"] < lo_price:
                        ticker_return = (lo_price/open_price) - 1
                        date_stats[date][ticker] = ticker_return
                        break
                    else:
                        ticker_return = (intraday_df.iloc[i]["close"]/open_price) - 1
                        date_stats[date][ticker] = ticker_return
                        
                if open_price != '' and direction == 'short':
                    if intraday_df.iloc[i]["low"] < lo_price*0.95:
                        ticker_return = 1 - ((lo_price*0.95)/open_price)
                        date_stats[date][ticker] = ticker_return
                        break
                    elif intraday_df.iloc[i]["high"] > hi_price:
                        ticker_return = 1 - (hi_price/open_price)
                        date_stats[date][ticker] = ticker_return
                        break
                    else:
                        ticker_return = 1 - (intraday_df.iloc[i]["close"]/open_price)
                        date_stats[date][ticker] = ticker_return
        except:
            print(ticker,date)
                                             
return date_stats

date_stats = backtest(top_gap_by_date, candle_data)

###########################KPIs#####################################

def abs_return(date_stats):
df = pd.DataFrame(date_stats).T
df["ret"] = df.mean(axis=1)
df["ret"].fillna(0,inplace=True)
return (1+df["ret"]).cumprod().iloc[-1] - 1

def win_rate(date_stats):
win_count = 0
lose_count = 0
for i in date_stats:
for ticker in date_stats[i]:
if date_stats[i][ticker] > 0:
win_count+=1
elif date_stats[i][ticker] < 0:
lose_count+=1
return (win_count/(win_count+lose_count))*100

def mean_ret_winner(date_stats):
win_ret = []
for i in date_stats:
for ticker in date_stats[i]:
if date_stats[i][ticker] > 0:
win_ret.append(date_stats[i][ticker])
return sum(win_ret)/len(win_ret)

def mean_ret_loser(date_stats):
los_ret = []
for i in date_stats:
for ticker in date_stats[i]:
if date_stats[i][ticker] < 0:
los_ret.append(date_stats[i][ticker])
return sum(los_ret)/len(los_ret)

def equity_curve(date_stats):
df = pd.DataFrame(date_stats).T
df["ret"] = df.mean(axis=1)
df["ret"].fillna(0,inplace=True)
df["cum_ret"] = (1+df["ret"]).cumprod() - 1
df["cum_ret"].plot(title="return profile")

print("*Strategy Performance Statistics")
print("total cumulative return = {}".format(round(abs_return(date_stats),4)))
print("total win rate = {}".format(round(win_rate(date_stats),2)))
print("mean return per win trade = {}".format(round(mean_ret_winner(date_stats),4)))
print("mean return per loss trade = {}".format(round(mean_ret_loser(date_stats),4)))
equity_curve(date_stats)

@Moderator_1 this is the error that I am facing for past 3 weeks top 5 gap stocks on 2022-10-13 00:00:00
WIPRO 5.135433
HINDALCO 2.698651
HCLTECH 2.106092
dtype: float64
top 5 gap stocks on 2022-10-14 00:00:00
INFY 4.584830
ICICIBANK 3.537957
HDFCLIFE 2.640930
ADANIPORTS 2.453011
HINDALCO 2.415639
dtype: float64
top 5 gap stocks on 2022-10-17 00:00:00
Series([], dtype: float64)
top 5 gap stocks on 2022-10-18 00:00:00
WIPRO 2.292722
dtype: float64
top 5 gap stocks on 2022-10-19 00:00:00
Series([], dtype: float64)
top 5 gap stocks on 2022-10-20 00:00:00
HINDALCO 1.870356
dtype: float64
top 5 gap stocks on 2022-10-21 00:00:00
AXISBANK 4.147242
dtype: float64
[E 240603 11:56:34 smartConnect:243] Error occurred while making a POST request to https://apiconnect.angelbroking.com/rest/secure/angelbroking/historical/v1/getCandleData. Error: Something Went Wrong, Please Try After Sometime. URL: https://apiconnect.angelbroking.com/rest/secure/angelbroking/historical/v1/getCandleData, Headers: {'Content-type': 'application/json', 'X-ClientLocalIP': '127.0.0.1', 'X-ClientPublicIP': '106.193.147.98', 'X-MACAddress': 'a9:31:1f:9d:a7:f3', 'Accept': 'application/json', 'X-PrivateKey': 'te2Wr9fI', 'X-UserType': 'USER', 'X-SourceID': 'WEB'}, Request: {'exchange': 'NSE', 'symboltoken': '910', 'interval': 'FIVE_MINUTE', 'fromdate': '2021-11-04 09:15', 'todate': '2021-11-04 15:30'}, Response: {'message': 'Something Went Wrong, Please Try After Sometime', 'errorcode': 'AB1004', 'status': False, 'data': None}
EICHERMOT 2021-11-04 00:00:00
[E 240603 11:58:57 smartConnect:218] Error occurred while making a POST request to https://apiconnect.angelbroking.com/rest/secure/angelbroking/historical/v1/getCandleData. Headers: {'Content-type': 'application/json', 'X-ClientLocalIP': '127.0.0.1', 'X-ClientPublicIP': '106.193.147.98', 'X-MACAddress': 'a9:31:1f:9d:a7:f3', 'Accept': 'application/json', 'X-PrivateKey': 'te2Wr9fI', 'X-UserType': 'USER', 'X-SourceID': 'WEB', 'Authorization': 'Bearer eyJhbGciOiJIUzUxMiJ9.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.MgTimFvHRX-6rcOwfdJZ7fLDxqc1gfMUyBcummhbyilM71zlLbkS5mNs_sCS0SQsosfLu-nxtnuynGQtg_MSVw'}, Request: {'exchange': 'NSE', 'symboltoken': '15083', 'interval': 'FIVE_MINUTE', 'fromdate': '2022-04-05 09:15', 'todate': '2022-04-05 15:30'}, Response: HTTPSConnectionPool(host='apiconnect.angelbroking.com', port=443): Read timed out. (read timeout=7)
ADANIPORTS 2022-04-05 00:00:00
[E 240603 11:59:04 smartConnect:218] Error occurred while making a POST request to https://apiconnect.angelbroking.com/rest/secure/angelbroking/historical/v1/getCandleData. Headers: {'Content-type': 'application/json', 'X-ClientLocalIP': '127.0.0.1', 'X-ClientPublicIP': '106.193.147.98', 'X-MACAddress': 'a9:31:1f:9d:a7:f3', 'Accept': 'application/json', 'X-PrivateKey': 'te2Wr9fI', 'X-UserType': 'USER', 'X-SourceID': 'WEB', 'Authorization': 'Bearer eyJhbGciOiJIUzUxMiJ9.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.MgTimFvHRX-6rcOwfdJZ7fLDxqc1gfMUyBcummhbyilM71zlLbkS5mNs_sCS0SQsosfLu-nxtnuynGQtg_MSVw'}, Request: {'exchange': 'NSE', 'symboltoken': '20374', 'interval': 'FIVE_MINUTE', 'fromdate': '2022-04-08 09:15', 'todate': '2022-04-08 15:30'}, Response: HTTPSConnectionPool(host='apiconnect.angelbroking.com', port=443): Max retries exceeded with url: /rest/secure/angelbroking/historical/v1/getCandleData (Caused by ConnectTimeoutError(<urllib3.connection.HTTPSConnection object at 0x000001EDE1DD0A90>, 'Connection to apiconnect.angelbroking.com timed out. (connect timeout=7)'))
COALINDIA 2022-04-08 00:00:00
[E 240603 11:59:11 smartConnect:218] Error occurred while making a POST request to https://apiconnect.angelbroking.com/rest/secure/angelbroking/historical/v1/getCandleData. Headers: {'Content-type': 'application/json', 'X-ClientLocalIP': '127.0.0.1', 'X-ClientPublicIP': '106.193.147.98', 'X-MACAddress': 'a9:31:1f:9d:a7:f3', 'Accept': 'application/json', 'X-PrivateKey': 'te2Wr9fI', 'X-UserType': 'USER', 'X-SourceID': 'WEB', 'Authorization': 'Bearer eyJhbGciOiJIUzUxMiJ9.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.MgTimFvHRX-6rcOwfdJZ7fLDxqc1gfMUyBcummhbyilM71zlLbkS5mNs_sCS0SQsosfLu-nxtnuynGQtg_MSVw'}, Request: {'exchange': 'NSE', 'symboltoken': '1594', 'interval': 'FIVE_MINUTE', 'fromdate': '2022-04-18 09:15', 'todate': '2022-04-18 15:30'}, Response: HTTPSConnectionPool(host='apiconnect.angelbroking.com', port=443): Max retries exceeded with url: /rest/secure/angelbroking/historical/v1/getCandleData (Caused by ConnectTimeoutError(<urllib3.connection.HTTPSConnection object at 0x000001EDE1DD2C50>, 'Connection to apiconnect.angelbroking.com timed out. (connect timeout=7)'))
INFY 2022-04-18 00:00:00

Moderator_3

Hello @swathi-priya

Can you please use the time.Sleep() in between mutiple request.

Regards,
SmartAPI Team

swathi priya

@Moderator_3 I am using tls 1.3

swathi priya

@Moderator_3 tell me how to check which version of TLS I am using and how to update the tls

Moderator_3

Hello @swathi-priya

Kindly update your TLS version 1.2 or 1.3 then try

Regards,
SmartAPI Team