Hello @Tradehull_Imran
Sir If if people_intrested > required_people_intrested:
print(“BUILD LIVE ALGO”)
Thanks
2 Likes
Hi @Tradehull_Imran
The “required_people_interested” has to be >16. If yes, then you will…
“red_circle GO LIVE SESSION ON YOUTUBE”
"red_circle BUILD ALGO LIVE "
“red_circle LIVE QUESTIONS AND ANSWER IMPLEMENTATION”
However, I would suggest one small change…
If interest_level_of_current_participants >100%:
print(“@Tradehull_Imran may make an exception to the above rule and still do a live session on youtube/build algo live/live q&a”)
1 Like
Hi @Tradehull_Imran, Thank you for your help. I’ll check again today.
Thanks
1 Like
Thank you for your kind words @Tradehull_Imran. Coming from an Algo trading expert like you, Its a big motivation for a novice like me. 
1 Like
@Tradehull_Imran Sir really need your help, what i am doing wrong here …i am able to place order in equity but not for options …why?
Hi @Kishore007
Dhan_Tradehull_V2 has no function for get_position
now if you want to check if you have bought/sold the position in this case we need to implement trade_info dictionary
see : https://youtu.be/wlQWSLzp_UI?si=LC7lZmWat_K-3JdI&t=2685
I am adding pseudocode for it, do make the changes accordingly.
import pdb
import time
import datetime
import traceback
from Dhan_Tradehull_V2 import Tradehull
import pandas as pd
from pprint import pprint
import talib
import pandas_ta as pta
import pandas_ta as ta
import warnings
warnings.filterwarnings("ignore")
#-----------------------------------------------------------------------------------
client_code = "11"
token_id = "11"
tsl = Tradehull(client_code,token_id)
#----------------------------------------------------------------------------------
available_balance = tsl.get_balance()
leveraged_margin = available_balance*5
max_trades = 20
per_trade_margin = (leveraged_margin/max_trades)
max_loss = available_balance * -0.09 # max loss of 9%
#-----------------------------------------------------------------------------------------
watchlist = ['GOLDPETAL DEC FUT']
traded_wathclist = []
#-----------------------------------------------------------------------------------------------------
trade_info = {"stock_name":None, "qty":None, "entry_orderid":None, "direction":None}
while True:
live_pnl = tsl.get_live_pnl()
current_time = datetime.datetime.now().time()
if current_time < datetime.time(9, 18):
print("Wait for market to start", current_time)
time.sleep(1)
continue
if (current_time > datetime.time(23, 15)) or (live_pnl < max_loss):
# I_want_to_trade_no_more = tsl.kill_switch('ON')
order_details = tsl.cancel_all_orders()
print("Market is over, Bye see you tomorrow", current_time)
break
for stock_name in watchlist:
time.sleep(2)
print(f"Scanning {stock_name}")
# Conditions that are on 1 minute timeframe -------------------------------------------
chart_1 = tsl.get_historical_data(tradingsymbol=stock_name, exchange='MCX', timeframe="1")
pervious_candle = chart_1.iloc[-2]
no_repeat_order = stock_name not in traded_wathclist
# rsi ------------------------ apply indicators--------------------------------------
# Buy when rsi crosses above 55 and sell when rsi crosses below 45
# Ensure chart_1 has sufficient rows
if len(chart_1) <= 15:
print(f"Not enough data for {stock_name}. Skipping.")
continue
# Calculate RSI and drop NaN values
chart_1['rsi'] = talib.RSI(chart_1['close'], timeperiod=14)
chart_1['prev_rsi'] = chart_1['rsi'].shift(1)
chart_1.dropna(subset=['rsi', 'prev_rsi'], inplace=True)
# Add crossover columns
chart_1['uptrend_cross'] = (chart_1['prev_rsi'] <= 55) & (chart_1['rsi'] > 55)
chart_1['downtrend_cross'] = (chart_1['prev_rsi'] >= 45) & (chart_1['rsi'] < 45)
# Ensure the columns exist in the completed candle
cc_1 = chart_1.iloc[-2] # Second-to-last row
if 'uptrend_cross' not in cc_1 or 'downtrend_cross' not in cc_1:
print(f"Missing crossover columns for {stock_name}. Skipping.")
continue
# Access crossover values
uptrend_1 = cc_1['uptrend_cross']
downtrend_1 = cc_1['downtrend_cross']
print(f"Uptrend: {uptrend_1}, Downtrend: {downtrend_1}")
# Supertrend for Exit from open position -------------------------- apply indicators-----------------------------------
indi = ta.supertrend(chart_1['high'], chart_1['low'], chart_1['close'], 10, 1)
chart_1 = pd.concat([chart_1, indi], axis=1, join='inner')
cc_1 = chart_1.iloc[-2] #pandas completed candle of 1 min timeframe
exit_sell = cc_1['close'] > cc_1['SUPERT_10_1.0']
exit_buy = cc_1['close'] < cc_1['SUPERT_10_1.0']
# BUY conditions ------------------------------------------------------------------------------
breakout_b1 = ((pervious_candle['close'] - pervious_candle['open']) / pervious_candle['open']) * 100 # percentage change
breakout_b2 = pervious_candle['volume'] > 0.2 * chart_1['volume'].mean()
if uptrend_1 and breakout_b2 and (0.01 <= breakout_b1 <= 0.4) and no_repeat_order:
print(stock_name, "is in uptrend, Buy this script")
lot_size = tsl.get_lot_size(stock_name)
# Place buy order-------------------------------------------------------------------------
entry_orderid = tsl.order_placement(stock_name, 'MCX', lot_size, 0, 0, 'MARKET', 'BUY', 'MIS')
traded_wathclist.append(stock_name)
trade_info['stock_name'] = stock_name
trade_info['qty'] = lot_size
trade_info['entry_orderid'] = entry_orderid
trade_info['direction'] = "BUY"
# SELL conditions -----------------------------------------------------------------------------
breakout_s1 = ((pervious_candle['close'] - pervious_candle['open']) / pervious_candle['open']) * 100 # percentage change
breakout_s2 = pervious_candle['volume'] > 0.2 * chart_1['volume'].mean()
if downtrend_1 and breakout_s2 and (-0.4 <= breakout_s1 <= -0.01) and no_repeat_order:
print(stock_name, "is in downtrend, Sell this script")
lot_size = tsl.get_lot_size(stock_name)
# Place sell order-------------------------------------------------------------------------
entry_orderid = tsl.order_placement(stock_name, 'MCX', lot_size, 0, 0, 'MARKET', 'SELL', 'MIS')
traded_wathclist.append(stock_name)
# Exit conditions based on Supertrend indicator----------------------------------------------------
for stock_name in traded_wathclist:
time.sleep(2)
print(f"Checking exit conditions for {stock_name}")
# Fetch updated 1-minute chart
chart_1 = tsl.get_historical_data(tradingsymbol=stock_name, exchange='MCX', timeframe="1")
# Apply Supertrend indicator again
indi = ta.supertrend(chart_1['high'], chart_1['low'], chart_1['close'], 10, 1)
chart_1 = pd.concat([chart_1, indi], axis=1, join='inner')
cc_1 = chart_1.iloc[-2] # Get the completed candle
# Exit conditions
exit_sell = cc_1['close'] > cc_1['SUPERT_10_1.0']
exit_buy = cc_1['close'] < cc_1['SUPERT_10_1.0']
# Check for existing positions to square off
position = trade_info['direction']
if position == 'BUY' and exit_buy:
print(f"Exiting BUY position for {stock_name}")
exit_orderid = tsl.order_placement(stock_name, 'MCX', position['lot_size'], 0, 0, 'MARKET', 'SELL', 'MIS')
traded_wathclist.remove(stock_name)
elif position == 'SELL' and exit_sell:
print(f"Exiting SELL position for {stock_name}")
exit_orderid = tsl.order_placement(stock_name, 'MCX', position['lot_size'], 0, 0, 'MARKET', 'BUY', 'MIS')
traded_wathclist.remove(stock_name)
But trade_info will only work for a single script,
as of now I have not taught how to manage multiple positions with all the details.
I will take this topic in next live lecture This week.
1 Like
There were many upgraded along the way , do check below sequence for practice
use below code for order placement into options
tsl.order_placement(ce_name,'NFO', lot_size, 0, 0, 'MARKET', 'BUY', 'MIS')
for video tutorial see : https://youtu.be/wlQWSLzp_UI?si=ZF5z38v2pnl_S2Xj&t=2472
Thankyou sir,
Awaiting for live session, sir…
Hi
@Tradehull_Imran
I tried to make Nifty & BankNifty code with the help of chatgpt
But there is when conditions meet then multiple order generate and same time SL also hit
Please help solve error and verify my code
Thank you
BANKNIFTY DEC FUT Buy CALL
Order Exited {‘options_name’: ‘BANKNIFTY 24 DEC 52300 CALL’, ‘qty’: 15, ‘sl’: 944.9, ‘CE_PE’: ‘CE’, ‘entry_price’: 944.9, ‘Trailed’: ‘yes_I_have_trailed’, ‘entry_orderid’: ‘42241127396413’}
BUY NIFTY DEC FUT 12:00:11.177718 False True False cc_1 2024-11-27 12:00:00+05:30
SELL NIFTY DEC FUT 12:00:11.177718 False True False cc_1 2024-11-27 12:00:00+05:30
Order Exited {‘options_name’: ‘BANKNIFTY 24 DEC 52300 CALL’, ‘qty’: 15, ‘sl’: 944.9, ‘CE_PE’: ‘CE’, ‘entry_price’: 944.9, ‘Trailed’: ‘yes_I_have_trailed’, ‘entry_orderid’: ‘42241127396413’}
BUY BANKNIFTY DEC FUT 12:00:11.177718 True True True cc_1 2024-11-27 12:00:00+05:30
SELL BANKNIFTY DEC FUT 12:00:11.177718 False True False cc_1 2024-11-27 12:00:00+05:30
BANKNIFTY DEC FUT Buy CALL
BUY NIFTY DEC FUT 12:00:23.511704 False True False cc_1 2024-11-27 12:00:00+05:30
SELL NIFTY DEC FUT 12:00:23.511704 False True False cc_1 2024-11-27 12:00:00+05:30
Order Exited {‘options_name’: ‘BANKNIFTY 24 DEC 52300 CALL’, ‘qty’: 15, ‘sl’: 52422.25, ‘CE_PE’: ‘CE’, ‘entry_price’: 978.0, ‘Trailed’: ‘yes_I_have_trailed’, ‘entry_orderid’: ‘22241127378613’}
BUY BANKNIFTY DEC FUT 12:00:23.511704 True True True cc_1 2024-11-27 12:00:00+05:30
SELL BANKNIFTY DEC FUT 12:00:23.511704 False True False cc_1 2024-11-27 12:00:00+05:30
BANKNIFTY DEC FUT Buy CALL
BUY NIFTY DEC FUT 12:00:35.661303 False True False cc_1 2024-11-27 12:00:00+05:30
SELL NIFTY DEC FUT 12:00:35.661303 False True False cc_1 2024-11-27 12:00:00+05:30
Order Exited {‘options_name’: ‘BANKNIFTY 24 DEC 52300 CALL’, ‘qty’: 15, ‘sl’: 52422.25, ‘CE_PE’: ‘CE’, ‘entry_price’: 993.95, ‘Trailed’: ‘yes_I_have_trailed’, ‘entry_orderid’: ‘22241127380013’}
BUY BANKNIFTY DEC FUT 12:00:35.661303 True True True cc_1 2024-11-27 12:00:00+05:30
SELL BANKNIFTY DEC FUT 12:00:35.661303 False True False cc_1 2024-11-27 12:00:00+05:30
BANKNIFTY DEC FUT Buy CALL
BUY NIFTY DEC FUT 12:00:48.302710 False True False cc_1 2024-11-27 12:00:00+05:30
SELL NIFTY DEC FUT 12:00:48.302710 False True False cc_1 2024-11-27 12:00:00+05:30
Order Exited {‘options_name’: ‘BANKNIFTY 24 DEC 52400 CALL’, ‘qty’: 15, ‘sl’: 52422.25, ‘CE_PE’: ‘CE’, ‘entry_price’: 949.9, ‘Trailed’: ‘yes_I_have_trailed’, ‘entry_orderid’: ‘42241127399413’}
hi,
get_historical_data method is not working from Dhan_tradehull.py, i have passed the following parameters from my temp.py
import talib
import pdb
from Dhan_Tradehull import Tradehull
import pandas as pd
tsl = Tradehull(client_code,token_id) # tradehull_support_library
previous_hist_data = tsl.get_historical_data(‘HDFCBANK’,‘NSE’,12)
print(previous_hist_data)
OHLC Response: {‘status’: ‘failure’, ‘remarks’: “expiry_code value must be [‘0’,‘1’,‘2’,‘3’]”, ‘data’: ‘’}
Invalid OHLC data or missing.
Please help. how can it we resolved
Exception at calling ltp as {‘status’: ‘failure’, ‘remarks’: {‘error_code’: None, ‘error_type’: None, ‘error_message’: None}, ‘data’: {‘data’: {‘805’: ‘Too many requests. Further requests may result in the user being blocked.’}, ‘status’: ‘failed’}}
Traceback (most recent call last):
File “/Users/parveenchugh/latest/strategy1.py”, line 44, in
current_price = ltp_data[‘NIFTY 28 NOV 24300 PUT’]
~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^
KeyError: ‘NIFTY 28 NOV 24300 PUT’
Do find updated code, I have made changes in buy side
-
Added up4 for entry
up4 = trade_info['traded'] is None -
For trailing the code says
price_has_moved_20_pct = index_ltp_value > (trade_info['entry_price'] * 1.2)Notice your entry is in options , so entry price is around Rs 993.95 and index ltp is around 52350 # Note I have taken example rates
so price_has_moved_20_pct condition equates to = (52350 > (993.95*1.2)) which will always be Truewhen the condition becomes True, below code sets stoploss to entry price (993.95)
if price_has_moved_20_pct and position_has_not_been_trailed:
trade_info['sl'] = trade_info['entry_price']
and the SL hit condition becomes True, because code is comparing index_ltp to options ltp, which is always True
sl_hit = index_ltp_value < trade_info['sl']
tg_hit = index_ltp_value < cc5_2['SUPERT_10_3.0']
Which leads to immdeiate SL exit
Important:
As of now work only with single script and trade_info,
as of now I have not taught how to manage multiple positions with all the details.
I will take this topic in next live lecture This week.
Also till then do work with a test account
Also we can review this code in live lecture also,
CODE
import pdb
import traceback
import time
import datetime
from Dhan_Tradehull_V2 import Tradehull
import pandas as pd
from pprint import pprint
import pandas_ta as ta
import talib
import warnings
warnings.filterwarnings("ignore")
# ---------------for Dhan login ----------------
client_code = ""
token_id = ""
tsl = Tradehull(client_code, token_id)
available_balance = tsl.get_balance()
print("Available Balance:", available_balance)
# Define the symbols to trade
symbols = ['NIFTY DEC FUT']
traded = "no"
trade_info = {"options_name": None, "qty": None, "sl": None, "CE_PE": None, "entry_price": None, "Trailed": None, "entry_orderid": None, "traded":None}
while True:
current_time = datetime.datetime.now().time()
if current_time < datetime.time(9, 20):
print("Wait for market to start", current_time)
continue
if current_time > datetime.time(23, 25):
print("Market is over, Bye Bye see you tomorrow", current_time)
break
for index_name in symbols:
index_chart = tsl.get_historical_data(tradingsymbol=index_name, exchange='NFO', timeframe="15")
time.sleep(3)
index_chart_5 = tsl.get_historical_data(tradingsymbol=index_name, exchange='NFO', timeframe="5")
index_ltp = tsl.get_ltp_data(names=[index_name])
if index_chart.empty or index_chart_5.empty:
time.sleep(60)
continue
index_chart['rsi'] = talib.RSI(index_chart['close'], timeperiod=14)
supertrend = ta.supertrend(index_chart_5['high'], index_chart_5['low'], index_chart_5['close'], 10, 3)
index_chart_5 = pd.concat([index_chart_5, supertrend], axis=1, join='inner')
cc_1 = index_chart.iloc[-1]
cc_2 = index_chart.iloc[-2]
cc_3 = index_chart.iloc[-3]
cc5_2 = index_chart_5.iloc[-2]
# ---------------------------- BUY ENTRY CONDITIONS ----------------------------
up1 = cc_2['rsi'] > 60
up2 = cc_3['rsi'] < 60
up3 = cc_2['high'] < cc_1['close']
up4 = trade_info['traded'] is None
print(f"BUY {index_name}\t{current_time}\t{up1}\t{up2}\t{up3}\tcc_1 {str(cc_1['timestamp'])}")
# ---------------------------- SELL ENTRY CONDITIONS ----------------------------
dt1 = cc_2['rsi'] < 40
dt2 = cc_3['rsi'] > 40
dt3 = cc_2['low'] > cc_1['close']
dt4 = ???
print(f"SELL {index_name}\t{current_time}\t{dt1}\t{dt2}\t{dt3}\tcc_1 {str(cc_1['timestamp'])}\n")
expiry = '24-12-2024' if 'BANKNIFTY' in index_name else '26-12-2024'
if up1 and up2 and up3 and up4:
print(index_name, "Buy CALL")
ce_name, pe_name, strike = tsl.ATM_Strike_Selection(Underlying=index_name.split()[0], Expiry=expiry)
lot_size = tsl.get_lot_size(ce_name) * 1
entry_orderid = tsl.order_placement(ce_name, 'NFO', lot_size, 0, 0, 'MARKET', 'BUY', 'MIS')
traded = "yes"
trade_info.update({"options_name": ce_name, "qty": lot_size, "sl": cc_2['low'], "CE_PE": "CE", "entry_orderid": entry_orderid, "traded":"yes_I_have_entered_position"})
time.sleep(1)
trade_info['entry_price'] = tsl.get_executed_price(orderid=trade_info['entry_orderid'])
if dt1 and dt2 and dt3:
print(index_name, "Buy PUT")
ce_name, pe_name, strike = tsl.ATM_Strike_Selection(Underlying=index_name.split()[0], Expiry=expiry)
lot_size = tsl.get_lot_size(pe_name) * 1
entry_orderid = tsl.order_placement(pe_name, 'NFO', lot_size, 0, 0, 'MARKET', 'BUY', 'MIS')
traded = "yes"
trade_info.update({"options_name": pe_name, "qty": lot_size, "sl": cc_2['high'], "CE_PE": "PE", "entry_orderid": entry_orderid})
time.sleep(1)
trade_info['entry_price'] = tsl.get_executed_price(orderid=trade_info['entry_orderid'])
if traded == "yes":
long_position = trade_info['CE_PE'] == "CE"
short_position = trade_info['CE_PE'] == "PE"
# Check if LTP is a dictionary or an integer and extract the correct value
index_ltp_value = index_ltp.get(index_name) if isinstance(index_ltp, dict) else index_ltp
if index_ltp_value is None:
print(f"Failed to get LTP for {index_name}")
continue
# Ensure comparison is with the correct type
price_has_moved_20_pct = index_ltp_value > (trade_info['entry_price'] * 1.2)
position_has_not_been_trailed = trade_info['Trailed'] is None
if price_has_moved_20_pct and position_has_not_been_trailed:
trade_info['sl'] = trade_info['entry_price']
trade_info['Trailed'] = "yes_I_have_trailed"
sl_hit = index_ltp_value < trade_info['sl']
tg_hit = index_ltp_value < cc5_2['SUPERT_10_3.0']
if sl_hit or tg_hit:
print("Order Exited", trade_info)
exit_orderid = tsl.order_placement(trade_info['options_name'], 'NFO', trade_info['qty'], 0, 0, 'MARKET', 'SELL', 'MIS')
# if you want re-entry to happen, unblock below code
# trade_info = {"options_name": None, "qty": None, "sl": None, "CE_PE": None, "entry_price": None, "Trailed": None, "entry_orderid": None, "traded":None}
check this link : Learn Algo Trading with Python | Codes | Youtube Series - #1065 by Tradehull_Imran
The code was calling data too fast
See this link : Learn Algo Trading with Python | Codes | Youtube Series - #860 by Tradehull_Imran
Hi
@Tradehull_Imran
I am glad and appreciate for your back-to-back support
Thank You Very much
1 Like
Thanks sir, now change time.sleep(5) for slow data
class DhanHQMock:
pass
def get_live_data(url):
return 120
api = DhanHQMock()
required_people_intrested = (100 // 6)
url = “Learn Algo Trading with Python | Codes | Youtube Series”
people_intrested = get_live_data(url)
if people_intrested > required_people_intrested:
print(“
BUILD ALGO LIVE SESSION ON YOUTUBE”)
print(“ LIVE QUESTIONS AND ANSWER IMPLEMENTATION”)
else:
print(“Wait 
”) i mean to say supper interested to continue learning with @Tradehull_Imran
There’s only one video that remains in this series! 
Are you all excited for it ?
1 Like
Sir, I’m excited for the remaining video and looking forward to the next one more series.This will keep our community members engaged and help them gain more expertise while fostering a user-friendly experience through continuous interaction. Request keep the same teacher for next series.