def place_limit_order_sell(tradingsymbol, limit_price, quantity):
logger.info(
f"Placing sell limit order: {tradingsymbol}, quantity:{quantity}, limit price: {limit_price}"
)
order_id = connect.KITE.place_order(
variety=connect.KITE.VARIETY_REGULAR,
exchange=connect.KITE.EXCHANGE_NSE,
order_type=connect.KITE.ORDER_TYPE_LIMIT,
tradingsymbol=tradingsymbol,
transaction_type=connect.KITE.TRANSACTION_TYPE_SELL,
quantity=quantity,
product=connect.KITE.PRODUCT_CNC,
price=limit_price)
logger.info(f"Order id: {order_id}")
from nsetools import Nse
from kitelib import kiteops
from datetime import datetime
from pylib.logger import logger
from pylib import pyops
nse = Nse()
def get_day_low_high_price():
watch_list = pyops.get_dict_from_json_file('data', "watch_instruments.json")
print(watch_list)
day_low_high_price = {}
for instrument in watch_list:
stock = instrument.split(":")[1]
#print(stock)
print(nse.get_quote(stock)['dayHigh'])
try:
get_day_low_high_price()
except Exception as ex:
logger.info(ex)
def get_orders():
logger.info("Fetching all orders.")
return connect.KITE.orders()
def update_holdings_info():
logger.info("Fetching live holdings.")
# get the live holdings status from kite account.
holdings_info_live = kiteops.get_holdings()
# Save current live holdings in a json file.
pyops.write_dict_into_json_file('data', "holdings_info_live.json",
holdings_info_live)
# get the holdings status from previously saved holdings.
offline_holdings = pyops.get_dict_from_json_file(
'result', "holdings_info_five_min_update.json")
# All the required key of offline holdings json.
holdings_info_schema_dict = pyops.get_dict_from_json_file(
"data", "holdings_info_schema.json")
date_time_now = datetime.now()
# Run a loop over all live holdings and update offline holdings.
for i in range(len(holdings_info_live)):
found = False
for j in range(len(offline_holdings)):
# if a stock name is matched in live and offline holdings.
if holdings_info_live[i]["tradingsymbol"].rstrip(
'*') == offline_holdings[j]['tradingsymbol']:
if "price_day_max_list" not in offline_holdings[j].keys():
offline_holdings[j]["price_day_max_list"] = [0]
if "price_day_min_list" not in offline_holdings[j].keys():
offline_holdings[j]["price_day_min_list"] = [0]
found = True
# This is to record the min and max price of the day.
# In the start of the day set the day min and max = last price.
ltp_date_offline = datetime.fromisoformat(
offline_holdings[j]["ltp_datetime"]).date()
authorised_date_live = datetime.fromisoformat(
holdings_info_live[i]["authorised_date"]).date()
delta_days = (authorised_date_live - ltp_date_offline).days
if delta_days >= 1:
offline_holdings[j]['price_day_max'] = holdings_info_live[
i]["last_price"]
offline_holdings[j]['price_day_min'] = holdings_info_live[
i]["last_price"]
offline_holdings[j]["price_day_min_list"].append(
holdings_info_live[i]["last_price"])
offline_holdings[j]["price_day_max_list"].append(
holdings_info_live[i]["last_price"])
# In the start of the day, add current day's max and min diff = 0 in the list.
offline_holdings[j]['price_diff_day_max_min'].append(
holdings_info_live[i]["last_price"])
# Hold only 10 values in the list. List for holding last 10 days max and min price diff.
if len(offline_holdings[j]
['price_diff_day_max_min']) >= 30:
# Remove the first day value from the list on 11th day.
logger.debug(
"Removing one entry from day max min price diff list."
)
offline_holdings[j][
'price_diff_day_max_min'] = offline_holdings[j][
'price_diff_day_max_min'][1:]
# Update basic values.
offline_holdings[j]['quantity'] = holdings_info_live[i][
"quantity"]
offline_holdings[j]['average_price'] = round(
holdings_info_live[i]["average_price"], 2)
offline_holdings[j]['last_price'] = round(
holdings_info_live[i]["last_price"], 2)
offline_holdings[j]['ltp_datetime'] = str(date_time_now)
# If last price of live holding is greater then max price of offline holding.
# Update max price of offline holding. And increase the max count by one.
# Update the max and min price diff.
if holdings_info_live[i]["last_price"] > offline_holdings[j][
'price_max']:
offline_holdings[j]['price_max'] = holdings_info_live[i][
"last_price"]
offline_holdings[j]['count_max_price'] += 1
offline_holdings[j]['datetime_max_price'] = str(
date_time_now)
offline_holdings[j]['price_diff_max_min'] = \
round(offline_holdings[j]['price_max'] - offline_holdings[j]['price_min'], 2)
# If last price of live holding is less then min price of offline holding.
# Update min price of offline holding. And increase the min count by one.
# Update the max and min price diff.
elif holdings_info_live[i]["last_price"] < offline_holdings[j][
'price_min']:
offline_holdings[j]['price_min'] = holdings_info_live[i][
"last_price"]
offline_holdings[j]['count_min_price'] += 1
offline_holdings[j]['datetime_min_price'] = str(
date_time_now)
offline_holdings[j]['price_diff_max_min'] = \
round(offline_holdings[j]['price_max'] - offline_holdings[j]['price_min'], 2)
# If the new value of day max price is hit, add it in day max.
# And update the day max and min price diff in the list.
if holdings_info_live[i]["last_price"] > offline_holdings[j][
'price_day_max']:
offline_holdings[j]['price_day_max'] = holdings_info_live[
i]["last_price"]
offline_holdings[j]['price_diff_day_max_min'][-1] = \
round(offline_holdings[j]['price_day_max'] - offline_holdings[j]['price_day_min'], 2)
offline_holdings[j]["price_day_max_list"][
-1] = offline_holdings[j]['price_day_max']
# If the new value of day min price is hit, add it in day min.
# And update the day max and min price diff in the list.
elif holdings_info_live[i]["last_price"] < offline_holdings[j][
'price_day_min']:
offline_holdings[j]['price_day_min'] = holdings_info_live[
i]["last_price"]
offline_holdings[j]['price_diff_day_max_min'][-1] = \
round(offline_holdings[j]['price_day_max'] - offline_holdings[j]['price_day_min'], 2)
offline_holdings[j]["price_day_min_list"][
-1] = offline_holdings[j]['price_day_min']
# if the stock is added for the first time. That is newly bought stock.
# Add that stock in the offline json.
if not found:
temp_dict = holdings_info_schema_dict
temp_dict["tradingsymbol"] = holdings_info_live[i]["tradingsymbol"]
temp_dict["quantity"] = holdings_info_live[i]["quantity"]
temp_dict["average_price"] = round(
holdings_info_live[i]["average_price"], 2)
temp_dict["last_price"] = holdings_info_live[i]["last_price"]
temp_dict["price_max"] = holdings_info_live[i]["last_price"]
temp_dict["price_min"] = holdings_info_live[i]["last_price"]
temp_dict["count_max_price"] = 0
temp_dict["count_min_price"] = 0
temp_dict["datetime_max_price"] = ""
temp_dict["datetime_min_price"] = ""
temp_dict["ltp_datetime"] = str(date_time_now)
temp_dict['price_diff_max_min'] = 0
temp_dict['priority_buy'] = 0
temp_dict['priority_sell'] = 0
temp_dict['price_day_max'] = holdings_info_live[i]["last_price"]
temp_dict['price_day_min'] = holdings_info_live[i]["last_price"]
temp_dict['price_diff_day_max_min'] = [0]
temp_dict['price_day_max_list'] = [0]
temp_dict['price_day_min_list'] = [0]
offline_holdings.append(temp_dict)
logger.info("Updating offline holdings.")
pyops.write_dict_into_json_file('result',
"holdings_info_five_min_update.json",
offline_holdings)
def update_watch_instruments():
logger.info("Running update_watch_instruments function.")
date_time_now = datetime.now()
watch_list = pyops.get_dict_from_json_file('data',
"watch_instruments.json")
live_ltp_info = kiteops.get_ltp(watch_list)
price_info = pyops.get_dict_from_json_file('result', "price_info.json")
price_info_date_time = price_info["date_time"]
logger.info(f"date_time_now {date_time_now}")
logger.info(
f"datetime.fromisoformat(price_info_date_time) {datetime.fromisoformat(price_info_date_time)}"
)
delta_days = (date_time_now.date() -
datetime.fromisoformat(price_info_date_time).date()).days
logger.info(delta_days)
price_info["date_time"] = str(date_time_now)
for live_instrument, live_ltp in live_ltp_info.items():
if live_instrument in price_info.keys():
price_info[live_instrument]["last_price"] = live_ltp["last_price"]
if live_ltp["last_price"] > price_info[live_instrument][
"max_price"]:
price_info[live_instrument]["max_price"] = live_ltp[
"last_price"]
price_info[live_instrument]["max_price_date"] = str(
date_time_now)
elif live_ltp["last_price"] < price_info[live_instrument][
"min_price"]:
price_info[live_instrument]["min_price"] = live_ltp[
"last_price"]
price_info[live_instrument]["min_price_date"] = str(
date_time_now)
if delta_days >= 1:
price_info[live_instrument]["max_price_list"].append(
live_ltp["last_price"])
price_info[live_instrument]["min_price_list"].append(
live_ltp["last_price"])
if live_ltp["last_price"] > price_info[live_instrument][
"max_price_list"][-1]:
price_info[live_instrument]["max_price_list"][-1] = live_ltp[
"last_price"]
elif live_ltp["last_price"] < price_info[live_instrument][
"min_price_list"][-1]:
price_info[live_instrument]["min_price_list"][-1] = live_ltp[
"last_price"]
else:
price_info[live_instrument] = live_ltp
price_info[live_instrument]["min_price"] = live_ltp["last_price"]
price_info[live_instrument]["max_price"] = live_ltp["last_price"]
price_info[live_instrument]["min_price_date"] = str(date_time_now)
price_info[live_instrument]["max_price_date"] = str(date_time_now)
price_info[live_instrument]["min_price_list"] = [
live_ltp["last_price"]
]
price_info[live_instrument]["max_price_list"] = [
live_ltp["last_price"]
]
pyops.write_dict_into_json_file("result", "price_info.json", price_info)