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Test.py
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Test.py
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# from scipy.signal import argrelmax,argrelmin
# import ta as tech_ana
import csv
import datetime
import io
import math
import multiprocessing
import time
import time as sleep_time
import traceback
# from datetime import datetime
from urllib.request import Request, urlopen
# import face_recognition
import TradingScripts.DerivativeUtils as dutil
# import TradingScripts.GenericStatPrinter as gstats
import TradingScripts.ScrapUtils as sUtils
import TradingScripts.Utils as util
from TradingScripts.UpDownGapUtils import get_fo_stock_ids
from pytz import timezone, utc
x = datetime.datetime(2018, 9, 15)
print(x.strftime("%b %d %Y %H:%M:%S"))
exit(0)
kite = util.intialize_kite_api()
# print(kite.instruments())
print(kite.historical_data(260105, datetime.datetime(2021, 1, 22), datetime.datetime(2021, 1, 25), '3minute'))
exit(0)
#
# print(int(round(19249 / 100.0) * 100))
timestamp = datetime.datetime(2021, 1, 25, 15, 10, 6)
print(timestamp.hour)
print(timestamp.minute)
hr = 9
min =18
print(int((hr * 60) + (int(min/3) * 3)))
candles = {}
candles[123] = {'1': 12, 'LOW': 13}
print(candles)
candles[123]['LOW'] = 14
print(candles)
exit(0)
instruments_map = {}
with open('C:/Users/himan/Downloads/NSE_small.csv') as csv_file:
csv_reader = csv.reader(csv_file, delimiter=',')
line_count = 0
for row in csv_reader:
instruments_map[row[1]] = row[0]
print(instruments_map)
exit(0)
# lines_to_write = '####Bought:' + ' at CE:' + ' and PE:'
# lines_to_write += '####Bought:'
# print(lines_to_write)
# exit(0)
# x = math.inf
#
# print(x == math.inf)
#
# exit(0)
instruments = kite.instruments()
# open('F:/Trading_Responses/instruments.txt','w').write(str(kite.instruments()))
tokens = {}
strikes = {}
for instrument in instruments:
if instrument['name'] == 'BANKNIFTY' and instrument['expiry'] == datetime.date(2020, 4, 30) and instrument['segment'] == 'NFO-OPT':
# print(instrument)
tokens[instrument['exchange'] + ':' + instrument['tradingsymbol']] = {'tradingsymbol': instrument['tradingsymbol'], 'strike': instrument['strike'], 'instrument_type': instrument['instrument_type']}
if instrument['strike'] not in strikes:
strikes[instrument['strike']] = [instrument['tradingsymbol']]
else:
strikes[instrument['strike']].append(instrument['tradingsymbol'])
# strikes.append(instrument['strike'])
if instrument['name'] == 'NIFTY BANK' and instrument['segment'] == 'INDICES':
# print (instrument)
tokens[instrument['exchange'] + ':' + instrument['tradingsymbol']] = instrument['tradingsymbol']
print(tokens)
exit(0)
from TempData import CE, PE
from dateutil import parser
excel_location = 'F:/Trading_Responses/BankNiftyATM_Backtest_excel_' '.xlsx'
ce_data = {}
for candles in CE['data']['candles']:
ce_data[parser.parse(candles[0])] = [candles[1], candles[2], candles[3], candles[4]]
pe_data = {}
for candles in PE['data']['candles']:
pe_data[parser.parse(candles[0])] = [candles[1], candles[2], candles[3], candles[4]]
responses = []
for date, c_data in ce_data.items():
if date in pe_data:
responses.append([date, c_data[0], c_data[1], c_data[2], c_data[3], pe_data[date][0], pe_data[date][1], pe_data[date][2], pe_data[date][3]])
responses.insert (0, ['BUY DATETIME', 'CE(OPEN)', 'CE(HIGH)', 'CE(LOW)', 'CE(CLOSE)', 'PE(OPEN)', 'PE(HIGH)', 'PE(LOW)', 'PE(CLOSE)'])
gstats.print_statistics(responses, excel_location)
exit(0)
today = p_datetime.date.today()
first = today.replace(day=1)
lastMonth = first - p_datetime.timedelta(days=1)
print(lastMonth.strftime("%d-%b-%Y"))
print(lastMonth.replace(day=1).strftime ("%d-%b-%Y"))
exit(0)
arr = [1,2,3,4,5,6,7,8]
for i in range(5, len(arr)):
print(arr[i])
print(arr[-1])
print(arr[-5])
print(arr[5:])
exit(0)
print(dutil.get_equity_live_ltp('HDFC'))
exit(0)
## Starting timer which keep track of the runtime
start_time = time.time()
image_dir = 'E:/RJIL_POS Crop Images Dec 2019/'
## Define the function which will be executed within the pool
def asyncProcess(data):
print(face_recognition.face_encodings (face_recognition.load_image_file ('E:/RJIL_POS Crop Images Dec 2019/3729_60341259.jpg')))
## Define Pool Size of maximal concurrent processes
pool_size = 4
## Define an empty list where we store child processes
processes = []
if __name__ == '__main__':
## Define an empty pool whith maximal concurrent processes
pool = multiprocessing.Pool (processes=pool_size)
## Firing in total of 10 processes
pool.map(asyncProcess, [1, 2, 3, 4])
print("---%d images encoded in %s seconds ---" % (pool_size, time.time() - start_time))
exit(0)
kite = util.intialize_kite_api()
# print(kite.margins())
print(kite.quote(['NSE:HDFC','NSE:HDFCBANK']))
exit(0)
print([1,2,3,4][-2:])
exit(0)
ascent_stocks = {}
ascent_stocks['a'] = ['a', 4]
ascent_stocks['b'] = ['b', 2]
ascent_stocks['c'] = ['c', 3]
print(ascent_stocks.items())
ascent_stocks = [(k[0], ascent_stocks[k[0]]) for k in sorted(ascent_stocks.items(), key=lambda x: x[1][1])]
print(ascent_stocks)
today_date = datetime.now().date()
print(kite.quote('NSE:HDFC')['NSE:HDFC']['timestamp'].date() == today_date)
exit(0)
fo_stock_ids = get_fo_stock_ids('C:/Users/Admin/Desktop/')
stocks_to_buy = []
stocks_to_sell = []
while datetime.now().time () < p_datetime.time(9, 15, 50):
pass
ascent_stocks = {}
descent_stocks = {}
stocks_live_data = kite.quote (fo_stock_ids)
stock_in_uptrend = None
stock_in_downtrend = None
for key, stock_live_data in stocks_live_data.items ():
open_price = stock_live_data['ohlc']['open']
ltp = stock_live_data['last_price']
high_price = stock_live_data['ohlc']['high']
low_price = stock_live_data['ohlc']['low']
close = stock_live_data['ohlc']['close']
ascent = 0
descent = 0
if open_price > close:
ascent = abs ((open_price - close) / close)
ascent_stocks[key] = ascent
elif open_price < close:
descent = abs ((open_price - close) / close)
descent_stocks[key] = descent
if stock_in_uptrend is None or ascent > stock_in_uptrend[1]:
stock_in_uptrend = [key, ascent]
if stock_in_downtrend is None or descent > stock_in_downtrend[1]:
stock_in_downtrend = [key, descent]
if stock_in_uptrend[1] != 0:
print(stock_in_uptrend)
if stock_in_uptrend[0] not in stocks_to_sell:
stocks_to_sell.append(stock_in_uptrend[0])
if stock_in_downtrend[1] != 0:
print (stock_in_downtrend)
if stock_in_downtrend[0] not in stocks_to_buy:
stocks_to_buy.append (stock_in_downtrend[0])
ascent_stocks = [(k, ascent_stocks[k]) for k in sorted (ascent_stocks, key=ascent_stocks.get, reverse=True)]
descent_stocks = [(k, descent_stocks[k]) for k in sorted (descent_stocks, key=descent_stocks.get, reverse=True)]
print ('Ascent_stocks:')
print(ascent_stocks)
print ('Descent_stocks:')
print (descent_stocks)
exit(0)
kite = util.intialize_kite_api()
today_date = datetime.now().date()
print(kite.quote('NSE:HDFC')['NSE:HDFC']['timestamp'].date() == today_date)
exit(0)
co_bo_stocks = []
try:
with urlopen (Request ('http://www.sharecsv.com/s/9e419f5ff41230a35e9921b94edb039b/CM_Margin_Sep-13-2019.csv', headers={'User-Agent': 'Mozilla/5.0'})) as csv_file:
csv_reader = csv.reader (io.StringIO (csv_file.read ().decode ('utf-8')), delimiter=',')
line_count = 0
for row in csv_reader:
co_bo_stocks.append(row[0].strip ())
except Exception as e:
print (traceback.format_exc ())
print('co_bo_stocks', len(co_bo_stocks))
exit(0)
print(kite.quote('NSE:HDFC'))
exit(0)
print(((datetime.now(indian_timezone) - kite.orders()[0]['order_timestamp'].replace(tzinfo=indian_timezone)).seconds - 1380))
a = {'r': 'q'}
a['p'] = ['q']
a['p'].append('r')
print(a)
print(list(a.values())[0])
print(a)
exit(0)
exclude = ['ABB', 'ABFRL', 'ALKEM', 'AUBANK', 'BAJAJHLDNG', 'BANDHANBNK', 'BBTC', 'COROMANDEL', 'CROMPTON', 'DBL', 'DMART', 'ENDURANCE', 'FCONSUMER', 'FRETAIL', 'GICRE', 'GODREJAGRO', 'GODREJIND', 'GSKCONS', 'GSPL', 'HUDCO', 'ICICIGI', 'JSWENERGY', 'LTI', 'LTTS', 'MPHASIS', 'MRPL', 'NATCOPHARM', 'NAUKRI', 'NHPC', 'NIACL', 'PFIZER', 'PGHH', 'PNBHOUSING', 'PRESTIGE', 'QUESS', 'RAJESHEXPO', 'RPOWER', 'SBILIFE', 'SPARC', 'SYNGENE', 'VARROC', 'VGUARD']
co_bo_stocks = []
try:
with open ('http://www.sharecsv.com/s/9e419f5ff41230a35e9921b94edb039b/CM_Margin_Sep-13-2019.csv') as csv_file:
csv_reader = csv.reader (csv_file, delimiter=',')
for row in csv_reader:
co_bo_stocks.append(row[0].strip ())
except Exception as e:\
print (traceback.format_exc ())
print('co_bo_stocks', len(co_bo_stocks))
fo_stocks = sUtils.get_nse_fo_stocks()
fo_stock_ids = []
for fo_stock in fo_stocks:
fo_stock_ids.append(fo_stock[sUtils.STOCK_ID])
print('fo_stock_ids', len(fo_stock_ids))
count = 1
for co_bo_stock in co_bo_stocks:
if co_bo_stock not in fo_stock_ids:
print('%d CO BO stock:%s not in FO stock' %(count, co_bo_stock))
count += 1
exit(0)
print(kite.orders()[5]['exchange_timestamp'].replace(tzinfo=timezone('America/Los_Angeles')))
exit(0)
print(kite.quote('NSE:HDFC'))
exit(0)
lot_multi_factor = .9
print(util.round_to_tick(200 * lot_multi_factor))
net_profit = 7100 - 4000
net_profit = round (1000 * math.floor (net_profit / 1000), 0)
print(net_profit)
print(util.round_to_tick(net_profit * lot_multi_factor))
print(round ((lot_multi_factor * 500) * math.floor ((2600 - (lot_multi_factor * 1000)) / (lot_multi_factor * 500)), 0))
exit(0)
# print((datetime.now(indian_timezone) - parent_order['exchange_timestamp']).seconds)
x = collections.deque(5*[None], 5)
x.appendleft(2.35)
x.appendleft(3)
print(x)
for ele in x:
print(ele > 0)
exit(0)
logging.basicConfig(format="%(asctime)s %(message)s")
logger = logging.getLogger(__name__)
def customTime(*args):
utc_dt = utc.localize(datetime.utcnow())
my_tz = timezone("US/Eastern")
converted = utc_dt.astimezone(my_tz)
return converted.timetuple()
logging.Formatter.converter = customTime
logger.error("customTime")
print(datetime.now(timezone('US/Eastern')))
exit(0)
lot_multi_factor = 32 / 200
print(round ((lot_multi_factor * 1000) * math.floor ((1 - (lot_multi_factor * 4000)) / (lot_multi_factor * 1000)), 0))
exit(0)
fo_lots = nse_bse.get_nse_fo_lots()
responses = []
with open ('C:/Users/Admin/Desktop/Technical analysis testing - Tradebook 1.csv') as csv_file:
csv_reader = csv.reader (csv_file, delimiter=',')
for row in csv_reader:
stock_id = (row[1]).strip ()
price = float((row[2]).strip ())
if price != 0 and stock_id in fo_lots:
responses.append([(row[0]).strip (), stock_id, fo_lots[stock_id], int(500000 / price)])
gstat.print_statistics (responses, 'C:/Users/Admin/Desktop/res.csv')
exit(0)
re_prodId = re.compile(r'Symbol:\"(\w+?)\"')
print(re_prodId.findall('{ success:true ,results:103,rows:[{Symbol:"CLNINDIA",CompanyName:"Clariant Chemicals (India) Limited",ISIN:"INE492A01029",Ind:"-",Purpose:"Financial Results",BoardMeetingDate:"08-Aug-2019",DisplayDate:"04-Jul-2019",seqId:"103630857",Details:"To consider and approve the financial results for the period ended Jun 30, 2019"},{Symbol:"COFFEEDAY",CompanyName:"Coffee Day Enterprises Limited",ISIN:"INE335K01011",'))
exit(0)
today_date_str = datetime.now ().strftime ('%Y-%m-%d')
logFormatter = logging.Formatter("%(asctime)s [%(module)s] [%(levelname)-5.5s] %(message)s")
logger = logging.getLogger('Trading')
logger.setLevel(logging.INFO)
fileHandler = logging.FileHandler('F:/test.log')
fileHandler.setFormatter(logFormatter)
logger.addHandler(fileHandler)
consoleHandler = logging.StreamHandler()
consoleHandler.setFormatter(logFormatter)
logger.addHandler(consoleHandler)
start_time = datetime.now().microsecond
logger.info('test')
print((datetime.now().microsecond - start_time) )
exit(0)
lot = 1
lot *= 2
print(lot)
exit(0)
kite = util.intialize_kite_api()
print(kite.quote('NSE:BERGEPAINT'))
print(kite.quote('NSE:BERGEPAINT', 'NSE:TORNTPOWER'))
exit(0)
# print(datetime.strptime('2019-08-05 09:15:00.846397', '%Y-%m-%d %H:%M:%S.%f').time() > util.MARKET_START_TIME)
# print(494.5 - .35 + (abs(1000) / (.3 * 1100)))
print(494.5 - .35 + (abs(1000) / (.3 * 1100)))
print(1000 / (298.6 - 297.40))
half_future_lot = 1851 / 2
print([1, 690 / half_future_lot][690 < half_future_lot])
print(('SELL' == 'BUY' and (330.3351 - 330.55) >= 20) or ('SELL' == 'SELL' and (330.55 - 330.3351) >= 20) or 148.281 >= (0.7455429497568882 * 20000))
exit(0)
logFormatter = logging.Formatter("%(asctime)s [%(module)s] [%(levelname)-5.5s] %(message)s")
rootLogger = logging.getLogger()
fileHandler = logging.FileHandler('F:test.txt')
fileHandler.setFormatter(logFormatter)
rootLogger.addHandler(fileHandler)
consoleHandler = logging.StreamHandler()
consoleHandler.setFormatter(logFormatter)
rootLogger.addHandler(consoleHandler)
rootLogger.setLevel(logging.INFO)
rootLogger.info('Test info.')
rootLogger.info('Test error.')
exit(0)
half_future_lot = 1851 / 2
print([1, 690 / half_future_lot][690 < half_future_lot])
exit(0)
positions_day = kite.positions ()['day']
positions_net = kite.positions ()['net']
for position in positions_day:
if position['tradingsymbol'].upper() == 'INFRATEL':
print(position)
print(position['unrealised'], position['realised'])
break
for position in positions_net:
if position['tradingsymbol'].upper() == 'INFRATEL':
print(position)
print(position['unrealised'], position['realised'])
break
kite = util.intialize_kite_api()
orders = kite.orders()
kite.modify_order(kite.VARIETY_CO, '190729001773509', parent_order_id='190729001773508', trigger_price=252.0)
exit(0)
print(math.ceil(1.234))
exit(0)
def increment():
global test
test += 1
test = 0
print(test)
increment()
print(test)
exit(0)
kite = util.intialize_kite_api()
order_id = kite.place_order(tradingsymbol="JUBLFOOD",
variety=kite.VARIETY_CO ,
exchange=kite.EXCHANGE_NSE,
transaction_type=kite.TRANSACTION_TYPE_BUY,
quantity=1,
order_type=kite.ORDER_TYPE_LIMIT,
product=kite.PRODUCT_CO,
price=1165,
trigger_price=1160)
print(order_id)
exit(0)
logger = logging.getLogger('spam_application')
logger.setLevel(logging.INFO)
fh = logging.FileHandler('F:/test.txt')
# create formatter and add it to the handlers
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
fh.setFormatter(formatter)
# add the handlers to the logger
logger.addHandler(fh)
logger.info ('Cancelled order of symbol:%s and id:%d.' , 'LT', 12345)
logger.error('Test error.')
exit(0)
print(kite.orders())
print(kite.trades())
# for o in kite.instruments():
# for i, (key, value) in enumerate(o.items()):
# if i == 2 and value in ('INFRATEL', 'IDFCFIRSTB', 'ASIANPAINT', 'CANBK', 'JUBLFOOD', 'ICICIPRULI',):
# print(o)
# start_time = datetime.now()
# print(kite.quote('NSE:JUBLFOOD', 'NSE:INFRATEL', 'NSE:IDFCFIRSTB', 'NSE:ICICIPRULI', 'NSE:ASIANPAINT', 'NSE:CANBK'))
# print(datetime.now(), (datetime.now() - start_time).seconds)
exit(0)
datetime.now().astimezone(pytz.timezone('Asia/Kolkata'))
stock_tickers = {}
stocks = []
print(util.is_number(str('190722000342580|1').split('|')[0]))
print ((datetime.now() > datetime.fromtimestamp(1563555469)))
try:
with open ('C:/Users/Admin/Desktop/CM_Margin_Jun-28-2019.csv') as csv_file:
csv_reader = csv.reader (csv_file, delimiter=',')
for row in csv_reader:
stocks.append(row[0].strip ())
except Exception as e:\
print (traceback.format_exc ())
for stock in stocks:
try:
page = urlopen(Request(
'https://tvc4.forexpros.com/783a9d5e01ae63dabd6a68480bb0f3e4/1556685636/56/56/23/search?limit=30&query={0}&type=&exchange='.format(stock), headers={'User-Agent': 'Mozilla/5.0', 'Referer': 'https://in.investing.com'}))
# parse the html using beautiful soup and store in variable `soup`
soup = BeautifulSoup(page, 'html.parser')
datas = json.loads(soup.string.strip())
stock_name = ''
for data in datas:
if data['exchange'] == 'NSE' and data['type'] == 'Stock' and stock[0].upper() == data['description'][0].upper():
ticker = data['ticker']
stock_name = data['description']
stock_tickers[stock.upper()] = {'ticker': ticker, 'description': stock_name}
break
sleep_time.sleep(1)
except Exception:
print(traceback.format_exc())
print(stock_tickers)
exit(0)
MARKET_START_TIME_AFTER_VOLATILITY = time (9, 15, 1, 0)
while datetime.now().time() < MARKET_START_TIME_AFTER_VOLATILITY:
pass
for i in range(1,5):
FUTURE_HEADERS = {'User-Agent': 'Mozilla/5.0', 'Referer': 'https://kite.zerodha.com/chart/ext/ciq/NSE/ITC/424961'}
today_timestamp = int(
datetime(datetime.today().year, datetime.today().month, datetime.today().day, 15, 58, 56).timestamp())
page = urlopen(Request(
'https://kitecharts-aws.zerodha.com/api/chart/141569/day?public_token=JkPP1XVYS4DCfWYf2ifIeC65afq55Cy0&user_id=DH1355&oi=1&api_key=kitefront&access_token=&from=2019-06-24&to=2019-06-27&ciqrandom=1561600055480' + str(
today_timestamp),
headers=FUTURE_HEADERS))
# parse the html using beautiful soup and store in variable `soup`
soup = BeautifulSoup(page, 'html.parser')
js = json.loads(soup.string.strip())
print(js)
print(datetime.now())
exit(0)
locale.setlocale(locale.LC_ALL, '')
print(locale.currency(100000, grouping=True))
exit(0)
print(round(util.min_tick_size * round(
(1000 / 125) / util.min_tick_size), 2))
exit(0)
# from upstox_api.api import TransactionType
dates = ['2019-03-01', '2019-03-04', '2019-03-05', '2019-03-06', '2019-03-07']
changed_dates = []
for date in dates:
changed_dates.append(mdates.date2num(datetime.strptime(date, '%Y-%m-%d')))
kurse_l = [172.889999, 173.970001, 174.539993, 173.940002, 172.020004]
kurse_o = [174.279999, 175.690002, 175.940002, 174.669998, 173.869995]
kurse_h = [175.149994, 177.750000, 176.000000, 175.490005, 174.440002]
kurse_c = [174.970001, 175.850006, 175.529999, 174.520004, 172.500000]
# Plot candlestick.
##########################
quotes = [tuple([changed_dates[i],
kurse_o[i],
kurse_h[i],
kurse_l[i],
kurse_c[i]]) for i in range(5)]
fig, ax = plt.subplots()
candlestick_ohlc(ax, quotes, width=0.5, colorup='g', colordown='r');
# Customize graph.
##########################
plt.xlabel('Date')
plt.ylabel('Price')
plt.title('Apple')
# Format time.
ax.xaxis_date()
ax.xaxis.set_major_formatter(mdates.DateFormatter("%Y-%m-%d"))
plt.gcf().autofmt_xdate() # Beautify the x-labels
plt.autoscale(tight=True)
# Save graph to file.
plt.savefig('F:/mpl_finance-apple.png')
exit(0)
print(util.round_to_tick(659.3045))
exit(0)
print(util.get_date_from_timestamp(1559533557379466 / 1000).time())
print((datetime.now() - util.get_date_from_timestamp(1559533557379466 / 1000)).seconds)
exit(0)
print (round (
util.min_tick_size * round ((150 / 4000) / util.min_tick_size), 2))
exit (0)
lots = nse_bse.get_nse_fo_lots ()
stocks = nse_bse.get_nse_fo_stocks ()
earnings = {}
for stock in stocks:
stock_id = stock[nse_bse.STOCK_ID]
if stock_id in c_limit.calculated_calendar_spread_limits:
earnings[stock_id] = lots[stock_id] * (c_limit.calculated_calendar_spread_limits[stock_id][0] -
c_limit.calculated_calendar_spread_limits[stock_id][1])
else:
print ('No limit found for:', stock_id)
listofTuples = sorted (earnings.items (), reverse=True, key=lambda x: x[1])
# Iterate over the sorted sequence
for elem in listofTuples:
print (elem[0], " ::", elem[1])
exit (0)
x = {}
x.update ({'1': '2'})
print (x)
exit (0)
x = [1, 3, 3.1, 3, 4, 2, 3, 4, 3, 2, 5]
print (x[-2:])
exit (0)
high_low_means = {}
high_low_means['test'] = 1.2
high_low_means['test1'] = 1.3
FUTURE_HEADERS = {'User-Agent': 'Mozilla/5.0', 'Referer': 'https://tvc-invdn-com.akamaized.net'}
today_timestamp = int(
datetime(datetime.today().year, datetime.today().month, datetime.today().day, 15, 58, 56).timestamp())
page = urlopen(Request(
'https://tvc4.forexpros.com/783a9d5e01ae63dabd6a68480bb0f3e4/1556685636/56/56/23/history?symbol=993246&resolution=D&from=1525585469&to=' + str(
today_timestamp),
headers=FUTURE_HEADERS))
# parse the html using beautiful soup and store in variable `soup`
soup = BeautifulSoup(page, 'html.parser')
js = json.loads(soup.string.strip())
print(util.round_to_tick(js['c'][-1]))
print(util.round_to_tick(js['o'][-1]))
print(js['t'][-1])
today_date = datetime.today().date()
dt = util.get_date_from_timestamp(int(js['t'][-1]) * 1000)
print(dt)
print(datetime.today())
exit(0)
orders = [{'lot': 455, 'stop_loss': 2.2, 'square_off': 6.6, 'square_off_secon': 4.4, 'trailing_ticks': 20, 'action': 0,
'price_pts': 0.7, 'trigger_price_pts': 0.6, 'price_pts_secon': 0.9, 'trigger_price_pts_secon': 0.8,
'live_data_url': "'https://tvc4.forexpros.com/783a9d5e01ae63dabd6a68480bb0f3e4/1556685636/56/56/23/history?symbol=18040&resolution=D&from=1525704109&to='+str (today_timestamp)",
'instrument': "upstox_api.get_instrument_by_symbol (nse_bse.NSE, 'BPCL')"},
{'lot': 455, 'stop_loss': 2.2, 'square_off': 6.6, 'square_off_secon': 4.4, 'trailing_ticks': 20, 'action': 0,
'price_pts': 0.7, 'trigger_price_pts': 0.6, 'price_pts_secon': 0.9, 'trigger_price_pts_secon': 0.8,
'live_data_url': "'https://tvc4.forexpros.com/783a9d5e01ae63dabd6a68480bb0f3e4/1556685636/56/56/23/history?symbol=18040&resolution=D&from=1525704109&to='+str (today_timestamp)",
'instrument': "upstox_api.get_instrument_by_symbol (nse_bse.NSE, 'BPCL')"}]
print ('[')
for order in orders:
print (' {')
for k, v in order.items ():
print (" '" + k + "':", str (v) + ",")
print (' },')
print (']')
exit (0)
print(int(datetime(datetime.today().year, datetime.today().month, datetime.today().day, 15, 58, 56).timestamp()))
exit(0)
# ind, price = '0#1234.5'.split('#')
# print(ind, price)
# exit(0)
upstox_api = util.intialize_upstox_api ([nse_bse.NSE_FO, nse_bse.NSE])
print (upstox_api.get_order_history ())
exit (0)
upstox_api = util.intialize_upstox_api([nse_bse.NSE_FO, nse_bse.NSE])
orders = upstox_api.get_order_history()
if orders is not None and len(orders) > 0:
for order in orders:
if order['parent_order_id'] == 'NA' and order['status'] == 'open':
upstox_api.cancel_order(order['order_id'])
print('Order cancelled:', order['order_id'])
else:
print('No orders found')
print(upstox_api.get_order_history())
exit (0)
# [{'exchange': 'NSE_EQ', 'product': 'OCO', 'symbol': 'GODFRYPHLP', 'token': 1181, 'buy_amount': 0, 'sell_amount': 614163.55, 'buy_quantity': 0, 'sell_quantity': 539, 'cf_buy_amount': 0, 'cf_sell_amount': 0, 'cf_buy_quantity': 0, 'cf_sell_quantity': 0, 'avg_buy_price': '', 'avg_sell_price': 1139.45, 'net_quantity': -539, 'close_price': 1141.95, 'last_traded_price': 1136.8, 'realized_profit': '', 'unrealized_profit': 1428.350000000049, 'cf_avg_price': ''}, {'exchange': 'NSE_EQ', 'product': 'OCO', 'symbol': 'NBCC', 'token': 31415, 'buy_amount': 0, 'sell_amount': 259200, 'buy_quantity': 0, 'sell_quantity': 4000, 'cf_buy_amount': 0, 'cf_sell_amount': 0, 'cf_buy_quantity': 0, 'cf_sell_quantity': 0, 'avg_buy_price': '', 'avg_sell_price': 64.8, 'net_quantity': -4000, 'close_price': 65, 'last_traded_price': 65.05, 'realized_profit': '', 'unrealized_profit': -1000, 'cf_avg_price': ''}]
# print('a', 'b')
# exit(0)
# data = pickle.load(open(util.get_instrument_latest_data_file_name(), 'rb'))
#
# print(data)
#
# exit(0)
# while util.is_market_open () is False:
# pass
#
# while True:
# print (outil.get_equity_live_ltp ('TCS'))
# print ('Curr. time:', datetime.datetime.now ())
# time.sleep (.5)
#
# n = [{'a': 1, 'b': 2}]
# print (1 in x['a'] for x in n)
# exit (0)
upstox_api = util.intialize_upstox_api ([nse_bse.NSE_FO, nse_bse.NSE])
util.unsubscribe_symbols (upstox_api)
print (util.round_to_tick (6.9789768))
exit (0)
price_data = {}
price_data['test'] = []
price_data['test'].insert(0, {'t': 1, 'ltp': 2})
price_data['test'].insert (0, {'t': 2, 'ltp': 3})
# price_data['test'].pop()
print(price_data)
exit(0)
test = {}
test['test'] = {'test1': 1}
print('test' in test)
exit(0)
print('Curr(10)', datetime.datetime.now() - datetime.timedelta(seconds=10))
print('Curr', datetime.datetime.now())
exit(0)
data = pickle.load(open(util.get_instrument_latest_data_file_name(), 'rb'))
print(len(data))
timestamps = []
for stock_id, live_quote in data.items():
timestamps.append(live_quote['timestamp'])
timestamps.sort(reverse=True)
# # print (data)
# exit (0)
for timestamp in timestamps:
print(timestamp)
print((max(data[x]['timestamp'] for x in data)))
print((min(data[x]['timestamp'] for x in data)))
print('Curr', datetime.datetime.now())
exit(0)
# upstox_api = util.intialize_upstox_api ([nse_bse.NSE_FO, nse_bse.NSE])
# util.unsubscribe_symbols (upstox_api)
# print (util.round_to_tick (6.9789768))
# exit (0)
data = pickle.load (open (util.get_instrument_latest_data_file_name (), 'rb'))
print (data)
print (len (data))
# print (util.round_to_tick (6.9589768))
# print(datetime.datetime.now().date() == datetime.datetime(2019, 3, 4))
exit (0)
test = {}
test['test'] = {'test': 1}
print (test)
test['test'] = {'test': 2}
print (test)
exit (0)
# options = outil.get_all_strikes ('HDFC', datetime.datetime.now ().month, datetime.datetime.now ().year)
# print (ostrat.get_bear_call_spreads (options))
# print (ostrat.get_bear_put_spreads (options))
# print (ostrat.get_bull_call_spreads (options))
# print (ostrat.get_bull_put_spreads (options))
exit (0)
start_time = time.time ()
arr = []
for i in range (1, 2000):
arr.append (i)
mean = statistics.mean (arr)
print (mean)
print (time.time () - start_time)
exit (0)
traded = {}
traded.update ({'prev_price': 5})
print (traded)
traded.update ({'prev5_price': 6})
print (traded)
traded.clear ()
print (traded)
exit (0)
x = - math.inf
print (0 > x)
exit (0)
now = datetime.datetime.now()
print(now.time())
print(util.is_market_open())
exit(0)
print (
outil.get_last_thurday_of_month (datetime.datetime.today ().date ().month, datetime.datetime.today ().date ().year))
exit (0)
print (util.trim_date (datetime.datetime (2019, 3, 4)))
exit (0)
frequency = 2500 # Set Frequency To 2500 Hertz
duration = 1000 # Set Duration To 1000 ms == 1 second
winsound.Beep(frequency, 300)
exit(0)
print (round (79.89) == round (79.80))
exit (0)
x = [1, 3, 3.1, 3, 4, 2, 3, 4, 3, 2, 5]
print ([i for i in x if i == 4])
exit (0)
print(datetime.datetime.now())
exit(0)
# test = [{'exchange': 'NSE_FO', 'product': 'D', 'symbol': 'BANKBARODA19JANFUT', 'token': 52373, 'buy_amount': 0, 'sell_amount': 0, 'buy_quantity': 0, 'sell_quantity': 0, 'cf_buy_amount': 486800, 'cf_sell_amount': 0, 'cf_buy_quantity': 4000, 'cf_sell_quantity': 0, 'avg_buy_price': 121.7, 'avg_sell_price': '', 'net_quantity': 4000, 'close_price': 121.7, 'last_traded_price': 121.65, 'realized_profit': '', 'unrealized_profit': -199.99999999998863, 'cf_avg_price': '122.75'}]
# pickle_file1 = open('C:/Users/Admin/Desktop/New Text Document.txt','wb')
# pickle.dump(test, pickle_file1)
pickle_file1 = open('C:/Users/Admin/Desktop/New Text Document.txt', 'rb')
print(pickle.load(pickle_file1))
exit(0)
a = []
a.append('aaa')
print('aaa' in a)
exit(0)
a = {}
a.update({'aaa': 2.0})
print('aaa' in a)
print(a['aaa'])
exit(0)
age = input("What is your age? ")
print("Your age is: ", age)
exit(0)
# upstox_api = util.intialize_upstox_api([nse_bse.NSE_FO])
# print (upstox_api.get_positions()[0]['symbol'])
# print(upstox_api.get_trade_book())
# [{'exchange': 'NSE_FO', 'product': 'D', 'symbol': 'BANKBARODA19JANFUT', 'token': 52373, 'buy_amount': 0, 'sell_amount': 0, 'buy_quantity': 0, 'sell_quantity': 0, 'cf_buy_amount': 486800, 'cf_sell_amount': 0, 'cf_buy_quantity': 4000, 'cf_sell_quantity': 0, 'avg_buy_price': 121.7, 'avg_sell_price': '', 'net_quantity': 4000, 'close_price': 121.7, 'last_traded_price': 121.65, 'realized_profit': '', 'unrealized_profit': -199.99999999998863, 'cf_avg_price': '122.75'}]
exit(0)
# print(cutil.get_fair_future_value(7392.40, 7, 0))
exit(0)
x = [1, 3, 3.1, 3, 4, 2, 3, 4, 3, 2, 5]
print (all (3 > i for i in x) is False)
exit (0)
class Option1:
def __init__(self, strike_price, oi, symbol):
self.strike_price = strike_price
self.oi = oi
self.symbol = symbol
def __str__(self):
return str(self.strike_price)
def Option(strike_price, call_oi, put_oi, options):
x = Option1(strike_price, call_oi, 'HDFC' + str(strike_price) + 'ce')
y = Option1(strike_price, put_oi, 'HDFC' + str(strike_price) + 'PE')
options.append(x)
options.append(y)
print (urllib.parse.unquote ('M%26M'))
exit (0)
print ([1, 3, 3.1, 3, 4, 2, 3, 4, 3, 2, 5][0:4 + 1])
print ([1, 3, 3.1, 3, 4, 2, 3, 4, 3, 2, 5][-4:])
exit (0)
print (outil.get_all_bids ('HDFCBANK', datetime.datetime (2019, 2, 28).date ()))
# print(outil.get_all_bids('HDFC', datetime.datetime(2019, 1, 31).date()).strip())
exit (0)
# print (cutil.get_fair_future_value (2280.5, 80, 0))
exit (0)
date1 = parser.parse ('23-Feb-2018')
date2 = parser.parse ('24-Feb-2018')
print ((date2 - date1).days)
# for d in data.split(':'):
# for e in d.split(','):
# print(e.replace('"', ''))
exit(0)
exit(0)
options = outil.get_all_strikes('ITC', 1, 2019, '200')
for option in options:
print(option)
exit(0)
array1 = [0, 10, 20, 40]
array2 = [0, 10, 20, 40, 50]
array3 = [0, 10, 20, 40, 50, 60]
for data1, data2, data3 in zip(reversed(array1), reversed(array2), reversed(array3)):
print(data1, data2, data3)
reversed(array1)
for data1 in array1:
print(data1)
exit(0)
# print(datetime.datetime.strptime('31JAN2019', '%d%b%Y'))
# exit(0)
futures = outil.get_all_futures('HDFC', 1, 19)
for future in futures:
print(future)
exit(0)
kite = util.intialize_kite_api()
# instruments = (kite.instruments())
# with open('C:/Users/Admin/Desktop/intruments.txt', 'a') as the_file:
# for instrument in instruments:
# the_file.write(str(instrument)+'\n')
print(kite.historical_data(18362370, datetime.datetime(2018, 8, 21).date(), datetime.datetime(2019, 1, 1).date(),
'day', continuous=True))
exit(0)
print (parser.parse (
'"HDFCBANK","29-Dec-2016","25-Jan-2017","1189.85","1208.95","1187.7","1206.7","1206.1","1206.7","15087","90380","28076500","3623000","'.split (
',')[1].split ('"')[1].strip ()))
exit (0)
matchObj = re.match (r'.*>(.*)<.*',
'<DT><A HREF="http://www.girls-mag.de/images/product_images/info_images/711_1.jpg" ADD_DATE="1487221468"> red cute </A>')
if matchObj:
print ("matchObj.group(1) : ", matchObj.group (1))
words = matchObj.group (1).split ()
print (words)
exit (0)
future_data = {'timestamp': 1545991201000, 'exchange': 'NSE_FO', 'symbol': 'JPASSOCIAT19JANFUT', 'ltp': 7.7,
'open': 7.75, 'high': 7.8, 'low': 7.6, 'close': 7.7, 'vtt': 22880000, 'atp': 7.7, 'oi': 111320000,
'spot_price': 7.65, 'total_buy_qty': 9405000, 'total_sell_qty': 8305000, 'lower_circuit': 6.95,
'upper_circuit': 8.5, 'yearly_low': '', 'yearly_high': '',
'bids': [{'quantity': 990000, 'price': 7.65, 'orders': 18},
{'quantity': 1375000, 'price': 7.6, 'orders': 22},
{'quantity': 1100000, 'price': 7.55, 'orders': 4},
{'quantity': 1320000, 'price': 7.5, 'orders': 11},
{'quantity': 220000, 'price': 7.45, 'orders': 3}],
'asks': [{'quantity': 1265000, 'price': 7.75, 'orders': 22},
{'quantity': 715000, 'price': 7.8, 'orders': 12},
{'quantity': 990000, 'price': 7.85, 'orders': 7},
{'quantity': 1045000, 'price': 7.9, 'orders': 7},
{'quantity': 935000, 'price': 7.95, 'orders': 6}], 'ltt': 1545991198000}
print (outil.is_instrument_liquid (future_data['bids'], future_data['asks']))
exit (0)
# s = ' ddd 2,000.00 '
# print(util.remove_non_no_chars(s))
# exit (0)
options = []
Option(7000, 1404300, 4087050, options)
Option(7100, 335700, 1029150, options)
Option(7200, 482100, 2977875, options)
Option(7300, 422475, 1975650, options)
Option(7400, 963900, 2336700, options)
Option(7500, 999975, 4548450, options)
Option(7600, 785550, 3690900, options)
Option(7700, 1823400, 5783025, options)
Option(7800, 3448575, 4864125, options)
Option(7900, 5367450, 2559375, options)
Option(8000, 6510975, 1447125, options)
Option(8100, 5900325, 310500, options)
Option(8200, 5113350, 248775, options)
Option(8300, 3844500, 355725, options)
Option(8400, 2135625, 255525, options)
Option(8500, 2252250, 488475, options)
Option(8600, 1083750, 58500, options)