def get_equity_price(symbol):
scrip_id = symbol.upper()
n = Nse()
data = n.get_scrip_data(scrip_id)
price, lastUpdateTime = n.get_data_for_key(data, 'lastPrice')
print("Current LTP for {} is {} at time {} ".format(
scrip_id, price, lastUpdateTime))
def get_open_price_equity(symbol):
scrip_id = symbol.upper()
n = Nse()
data = n.get_scrip_data(scrip_id)
price, lastUpdateTime = n.get_data_for_key(data, 'open')
print("Open Price for {} is {} at time {} ".format(scrip_id, price,
lastUpdateTime))
# for j in range(i,len(mn)):
# x = mn[i][0],mn[j][0]
# y = mn[i][1],mn[j][1];
# c+=1
# print(c)
# plt.plot(x,y)
plt.xlabel("date")
plt.ylabel("price")
plt.title(STOCK)
plt.xticks(x, rotation='vertical')
# Pad margins so that markers don't get clipped by the axes
plt.margins(0.2)
plt.show()
plt.plot(maxdate, maxY)
df.plot(x='CH_TIMESTAMP', y='CH_CLOSING_PRICE')
db = Nse()
fno = nse.Nse()
fno_lot = fno.get_fno_lot_sizes(as_json=False)
fno_list = list(fno_lot.keys())
global df, historic_data, x, y, mapping, mn, mx, maxY, minY, mindate, maxdate, closingPrice, STOCK
for stk in fno_list:
try:
print("processing ... " + stk)
getMaxMin(stk, True)
except:
print(stk)
from nse import Nse
import time
from nsetools import nse
db = Nse()
fno = nse.Nse()
lis = fno.get_fno_lot_sizes(as_json=False)
fno_lot = dict(lis)
keys = list(fno_lot.keys())
print(keys)
for key in keys[10:]:
try:
price = db.live(key)['lastPrice']
if price * lis[key] > 200000 and price * lis[key] < 500000:
print(key.ljust(20),
str(lis[key]).ljust(20),
str(price).ljust(20), "{:,}".format(price * lis[key]))
except:
pass
# time.sleep(1)
# print(data)
from nse import Nse
db = Nse()
data = db.live("HDFCBANK")
print(data)
#Load OIL Brand Data.
data = db.load('HDFCBANK')
#Bar Grap Of Data
Hdata = db.history("HDFCBANK","05-10-2020",'15-10-2020')
print(Hdata)
def is_market_open():
n = Nse()
market_status = n.get_market_status()
print("Market is {} currently ".format(market_status))
def get_day_high_low(symbol):
scrip_id = symbol.upper()
n = Nse()
data = n.get_scrip_data(scrip_id)
low, high = n.get_day_high_low(data)
print(" Days Low is {} and Days High is {} ".format(low, high))
def changeLastRunDate(lastRunDate):
fh = open("lastRundate.txt", "w")
fh.write(lastRunDate)
fh.close()
def getLastRunDate():
filename = 'lastRundate.txt'
fh = open(filename, "r")
return fh.read()
if __name__ == '__main__':
nse = Nse()
count = 0
lastRunDate = getLastRunDate()
while (count <= 10000):
time.sleep(20)
if count == 0:
nse.download_bhavcopy(lastRunDate)
print('lastRunDate is', lastRunDate)
else:
previousDate = getPreviousDate(lastRunDate)
nse.download_bhavcopy(previousDate)
lastRunDate = previousDate
print('lastRunDate is', lastRunDate)
count = count + 1
changeLastRunDate(lastRunDate)
import logging
import json
import re
import six
import time
from nse import Nse
from datetime import datetime, timedelta
from dateutil import parser
from utils import js_adaptor, byte_adaptor
log = logging.getLogger('nse')
logging.basicConfig(level=logging.DEBUG)
def isHoliday(date):
return date.isoweekday() > 5
def getPreviousDay():
currentDay = datetime.now().date()
previousDay = currentDay - timedelta(days=1)
return previousDay.strftime('%dth %b %Y')
if __name__ == '__main__':
nse = Nse()
count = 0
yesterday = getPreviousDay()
print('lastRunDate is', yesterday)
nse.download_bhavcopy(yesterday)