import time
import argparse
import pandas as pd
from nsetools import Nse
nse = Nse()
t = time.time()
FILE_LOCATION = '' # csv file, blank because path not relevant to others
df = pd.read_csv(FILE_LOCATION)
CSV File contents:
Instrument,Qty,Avg buy price
APLAPOLLO,3,949.95
AVANTIFEED,6,554.55
BALAMINES,9,337.72
BALMLAWRIE,4,258.5
BANCOINDIA,15,217
DCMSHRIRAM,12,261.4
GHCL,12,267.2
GIPCL,27,101.95
JAMNAAUTO,15,182.1
JBCHEPHARM,15,344.85
KEI,24,143.95
KPRMILL,6,569.65
KRBL,9,312
MPHASIS,6,533.95
SHEMAROO,2,413.25
Code:
# using argparse to provide options for obtaining closePrice or buyPrice1
# of stocks
parser = argparse.ArgumentParser(description='Stock Quote fetcher')
parser.add_argument('-r', '--realtime', help='Obtain realtime stock\
quotes', action='store_true')
args = parser.parse_args()
def get_closing(stock):
"""Function to obtain closePrice or buyPrice1 of stocks"""
if args.realtime:
return nse.get_quote(stock)['buyPrice1']
else:
return nse.get_quote(stock)['closePrice']
# calculating current value of investment
current_value = sum(get_closing(row[0]) * row[1] for index, row in
df.iterrows())
print(current_value)
print("Completed in ", time.time() - t)
Currently the stock prices are obtained sequentially using the generator expression. Doing this takes 18-25 seconds to calculate the current value of investment. Is there any way to obtain these prices all together in parallel and calculate current value of investment?