soham874 / nsedt

Library to collect NSE data in pandas dataframe

NSE (national stock exchange) data

Introduction: This library serves as an api to fetch data from the NSE about stocks and indices and derivatives using python

Thank you for using Nsedt. Please feel free to send pull requests, comments, and suggestions, as well as get in touch with me if you require any additional help. I sincerely hope you will find this library useful.

For detailed doc please refer nse-doc

How to start

1. clone the repository git clone https://github.com/pratik141/nsedt
2. Install the requirements file after changing to cloned folder above pip install -r requirements.txt
3. Install locally pip installl . --upgrade

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Equity

Details

Name	Module name	Description	Argument	Response
companyinfo	get_companyinfo	Company info	symbol , response_type	json, panda df
marketstatus	get_marketstatus	marketstatus	--	panda_df
price	get_price	price	start_date, end_date, symbol, input_type	json, panda df
corpinfo	get_corpinfo	corpinfo	arg
event	get_event	event	start_date, end_date	panda df
chartdata	get_chartdata	chartdata	symbol	panda df
symbols_list	get_symbols_list	symbols_list	--	json
asm_list	get_asm_list	symbols_list	asm_type	json

Now get_price work with start_date, end_date without datetime format it support %d-%m-%Y

step to run

from nsedt import equity as eq
from datetime import date

start_date = date(2023, 1, 1)
end_date = date(2023, 1, 10)
print(eq.get_price(start_date, end_date, symbol="TCS"))
start_date = "01-05-2023"
end_date = "03-05-2023"
print(eq.get_corpinfo(start_date, end_date, symbol="TCS"))
print(eq.get_event(start_date, end_date))
print(eq.get_event())
print(eq.get_marketstatus())
print(eq.get_marketstatus(response_type="json"))
print(eq.get_companyinfo(symbol="TCS"))
print(eq.get_companyinfo(symbol="TCS", response_type="json"))
print(eq.get_chartdata(symbol="TCS"))
print(eq.get_symbols_list()) #print the list of symbols used by NSE for equities
print(eq.get_asm_list(asm_type = "shortterm"))

Indices

Details

Name	Module name	Description	Argument	Response
price	get_price	price	start_date, end_date, symbol	panda df

step to run

from nsedt import indices as ind
from datetime import date

start_date = date(2023, 1, 1)
end_date = date(2023, 1, 10)
print(ind.get_price(start_date=start_date, end_date=end_date, symbol="NIFTY 50"))
data = ind.get_price(start_date=start_date, end_date=end_date, symbol="NIFTY")
# To change date format from '%d-%b-%Y' to '%Y-%m-%d'
data["Date"] = pd.to_datetime(data["Date"],format='%d-%b-%Y')

Derivatives

Details

Name	Module name	Description	Argument	Response
vix	get_vix	price	start_date, end_date,columns_drop_list	panda df
option chain	get_option_chain	get option price	symbol,strikePrice,expiryDate	panda df
option chain expiry date	get_option_chain_expdate	option chain expiry date	symbol	json
future price	get_future_price	get future price	symbol, start_date, end_date, expiryDate,response_type, columns_drop_list	panda df
future expiry date	get_future_expdate	future expiry date	symbol	json

step to run

from nsedt import derivatives as de
start_date = "01-09-2023"
end_date = "03-09-2023"
# date format "%d-%m-%Y"
print(de.get_vix(start_date, end_date))
print(de.get_option_chain_expdate(symbol="TCS"))
print(de.get_option_chain(symbol="TCS", strike_price=3300, expiry_date="expiryDate"))
print(de.get_future_price(symbol="TCS", start_date=start_date, end_date=end_date))
print(de.get_future_expdate(symbol="TCS"))