nifpy

nifpy is an easy to use python package that can be used to fetch live price, closing price, stock summary, index list and fundamentals such as income statement, cash flow statement and balance sheet of stocks that trade on the National Stock Exchange(NSE).

Getting Started

Installation

You can install the package from Pypi

pip3 install nifpy

Dependencies

You can install the dependencies by executing the following code in your terminal

pip3 install -r requirements.txt

How to get the scrip name

You can get the scrip/symbol/ticker of the stock you want by opening the yahoo finance website and searching for the company as shown below.

Methods

• get_live_price
• get_balance_sheet
• get_cash_flow
• get_income_statement

Chart Center

• moving_avg
• bollinger_bands
• get_chart

get_live_price

This function returns the live/latest price for the symbol that has been passed as the parameter

from nifpy import *
price = get_live_price(ticker)
print(price)

""" 
Parameters
-------------------------------
ticker : Contains the symbol/ticker for which the live price will be returned
"""
#Example
price = get_live_price('ITC.NS')

get_balance_sheet

Used to obtain the balance sheet of the specified ticker

from nifpy import get_balance_sheet

balance_sheet = get_balance_sheet(symbol)
print(balance_sheet)

"""
Parameters
-------------------------------
symbol : str
    The stock symbol/ticker for which the balance sheet is to be fetched.

Returns
--------------------------------
A DataFrame containing the annual balance sheet of the company.
"""
#Example
balance_sheet = get_balance_sheet('RELIANCE.NS')

get_cash_flow

Used to obtain the cash flow statement of the specified ticker

from nifpy import get_cash_flow

cash_flow = get_cash_flow(symbol, quarterly=True)
print(cash_flow)

"""
Parameters
-------------------------------
symbol : str
    The stock symbol/ticker for which the cash flow statement is to be fetched.

quarterly : bool, optional (default=True)
    If True, returns the quarterly cash flow statement.
    If False, returns the annual cash flow statement.

Returns
--------------------------------
A DataFrame containing the cash flow statement of the company.
"""
# Example

# Quarterly cash flow
cash_flow = get_cash_flow("HCLTECH.NS", quarterly=True)

# Annual cash flow
cash_flow = get_cash_flow("HCLTECH.NS", quarterly=False)

get_income_statement

Used to obtain the income statement of the specified ticker

from nifpy import get_income_statement

income_statement = get_income_statement(symbol, quarterly=False)
print(income_statement)

"""
Parameters
-------------------------------
symbol : str
    The stock symbol/ticker for which the income statement is to be fetched.

quarterly : bool, optional (default=False)
    If True, returns the quarterly income statement.
    If False, returns the annual income statement.

Returns
--------------------------------
A DataFrame containing the income statement of the company.
"""
# Example

# Annual income statement
income_statement = get_income_statement("TITAN", quarterly=False)

# Quarterly income statement
income_statement = get_income_statement("TITAN", quarterly=True)

Indices

• get_nifty()
• get_sensex()
• get_nifty_next50()
• get_nifty_bank()
• get_nifty_auto()
• get_nifty_financial()
• get_nifty_fmcg()
• get_nifty_it()
• get_nifty_media()
• get_nifty_metal()
• get_nifty_pharma()
• get_nifty_psubank()
• get_nifty_privatebank()
• get_nifty_realty()

from nifpy import get_nifty_it
it_stocks = get_nifty_it()
print(it_stocks)

In a similar way stocks trading in other indices are returned as a list and can be used for further analysis.

moving_avg

Used to plot the moving average of the specified ticker

from nifpy import moving_avg
moving_avg(scrip, num_days)

""" 
Parameters
-------------------------------
scrip : It is used to specify the symbol/ticker for which the moving average has to be plotted
num_days : Number of days for which moving average has to be plotted. Commonly used values
            are 14, 20, 50, 100, 200 

Returns
--------------------------------
Plot consisting of moving average along with the closing price
"""
#Example

#Moving average for 20 days
moving_avg('ITC.NS', 20)

#Moving average for 50 days
moving_avg('ITC.NS', 50)

bollinger_bands

Used to plot Bollinger Bands of the specified ticker

from nifpy import bollinger_bands
bollinger_bands(scrip)

""" 
Parameters
-------------------------------
scrip : Used to specify the symbol/ticker for which Bollinger Bands has to be plotted 

Returns
--------------------------------
Plot consisting of Bollinger Bands for the past 600 days
"""
#Example
bollinger_bands('DIVISLAB.NS')

get_chart

Used to get the historical chart of the specified ticker

from nifpy import get_chart
import datetime

get_chart(scrip, kind = 'line',start = TODAY-PREV, end = TODAY)

# TODAY = datetime.date.today()
# PREV = datetime.timedelta(600)

""" 
Parameters
-------------------------------
scrip : Used to specify the symbol/ticker for which historical chart has to be plotted

kind : The type of chart - 'line' or 'area'

start :   Contains the starting date
          Format: 'dd/mm/yyyy' as in '25/04/2020' 
          Default: 600 days from today's date

end :     Contains the end date
          Format: 'dd/mm/yyyy' as in '27/05/2021' 
          Default: Today's date

Returns
--------------------------------
Historical chart based on time frame
"""
#Example

#For area chart with default timeframe of 600 days
get_chart('SBIN.NS','area')

#For line chart with custom timeframe
get_chart('SBIN.NS','line','25/04/2020','27/05/2021')