BSE-Stocks-API

An API for Indian BSE Stock Quotes

We can retrieve both daily stock quotes as well as archives of stock quotes.

Daily Stock Quotes :

Usage :

Create an instance of BSEDailyStockQuotes by passing a list of company scrip codes as constructor argument.
Each company in bseindia.com has a scrip code identifier.
For example : scrip code for INFOSYS LTD. is 500209, HDFC BANK LTD. is 500180

The various stock data attributes scraped from bseindia.com website are :
company_name
face_value
stock_price
change
percentage_change
day_high_low
prev_close_open
wtd_avg_price
total_traded_val
total_traded_val_unit
ttq_2wAvgQ
ttq_unit
circuit_limits
market_cap_full
weekly_high
weekly_low
monthly_high
monthly_low
weeks52_high
weeks52_high_date
weeks52_low
weeks52_low_date
var_elm
delivery
exdate

lstCodes = ["500209", "500180"]  
data = BSEDailyStockQuotes(lstCodes)  

To retrieve a specific attribute value:

data.stockQuotes["500180"].company_name  
data.stockQuotes["500209"].face_value  

or to retrieve all companies values :

for code in lstCodes:  
	print data.stockQuotes[code].company_name  
	print data.stockQuotes[code].stock_price  

To print output as csv file:

data.print_csv_output()  

To print output as text summary report:

data.print_txt_output()  

Archived Stock Quotes :

Usage :

Create an instance of BSEArchivedStockQuotes by passing a list of company scrip codes as constructor argument.
Each company in bseindia.com has a unique scrip code identifier.
For example : scrip code for INFOSYS LTD. is 500209, HDFC BANK LTD. is 500180

The various attributes of archived stock data scraped from bseindia.com website are :
company_name
date
open_price
day_high
day_low
close_price
wap
no_of_shares
no_of_trades
total_turnover
deliverable_qty
percent_qty
highlow_spread
closeopen_spread

lstCodes = ["500209", "500180"]  
data = BSEArchivedStockQuotes(lstCodes)  

To retrieve a specific attribute value:

data.stockQuotes["500180"].company_name  
data.stockQuotes["500180"].open_price[0]  
data.stockQuotes["500209"].total_turnover[5]  

or to retrieve all archived values over the period

for i in range(1, len(data.stockQuotes["500180"].date)):  
	print data.stockQuotes["500180"].no_of_shares[i]  
	print data.stockQuotes["500180"].no_of_trades[i]  

or to retrieve all companies values :

for code in lstCodes:  
	for i in range(1, len(data.stockQuotes[code].date)):  
			print data.stockQuotes[code].day_high[i]  
			print data.stockQuotes[code].day_low[i]  

To print entire output:

data.print_output()   

We can also print the output separated by other delimiters:

data.print_output("|")