import tehran_stocks
# On first import package initialize itself

from tehran_stocks import get_all_price, Stocks, update_group

get_all_price() # download and(or) update all prices

update_group(34) #download and(or) update Stocks in groupCode = 34 (Cars)

Stocks.get_group() # to see list of group codes

from tehran_stocks import Stocks, db

# You can use query to find stocks
stock = Stocks.query.filter_by(name='كگل').first() #find by symbol(نماد)

stock = Stocks.query.filter_by(code='35700344742885862').first() # find by code on tsetmc url

stock = Stocks.query.filter(Stocks.title.like('%گل گهر%')).first() # Search by title

stock_list = Stocks.query.filter_by(group_code =34).all() # find all Stocks in Khodro

stock_list = Stocks.query.filter(Stocks.group_code.in_([13,34])).all() # all stocks in khodro and felezat


## (Advanced)or run sql query using orm or raw sql
db.session.query(Stocks.group_code, Stocks.group_name).group_by(Stocks.group_code).all()

db.session.execute('select group_code , group_name from stocks group by group_name').fetchall()

# use data as a pandas dataframe
>>> stock.df#
      id               code        ticker  dtyyyymmdd    first     high      low    close        value      vol  openint per     open     last       date
0  22491  35700344742885862  Gol-E-Gohar.    20040829  12000.0  12021.0  12000.0  12000.0  18841605000  1570000     2708   D  12000.0  12000.0 2004-08-29

>>> stock.summary()
Start date: 2004/08/29
End date: 2019/07/14
Total days: 2987

>>> stock.update()
# update stock price history

# Export to your preferred format
>>> stock.df.to_csv('price.csv')
>>> stock.df.to_excel('price.xlsx')
>>> stock.df.to_stata('price.dta')

>>> stock.get_instant_detail()
{'time': '12:29:57',
 'last_price': '12950',
 'last_close': '13060',
 'last_high': '13300',
 'last_low': '13130',
 'last_open': '13330',
 'trade_count': '12760',
 'trade_volume': '1140',
 'trade_value': '4671236',
 'market_cap': '60715047900',
 'date_string': '20220404',
 'time_string': '122957'}

# get change in share count
>>> stock.get_shares_history()

date	new_shares	old_shares	gdate
0	1400-12-08 00:00:00	200.000 B	100.000 B	2022-02-27
1	1400-04-20 00:00:00	100.000 B	74.400 B	2021-07-11

# get change in price ~ dividend, split, etc.
>> stock.get_dividend()
date	after	before	dividend	gdate
0	1400-04-16 00:00:00	18770	20070	1300	2021-07-07
1	1399-04-18 00:00:00	16350	17250	900	2020-07-08
)