tse_dataloader

tse_dataloader is a python package for extracting stock historical data from Tehran Stock Exchange.

• Extract data and load them in Pandas data frame
• Calculate SMA and EMA
• Create line charts with matplotlib

Install:

pip install tse_dataloader

Functions:

• Loading data with get_data(ticker) or getcode_data(code)

>>> from tse_dataloader import download
>>> MELT= download.get_data('وبملت')
>>> print(MELT)

                   TICKER    FIRST     HIGH  ...     OPEN     LAST  date_shamsi
Date                                         ...                               
2009-02-18  S*Mellat.Bank   1050.0   1050.0  ...   1000.0   1050.0   1387/11/30
2009-02-21  S*Mellat.Bank   1051.0   1076.0  ...   1050.0   1057.0   1387/12/03
2009-02-22  S*Mellat.Bank   1065.0   1074.0  ...   1050.0   1055.0   1387/12/04
2009-02-23  S*Mellat.Bank   1066.0   1067.0  ...   1065.0   1060.0   1387/12/05
2009-02-25  S*Mellat.Bank   1061.0   1064.0  ...   1061.0   1060.0   1387/12/07
...                   ...      ...      ...  ...      ...      ...          ...
2020-07-01  S*Mellat.Bank  27350.0  27370.0  ...  26110.0  26690.0   1399/04/11
2020-07-04  S*Mellat.Bank  26940.0  27000.0  ...  26940.0  25600.0   1399/04/14
2020-07-05  S*Mellat.Bank  24560.0  27040.0  ...  25760.0  25860.0   1399/04/15
2020-07-06  S*Mellat.Bank  26200.0  26950.0  ...  25670.0  26950.0   1399/04/16
2020-07-07  S*Mellat.Bank  27320.0  28200.0  ...  26860.0  26040.0   1399/04/17

[2374 rows x 12 columns]

>>> MELT= download.getcode_data(778253364357513)

• Plot Close price and Volume line chart with close_vol()

>>> from tse_dataloader import analysis
>>> analysis.close_vol(MELT)

# to create a chart without gaps you can use df.reset_index()
>>> analysis.close_vol(MELT.reset_index())

• Calculate short and long term Simple Moving Average, Exponential Moving Average, add them to your data frame and plot chart line with sma() and ema()

>>> from tse_dataloader import analysis
>>> analysis.sma(MELT, 20, 50)
>>> analysis.ema(MELT, 20, 50)

• For your convenience, I create a list of tickers and attached it to the package to load data faster. In order to update your symbol list, you can use stock_list.update(). it takes a few minutes to update data from tsetmc.

>>> import tse_dataloader
>>> stock_list.update()

Database has updated!

• In some cases, if you couldn't find your specific symbol in the list, you can add it to the list manually with the stock_list.add() function.

>>> import tse_dataloader
>>> stock_list.add(2400322364771558, 'شستا')


Symbol added to the list!

You can find every symbol's code at the end of its URL:
http://www.tsetmc.com/loader.aspx?ParTree=151311&i=2400322364771558

Thanks to tehran-stock