Metadata-Version: 2.3
Name: tsetmc
Version: 2.0.0
Summary: a library to retrieve data from tsetmc.com website
Keywords: tsetmc,client
Author: 5j9
Author-email: 5j9 <5j9@users.noreply.github.com>
License: GNU General Public License v3 (GPLv3)
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: aiohutils>=0.20.0
Requires-Dist: jdatetime
Requires-Dist: lxml
Requires-Dist: numpy
Requires-Dist: pandas>=2.1.0
Requires-Dist: pyarrow
Requires-Python: >=3.13
Project-URL: Homepage, https://github.com/5j9/tsetmc
Description-Content-Type: text/x-rst

.. image:: https://github.com/5j9/tsetmc/actions/workflows/pytest.yml/badge.svg
   :alt: Pytest Status
   :target: https://github.com/5j9/tsetmc/actions/workflows/pytest.yml

An ``async`` Python library to fetch data from https://tsetmc.com/.

Installation
------------
Requires Python 3.13 or later.

``pip install tsetmc``

Overview
--------
Let's start with a simple script:

.. code-block:: python

    import asyncio

    from tsetmc.instruments import Instrument


    async def main():
        inst = await Instrument.from_l18('فملی')
        info = await inst.info()
        print(info)


    asyncio.run(main())


The ``Instrument`` class provides many methods for getting information about an instrument.
The following code blocks try to demonstrate some of its capabilities.

Note: You need an asyncio capable REPL, like ``python -m asyncio`` or `IPython`_, to run the following code samples, otherwise you'll have to run them inside an async function like the sample code above.

.. code-block:: python

    >>> from tsetmc.instruments import Instrument
    >>> inst = await Instrument.from_l18('فملی')
    >>> await inst.info()
    {'eps': {'epsValue': None,
      'estimatedEPS': '721',
      'sectorPE': 12.02,
      'psr': 1472.8279},
     'sector': {'dEven': 0, 'cSecVal': '27 ', 'lSecVal': 'فلزات اساسی'},
     'staticThreshold': {'insCode': None,
      'dEven': 0,
      'hEven': 0,
      'psGelStaMax': 8270.0,
      'psGelStaMin': 7190.0},
     'minWeek': 7630.0,
     'maxWeek': 7970.0,
     'minYear': 4630.0,
     'maxYear': 10670.0,
     'qTotTran5JAvg': 179233329.0,
     'kAjCapValCpsIdx': '43',
     'dEven': 0,
     'topInst': 1,
     'faraDesc': '',
     'contractSize': 0,
     'nav': 0.0,
     'underSupervision': 0,
     'cValMne': None,
     'lVal18': 'S*I. N. C. Ind.',
     'cSocCSAC': None,
     'lSoc30': None,
     'yMarNSC': None,
     'yVal': '300',
     'insCode': '35425587644337450',
     'lVal30': 'ملی\u200c صنایع\u200c مس\u200c ایران\u200c',
     'lVal18AFC': 'فملی',
     'flow': 1,
     'cIsin': 'IRO1MSMI0000',
     'zTitad': 600000000000.0,
     'baseVol': 15584416,
     'instrumentID': 'IRO1MSMI0001',
     'cgrValCot': 'N1',
     'cComVal': '1',
     'lastDate': 0,
     'sourceID': 0,
     'flowTitle': 'بازار بورس',
     'cgrValCotTitle': 'بازار اول (تابلوی اصلی) بورس'}


Getting the latest price information:

.. code-block:: python

    >>> await inst.closing_price_info()
    {'instrumentState': {'idn': 0,
      'dEven': 0,
      'hEven': 0,
      'insCode': None,
      'cEtaval': 'A ',
      'realHeven': 0,
      'underSupervision': 0,
      'cEtavalTitle': 'مجاز'},
     'instrument': None,
     'lastHEven': 170725,
     'finalLastDate': 20230524,
     'nvt': 0.0,
     'mop': 0,
     'thirtyDayClosingHistory': None,
     'priceChange': 0.0,
     'priceMin': 7630.0,
     'priceMax': 7900.0,
     'priceYesterday': 7730.0,
     'priceFirst': 7750.0,
     'last': True,
     'id': 0,
     'insCode': '0',
     'dEven': 20230524,
     'hEven': 170725,
     'pClosing': 7700.0,
     'iClose': False,
     'yClose': False,
     'pDrCotVal': 7670.0,
     'zTotTran': 7206.0,
     'qTotTran5J': 84108817.0,
     'qTotCap': 648015842640.0}


Getting the daily trade history for the last n days: (as a DataFrame)

.. code-block:: python

    >>> await inst.daily_closing_price(n=2)
       priceChange  priceMin  priceMax  ...  zTotTran  qTotTran5J       qTotCap
    0         30.0    7490.0    7600.0  ...    4555.0  75649965.0  5.689944e+11
    1         10.0    7500.0    7590.0  ...    4614.0  83570336.0  6.276337e+11
    [2 rows x 17 columns]


Getting adjusted daily prices:

.. code-block:: python

    >>> await inst.price_history(adjusted=True)
                 pmax   pmin     pf     pl       tvol     pc
    date
    2007-02-04     45     41     45     42  172898994     42
    2007-02-05     43     43     43     43   10826496     43
    2007-02-06     44     44     44     44   26850133     44
    2007-02-07     45     45     45     45   31086849     45
    2007-02-10     45     45     45     45   40645528     45
               ...    ...    ...    ...        ...    ...
    2021-07-12  13340  12840  13110  12860  106208763  13020
    2021-07-13  13010  12640  12840  12680   66812306  12770
    2021-07-14  12830  12450  12540  12690   70277940  12670
    2021-07-17  12960  12550  12800  12640   68542961  12750
    2021-07-18  12880  12530  12600  12630   88106162  12650
    [3192 rows x 6 columns]


Getting intraday data for a specific date:

.. code-block:: python

    >>> await inst.on_date(20210704).states()  # a dataframe:
       idn  dEven  hEven insCode cEtaval  realHeven  underSupervision cEtavalTitle
    0    0      0      1       0      A       94838                 0         None


Searching for an instrument:

.. code-block:: python

    >>> await Instrument.from_search('چادرملو')
    Instrument(18027801615184692, 'کچاد')

The ``instruments.price_adjustments`` function gets all the price adjustments for a specified flow.


The `market_watch`_ module contains several function to fetch market watch data. They include:

* ``market_watch_init``
* ``market_watch_plus``
* ``closing_price_all``
* ``client_type_all``
* ``key_stats``
* ``ombud_messages``
* ``status_changes``

Use ``market_watch.MarketWatch`` for watching the market. Here is how:

.. code-block:: python

    from asyncio import new_event_loop

    from tsetmc.market_watch import MarketWatch


    async def listen_to_update_events():
        while True:
            await market_watch.update_event.wait()
            df = market_watch.df
            print(df.at['35425587644337450', 'pl'])  # last price of فملی


    market_watch = MarketWatch()
    loop = new_event_loop()
    watch_task = loop.create_task(listen_to_update_events())
    loop.run_until_complete(market_watch.start())



There are many other functions and methods that are not covered here. Explore the codebase to learn more.

To keep the offline dataset up-to-date, run the `tsetmc.dataset.update()` function periodically (e.g., daily). This dataset acts as a cache for basic information about common instruments.

If you are interested in other information available on tsetmc.com that this library has no API for, please `open an issue`_ for them.


See also
--------

* https://github.com/5j9/fipiran

.. _pandas: https://pandas.pydata.org/
.. _market_watch: http://www.tsetmc.com/Loader.aspx?ParTree=15131F
.. _open an issue: https://github.com/5j9/tsetmc/issues
.. _IPython: https://ipython.org/
