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SANDWORM_MODE: Shai-Hulud-Style npm Worm Hijacks CI Workflows and Poisons AI Toolchains
An emerging npm supply chain attack that infects repos, steals CI secrets, and targets developer AI toolchains for further compromise.
tsetmc
Advanced tools
.. 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/.
Requires Python 3.13 or later.
pip install tsetmc
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_initmarket_watch_plusclosing_price_allclient_type_allkey_statsombud_messagesstatus_changesUse 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.
.. _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/
FAQs
a library to retrieve data from tsetmc.com website
We found that tsetmc demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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