sonntagsgesicht/bf4py

A Python Package for retrieving data from boerse-frankfurt.de

bf4py

A Python Package for retrieving data from boerse-frankfurt.de

New methods: Now you can search derivatives using specified parameters.

Latest update: A lot of improvements were made under the hood. It's now object oriented resulting in better perfomance since http-sessions are reused for consecutive calls. Functions are now capsuled in classes but calls stay the same. However you must adapt function parameters since isin is not a positional argument anymore but an optional keyword-argument.

Description

This package uses an undocumented API to retrieve data that is available on www.boerse-frankfurt.de (no web-scraping!). It can be used by everyone who is interested in the german stock market as an alternative to available packages like yfinance which provides data for the US stock market.

So far functions for retrieving basic data are available, especially for equities, company information and news. Some more for bonds, funds, commodities and derivatives will come in future depending on demand, since most of the data from the website is provided via API.

Important notice

Data is usually delayed by 15Min by the provider and some data like bid/ask history are available only for short periods of history.

API Reference

Functions are encapsuled in submodules. See docstrings for details about parameters. Return values are always dicts with self-describing keys, so just try out.

bf4py.BF4Py() - NEW 🚨

This new class holds the https connection and provides functions via submodules like the previous version. Furthermore a default isin can be set, if not you have to provide it with every function call as before.

bf4py = BF4Py(default_isin='...', default_mic='...')

bf4py.general

.eod_data(...)
.data_sheet_header(...)
.instrument_information(...)
.index_instruments(...)

bf4py.equities

.equity_details(...)
.key_data(...)
.bid_ask_history(...)
.times_sales(...)
.related_indices(...)

bf4py.company

.about(...)
.upcoming_events(...)
.contact_information(...)
.company_information(...)
.ipo_details(...)

bf4py.news

.news_by_category(...)
.news_by_isin(...)
.news_by_id(...)
.get_categories()

bf4py.derivatives

.trade_history(...)
.instrument_data(...)
.search_parameter_template()
.search_derivatives(...)

bf4py.live_data

.price_information(...)
.live_quotes(...)
.bid_ask_overview(...)

Examples

from bf4py import BF4Py
from datetime import datetime, timedelta

bf4py = BF4Py(default_isin='DE0005190003') # Default BMW

Get some basic data about BMW stock:

bf4py.general.data_sheet_header() # Get info for BMW

Yields in:

{'participationCertificate': False,
 'isin': 'DE0005190003',
 'wkn': '519000',
 'instrumentName': {'originalValue': 'BAY.MOTOREN WERKE AG ST',
  'translations': {'others': 'BMW AG St'}},
 'exchangeSymbol': 'BMW',
 'instrumentTypeKey': 'equity',
 'underlyingValueList': None,
 'issuer': None,
 'companyIcon': 'https://erscontent.deutsche-boerse.com/erscontentXML/logo/204.jpg',
 'isParticipationCertificate': False}

If you want to get data about another instrument just provide the ISIN:

bf4py.general.data_sheet_header(isin='DE0005190003') # Get info for Mercedes Benz

Get the daily OHLC data of default stock on XETRA for one year:

end_date = date.today()
start_date = end_date - timedelta(days=365)

history = bf4py.general.eod_data(start_date, end_date)

Returns:

[{'date': '2022-03-29',
  'open': 217.3,
  'close': 218.55,
  'high': 220.45,
  'low': 216.4,
  'turnoverPieces': 1242298,
  'turnoverEuro': 271453308.35
 }, ...]

Get the times and sales list of that stock on XETRA:

start_date = datetime.now() - timedelta(days=1)
end_date = datetime.now()

ts = bf4py.equities.times_sales(start_date, end_date)

Result is a list of dicts where each dict is an executed trade:

[{'time': '2022-02-18T17:37:22+01:00',
 'price': 214.1,
 'turnover': 567076.0,
 'turnoverInEuro': 121410971.6}, ...]

Get live-data

For getting live data just create an receiver-client and start streaming:

client = bf4py.live_data.live_quotes(isin) 	client.open_stream()

Print output will be like:

{'isin': 'DE0008404005', 'bidLimit': 191.76, 'askLimit': 191.8, 'bidSize': 1135.0, 'askSize': 109.0, 'lastPrice': 191.78, 'timestampLastPrice': '2022-06-08T15:06:07+02:00', 'changeToPrevDayAbsolute': -4.38, 'changeToPrevDayInPercent': -2.2328711257, 'spreadAbsolute': 0.04, 'spreadRelative': 0.0208594076, 'timestamp': '2022-06-08T15:06:12+02:00', 'nominal': False, 'tradingStatus': 'CONTINUOUS'}

Finally stop transmission

client.close()

Notes:

• By default received data is sent to print() function but you can provide your own callback function for data evaluation
• Received data can be stored in client.data, use flag cache_data=True
• Cached data is cleared with every call of .open_stream()
• Sometimes it will need some seconds to start receiving data continuously
• Now you can reuse a client after a connection was closed by intend or error
• You can check client's status by client.active

Requirements

urllib
hashlib
requests
json
sseclient

Misc

Börse Frankfurt, Allianz and XETRA are registered brand names of their respective owners. I'm not connected in any way to one of the mentioned companys. Beyond that, I give no guarantee for the future functioning of the package as this depends on the technical framework of the provider.

Furthermore I'm not a developer, I'm just interested in exploring data. If you have an idea for improvement just let me know.