Betfairstreamer

Features

• Run single or multiple streams simultaneously.
• Making use of numpy arrays to access market price/size.
• Synchronous and asynchronous streaming.
• Parse historical data.

Installation

!! Requires >= 3.8.0

Conda installation

# If you already have an environment

conda activate your_environment
conda install -c anaconda python=3.8
pip install betfairstreamer==0.8.0

# If not, create an environment with python 3.8

conda create -n your_environment_name python=3.8
conda activate your_environment_name
pip install betfairstreamer==0.8.0

Virtual environment installation

mkdir your_project
cd your_project
python3.8 -m venv venv
source venv/bin/activate
pip install betfairstreamer==0.8.0

Examples

session_token = api_client.get_session_token()

soccer_subscription = create_market_subscription(
    event_type_ids=["1"],
    country_codes=["DE"],
    market_types=["MATCH_ODDS"],
    fields=["EX_MARKET_DEF", "EX_LTP", "EX_BEST_OFFERS_DISP"],
    ladder_levels=2,
)

order_subscription = create_order_subscription()

connection_pool = BetfairConnectionPool.create_connection_pool(
    subscription_messages=[
        soccer_subscription_message, 
        order_subscription_message
    ],
    app_key=APP_KEY,
    session_token=session_token
)

for stream_update in connection_pool.read():
    print(stream_update)

Jupyter notebooks available in ./examples

Benchmark

Setup: Two processes, one sending betfair stream messages , one receiving.

Hardware: I7 8550U, 16GB ram

Results: 
 * Using a market cache it can read around ~90k decoded messages/second