Skip to main content

Betting trading framework

Project description

flūmine

Build Status Coverage Status PyPI version Downloads

flumine is an open-source, event-based trading framework for sports betting, designed to simplify the development and execution of betting strategies on betting exchanges. flumine provides efficient handling of data streams, risk management, and execution capabilities.

docs

join betcode slack group (2k+ members!)

overview

  • Event-based Execution: Real-time execution of trading strategies based on incoming market events
  • Custom Strategy Implementation: Easily define and implement trading strategies
  • Risk Management: Integrated risk management tools to monitor and limit exposure
  • Modular Design: Easily extendable and customizable components
  • Simulation: Simulate strategies/execution using historical data
  • Paper Trading: Test strategies in a simulated environment before going live
  • Data: Support for market, order and custom streaming data
  • Exchanges: Betfair, Betdaq (dev) and Betconnect

Backtesting Analysis

Tested on Python 3.8, 3.9, 3.10, 3.11 and 3.12.

installation

$ pip install flumine

flumine requires Python 3.8+

setup

Get started...

from flumine import Flumine, BaseStrategy
from betfairlightweight.filters import streaming_market_filter

# Define your strategy here
class ExampleStrategy(BaseStrategy):
    def check_market_book(self, market, market_book) -> bool:
        # process_market_book only executed if this returns True
        return True

    def process_market_book(self, market, market_book):
        # Your strategy logic
        pass

# Initialize the framework
framework = Flumine()

# Add your strategy to the framework
framework.add_strategy(
    ExampleStrategy(
        market_filter=streaming_market_filter(
            event_type_ids=["7"],
            country_codes=["GB"],
            market_types=["WIN"],
        )
    )
)

# Start the trading framework
framework.run()

Example strategy with logic and order execution:

from flumine import BaseStrategy
from flumine.order.trade import Trade
from flumine.order.order import LimitOrder, OrderStatus
from flumine.markets.market import Market
from betfairlightweight.filters import streaming_market_filter
from betfairlightweight.resources import MarketBook


class ExampleStrategy(BaseStrategy):
    def start(self, flumine) -> None:
        print("starting strategy 'ExampleStrategy'")

    def check_market_book(self, market: Market, market_book: MarketBook) -> bool:
        # process_market_book only executed if this returns True
        if market_book.status != "CLOSED":
            return True

    def process_market_book(self, market: Market, market_book: MarketBook) -> None:
        # process marketBook object
        for runner in market_book.runners:
            if runner.status == "ACTIVE" and runner.last_price_traded < 1.5:
                trade = Trade(
                    market_id=market_book.market_id,
                    selection_id=runner.selection_id,
                    handicap=runner.handicap,
                    strategy=self
                )
                order = trade.create_order(
                    side="LAY",
                    order_type=LimitOrder(price=1.01, size=2.00)
                )
                market.place_order(order)

    def process_orders(self, market: Market, orders: list) -> None:
        for order in orders:
            if order.status == OrderStatus.EXECUTABLE:
                if order.size_remaining == 2.00:
                    market.cancel_order(order, 0.02)  # reduce size to 1.98
                if order.order_type.persistence_type == "LAPSE":
                    market.update_order(order, "PERSIST")
                if order.size_remaining > 0:
                    market.replace_order(order, 1.02)  # move


# Initialize the framework
framework = Flumine()

# Add your strategy to the framework
framework.add_strategy(
    ExampleStrategy(
        market_filter=streaming_market_filter(
            event_type_ids=["7"],
            country_codes=["GB"],
            market_types=["WIN"],
        )
    )
)

# Start the trading framework
framework.run()

features

  • Streaming
  • Multiple strategies
  • Multiple clients
  • Order execution
  • Paper trading
  • Simulation
  • Event simulation (multi market)
  • Middleware and background workers to enable Scores / RaceCard / InPlayService

dependencies

flumine relies on these libraries:

  • betfairlightweight - Betfair API support
  • betdaq-retail - BETDAQ API support
  • betconnect - BetConnect API support
  • tenacity - Used for connection retrying (streaming)
  • python-json-logger - JSON logging
  • requests - HTTP support
  • smart-open - Efficient streaming of very large files from/to storages such as S3, including (de)compression

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

flumine-2.8.3.tar.gz (3.3 MB view details)

Uploaded Source

Built Distribution

flumine-2.8.3-py3-none-any.whl (87.3 kB view details)

Uploaded Python 3

File details

Details for the file flumine-2.8.3.tar.gz.

File metadata

  • Download URL: flumine-2.8.3.tar.gz
  • Upload date:
  • Size: 3.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.8.18

File hashes

Hashes for flumine-2.8.3.tar.gz
Algorithm Hash digest
SHA256 d155a40a629b540387f0c8f1c056eb746fa9b336db4e0bb179f3dc33086fcbc2
MD5 695683ee53e127d31df3df5d1a52f402
BLAKE2b-256 8d5dbb2b42970b016c3978b1f7f49ad0ffe0a8c9bcefc3223098ae1ac4846e34

See more details on using hashes here.

File details

Details for the file flumine-2.8.3-py3-none-any.whl.

File metadata

  • Download URL: flumine-2.8.3-py3-none-any.whl
  • Upload date:
  • Size: 87.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.8.18

File hashes

Hashes for flumine-2.8.3-py3-none-any.whl
Algorithm Hash digest
SHA256 73e52ddca08476f0952e7c14792de708e00ade814427a52c7c586318305b5627
MD5 47303652560e81522d744b3248b46875
BLAKE2b-256 f8dc2a3d14b2b02fce512cbb66a7405d2d0408db0ee936935b363e9fb9cf7f4b

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page