alpha-rptr
A trading bot for automated algorithmic trading on Binance Futures, Bybit, BitMEX and FTX written in python.
시스템 구조
저장소별 전략/실행 조건 확인 필요
거래소 API 기반 자동 주문 실행
에디터 요약저장소 설명과 공개 메타데이터 기준으로 Python 기반 구현, 암호화폐 거래 봇, 거래소 API/프레임워크, 백테스트 성격의 프로젝트로 파악했습니다. 확인 근거는 README, 저장소 토픽, 저장소 설명, GitHub 지표, 파이프라인 필드이며, 주요 데이터는 Binance, Bybit, BitMEX, FTX(역사 데이터), OHLCV/호가/체결 데이터입니다. 전략/실행 조건은 저장소별 문서와 코드 확인이 필요하며, 실행 방식은 "거래소 API 기반 자동 주문 실행"라고 보수적으로 기록했습니다. GitHub 지표는 별 678개, 포크 83개입니다.
| 저장소 | TheFourGreatErrors/alpha-rptr |
|---|---|
| 제작자 | TheFourGreatErrors |
| 스타 / 포크 | ★ 678 / 83 |
| 라이선스 | MIT |
| 최근 업데이트 | 2026-06-19 |
| 스냅샷 시점 | 2026-07-08 (아래 README는 이 시점의 사본입니다) |
아래는 제3자가 작성·공개한 오픈소스 코드입니다. QuantField는 해당 코드의 동작과 안전성을 보증하지 않으며, 설치·실행 전 코드를 직접 검토하시기 바랍니다.
README
alpha rptr
About
The Github repository features a trading system designed for automated algorithmic trading on Binance Futures, Bybit, BitMEX and FTX.
This trading system aims to offer an easy-to-use platform for users to test their trading strategies through backtesting and paper trading, as well as execute trades in live environments. With the goal of minimizing discrepancies between simulated and live trading results, the system allows for seamless transitions from backtesting to paper trading and finally to live trading. Additionally, users can expect minimal changes to their strategy code when transitioning from simulated to live trading.
While developing strategies, users are expected to have a basic understanding of trading and are not subject to many limitations. The system is designed around pre-defined events, such as market data updates, order updates, and trade executions, and provides various technical features, including advanced order types, and real-time position and order monitoring, to support the development and execution of trading strategies.
Disclaimer
Please note that the author of this software is not liable for any losses, damages or other adverse consequences resulting from the use of this software. It is highly recommended that you exercise caution and thoroughly test your trading strategy using small sizes over an extended period of time to ensure that it performs as expected before deploying it with larger sums of money.
Table of Contents
- About
- Disclaimer
- Features
- Refrence Strategies
- Installation
- How to Run
- How To Add a Custom Strategy
- Key Functions
- Strategy Session Persistence
- Advanced Session Usage
- HTML5 Workbench for Backtests
- Plotting in Matplotlib
- Logging Metrics to InfluxDB
- Discord Server
- Tip Jar
Features
- REST API and Websocket implementation for multiple cryptocurrency exchanges, including Bybit, BitMEX, Binance Futures, and FT