Raderbot

Table of Contents

• Overview
• Getting Started
• Bootstrap and Storage
• Historical Data
• Development
• Features
• Contributing
• License

Overview

Raderbot is a Rust-based trading bot designed to interact with the Binance or BingX for market data analysis and trading operations. It utilizes the Actix Web framework for building a WebSocket server and handling incoming messages.

The bot connects to the exchange API to receive real-time market data updates, including ticker, trades and kline information.

Getting Started

Notes:

• The project is still in the development phase, everything is still experimental and may not work or undocumented.
• Any contributions are welcome to source code or documentation.
• Build only work for Unix systems.
• Bot only runs in Dry Mode
• By default the bot starts with 3 active streams. It starts these streams and starts saving data from these streams. Use the API to check active streams.
• In order to run backtests you will need historical data. Pleas see Historical Data section for details on how to get historical data for the bot.

Postman API Docs: Current API docs can be found here: Postman Docs

1. Configure environment

• Change values of .env.example
• Rename .env.example to .env
• Run build

make build

2. Run Bot

./raderbot

3. Interact with bot through Postman on address http://localhost:3000

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Storage And Bootstrap

• By default the bot is configured to use system file storage. This means a directory is created within the user home directory at ~/.raderbot. All data loaded through the BootstrapKlineData or BootstrapTradeData API requests will be saved here.
• All new market data is saved in this directory, data such as streamed K-Line data and Market Trades.
• It is possible to use a more performant storage solution such as MongoDB time series data. You will need access to MongoDB instance. In order to configure the bot to use MongoDB. Update the .env and restart the bot, new values are:

.env
...
STORAGE_TYPE=MONGO
MONGO_URI={NEW_URI}
...

Historical Data

• In order to run BootstrapKlineData or BootstrapTradeData you will need to download the historical data first. The data can be downloaded from Binance, the data collections are:

• https://www.binance.com/en-AU/landing/data

  • K-Line
  • Aggregated Trades

The historical data will need to be placed in this exact directory ~/Projects/BinanceData, the folder structure looks like this

   ~/Projects/BinanceData/
      ├── Kline/
         ├── BTCSTUSDT-5m-2023-12.csv
         ├── ...
         └── ...
      └── MarketTrade/
         ├── /BTCUSDT-aggTrades-2020-01.csv
         ├── ...
         └── ...

Development

Prerequisites

Make sure you have the following tools installed on your system:

• Rust: The programming language used for the project.
• cargo-watch: Used for automatically restarting the server during development.
• make: Used for managing development tasks.

Getting Started

1. Clone the repository:

git clone https://github.com/subaquatic-pierre/raderbot.git

2. Navigate to the project directory:

cd raderbot

3. Build and run the project:

make dev

This command will start the Actix server at http://localhost:3000 and automatically restart it when code changes are detected.

Cleaning Up

To clean up build artifacts, run:

make clean

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Features

Account Features

Position Management

• Open Positions: Allows opening positions with detailed parameters (symbol, margin, leverage, order side, and optional stop loss).
• Close Position: Enables closing an individual position using its ID, with automatic handling of price lookup and trade execution.
• Close All Positions: Offers the capability to close all open positions with a single request, facilitating quick portfolio adjustments or strategy changes.

Account Information Retrieval

• Account Snapshot: Provides real-time account information, including current holdings, positions, and trading capabilities.
• List Active Positions: Lists all active positions to provide insights into market exposure and position specifics.
• Recent Trades: Retrieves a list of recent trades, aiding in the analysis of trading performance and strategy outcomes.

Exchange API Flexibility

• Dynamic API Switching: Features an endpoint to dynamically set the exchange API, supporting transitions between live and mock environments or different exchanges without downtime.
• Multiple Exchange Support: Accommodates various exchange APIs, including a mock interface for risk-free testing and strategy development.

Real-time Market Data Integration

• Leverages live market data for informed decision-making in trading operations, ensuring that actions reflect the latest market conditions.

Safety Features

• Stop Loss Functionality: Incorporates stop-loss options in position opening, enhancing risk management through predefined loss limits.
• Robust Error Handling: Delivers comprehensive error handling and response messaging, clearly indicating the outcomes of API requests.

Market Data Features

Kline Data

• Retrieve Kline Data: Fetch historical k-line (candlestick) data for a given symbol and interval, allowing users to analyze past market movements.
• Range-based Kline Data Retrieval: Obtain k-line data within a specified date range, supporting in-depth analysis and backtesting strategies over specific periods.

Ticker Data

• Last Price Query: Access the most recent trading price for a specified symbol, crucial for real-time decision making.
• Ticker Data Access: Get detailed ticker information, including price changes, high, low, and volume data, providing a comprehensive market overview.

Stream Management

• Open Data Stream: Initiate a live data stream for k-lines or ticker updates, enabling real-time market monitoring and analysis.
• Close Data Stream: Terminate an active data stream, managing resource usage and focusing on relevant market data.
• Active Streams Information: List all active streams, offering insights into currently monitored symbols and intervals.

Market Information

• Market Summary: Present a general market overview, including available symbols, trading pairs, and other relevant information, helping users stay informed about market conditions.

Strategy Management Features

Strategy Operations

• Create New Strategies: Initiate new trading strategies with customized settings including symbols, strategy names, algorithm parameters, intervals, margins, and leverage.
• Stop Strategy: Terminate an active strategy optionally closing all associated positions.
• List Strategy Positions: Retrieve all positions opened under a specific strategy, facilitating detailed performance analysis.
• Active Strategy Summary: Generate summaries for active strategies, providing insights into their current state and effectiveness.
• Strategy Information: Fetch detailed information about specific strategies, including configuration and performance metrics.
• List Active and Historical Strategies: View active strategies for ongoing monitoring and historical strategies for post-analysis.
• Stop All Strategies: Conveniently stop all active strategies with an option to close all positions, useful for rapid response to market changes or strategy realignment.

Strategy Configuration

• Set Strategy Parameters: Dynamically adjust strategy parameters to adapt to changing market conditions or refine strategy logic.
• Change Strategy Settings: Modify strategy settings such as maximum open orders, margin, leverage, and stop-loss thresholds.

Strategy Testing

• Run Backtest: Perform backtesting on strategies with specific parameters over designated time frames, aiding in strategy validation and optimization.

Roadmap

The project is currently in the development phase.

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Contributing

We welcome contributions from the community! If you would like to contribute to the project, please follow these guidelines:

• Fork the repository.
• Create a new branch: git checkout -b my-branch.
• Make your changes and commit them: git commit -am 'Add new feature'.
• Push to the branch: git push origin my-branch.
• Submit a pull request.

License

This project is licensed under the MIT License.