freqtrade-bot

Freqtrade — Configuration and management tool for the Freqtrade open-source crypto trading bot with strategy backtesting, live/dry-run modes, 10+ exchange support (Binance, Kraken, OKX), hyperparameter optimization, FreqUI dashboard, and Rich terminal menu interface

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CLI launcher and management console for the Freqtrade open-source crypto trading bot

Features · Getting Started · Configuration · Usage · FAQ

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Registration & Official Links

#	Resource	Link
1	Freqtrade Official Docs	freqtrade.io
2	Freqtrade GitHub	github.com/freqtrade/freqtrade
3	FreqUI Web Interface	github.com/freqtrade/frequi
4	Freqtrade on PyPI	pypi.org/project/freqtrade
5	Freqtrade on Docker Hub	hub.docker.com/r/freqtradeorg/freqtrade
6	Freqtrade Discord	discord.gg/freqtrade

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Features

Trading & Strategy
Live trading (Spot & Futures) Dry-run mode (paper trading) Strategy backtesting Hyperopt strategy optimization	FreqAI — machine learning models Custom strategy creation Download historical data Plotting & performance analysis
Supported Exchanges
Binance (Spot + Futures) Bybit (Spot + Futures) OKX (Spot + Futures) Gate.io (Spot + Futures) Kraken (Spot) KuCoin (Community-tested)	Bitget (Spot + Futures) Bitmart (Spot) HTX / Huobi (Spot) Hyperliquid DEX (Spot + Futures) BingX (Spot) Bitvavo (Community-tested)
Launcher Interface
Rich terminal UI with styled panels Questionary interactive menus ASCII art header with cyan theme	Windows run.cmd with auto-venv Telegram & WebUI management Cross-platform (Windows / Linux / macOS)

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Getting Started

Prerequisites

Requirement	Version	Purpose
Python	3.11+	Runtime
pip	latest	Package manager
Freqtrade	latest	Core trading bot (pip install freqtrade)
Exchange account	—	API keys for live or dry-run trading

Installation

Windows (One-Click)

Double-click run.cmd — it creates a virtual environment, installs launcher dependencies, and starts the console:

@echo off
chcp 65001 >nul
title Freqtrade Launcher
color 0A
cd /d "%~dp0"
if not exist "venv" (
    echo Creating virtual environment...
    python -m venv venv
)
call venv\Scripts\activate.bat
pip install rich questionary --quiet 2>nul
python main.py
pause

Manual Setup (All Platforms)

git clone <repository-url>
cd freqtrade-launcher
python -m venv venv

# Windows
venv\Scripts\activate

# Linux / macOS
source venv/bin/activate

pip install -r requirements.txt
python main.py

Install Freqtrade Itself

The launcher wraps the Freqtrade CLI. Install the core bot via one of:

# Option 1: pip (recommended)
pip install freqtrade

# Option 2: Docker
docker pull freqtradeorg/freqtrade

# Option 3: From source
git clone https://github.com/freqtrade/freqtrade.git
cd freqtrade
./setup.sh --install

Dependency Table

Package	Version	Purpose
rich	>=13.7.0	Terminal UI — panels, tables, markdown rendering
questionary	>=2.0.0	Interactive arrow-key menu selection
freqtrade	latest	Core trading bot (installed separately)

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Configuration

Freqtrade Config (user_data/config.json)

The launcher helps create and manage the Freqtrade configuration file:

{
    "trading_mode": "spot",
    "exchange": {
        "name": "binance",
        "key": "your_api_key",
        "secret": "your_api_secret"
    },
    "stake_currency": "USDT",
    "stake_amount": "unlimited",
    "dry_run": true,
    "dry_run_wallet": 1000,
    "telegram": {
        "enabled": true,
        "token": "your_telegram_bot_token",
        "chat_id": "your_chat_id"
    },
    "api_server": {
        "enabled": true,
        "listen_ip_address": "127.0.0.1",
        "listen_port": 8080,
        "username": "freqtrader",
        "password": "SuperSecurePassword"
    }
}

Field	Description
trading_mode	spot or futures
exchange.name	Exchange identifier (binance, bybit, okx, etc.)
exchange.key / secret	Exchange API credentials
stake_currency	Base currency for trading (USDT, BTC, etc.)
dry_run	true for paper trading, false for live
telegram	Telegram bot for notifications and control
api_server	FreqUI web interface access

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Usage

Run the launcher:

python main.py

CLI Menu

╔══════════════════════════════════════════╗
║  Freqtrade — Main Menu                  ║
╠══════════════════════════════════════════╣
║  [ 1] Install Dependencies              ║
║  [ 2] Settings                          ║
║  [ 3] About                             ║
║  [ 4] Create User Directory             ║
║  [ 5] New Strategy                      ║
║  [ 6] Download Data                     ║
║  [ 7] Backtesting                       ║
║  [ 8] Trade                             ║
║  [ 9] Webserver (WebUI)                 ║
║  [10] List Strategies                   ║
║  [11] List Exchanges                    ║
║  [12] Exit                              ║
╚══════════════════════════════════════════╝

Option	Freqtrade Command	Description
1	pip install freqtrade	Install via pip, Docker, or setup script
2	freqtrade new-config / show-config	Create, view, or edit configuration
3	—	About info, hashtags, supported exchanges
4	freqtrade create-userdir	Initialize user_data/ directory structure
5	freqtrade new-strategy	Scaffold a new trading strategy file
6	freqtrade download-data	Fetch historical OHLCV data for backtesting
7	freqtrade backtesting	Run strategy backtest against historical data
8	freqtrade trade	Start live or dry-run trading
9	freqtrade webserver	Launch FreqUI web dashboard
10	freqtrade list-strategies	Show available strategies in user_data/
11	freqtrade list-exchanges	Show supported exchanges
12	—	Exit launcher

Typical Workflow

Install Dependencies → Create User Directory → Settings (new-config)
    → New Strategy → Download Data → Backtesting → Trade

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Project Structure

freqtrade-launcher/
├── main.py              # Entry point — Rich/Questionary CLI, Freqtrade command wrapper
├── run.cmd              # Windows one-click launcher (auto-venv, dependency install)
├── requirements.txt     # Launcher dependencies (rich, questionary)
└── about/
    └── hashtags.txt     # Tag collection for discovery

Freqtrade Directory (created via launcher)

user_data/
├── config.json          # Bot configuration (exchange, strategy, telegram)
├── strategies/          # Custom strategy Python files
├── data/                # Downloaded historical OHLCV data
├── backtest_results/    # Backtesting output and reports
├── logs/                # Trading and error logs
└── notebooks/           # Jupyter analysis notebooks

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FAQ

What is Freqtrade?

Freqtrade is a free, open-source crypto trading bot written in Python with 38.6k+ GitHub stars. It supports backtesting, dry-run paper trading, and live trading across 10+ exchanges. Key features include FreqAI machine learning, Telegram/WebUI control, and hyperparameter optimization. Licensed under GPL-3.0.

Is this the official Freqtrade?

No. This is a launcher/management console that wraps the official Freqtrade CLI commands in an interactive terminal UI. You still need to install Freqtrade itself (pip install freqtrade) for the launcher to function fully.

Which exchanges are supported?

Officially supported for Spot: Binance, BingX, Bitget, Bitmart, Bybit, Gate.io, HTX, Hyperliquid, Kraken, OKX. For Futures: Binance, Bitget, Gate.io, Hyperliquid, OKX, Bybit. Community-tested: KuCoin, Bitvavo, and others via CCXT.

Should I start with dry-run?

Absolutely. Always start with "dry_run": true in your config to test your strategy with paper money before risking real funds. The launcher prompts a confirmation before starting live trading.

How does FreqAI work?

FreqAI is Freqtrade's machine learning module that trains models on historical data to predict market movements. It supports various ML frameworks and can be combined with traditional technical analysis strategies for hybrid approaches.

Can I use Docker instead of pip?

Yes. Select "Docker" from the Install Dependencies menu, then run docker pull freqtradeorg/freqtrade and docker run -it freqtradeorg/freqtrade. Docker images are maintained on Docker Hub with regular updates.

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Disclaimer

This software is provided for educational purposes only. Cryptocurrency trading involves significant risk of financial loss. Past performance in backtesting does not guarantee future results. The developers are not financial advisors and assume no liability for trading losses. Always do your own research and never trade with funds you cannot afford to lose.

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