freqtrade-bot

freqtrade-bot

USE FOR:

• "crypto trading bot Python"
• "freqtrade strategy development"
• "backtesting crypto strategy"
• "hyperopt parameter optimization"
• "FreqAI machine learning trading"
• "Binance/Bybit/Kraken automated bot"
• "Telegram trading bot" tags: [freqtrade, crypto, trading-bot, backtesting, hyperopt, FreqAI, Binance, Bybit, Python, Telegram, ML] kind: framework category: crypto-defi-trading

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What Is Freqtrade?

Free open-source Python crypto trading bot with full backtesting and ML optimization.

• Repo: https://github.com/freqtrade/freqtrade
• Python: 3.11+
• Requirements: 2GB RAM, 1GB disk, 2vCPU
• Control: Telegram · WebUI · CLI

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Supported Exchanges

Type	Exchanges
Spot	Binance · Kraken · Gate.io · OKX · Bybit · Kucoin · Bitvavo
Futures	Binance · Bitget · Gate.io · OKX · Bybit

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Installation

# Docker (recommended)
docker compose up -d

# pip install
pip install freqtrade
freqtrade install-ui   # optional WebUI

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

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CLI Commands

# Create new strategy template
freqtrade new-strategy --strategy MyStrategy

# Run backtesting
freqtrade backtesting --strategy MyStrategy --timerange 20240101-20241231

# Hyperopt (ML parameter search)
freqtrade hyperopt --strategy MyStrategy --hyperopt-loss SharpeHyperOptLoss --epochs 500

# Paper trading (dry run)
freqtrade trade --strategy MyStrategy --dry-run

# Live trading
freqtrade trade --strategy MyStrategy

# Plot strategy signals
freqtrade plot-dataframe --strategy MyStrategy

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Strategy Structure

from freqtrade.strategy import IStrategy, DecimalParameter, IntParameter
import pandas as pd
from pandas import DataFrame
import talib.abstract as ta

class MyStrategy(IStrategy):
    # Required settings
    minimal_roi = {"0": 0.10, "30": 0.05, "60": 0.01}
    stoploss = -0.05
    timeframe = "1h"

    # Hyperopt parameters (searchable)
    rsi_period = IntParameter(10, 30, default=14, space="buy")
    rsi_buy    = IntParameter(20, 40, default=30, space="buy")
    rsi_sell   = IntParameter(60, 80, default=70, space="sell")

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe["rsi"]  = ta.RSI(dataframe, timeperiod=self.rsi_period.value)
        dataframe["macd"], dataframe["macdsignal"], _ = ta.MACD(dataframe)
        dataframe["ema20"] = ta.EMA(dataframe, timeperiod=20)
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (dataframe["rsi"] < self.rsi_buy.value) &
            (dataframe["close"] > dataframe["ema20"]),
            "enter_long"
        ] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            dataframe["rsi"] > self.rsi_sell.value,
            "exit_long"
        ] = 1
        return dataframe