Deploy Freqtrade Strategies on TradingHost
Run open-source Freqtrade strategies from GitHub on always-on TradingHost runtimes.
Freqtrade is a Python crypto trading framework with backtesting, hyperopt, FreqAI, dry-run and live execution. TradingHost gives that strategy a production runtime.
- GitHub-native deployment
- 10+ supported exchanges
- Backtest, hyperopt, FreqAI
- Dry-run and live modes
- Telegram and WebUI access
- Always-on runtime
- Encrypted API keys
- Region proximity to exchanges
- MCP-ready
Introduction
New to Freqtrade?
Freqtrade is a free, open-source crypto trading framework written in Python. It gives you a working trading loop out of the box: a strategy interface, a backtester, a hyperparameter optimiser, a paper-trading mode, a Telegram interface, a built-in web UI, and live execution against your exchange of choice.
You write the rules. Freqtrade handles candle ingestion, indicator computation, order placement, position tracking, and reporting. Under the hood, exchange connectivity uses the CCXT library, which is why the supported exchange list aligns with the major CCXT-supported crypto venues.
Freqtrade is GPL-3.0 licensed, actively maintained, and explicitly educational. Strategies that work in backtest do not automatically work in live. The framework gives you the tools to know the difference: backtesting against historical candles, hyperopt to tune parameters, dry-run to paper trade against live market data, and FreqAI for adaptive ML-based prediction.
TradingHost is where a Freqtrade strategy runs in production. Instead of leaving your strategy on a laptop or a generic VPS, you deploy your Freqtrade repo to a TradingHost cloud runtime that stays online, manages your exchange API keys as encrypted secrets, and streams logs back to you.
Section 01 · At a glance
At a glance
- What Freqtrade is
- Open-source Python crypto trading framework, GPL-3.0 licensed
- Maintained by
- The Freqtrade project on GitHub
- Language
- Python
- Markets
- Crypto spot and futures
- Exchange connectivity
- CCXT under the hood; documented exchange list of 10+ venues
- Modes
- Backtest, hyperopt, dry-run, live, FreqAI
- Operator surfaces
- Telegram, built-in WebUI, CLI
- Deployment source
- GitHub
- TradingHost role
- Runtime, deployment, logs, secrets, region selection
- Freqtrade role
- Strategy framework, execution loop, backtester, optimiser
- Affiliation
- TradingHost is independent and is not affiliated with the Freqtrade project
- Best for
- Multi-exchange crypto strategies, indicator-based entries, ML-assisted regimes via FreqAI
Section 02 · Where Freqtrade fits
How Freqtrade fits into the trading stack
Freqtrade is an opinionated strategy framework built on top of CCXT for exchange connectivity. CCXT is the connectivity layer, Freqtrade is the strategy framework that uses it, and your strategy class is the trading logic that lives inside the framework.
That gives you two complementary entry points:
Path 01
Strategy class
Subclass IStrategy in Python. Define indicators, entry rules, exit rules, stoploss, and timeframe. Backtest, hyperopt, dry-run, and live all use the same strategy file.
Path 02
FreqAI module
Layer FreqAI on top to train models against your features and re-train on a rolling window. The strategy class consumes model predictions as just another indicator.
Either path runs the same way on TradingHost. You bring a Freqtrade GitHub repo. We run it.
- You
- Your strategy class owns the trading rules.
- Freqtrade
- Runs the strategy loop, backtester, optimiser, and dry-run.
- CCXT
- Standardises the exchange API underneath Freqtrade.
- TradingHost
- Runs the strategy process, manages secrets, streams logs.
Section 03 · Why on TradingHost
Why deploy Freqtrade on TradingHost
A live Freqtrade instance needs to run continuously, hold your exchange API keys, and stay reachable for Telegram or WebUI commands. Running on a laptop, desktop, or generic VPS introduces operational drag, including process supervision, restarts, dependency management, log scattering, and manual deployment.
TradingHost gives a Freqtrade strategy a production-oriented runtime designed for long-running trading processes.
What you get
- GitHub-native deployment
- Always-on container runtime
- Multi-strategy support inside one runtime
- Encrypted exchange API key storage
- Region selection close to your exchange
- Streaming logs and basic health
- Strategy-level start, stop, restart, inspect
- Update one strategy without restarting the runtime
- MCP-compatible AI IDE workflows
What you keep
- Full control over your Freqtrade strategy code
- Direct ownership of your exchange accounts and API permissions
- Your choice of Freqtrade modes: backtest, hyperopt, dry-run, FreqAI, live
Section 04 · Supported exchanges
Supported exchanges
Freqtrade documents first-class support for ten crypto exchanges across spot and futures markets. Because exchange connectivity uses CCXT under the hood, the functional reach extends further, but the documented matrix is the source of truth for production deployments.
Five popular pairings are linked below. For the full directory of supported crypto venues, see /brokers/crypto/.
- Freqtrade
- your exchange
- TradingHost runtime
Freqtrade also documents support for Bitget, BingX, Bitmart, HTX, Hyperliquid, MyOKX, plus community-tested venues. Find your exchange in the full crypto broker directory.
Browse the crypto broker directorySection 05 · Deployment flow
How a Freqtrade deployment works
A Freqtrade strategy on TradingHost follows the same deployment pattern as any GitHub-based project.
- STEP 01
Connect or create a repo
Sign in with GitHub and connect an existing Freqtrade strategy repository, or create one from a TradingHost Freqtrade template with sensible defaults.
- STEP 02
Configure the runtime
TradingHost reads your project’s runtime configuration to know how to install dependencies and start Freqtrade in the mode you want.
- STEP 03
Add encrypted exchange API keys
Add your exchange API keys as TradingHost secrets. They are encrypted, injected into the runtime at start, and never written to your repository.
/platform/secrets/ - STEP 04
Choose a region
Select a region close to your exchange’s matching engine. AWS Tokyo for Binance Spot, AWS Frankfurt for many EU-domiciled exchanges.
/platform/regions/ - STEP 05
Deploy
TradingHost starts Freqtrade in a managed container. Logs stream back to the dashboard. Telegram and the WebUI keep working as configured.
/platform/observability/
Section 06 · Freqtrade modes
Backtest, hyperopt, dry-run, FreqAI, live
Freqtrade is one strategy file with five operating modes. The same code path runs in backtest, hyperopt, dry-run, FreqAI, and live, which makes it unusually friendly to the rehearse-before-promote workflow that long-running strategies need.
All five modes run on the same TradingHost runtime. Pick the mode at start time, or run several side-by-side as separate strategy processes.
Section 07 · What we don’t do
What TradingHost does not do
- TradingHost does not act as your exchange.
- TradingHost does not provide trading strategies or financial advice.
- TradingHost does not modify your Freqtrade configuration or strategy code.
- TradingHost does not custody your exchange API keys beyond encrypted runtime injection.
- TradingHost does not guarantee strategy performance, exchange uptime, or market connectivity.
Section 08 · FAQ
FAQ
No. TradingHost is independent. Freqtrade is open-source, GPL-3.0 licensed software maintained by the Freqtrade project on GitHub.
Python. You write strategies as Python classes that subclass IStrategy. The same class is used for backtesting, hyperopt, dry-run, FreqAI, and live trading.
Freqtrade documents support for Binance, BingX, Bitget, Bitmart, Bybit, Gate.io, HTX, Hyperliquid, Kraken, OKX, and MyOKX, with futures support on Binance, Bitget, Bybit, Gate.io, Hyperliquid, OKX, and Kraken. Bitvavo and KuCoin are community-tested.
Yes. Exchange connectivity is provided by CCXT under the hood, which is why the supported exchange list aligns with major CCXT-supported crypto venues.
FreqAI is the adaptive machine-learning module bundled with Freqtrade. It trains predictive models against features you define, re-trains on a rolling window, and exposes predictions to your strategy class as inputs.
Yes. A TradingHost runtime can host multiple Freqtrade processes. A common pattern is one dry-run instance and one live instance with different config files.
You add them to TradingHost as encrypted secrets. They are injected into the Freqtrade runtime at start and are not written to your repository.
No. Freqtrade places trades through your exchange API credentials. TradingHost runs the Freqtrade process and streams logs.
Yes. The built-in WebUI and Telegram interface are part of Freqtrade. They keep working as configured. TradingHost runs the underlying process and exposes the necessary networking.
No. Freqtrade is designed specifically for cryptocurrency exchanges. For non-crypto markets, see /frameworks/nautilustrader/ or /frameworks/backtrader/.
Deploy your first Freqtrade strategy
Connect GitHub, choose a Freqtrade template or your own strategy repo, add your exchange API keys, choose a region, and launch into a TradingHost runtime.