Using Freqtrade with Docker¶
This page explains how to run the bot with Docker. It is not meant to work out of the box. You'll still need to read through the documentation and understand how to properly configure it.
Start by downloading and installing Docker CE for your platform:
Freqtrade with docker-compose¶
- The following section assumes that
docker-composeare installed and available to the logged in user.
- All below commands use relative directories and will have to be executed from the directory containing the
Docker quick start¶
Create a new directory and place the docker-compose file in this directory.
mkdir ft_userdata cd ft_userdata/ # Download the docker-compose file from the repository curl https://raw.githubusercontent.com/freqtrade/freqtrade/stable/docker-compose.yml -o docker-compose.yml # Pull the freqtrade image docker-compose pull # Create user directory structure docker-compose run --rm freqtrade create-userdir --userdir user_data # Create configuration - Requires answering interactive questions docker-compose run --rm freqtrade new-config --config user_data/config.json
The above snippet creates a new directory called
ft_userdata, downloads the latest compose file and pulls the freqtrade image.
The last 2 steps in the snippet create the directory with
user_data, as well as (interactively) the default configuration based on your selections.
How to edit the bot configuration?
You can edit the configuration at any time, which is available as
user_data/config.json (within the directory
ft_userdata) when using the above configuration.
You can also change the both Strategy and commands by editing the command section of your
Adding a custom strategy¶
- The configuration is now available as
- Copy a custom strategy to the directory
- Add the Strategy' class name to the
SampleStrategy is run by default.
SampleStrategy is just a demo!
SampleStrategy is there for your reference and give you ideas for your own strategy.
Please always backtest your strategy and use dry-run for some time before risking real money!
You will find more information about Strategy development in the Strategy documentation.
Once this is done, you're ready to launch the bot in trading mode (Dry-run or Live-trading, depending on your answer to the corresponding question you made above).
docker-compose up -d
While the configuration generated will be mostly functional, you will still need to verify that all options correspond to what you want (like Pricing, pairlist, ...) before starting the bot.
Monitoring the bot¶
You can check for running instances with
This should list the service
running. If that's not the case, best check the logs (see next point).
Logs will be written to:
You can also check the latest log with the command
docker-compose logs -f.
The database will be located at:
Updating freqtrade with docker-compose¶
Updating freqtrade when using
docker-compose is as simple as running the following 2 commands:
# Download the latest image docker-compose pull # Restart the image docker-compose up -d
This will first pull the latest image, and will then restart the container with the just pulled version.
Check the Changelog
You should always check the changelog for breaking changes / manual interventions required and make sure the bot starts correctly after the update.
Editing the docker-compose file¶
Advanced users may edit the docker-compose file further to include all possible options or arguments.
All freqtrade arguments will be available by running
docker-compose run --rm freqtrade <command> <optional arguments>.
docker-compose for trade commands
Trade commands (
freqtrade trade <...>) should not be ran via
docker-compose run - but should use
docker-compose up -d instead.
This makes sure that the container is properly started (including port forwardings) and will make sure that the container will restart after a system reboot.
docker-compose run --rm
--rm will remove the container after completion, and is highly recommended for all modes except trading mode (running with
freqtrade trade command).
Example: Download data with docker-compose¶
Download backtesting data for 5 days for the pair ETH/BTC and 1h timeframe from Binance. The data will be stored in the directory
user_data/data/ on the host.
docker-compose run --rm freqtrade download-data --pairs ETH/BTC --exchange binance --days 5 -t 1h
Head over to the Data Downloading Documentation for more details on downloading data.
Example: Backtest with docker-compose¶
Run backtesting in docker-containers for SampleStrategy and specified timerange of historical data, on 5m timeframe:
docker-compose run --rm freqtrade backtesting --config user_data/config.json --strategy SampleStrategy --timerange 20190801-20191001 -i 5m
Head over to the Backtesting Documentation to learn more.
Additional dependencies with docker-compose¶
If your strategy requires dependencies not included in the default image - it will be necessary to build the image on your host. For this, please create a Dockerfile containing installation steps for the additional dependencies (have a look at docker/Dockerfile.custom for an example).
You'll then also need to modify the
docker-compose.yml file and uncomment the build step, as well as rename the image to avoid naming collisions.
image: freqtrade_custom build: context: . dockerfile: "./Dockerfile.<yourextension>"
You can then run
docker-compose build to build the docker image, and run it using the commands described above.
Plotting with docker-compose¶
freqtrade plot-profit and
freqtrade plot-dataframe (Documentation) are available by changing the image to
*_plot in your docker-compose.yml file.
You can then use these commands as follows:
docker-compose run --rm freqtrade plot-dataframe --strategy AwesomeStrategy -p BTC/ETH --timerange=20180801-20180805
The output will be stored in the
user_data/plot directory, and can be opened with any modern browser.
Data analysis using docker compose¶
Freqtrade provides a docker-compose file which starts up a jupyter lab server. You can run this server using the following command:
docker-compose -f docker/docker-compose-jupyter.yml up
This will create a docker-container running jupyter lab, which will be accessible using
Please use the link that's printed in the console after startup for simplified login.
Since part of this image is built on your machine, it is recommended to rebuild the image from time to time to keep freqtrade (and dependencies) up-to-date.
docker-compose -f docker/docker-compose-jupyter.yml build --no-cache