This page explains how to prepare your environment for running the bot.
Before running your bot in production you will need to setup few external API. In production mode, the bot required valid Bittrex API credentials and a Telegram bot (optional but recommended).
Setup your exchange account¶
To be completed, please feel free to complete this section.
Setup your Telegram bot¶
The only things you need is a working Telegram bot and its API token. Below we explain how to create your Telegram Bot, and how to get your Telegram user id.
1. Create your Telegram bot¶
1.1. Start a chat with https://telegram.me/BotFather
1.2. Send the message
/newbot. BotFather response:
Alright, a new bot. How are we going to call it? Please choose a name for your bot.
1.3. Choose the public name of your bot (e.x.
Good. Now let's choose a username for your bot. It must end in `bot`. Like this, for example: TetrisBot or tetris_bot.
1.5. Father bot will return you the token (API key)
Copy it and keep it you will use it for the config parameter
Done! Congratulations on your new bot. You will find it at t.me/My_own_freqtrade_bot. You can now add a description, about section and profile picture for your bot, see /help for a list of commands. By the way, when you've finished creating your cool bot, ping our Bot Support if you want a better username for it. Just make sure the bot is fully operational before you do this. Use this token to access the HTTP API: 521095879:AAEcEZEL7ADJ56FtG_qD0bQJSKETbXCBCi0 For a description of the Bot API, see this page: https://core.telegram.org/bots/api
2. Get your user id¶
2.1. Talk to https://telegram.me/userinfobot
2.2. Get your "Id", you will use it for the config parameter
Freqtrade provides a Linux/MacOS script to install all dependencies and help you to configure the bot.
Windows installation is explained here.
Easy Installation - Linux Script¶
If you are on Debian, Ubuntu or MacOS a freqtrade provides a script to Install, Update, Configure, and Reset your bot.
$ ./setup.sh usage: -i,--install Install freqtrade from scratch -u,--update Command git pull to update. -r,--reset Hard reset your develop/master branch. -c,--config Easy config generator (Will override your existing file).
This script will install everything you need to run the bot:
- Mandatory software as:
- Setup your virtualenv
- Configure your
This script is a combination of
Update parameter will pull the last version of your current branch and update your virtualenv.
Reset parameter will hard reset your branch (only if you are on
develop) and recreate your virtualenv.
Config parameter is a
config.json configurator. This script will ask you questions to setup your bot and create your
Automatic Installation - Docker¶
Start by downloading Docker for your platform:
Once you have Docker installed, simply create the config file (e.g.
config.json) and then create a Docker image for
freqtrade using the Dockerfile in this repo.
1. Prepare the Bot¶
1.1. Clone the git repository
Linux/Mac/Windows with WSL
git clone https://github.com/freqtrade/freqtrade.git
Windows with docker
git clone --config core.autocrlf=input https://github.com/freqtrade/freqtrade.git
1.2. (Optional) Checkout the develop branch
git checkout develop
1.3. Go into the new directory
cp -n config.json.example config.json
To edit the config please refer to the Bot Configuration page.
1.5. Create your database file *(optional - the bot will create it if it is missing)
touch tradesv3.sqlite ```` Dry-Run ```bash touch tradesv3.dryrun.sqlite
2. Download or build the docker image¶
Either use the prebuilt image from docker hub - or build the image yourself if you would like more control on which version is used.
Branches / tags available can be checked out on Dockerhub.
2.1. Download the docker image
Pull the image from docker hub and (optionally) change the name of the image
docker pull freqtradeorg/freqtrade:develop # Optionally tag the repository so the run-commands remain shorter docker tag freqtradeorg/freqtrade:develop freqtrade
To update the image, simply run the above commands again and restart your running container.
2.2. Build the Docker image
cd freqtrade docker build -t freqtrade .
If you are developing using Docker, use
Dockerfile.develop to build a dev Docker image, which will also set up develop dependencies:
docker build -f ./Dockerfile.develop -t freqtrade-dev .
For security reasons, your configuration file will not be included in the image, you will need to bind mount it. It is also advised to bind mount an SQLite database file (see the "5. Run a restartable docker image" section) to keep it between updates.
3. Verify the Docker image¶
After the build process you can verify that the image was created with:
4. Run the Docker image¶
You can run a one-off container that is immediately deleted upon exiting with the following command (
config.json must be in the current working directory):
docker run --rm -v /etc/localtime:/etc/localtime:ro -v `pwd`/config.json:/freqtrade/config.json -it freqtrade
There is known issue in OSX Docker versions after 17.09.1, whereby /etc/localtime cannot be shared causing Docker to not start. A work-around for this is to start with the following cmd.
docker run --rm -e TZ=`ls -la /etc/localtime | cut -d/ -f8-9` -v `pwd`/config.json:/freqtrade/config.json -it freqtrade
More information on this docker issue and work-around can be read here.
In this example, the database will be created inside the docker instance and will be lost when you will refresh your image.
5. Run a restartable docker image¶
To run a restartable instance in the background (feel free to place your configuration and database files wherever it feels comfortable on your filesystem).
5.1. Move your config file and database
mkdir ~/.freqtrade mv config.json ~/.freqtrade mv tradesv3.sqlite ~/.freqtrade
5.2. Run the docker image
docker run -d \ --name freqtrade \ -v /etc/localtime:/etc/localtime:ro \ -v ~/.freqtrade/config.json:/freqtrade/config.json \ -v ~/.freqtrade/tradesv3.sqlite:/freqtrade/tradesv3.sqlite \ freqtrade --db-url sqlite:///tradesv3.sqlite
db-url defaults to
sqlite:///tradesv3.sqlite but it defaults to
dry_run=True is being used.
To override this behaviour use a custom db-url value: i.e.:
6. Monitor your Docker instance¶
You can then use the following commands to monitor and manage your container:
docker logs freqtrade docker logs -f freqtrade docker restart freqtrade docker stop freqtrade docker start freqtrade
For more information on how to operate Docker, please refer to the official Docker documentation.
You do not need to rebuild the image for configuration changes, it will suffice to edit
config.json and restart the container.
7. Backtest with docker¶
The following assumes that the above steps (1-4) have been completed successfully.
Also, backtest-data should be available at
docker run -d \ --name freqtrade \ -v /etc/localtime:/etc/localtime:ro \ -v ~/.freqtrade/config.json:/freqtrade/config.json \ -v ~/.freqtrade/tradesv3.sqlite:/freqtrade/tradesv3.sqlite \ -v ~/.freqtrade/user_data/:/freqtrade/user_data/ \ freqtrade --strategy AwsomelyProfitableStrategy backtesting
Head over to the Backtesting Documentation for more details.
Additional parameters can be appended after the image name (
freqtrade in the above example).
We've included/collected install instructions for Ubuntu 16.04, MacOS, and Windows. These are guidelines and your success may vary with other distros. OS Specific steps are listed first, the Common section below is necessary for all systems.
Click each one for install guide:
Linux - Ubuntu 16.04¶
Install Python 3.6, Git, and wget¶
sudo add-apt-repository ppa:jonathonf/python-3.6 sudo apt-get update sudo apt-get install python3.6 python3.6-venv python3.6-dev build-essential autoconf libtool pkg-config make wget git
Raspberry Pi / Raspbian¶
Before installing FreqTrade on a Raspberry Pi running the official Raspbian Image, make sure you have at least Python 3.6 installed. The default image only provides Python 3.5. Probably the easiest way to get a recent version of python is miniconda.
The following assumes that miniconda3 is installed and available in your environment. Last miniconda3 installation file use python 3.4, we will update to python 3.6 on this installation.
It's recommended to use (mini)conda for this as installation/compilation of
pandas takes a long time.
If you have installed it from (mini)conda, you can remove
requirements.txt before you install it with
Additional package to install on your Raspbian,
libffi-dev required by cryptography (from python-telegram-bot).
conda config --add channels rpi conda install python=3.6 conda create -n freqtrade python=3.6 conda activate freqtrade conda install scipy pandas numpy sudo apt install libffi-dev python3 -m pip install -r requirements.txt python3 -m pip install -e .
Install Python 3.6, git and wget¶
brew install python3 git wget
1. Install TA-Lib¶
Official webpage: https://mrjbq7.github.io/ta-lib/install.html
wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz tar xvzf ta-lib-0.4.0-src.tar.gz cd ta-lib sed -i.bak "s|0.00000001|0.000000000000000001 |g" src/ta_func/ta_utility.h ./configure --prefix=/usr/local make sudo make install cd .. rm -rf ./ta-lib*
An already downloaded version of ta-lib is included in the repository, as the sourceforge.net source seems to have problems frequently.
2. Setup your Python virtual environment (virtualenv)¶
This step is optional but strongly recommended to keep your system organized
python3 -m venv .env source .env/bin/activate
3. Install FreqTrade¶
Clone the git repository:
git clone https://github.com/freqtrade/freqtrade.git
Optionally checkout the stable/master branch:
git checkout master
4. Initialize the configuration¶
cd freqtrade cp config.json.example config.json
To edit the config please refer to Bot Configuration.
5. Install python dependencies¶
pip3 install --upgrade pip pip3 install -r requirements.txt pip3 install -e .
6. Run the Bot¶
If this is the first time you run the bot, ensure you are running it in Dry-run
"dry_run": true, otherwise it will start to buy and sell coins.
python3.6 ./freqtrade/main.py -c config.json
7. [Optional] Configure
freqtrade as a
From the freqtrade repo... copy
freqtrade.service to your systemd user directory (usually
~/.config/systemd/user) and update
ExecStart to match your setup.
After that you can start the daemon with:
systemctl --user start freqtrade
For this to be persistent (run when user is logged out) you'll need to enable
linger for your freqtrade user.
sudo loginctl enable-linger "$USER"
We recommend that Windows users use Docker as this will work much easier and smoother (also more secure).
If that is not possible, try using the Windows Linux subsystem (WSL) - for which the Ubuntu instructions should work. If that is not available on your system, feel free to try the instructions below, which led to success for some.
Install freqtrade manually¶
Clone the git repository¶
git clone https://github.com/freqtrade/freqtrade.git
Install ta-lib according to the ta-lib documentation.
As compiling from source on windows has heavy dependencies (requires a partial visual studio installation), there is also a repository of unofficial precompiled windows Wheels here, which needs to be downloaded and installed using
pip install TA_Lib‑0.4.17‑cp36‑cp36m‑win32.whl (make sure to use the version matching your python version)
>cd \path\freqtrade-develop >python -m venv .env >cd .env\Scripts >activate.bat >cd \path\freqtrade-develop REM optionally install ta-lib from wheel REM >pip install TA_Lib‑0.4.17‑cp36‑cp36m‑win32.whl >pip install -r requirements.txt >pip install -e . >python freqtrade\main.py
Error during installation under Windows¶
error: Microsoft Visual C++ 14.0 is required. Get it with "Microsoft Visual C++ Build Tools": http://landinghub.visualstudio.com/visual-cpp-build-tools
Unfortunately, many packages requiring compilation don't provide a pre-build wheel. It is therefore mandatory to have a C/C++ compiler installed and available for your python environment to use.
The easiest way is to download install Microsoft Visual Studio Community here and make sure to install "Common Tools for Visual C++" to enable building c code on Windows. Unfortunately, this is a heavy download / dependency (~4Gb) so you might want to consider WSL or docker first.
Now you have an environment ready, the next step is Bot Configuration.