13 KiB
Installation
This page explains how to prepare your environment for running the bot.
To understand how to set up the bot please read the Bot Configuration page.
Table of Contents
- Table of Contents
- Easy Installation - Linux Script
- Automatic Installation - Docker
- Custom Linux MacOS Installation
- Windows
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).
--install
This script will install everything you need to run the bot:
- Mandatory software as:
Python3
,ta-lib
,wget
- Setup your virtualenv
- Configure your
config.json
file
This script is a combination of install script
--reset
, --config
--update
Update parameter will pull the last version of your current branch and update your virtualenv.
--reset
Reset parameter will hard reset your branch (only if you are on master
or develop
) and recreate your virtualenv.
--config
Config parameter is a config.json
configurator. This script will ask you questions to setup your bot and create your config.json
.
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
git clone https://github.com/freqtrade/freqtrade.git
1.2. (Optional) Checkout the develop branch
git checkout develop
1.3. Go into the new directory
cd freqtrade
1.4. Copy config.json.example
to config.json
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)
Production
touch tradesv3.sqlite
Dry-Run
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 .
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:
docker images
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
Note: db-url defaults to sqlite:///tradesv3.sqlite
but it defaults to sqlite://
if dry_run=True
is being used.
To override this behaviour use a custom db-url value: i.e.: --db-url sqlite:///tradesv3.dryrun.sqlite
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.
Note: 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 ~/.freqtrade/user_data/
.
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.
Note: Additional parameters can be appended after the image name (freqtrade
in the above example).
Custom Installation
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.
Requirements
Click each one for install guide:
- Python >= 3.6.x
- pip
- git
- virtualenv (Recommended)
- TA-Lib
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, and is installed.
It's recommended to use (mini)conda for this as installation/compilation of scipy
and pandas
takes a long time.
conda config --add channels rpi
conda install python=3.6
conda create -n freqtrade python=3.6
conda install scipy pandas
python3 -m pip install -r requirements.txt
python3 -m pip install -e .
MacOS
Install Python 3.6, git, wget and ta-lib
brew install python3 git wget
common
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
make
make install
cd ..
rm -rf ./ta-lib*
Note: 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)
Note: 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
Note: If you run the bot on a server, you should consider using Docker a terminal multiplexer like screen
or tmux
to avoid that the bot is stopped on logout.
7. [Optional] Configure freqtrade
as a systemd
service
From the freqtrade repo... copy freqtrade.service
to your systemd user directory (usually ~/.config/systemd/user
) and update WorkingDirectory
and 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"
Windows
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
copy paste config.json
to ``\path\freqtrade-develop\freqtrade`
Install ta-lib
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 inofficial 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
Thanks Owdr for the commands. Source: Issue #222
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...