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Installation

This page explains how to prepare your environment for running the bot.

Prerequisite

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. Freqtrade bot) BotFather response:

Good. Now let's choose a username for your bot. It must end in `bot`. Like this, for example: TetrisBot or tetris_bot.
1.4. Choose the name id of your bot (e.x "My_own_freqtrade_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 token. BotFather response:

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
1.6. Don't forget to start the conversation with your bot, by clicking /START button

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 chat_id.


Quick start

Freqtrade provides a Linux/MacOS script to install all dependencies and help you to configure the bot.

Note

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).

--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

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

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

```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:

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/user_data/:/freqtrade/user_data \
  -v ~/.freqtrade/tradesv3.sqlite:/freqtrade/tradesv3.sqlite \
  freqtrade --db-url sqlite:///tradesv3.sqlite --strategy MyAwesomeStrategy

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

Note

All command line arguments can be added to the end of the docker run command.

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:

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 numpy, scipy and pandas takes a long time.

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-common.txt
python3 -m pip install -e .

MacOS

Install Python 3.6, git and wget

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/local
make
sudo 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 -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"

If you run the bot as a service, you can use systemd service manager as a software watchdog monitoring freqtrade bot state and restarting it in the case of failures. If the internals.sd_notify parameter is set to true in the configuration or the --sd-notify command line option is used, the bot will send keep-alive ping messages to systemd using the sd_notify (systemd notifications) protocol and will also tell systemd its current state (Running or Stopped) when it changes.

The freqtrade.service.watchdog file contains an example of the service unit configuration file which uses systemd as the watchdog.

Note

The sd_notify communication between the bot and the systemd service manager will not work if the bot runs in a Docker container.


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 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

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.