Installation¶
This page explains how to prepare your environment for running the bot.
Prerequisite¶
Requirements¶
Click each one for install guide:
- Python >= 3.6.x
- pip
- git
- virtualenv (Recommended)
- TA-Lib (install instructions below)
API keys¶
Before running your bot in production you will need to setup few external API. In production mode, the bot will require valid Exchange API credentials. We also recommend a Telegram bot (optional but recommended).
Setup your exchange account¶
You will need to create API Keys (Usually you get key
and secret
) from the Exchange website and insert this into the appropriate fields in the configuration or when asked by the installation script.
Quick start¶
Freqtrade provides the Linux/MacOS Easy Installation script to install all dependencies and help you configure the bot.
Note
Windows installation is explained here.
The easiest way to install and run Freqtrade is to clone the bot GitHub repository and then run the Easy Installation script, if it's available for your platform.
Version considerations
When cloning the repository the default working branch has the name develop
. This branch contains all last features (can be considered as relatively stable, thanks to automated tests). The master
branch contains the code of the last release (done usually once per month on an approximately one week old snapshot of the develop
branch to prevent packaging bugs, so potentially it's more stable).
Note
Python3.6 or higher and the corresponding pip
are assumed to be available. The install-script will warn you and stop if that's not the case. git
is also needed to clone the Freqtrade repository.
This can be achieved with the following commands:
git clone git@github.com:freqtrade/freqtrade.git
cd freqtrade
git checkout master # Optional, see (1)
./setup.sh --install
master
branch. It's not needed if you wish to stay on the develop
branch. You may later switch between branches at any time with the git checkout master
/git checkout develop
commands.
Easy Installation Script (Linux/MacOS)¶
If you are on Debian, Ubuntu or MacOS Freqtrade provides the script to install, update, configure and reset the codebase of 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 **
With this option, the script will install everything you need to run the bot:
- Mandatory software as:
ta-lib
- Setup your virtualenv
- Configure your
config.json
file
This option is a combination of installation tasks, --reset
and --config
.
** --update **
This option will pull the last version of your current branch and update your virtualenv. Run the script with this option periodically to update your bot.
** --reset **
This option will hard reset your branch (only if you are on either master
or develop
) and recreate your virtualenv.
** --config **
Use this option to configure the config.json
configuration file. The script will interactively ask you questions to setup your bot and create your config.json
.
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.
Note
Python3.6 or higher and the corresponding pip are assumed to be available.
Linux - Ubuntu 16.04¶
Install necessary dependencies¶
sudo apt-get update
sudo apt-get install build-essential git
Raspberry Pi / Raspbian¶
The following assumes the latest Raspbian Buster lite image from at least September 2019. This image comes with python3.7 preinstalled, making it easy to get freqtrade up and running.
Tested using a Raspberry Pi 3 with the Raspbian Buster lite image, all updates applied.
sudo apt-get install python3-venv libatlas-base-dev
git clone https://github.com/freqtrade/freqtrade.git
cd freqtrade
bash setup.sh -i
Installation duration
Depending on your internet speed and the Raspberry Pi version, installation can take multiple hours to complete.
Note
The above does not install hyperopt dependencies. To install these, please use python3 -m pip install -e .[hyperopt]
.
We do not advise to run hyperopt on a Raspberry Pi, since this is a very resource-heavy operation, which should be done on powerful machine.
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
cd freqtrade
Optionally checkout the master branch to get the latest stable release:
git checkout master
4. Install python dependencies¶
python3 -m pip install --upgrade pip
python3 -m pip install -e .
5. Initialize the configuration¶
# Initialize the user_directory
freqtrade create-userdir --userdir user_data/
cp config.json.example config.json
To edit the config please refer to Bot Configuration.
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.
freqtrade trade -c config.json
Note: If you run the bot on a server, you should consider using Docker or a terminal multiplexer like screen
or tmux
to avoid that the bot is stopped on logout.
7. (Optional) Post-installation Tasks¶
On Linux, as an optional post-installation task, you may wish to setup the bot to run as a systemd
service or configure it to send the log messages to the syslog
/rsyslog
or journald
daemons. See Advanced Logging for details.
Using Conda¶
Freqtrade can also be installed using Anaconda (or Miniconda).
conda env create -f environment.yml
Note
This requires the ta-lib C-library to be installed first.
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¶
Note
Make sure to use 64bit Windows and 64bit Python to avoid problems with backtesting or hyperopt due to the memory constraints 32bit applications have under Windows.
Hint
Using the Anaconda Distribution under Windows can greatly help with installation problems. Check out the Conda section in this document for more information.
Clone the git repository¶
git clone https://github.com/freqtrade/freqtrade.git
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
>.env\Scripts\activate.bat
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 .
>freqtrade
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.