The VarFish installation for developers should be set up differently from the installation for production use.

The reason being is that the installation for production use runs completely in a Docker environment. All containers are assigned to a Docker network that the host by default has no access to, except for the reverse proxy that gives access to the VarFish webinterface.

The developers installation is intended not to carry the full VarFish database such that it is light-weight and fits on a laptop. We advise to install the services not running in a Docker container.

Please find the instructions for the Windows installation at the end of the page.

Install Postgres

Follow the instructions for your operating system to install Postgres. Make sure that the version is 12 (11, 13 and 14 would also work). Ubuntu 20 already includes postgresql 12. In case of older Ubuntu versions, this would be:

$ sudo apt install postgresql-12

Adapt the postgres configuration file, for postgres 14 this would be:

sudo sed -i -e ‘s/.*max_locks_per_transaction.*/max_locks_per_transaction = 1024 # min 10/’ /etc/postgresql/14/main/postgresql.conf

Install Redis

Redis is the broker that celery uses to manage the queues. Follow the instructions for your operating system to install Redis. For Ubuntu, this would be:

$ sudo apt install redis-server

Install miniconda

miniconda helps to set up encapsulated Python environments. This step is optional. You can also use pipenv, but to our experience, resolving the dependencies in pipenv is terribly slow.

$ wget
$ bash -b -p ~/miniconda3
$ source ~/miniconda3/bin/activate
$ conda init
$ conda create -n varfish python=3.8 pip
$ conda activate varfish

Clone git repository

Clone the VarFish Server repository and switch into the checkout.

$ git clone
$ cd varfish-server

Install Python Requirements

Some required packages have dependencies that are usually not preinstalled. Therefore, run

$ sudo bash utility/

Now, with the conda/Python environment activated, install all the requirements.

$ for i in requirements/*; do pip install -r $i; done

Setup Database

Use the tool provided in utility/ to set up the database. The name for the database should be varfish (create new user: yes, name: varfish, password: varfish).

$ bash utility/

Setup vue.js

Use the tool provided in utility/ to set up vue.js.

$ sudo bash utility/

Open an additional terminal and switch into the vue directory. Then install the VarFish vue app.

$ cd varfish/vueapp
$ npm install

When finished, keep this terminal open to run the vue app.

$ npm run serve

Setup VarFish

First, create a .env file with the following content.

export DATABASE_URL="postgres://varfish:varfish@"
export CELERY_BROKER_URL=redis://localhost:6379/0
export DJANGO_SETTINGS_MODULE=config.settings.local

If you wish to enable structural variants, add the following line.


To create the tables in the VarFish database, run the migrate command. This step can take a few minutes.

$ python migrate

Once done, create a superuser for your VarFish instance. By default, the VarFish root user is named root (the setting can be changed in the .env file with the PROJECTROLES_ADMIN_OWNER variable).

$ python createsuperuser

Last, download the icon sets for VarFish and make scripts, stylesheets and icons available.

$ python geticons -c bi cil fa-regular fa-solid gridicons octicon
$ python collectstatic

When done, open two terminals and start the VarFish server and the celery server.

terminal1$ make serve
terminal2$ make celery

Installation (Windows)

The setup was done on a recent version of Windows 10 with Windows Subsystem for Linux Version 2 (WSL2).

Installation WSL2

Following [this tutorial]( to install WSL2.

  • Note that the whole thing appears to be a bit convoluted, you start out with wsl.exe –install

  • Then you can install latest LTS Ubuntu 22.04 with the Microsoft Store

  • Once complete, you probably end up with a WSL 1 (one!) that you can conver to version 2 (two!) with wsl –set-version Ubuntu-22.04 2 or similar.

  • WSL2 has some advantages including running a full Linux kernel but is even slower in I/O to the NTFS Windows mount.

  • Everything that you do will be inside the WSL image.

Install Dependencies

$ sudo apt install libsasl2-dev python3-dev libldap2-dev libssl-dev gcc make rsync
$ sudo apt install postgresql postgresql-server-dev-14 postgresql-client redis
$ sudo service postgresql start
$ sudo service postgresql status
$ sudo service redis-server start
$ sudo service redis-server status
$ sudo sed -i -e 's/.*max_locks_per_transaction.*/max_locks_per_transaction = 1024 # min 10/' /etc/postgresql/14/main/postgresql.conf
$ sudo service postgresql restart

Create a postgres user varfish with password varfish and a database.

$ sudo -u postgres createuser -s -r -d varfish -P
$ [enter varfish as password]
$ sudo -u postgres createdb --owner=varfish varfish

Create a miniconda3 installation with an environment.

$ mkdir -p Development Downloads
$ cd Downloads
$ wget
$ bash -b -p ~/miniconda3
$ source ~/miniconda3/bin/activate
$ conda install -y mamba
$ mamba create -y -n varfish-server python==3.9 nodejs=12
$ conda activate varfish-server

Finally, checkout varfish-server and create a development .env file:

$ cd ~/Development
$ git clone
$ cat <<"EOF" >.env

export DJANGO_SETTINGS_MODULE=config.settings.local

export DJANGO_SECRET_KEY="0Vabi8RKYcSgVTGhr23AlIFA5D1aXh25ZBvxXi9Tgu9UrrFdiolaQchS9k7CfqIMev7KoLV2RH84XxQDcDCmIoeyVmMmNUh7jE8N"
export DATABASE_URL="postgres://varfish:varfish@"

$ make test-noselenium

Open WSL image in PyCharm

This has been tested with PyCharm Professional only.

  • You can simply open projects in the WSL, e.g., \wsl$Ubuntu-22.04home….

  • You can add the interpreter in the varfish-server miniconda3 environment to PyCharm which gives you access to.