Installation
Current instructions tested on Mac, but likely work on most Unix systems.
The OpenML server will be developed and maintained for the latest minor release of Python (Python 3.12 as of writing). You can install the dependencies locally or work with docker containers.
Use pyenv
to manage Python installations
We recommend using pyenv
if you are working with
multiple local Python versions. After following the installation instructions for
pyenv
check that you can execute it:
> pyenv local
3.12
If pyenv
can't be found, please make sure to update the terminal environment
(either by reset
ing it, or by closing and opening the terminal). If you get the message
pyenv: no local version configured for this directory
first clone the repository
as described below and try again from the root of the cloned repository.
You can then install the Python version this project uses with:
cat .python-version | pyenv install
Local Installation
These instructions assume Python 3.12 and git are already installed.
You may need to install Python3 and MySQL development headers.
It may be necessary to first install additional headers before proceeding with a
local installation of the mysqlclient
dependency. They are documented under
"Installation" of the mysqlclient
documentation.
If you don't plan to make code changes, you can install directly from Github. We recommend to install the OpenML server and its dependencies into a new virtual environment.
python -m venv venv
source venv/bin/activate
python -m pip install git+https://github.com/openml/server-api.git
If you plan to make changes to this project, it will be useful to install
the project from a cloned fork. To fork the project, go to our
project page and click "fork".
This makes a copy of the repository under your own Github account.
You can then clone your own fork (replace USER_NAME
with your Github username):
git clone https://github.com/USER_NAME/server-api.git
cd server-api
Then we can install the project into a new virtual environment in edit mode:
python -m venv venv
source venv/bin/activate
python -m pip install -e ".[dev,docs]"
Setting up a Database Server
Depending on your use of the server, there are multiple ways to set up your own OpenML database. To simply connect to an existing database, see configuring the REST API Server below.
Setting up a new database
This sets up an entirely empty database with the expected OpenML tables in place. This is intended for new deployments of OpenML, for example to host a private OpenML server.
Instructions are incomplete. See issue#78.
Setting up a test database
We provide a prebuilt docker image that already contains test data.
To start the database through docker compose
, run:
docker compose up database
which starts a database.
To start a test database as stand-alone container, run:
docker run --rm -e MYSQL_ROOT_PASSWORD=ok -p 3306:3306 -d --name openml-test-database openml/test-database:latest
You may opt to add the container to a network instead, to make it reachable from other docker containers:
docker network create openml
docker run --rm -e MYSQL_ROOT_PASSWORD=ok -p 3306:3306 -d --name openml-test-database --network openml openml/test-database:latest
The container may take a minute to initialise, but afterwards you can connect to it.
Either from a local mysql
client at 127.0.0.1:3306
or from a docker container
on the same network. For example:
docker run --network NETWORK --rm -it mysql mysql -hopenml-test-database -uroot -pok
NETWORK
is openml
when using docker run
when following the example,
and NETWORK
is server-api_default
if you used docker compose
(specifically,
it is DIRECTORY_NAME
+ _default
, so if you renamed the server-api
directory to
something else, the network name reflects that).
Configuring the REST API Server
The REST API is configured through a TOML file.
Instructions are incomplete. Please have patience while we are adding more documentation.