Installing omegaml

Starting omega-ml locally

For a single-node installation, start the omega-ml platform as follows:

$ wget https://raw.githubusercontent.com/omegaml/omegaml/master/docker-compose.yml
$ docker-compose up -d

Jupyter Notebook is immediately available at http://localhost:8899 (omegamlisfun to login). Any notebook you create will automatically be stored in the integrated omega-ml database, making collaboration a breeze. The REST API is available at http://localhost:5000.

If you already have a Jupyter or other Python environment and would like to use omega-ml’s storage and runtime environment, you can start just the required parts:

# start the required services
$ docker-compose up -d mongodb rabbitmq worker

# run omegaml from the command line
$ om shell

# or in your Jupyter notebook
import omegaml as om

If you have secured MongoDB and RabbitMQ make sure to specify the user credentials in the respective environment variables or the omega-ml configuration file, $PWD/config.yml.

Getting User Credentials

Managed Service|Commercial Edition

omega-ml is also provided as a managed service at https://omegaml.io. For on-premise or private-cloud deployment, we provide the Commercial Edition available from the same address.

Sign up at hub.omegaml.io to retrieve your userid and apikey. Then login as follows. This will store your login credentials at ~/config/omegaml/config.yml and any subsequent API call will be directed to our cloud.

om cloud login --userid USERID --apikey APIKEY

Running omega-ml in JupyterLab, Jupyter Notebook

omega-ml is easy to integrate with JupyterLab and Jupyter Notebook. By default all notebooks are directly stored in the omega-ml jobs store, so that all team members have direct access (no sharing or uploading required).

Alternatively, any existing Jupyter installation can be used as normal. Then omega-ml is run from the Terminal and from within your notebooks as any other Python module (see below).

Running omega-ml from the command line

The cli command om provides access to all of the core APIs of omega-ml:

$ om -h
Usage: om <command> [<action>] [<args>...] [options]
   om (models|datasets|scripts|jobs) [<args>...] [--replace] [--csv...] [options]
   om runtime [<args>...] [--async] [--result] [--param] [options]
   om cloud [<args>...] [options]
   om shell [options]
   om help [<command>]

For example we can store and retrieve a dataset as follows:

# load sample.csv as a DataFrame and store it as sample
$ om datasets put sample.csv sample

# export the pandas dataframe to a csv
$ om datasets get sample sample.csv

Setting up R for omega-ml

install.packages("reticulate", repos = "https://cloud.r-project.org")