Anaconda Environment

Background

Anaconda is a free and open-source distribution of the Python and R programming languages for scientific computing. The big difference between conda and the pip package manager is in how package dependencies are managed, which is a significant challenge for Python data science and the reason conda exists.

(see webpage https://www.anaconda.com for details)

Existing Anaconda Environment

There are currently 6 conda environments supported on HAL system

Environment Name	Location	Description
base	/opt/apps/anaconda3
powerai_env_2	/opt/apps/anaconda3/envs/powerai_env_2
powerai_env_3	/opt/apps/anaconda3/envs/powerai_env_3
wmlce-v1.6.1-py2.7	/opt/apps/anaconda3/envs/wmlce-v1.6.1-py2.7
wmlce-v1.6.1-py3.6	/opt/apps/anaconda3/envs/wmlce-v1.6.1-py3.6
tensorflow-v2.0-beta	/opt/apps/anaconda3/envs/tensorflow-v2.0-beta

Create a New Env from Existing Envs

We recommend our users to create a new environment from one of our existing powerai or wmlce enviornment.

Create a New Env from Existing Env

conda create --name=<new_env> --clone=wmlce-v1.6.1-py3.6

The new conda environment will be located within $HOME/.conda/envs/<my_env>, then users can search and/or install python packages via conda

Example: Search for a New Package

conda search r-tensorflow

Example: Install a New Package

conda install r-tensorflow

Create Anaconda Environment from Scratch