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
Create a New Env from Existing Env
conda create --name=<new_env_name>