Configuring environments and sample projects
When you create a new project in Data Science & AI Workbench, you must select a base environment for the project. Anaconda provides several base Anaconda environments, along with Python, R, or Hadoop-Spark environments for you to choose from.
If these environments do not suit your needs, you can create a custom environment, then include it in the list of environments that are available upon project creation.
Creating your environment
-
Log in to Workbench as a user with administrator permissions.
The
anaconda-enterprise
user has the proper permissions. -
Click Create and select New Project.
-
Select any Environment and Resource Profile, then click Create.
-
Open a session for the project.
-
Open a terminal in the project session.
-
Configure conda to create new environments in the environments directory by running the following command:
-
Use conda to create or clone your custom environment.
Here is an example command for creating a conda environment:
Here is an example command for creating a conda environment:
Here is an example command for cloning a conda environment:
python
andipykernel
must be included in every environment you create for Workbench.
Providing your environment to users
There are two methods for providing your environment to your users:
- Place the environment in the sample projects gallery and allow other users to clone the environment as a project.
- Include the environment as an available option in the Environment dropdown when creating a new project.
Both of these methods are accomplished by creating a project template archive (.tar.bz2
) file that uses the environment you just created, and then placing the file in the correct directory.
The project template archive file must contain, at a minimum, the anaconda-project.yml
file. For more information and help building projects, see the official Anaconda Project documentation.
-
In your terminal, navigate to the project directory by running the following command:
-
Create a directory to store an
anaconda-project.yml
file for your custom environment by running the following command: -
Create a copy of your current project’s
anaconda-project.yml
file in the directory you just created by running the following command: -
Enter the project directory you just created by running the following command:
-
Using your preferred file editor, edit the
anaconda-project.yml
file in your project directory to represent your custom environment. This involves updating thename:
,description:
,packages:
, andenv_specs:
sections of the file.Delete the commented section below
env_specs:
showing available packages. It is likely that these do not align with your custom environment.Your project’s
name:
will display on the Sample Projects grid or the Environments dropdown list after the project is created. -
Create an archive file for the project, then set permissions for it by running the following commands:
This archive file is the template that other projects will use as a starting point for their own projects.
-
Move your project archive file to the sample project gallery by running the following command:
-
Enter the sample gallery directory by running the following command:
-
(Optional) If you want to include the environment as an available option in the Environment dropdown when creating a new project, add the project archive file name (
<PROJECT>.tar.bz2
) to theTEMPLATES
file. Save and close the file when complete. Otherwise, skip this step. -
Update the sample projects gallery to include your project by running the following command:
-
Verify that you can either find and select your sample project on the Sample Projects page, or select your environment from the Environment dropdown when creating a new project.
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