On the Environments page, the left column displays your environments. At the bottom of the environments list are the Create, Clone, Import, Backup, and Remove buttons.
Searching for an environment¶
In the Search Environments box, type all or part of an environment name to filter the environment list.
Creating a new environment¶
At the bottom of the environments list, select Create.
In the Create new environment dialog, type a descriptive name for the new environment.
Select Python or R to set the package type for your environment.
Select a version for your Python or R installation.
Using an environment¶
In the environments list, select the environment name to activate it.
Click the arrow button next to the environment name to open the activation options dropdown.
Select one of the following options for opening the environment: Terminal, Python interpreter, IPython Console, or Jupyter Notebook.
Some of these options may not be available if they were not installed in the environment.
Cloning an environment¶
- Activate the environment you want to clone by selecting it from the environments list.
- At the bottom of the environments list, click Clone.
- Type a descriptive name for the new environment.
- Click Clone.
Backing up an environment¶
Don’t delete your environment backup when removing and reinstalling Anaconda. If you do, you will not be able to import your existing environments into your new installation.
Activate the environment you want to back up by selecting it from the environments list.
At the bottom of the environments list, click Backup.
In the Backup Environment dialog, select either Local drive or Anaconda Nucleus as the backup location. You need to have a Nucleus account to back up your environment to Nucleus.
By backing up to the cloud (Nucleus), your environment is safe from hard drive failure and malfunctions with your machine.
Backing up locally can be useful for rolling back conda to an earlier state feature.
- If you choose to back up locally:
- Click Backup.
- Type a descriptive name for your environment’s YAML file.
- Choose a place on your computer to save it.
- Click Save.
- If you choose to back up to Nucleus:
- Type a descriptive name for the backup. By default, the environment name and current date is entered as the backup name.
- Choose whether to overwrite an existing environment backup file on Nucleus. Each backup name must be unique.
- Click Backup.
Importing an environment¶
Each environment has a YAML-formatted configuration file. If someone has given you an environment file that you want to use—for example
my-environment-file.yml—and you have saved it to your computer, you can import it into Navigator. Furthermore, if you have backed up an environment either locally or to Nucleus, you can import it onto your local computer with Navigator.
At the bottom of the environments list, select Import.
In the Import Environment dialog, choose whether to import from your Local drive or from Anaconda Nucleus.
Select the corresponding folder icon to choose the environment you want to import.
Type a descriptive name for the new environment, or use the existing name. Each environment name must be unique.
Choose whether or not to overwrite an existing environment with your import.
Your newly imported environment will appear in the environments list.
Removing an environment¶
- In the environments list, select the environment you want to remove.
- At the bottom of the list, click Remove.
Removing an environment in Navigator only removes your local copy. It will not remove or delete environments you have backed up to Nucleus.
- In a browser, open Anaconda Nucleus.
- Sign in using your email address and password.
- From your profile in the top-right corner, navigate to Subscriptions.
- Select the Environments page.
- Select Delete in the row associated with the environment you wish to remove.
Removing an environment in Nucleus only removes it from Nucleus. It does not affect any local copies.
Advanced environment management¶
Navigator provides a convenient graphical interface for managing conda environments, channels, and packages. If you’re comfortable working with Anaconda prompt (or terminal on Linux or macOS), you can access additional, advanced management features. To learn more, see Managing environments in the conda documentation.