remove_all_env | Manage User Environments | Open Analytics Framework - remove_all_envs - Teradata Vantage

Use the remove_all_env function to remove all user environments from Open Analytics Framework.

This function allows you to remove only Python user environments, or only R user environments, or all user environments, based on the value passed to the argument env_type.

Optional Arguments

env_type

Specifies the type of the user environment to be removed.

Permitted Values:

• 'PY' - Remove only Python user environments.
• 'R' - Remove only R user environments.
• None - Remove all (Python and R) user environments.

Default value is None.

**kwargs: Specifies the keyword arguments.

asynchronous

Specifies whether to remove environment synchronously or asynchronously.

When set to True, environment is removed asynchronously. Otherwise, the environment is removed synchronously.

Default value is False.

Example 1: Remove all user environments synchronously

• Create user environments.

  >>> create_env('Lie_Detection_ML', 'python_3.8.13', 'Detect lie through machine learning.')

  >>> create_env('Customer_Trends', 'r_4.1.3', 'Analyse customer trends.')

• List user environments.

  >>> list_user_envs()

             env_name                           env_description  base_env_name   language
  0   Customer_Trends                   Analyse customer trends        r_4.1.3         R
  1  Lie_Detection_ML      Detect lie through machine learning.  python_3.8.13    Python

• Remove all user environments.

  >>> remove_all_envs()

  All user environment(s) removed.
  True

• Verify all user environments are removed.

  >>> list_user_envs()

  No user environment(s) found.

Example 2: Remove all Python user environments synchronously

• Create user environments.

  >>> create_env('Lie_Detection_ML', 'python_3.8.13', 'Detect lie through machine learning.')

  >>> create_env('Customer_Trends', 'r_4.1.3', 'Analyse customer trends.')

• List user environments.

  >>> list_user_envs()

             env_name                           env_description  base_env_name   language
  0   Customer_Trends                   Analyse customer trends        r_4.1.3         R
  1  Lie_Detection_ML      Detect lie through machine learning.  python_3.8.13    Python

• Remove all Python user environments.

  >>> remove_all_envs(env_type="PY")

  User environment 'Lie_Detection_ML' removed.
  All Python environment(s) removed.
  True

• Verify all Python user environments are removed.

  >>> list_user_envs()

               env_name                           env_description  base_env_name    language
  0   Customer_Trends                   Analyse customer trends        r_4.1.3           R

Example 3: Remove all R user environments synchronously

• Create user environments.

  >>> create_env('Lie_Detection_ML', 'python_3.8.13', 'Detect lie through machine learning.')

  >>> create_env('Customer_Trends', 'r_4.1.3', 'Analyse customer trends.')

• List user environments.

  >>> list_user_envs()

             env_name                           env_description  base_env_name   language
  0   Customer_Trends                   Analyse customer trends        r_4.1.3         R
  1  Lie_Detection_ML      Detect lie through machine learning.  python_3.8.13    Python

• Remove all R user environments.

  >>> remove_all_envs(env_type="R")

  User environment 'Customer_Trends' removed.
  All R environment(s) removed.
  True

• Verify all R user environments are removed.

  >>> list_user_envs()

               env_name                           env_description  base_env_name language
  0  Lie_Detection_ML      Detect lie through machine learning.  python_3.8.13   Python

Example 4: Remove synchronously all R environments first and then all remaining Python environments

This example first removes all R environments synchronously, followed by Python environments.

• Create user environments.

  >>> env1 = create_env("env1", "python_3.7.13", "Environment 1")

  >>> env2 = create_env("env2", "python_3.7.13", "Environment 2")

  >>> env3 = create_env("env3", "r_4.1", "Environment 3")

  >>> env4 = create_env("env4", "r_4.1", "Environment 4")

• List user environments.

  >>> list_user_envs()

    env_name   env_description  base_env_name   language
  0     env1     Environment 1  python_3.7.13    Python
  1     env2     Environment 2  python_3.7.13    Python
  2     env3     Environment 3          r_4.1         R
  3     env4     Environment 4          r_4.1         R

• Remove all R user environments.

  >>> remove_all_envs(env_type="R")

  User environment 'env3' removed.
  User environment 'env4' removed.
  All R environment(s) removed.
  True

• Verify all R user environments are removed.

  >>> list_user_envs()

    env_name   env_description  base_env_name   language
  0     env1     Environment 1  python_3.7.13    Python
  1     env2     Environment 2  python_3.7.13    Python

• Try to remove R environments again.

  >>> remove_all_envs(env_type="R")

  No R user environment(s) found.
  True

• Remove all remaining Python environments.

  >>> remove_all_envs()

  All user environment(s) removed.
  True

Example 5: Remove asynchronously all R environments first and then all remaining Python environments

This example first removes all R environments asynchronously, followed by Python environments.

• Create user environments.

  >>> env1 = create_env("env1", "python_3.7.13", "Environment 1")

  >>> env2 = create_env("env2", "python_3.7.13", "Environment 2")

  >>> env3 = create_env("env3", "r_4.1", "Environment 3")

  >>> env4 = create_env("env4", "r_4.1", "Environment 4")

• List user environments.

  >>> list_user_envs()

    env_name   env_description  base_env_name   language
  0     env1     Environment 1  python_3.7.13    Python
  1     env2     Environment 2  python_3.7.13    Python
  2     env3     Environment 3          r_4.1         R
  3     env4     Environment 4          r_4.1         R

• Remove all R environments asynchronously.

  >>> remove_all_envs(env_type="R", asynchronous=True)

  Request to remove environment initiated successfully. Check the status using async_run_status(['5c23f956-c89a-4d69-9f1e-6491bac9973f', '6ec9ecc9-9223-4d3f-92a0-9d1abc652aca'])
  True

• Verify all R user environments are removed.

  >>> list_user_envs()

    env_name   env_description  base_env_name   language
  0     env1     Environment 1  python_3.7.13    Python
  1     env2     Environment 2  python_3.7.13    Python

• Remove all remaining Python environments asynchronously.

  >>> remove_all_envs(asynchronous=True)

  Request to remove environment initiated successfully. Check the status using async_run_status('7d86eb99-9ab3-4e0d-b4dd-8b5f1757b9c7')
  '7d86eb99-9ab3-4e0d-b4dd-8b5f1757b9c7'

Example 6: Remove all environments asynchronously

• Create user environments.

  >>> env1 = create_env("env1", "python_3.7.13", "Environment 1")

  >>> env2 = create_env("env2", "python_3.7.13", "Environment 2")

  >>> env3 = create_env("env3", "r_4.1", "Environment 3")

  >>> env4 = create_env("env4", "r_4.1", "Environment 4")

• List user environments.

  >>> list_user_envs()

    env_name   env_description  base_env_name   language
  0     env1     Environment 1  python_3.7.13    Python
  1     env2     Environment 2  python_3.7.13    Python
  2     env3     Environment 3          r_4.1         R
  3     env4     Environment 4          r_4.1         R

• Remove all environments asynchronously.

  >>> remove_all_envs(asynchronous=True)

  Request to remove environment initiated successfully. Check the status using async_run_status('22f5d693-38d2-469e-b434-9f7246c7bbbb')
  '22f5d693-38d2-469e-b434-9f7246c7bbbb'