Teradata Package for Python Function Reference on VantageCloud Lake - list_user_envs - Teradata Package for Python - Look here for syntax, methods and examples for the functions included in the Teradata Package for Python.
Teradata® Package for Python Function Reference on VantageCloud Lake
- Deployment
- VantageCloud
- Edition
- Lake
- Product
- Teradata Package for Python
- Release Number
- 20.00.00.03
- Published
- December 2024
- ft:locale
- en-US
- ft:lastEdition
- 2024-12-19
- dita:id
- TeradataPython_FxRef_Lake_2000
- Product Category
- Teradata Vantage
- teradataml.scriptmgmt.lls_utils.list_user_envs = list_user_envs(env_name=None, **kwargs)
- DESCRIPTION:
Lists the Python OR R environments created by the session user in
Open Analytics Framework.
PARAMETERS:
env_name:
Optional Argument.
Specifies the string or regular expression to filter name of the environment.
Types: str
base_env:
Optional Argument.
Specifies the string or regular expression to filter the base Python environment.
Types: str
desc:
Optional Argument.
Specifies the string or regular expression to filter the description
about the environment.
Types: str
case:
Optional Argument.
Specifies whether filtering operation should be case sensitive or not.
Default Value: False
Types: boolean
conda_env:
Optional Argument.
Specifies the boolean value to filter the conda environment(s).
When set to True, all conda environments are listed.
When set to False, all non-conda environments are listed.
If not specified, all user environments are listed.
Types: bool
regex:
Optional Argument.
Specifies whether string passed to "env_name", "base_env", and "desc"
should be treated as regular expression or a literal.
When set to True, string is considered as a regular expression pattern,
otherwise treats it as literal string.
Default Value: True
Types: boolean
flags:
Optional Argument.
Specifies flags to pass for regular expressions in filtering.
For example
re.IGNORECASE.
Default Value: 0
Types: int
RETURNS:
Pandas DataFrame.
Function returns remote user environments and their details in a Pandas dataframe.
Function will help user find environments created, version of Python language used
in the environment and description of each environment if provided at the time of
environment creation.
RAISES:
TeradataMlException.
EXAMPLES:
# Create example environments.
>>> create_env('Fraud_Detection',
... 'python_3.7.13',
... 'Fraud detection through time matching')
User environment 'Fraud_detection' created.
>>> create_env('Lie_Detection',
... 'python_3.7.13',
... 'Lie detection through time matching')
User environment 'Lie_Detection' created.
>>> create_env('Lie_Detection_ML',
... 'python_3.8.13',
... 'Detect lie through machine learning.')
User environment 'Lie_Detection_ML' created.
>>> create_env('Sales_env',
... 'python_3.9.13',
... 'Sales team environment.')
User environment 'Sales_env' created.
>>> create_env('Customer_Trends',
... 'r_4.1.3',
... 'Analyse customer trends.')
User environment 'Customer_Trends' created.
>>> create_env('Carbon_Credits',
... 'r_3.6.3',
... 'Prediction of carbon credits consumption.')
User environment 'Carbon_Credits' created.
>>> create_env('Sales_cond_env',
... 'python_3.9',
... 'Sales team environment.',
... conda_env=True)
Conda environment creation initiated
User environment 'Sales_cond_env' created.
# Example 1: List all available user environments.
>>> list_user_envs()
env_name env_description base_env_name language conda
0 Carbon_Credits Prediction of carbon credits consumption r_3.6.3 R False
1 Customer_Trends Analyse customer trends r_4.1.3 R False
2 Fraud_Detection Fraud detection through time matching python_3.7.13 Python False
3 Lie_Detection Lie detection through time matching python_3.7.13 Python False
4 Lie_Detection_ML Detect lie through machine learning. python_3.8.13 Python False
5 Sales_env Sales team environment. python_3.9.13 Python False
6 Sales_cond_env Sales team environment. python_3.9 Python True
# Example 2: List all user environments with environment name containing string
# "Detection" and description that contains string "."(period).
>>> list_user_envs(env_name="Detection", desc=".", regex=False)
env_name env_description base_env_name language conda
2 Lie_Detection_ML Detect lie through machine learning. python_3.8.13 Python False
>>>
# Example 3: List all user environments with description that contains string "lie"
# and is case sensitive.
>>> list_user_envs(desc="lie", case=True)
env_name env_description base_env_name language conda
4 Lie_Detection_ML Detect lie through machine learning. python_3.8.13 Python False
>>>
# Example 4: List all user environments with base environment version containing string
# "3.".
>>> list_user_envs(base_env="3.")
env_name env_description base_env_name language conda
0 Carbon_Credits Prediction of carbon credits consumption r_3.6.3 R False
2 Fraud_Detection Fraud detection through time matching python_3.7.13 Python False
3 Lie_Detection Lie detection through time matching python_3.7.13 Python False
4 Lie_Detection_ML Detect lie through machine learning. python_3.8.13 Python False
5 Sales_env Sales team environment. python_3.9.13 Python False
6 Sales_conda_env Sales team environment. python_3.9 Python True
>>>
# Example 5: List all user environments with environment name contains string "detection",
# description containing string "fraud" and base environment containing string "3.7".
>>> list_user_envs("detection", desc="fraud", base_env="3.7")
env_name env_description base_env_name language conda
2 Fraud_Detection Fraud detection through time matching python_3.7.13 Python False
>>>
# Example 6: List all user environments with environment name that ends with "detection".
>>> list_user_envs("detection$")
env_name env_description base_env_name language conda
2 Fraud_Detection Fraud detection through time matching python_3.7.13 Python False
3 Lie_Detection Lie detection through time matching python_3.7.13 Python False
>>>
# Example 7: List all user environments with description that has either "lie" or "sale".
# Use re.VERBOSE flag to add inline comment.
>>> list_user_envs(desc="lie|sale # Search for lie or sale.", flags=re.VERBOSE)
env_name env_description base_env_name language conda
3 Lie_Detection Lie detection through time matching python_3.7.13 Python False
4 Lie_Detection_ML Detect lie through machine learning. python_3.8.13 Python False
5 Sales_env Sales team environment. python_3.9.13 Python False
6 Sales_conda_env Sales team environment. python_3.9 Python True
>>>
# Example 8: List all user environments where python 3 environment release version has
# odd number. For e.g. python_3.7.x.
>>> list_user_envs(base_env="\.\d*[13579]\.")
env_name env_description base_env_name language
1 Customer_Trends Analyse customer trends r_4.1.3 R
2 Fraud_Detection Fraud detection through time matching python_3.7.13 Python
3 Lie_Detection Lie detection through time matching python_3.7.13 Python
5 Sales_env Sales team environment. python_3.9.13 Python
>>>
# Example 9: List all conda environments.
>>> list_user_envs(conda_env=True)
env_name env_description base_env_name language conda
6 Sales_conda_env Sales team environment. python_3.9 Python True
>>>
# Remove example environments.
remove_env("Fraud_Detection")
remove_env("Lie_Detection")
remove_env("Lie_Detection_ML")
remove_env("Sales_env")
remove_env("Carbon_Credits")
remove_env("Customer_Trends")
remove_env("Sales_conda_env")