Set Up and Manage User Environment | Score dataset using bank marking data | Teradata Open Analytics Framework - Set Up and Manage a User Environment

Explore the base environments offered on the target system.

list_base_envs()

       base_name        language       version
0        python_3.8        Python        3.8.18
1        python_3.9        Python        3.9.18
2        python_3.10       Python        3.10.13

Use the following JSON file to create the user environment.

{
    "env_specs": [
        {
            "env_name": "bank-marketing-env",
            "libs": [
                "dill",
                "pandas",
                "scikit-learn",
                "xgboost==2.0.0"
            ],
            "desc": "Env for Bank Marketing related demo",
            "files": [
                "bank-marketing-train.py",
                "bank-marketing-predict.py"
            ]
        }
    ]
}

Create a new user environment with required libraries using the template JSON file.

env_name = "bank-marketing-env"
template_filename = "bank-marketing-env.json"
bank_marketing_env = create_env(template=template_filename)
set_user_env(bank_marketing_env)

Out:

Creating environment 'bank-marketing-env'...
User environment 'bank-marketing-env' created.
An empty environment 'bank-marketing-env' is created.
Installing files in environment 'bank-marketing-env'...
File 'bank-marketing-train.py' installed successfully in the remote user environment 'bank-marketing-env'.
File 'bank-marketing-predict.py' installed successfully in the remote user environment 'bank-marketing-env'.
File installation in environment 'bank-marketing-env' - Completed.
Installing libraries in environment 'bank-marketing-env'...
Libraries installation in environment 'bank-marketing-env' - Completed.
Created environment 'bank-marketing-env' with specified requirements.

================================================
Environment Name: bank-marketing-env
Base Environment: python_3.10
Description: Env for Bank Marketing related demo

############ Files installed in User Environment ############

                        File  Size             Timestamp
0  bank-marketing-predict.py  1454  2024-04-26T07:18:52Z
1    bank-marketing-train.py  1141  2024-04-26T07:18:51Z

############ Libraries installed in User Environment ############

               name      version
0              dill        0.3.8
1            joblib        1.4.0
2             numpy       1.26.4
3            pandas        2.2.2
4               pip       23.0.1
5   python-dateutil  2.9.0.post0
6              pytz       2024.1
7      scikit-learn        1.4.2
8             scipy       1.13.0
9        setuptools       65.5.0
10              six       1.16.0
11    threadpoolctl        3.4.0
12           tzdata       2024.1
13          xgboost        2.0.0

================================================
Default environment is set to 'bank-marketing-env'.

Set Up and Manage User Environment | Score dataset using bank marking data | Teradata Open Analytics Framework - Set Up and Manage a User Environment - Teradata VantageCloud Lake

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