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teradatamodelops

library7.3.4pypypiunverified

Python client for Teradata ModelOps (TMO), enabling management of machine learning models and experiments on the Teradata Vantage platform. Current version 7.2.7, requires Python >=3.10. Release cadence is roughly monthly.

ai-ml database aws

pip install teradatamodelops

github ↗package ↗homepage ↗docs ↗changelog ↗

INSTALL

IMPORT

SIG · TERADATAMODELOPS

teradatamodelops

ai-mlpythonv7.3.4

Install

22.7s avg

Import

—

Disk

716MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v7.3.4 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.95 runs

installs and imports cleanly · install 0.0s · import 0.000s · 725.8MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 22.7s · import 0.000s · 717MB

716MB installed

● package 716MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

TMOModel

✓ from teradatamodelops import TMOModel

✗ import teradatamodelops.TMOModel

Module is a Python package; use direct import.

TMOExperiment

✓ from teradatamodelops import TMOExperiment

Basic workflow: connect to Teradata, load data, create a ModelOps model, train, and save.

from teradatamodelops import TMOModel from teradataml import DataFrame, create_context # Connect (adjust parameters for your environment) create_context(host='your_host', username='your_user', password='your_pass') # Load data df = DataFrame('your_table') # Create and train model (example classification) model = TMOModel(model_type='classification', target_column='target', feature_columns=['feat1','feat2']) model.fit(df) # Save model to ModelOps model_id = model.save(model_name='my_model', project_name='my_project') print(f'Model saved with ID: {model_id}')

Debug

Known issues

breakingIn version 7.x, the import path changed from 'teradatamodelops' (no subpackage) to the same but some classes were renamed. For example, 'Model' is now 'TMOModel'.

fix

Use 'from teradatamodelops import TMOModel' instead of 'from teradatamodelops import Model'.

affects: >=7.0.0

deprecatedThe method 'TMOModel.deploy()' is deprecated in 7.2.0+. Use 'TMOModel.deploy_model()' instead.

fix

Replace model.deploy(...) with model.deploy_model(...).

affects: >=7.2.0

gotchaThe library requires an active Teradata Vantage connection via teradataml. Calling any TMO method without a valid context will raise a connection error.

fix

Ensure you call teradataml.create_context() before using any teradatamodelops class.

affects: all

Upgrade

Version history

7.3.4latest on PyPI · released Jun 19, 2026

Audit

Dependencies

teradatamlrequiredRequired for Teradata database connectivity

numpyrequiredUsed for array operations

pandasrequiredUsed for data frames

Agent activity

40 hits · last 30 days

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