aoa 6.0.0rc5

Python client for Teradata AnalyticOps Accelerator (AOA)

Teradata AnalyticOps Client

• Official Documentation
• Release Notes

Official Documentation

The official documentation for the SDK and CLI can be found in the following links

• SDK
• CLI

Release Notes

5.0.0

• Feature: Add simpler teradataml context creation via aoa_create_context
• Feature: Add database to connections
• Feature: Support for human-readable model folder names
• Feature: Improve UX of aoa run
• Feature: Improved error messages for users related to auth and configure
• Refactor: Package refactor of aoa.sto.util to aoa.util.sto
• Bug: cli listing not filtering archived entities
• Cleanup: Remove pyspark support from CLI

4.1.12

• Bug: aoa connection add now hides password symbols
• Bug: sto.util.cleanup_cli() used hardcoded models table
• Feature: sto.util.check_sto_version() checks In-Vantage Python version compatibility
• Feature: sto.util.collect_sto_versions() fetches dict with Python and packages versions

4.1.11

• Bug: aoa run (evaluation) for R now uses the correct scoring file

4.1.10

• Bug: aoa init templates were out of date
• Bug: aoa run (score) didn't read the dataset template correctly
• Bug: aoa run (score) tried to publish to prometheus
• Bug: aoa run (score) not passing model_table kwargs

4.1.9

• Bug: Histogram buckets incorrectly offset by 1 for scoring metrics

4.1.7

• Bug: Quoted and escaped exported connection environmental variables
• Bug: aoa clone with path argument didn't create .aoa/config.yaml in correct directory
• Feature: aoa clone without path now uses repository name by default
• Feature: update BYOM import to upload artefacts before creating version

4.1.6

• Feature: Added local connections feature with Stored Password Protection
• Feature: Self creation of .aoa/config.yaml file when cloning a repo
• Bug: Fix argparse to use of common arguments
• Feature: Support dataset templates for listing datasets and selecting dataset for train/eval
• Bug: Fix aoa run for batch scoring, prompts for dataset template instead of dataset
• Bug: Fix batch scoring histograms as cumulative

4.1.5

• Bug: Fix computing stats
• Feature: Autogenerate category labels and support for overriding them
• Feature: Prompt for confirmation when retiring/archiving

4.1.4

• Feature: Retiring deployments and archiving projects support
• Feature: Added support for batch scoring monitoring

4.1.2

• Bug: Fix computing stats
• Bug: Fix local SQL model training and evaluation

4.1

• Bug: CLI shows archived entities when listing datasets, projects, etc
• Bug: Adapt histogram bins depending on range of integer types.

4.0

• Feature: Extract and record dataset statistics for Training, Evaluation

3.1.1

• Feature: aoa clone respects project branch
• Bug: support Source Model ID from the backend

3.1

• Feature: ability to separate evaluation and scoring logic into separate files for Python/R

3.0

• Feature: Add support for Batch Scoring in run command
• Feature: Added STO utilities to extract metadata for micro-models

2.7.2

• Feature: Add support for OAUTH2 token refresh flows
• Feature: Add dataset connections api support

2.7.1

• Feature: Add TrainedModelArtefactsApi
• Bug: pyspark cli only accepted old resources format
• Bug: Auth mode not picked up from environment variables

2.7.0

• Feature: Add support for dataset templates
• Feature: Add support for listing models (local and remote), datasets, projects
• Feature: Remove pykerberos dependency and update docs
• Bug: Fix tests for new dataset template api structure
• Bug: Unable to view/list more than 20 datasets / entities of any type in the cli

2.6.2

• Bug: Added list resources command.
• Bug: Remove all kerberos dependencies from standard installation, as they can be now installed as an optional feature.
• Feature: Add cli support for new artefact path formats

2.6.1

• Bug: Remove pykerberos as an installation dependency.