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v0.9.0

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@gee-senbong gee-senbong released this 21 Sep 05:33
· 16 commits to main since this release
0da838d

Highlights

  • Asynchronous jobs (client.jobs) — long-running work can now run server-side without blocking. jobs.forecast(), jobs.cross_validation(), jobs.finetune(), jobs.detect_anomalies(), jobs.simulate(), jobs.explain() and jobs.execute_step() each return a Job handle with .wait(), .status and .cancel(), mirroring the blocking method of the same name — note that jobs.detect_anomalies() mirrors detect_anomalies_online(), i.e. it runs online detection. Job, JobStatus, JobError, JobTimeoutError, JobCancelledError and ApiError are exported from the package root (#847, #879, #883, #887).
  • simulate() — draws temporally correlated sample paths per series, in long format with a sample_id column. multivariate=True keeps paths coherent across series (#852).
  • explain() — model-independent feature importance weights, via "granger" or "transfer_entropy". These describe predictive relationships, not causal ones (#852).
  • list_models() — returns the model names your API key may use. Needs the GET /v2/models route, which is not deployed yet; until it ships the call raises ApiError with status 404 (#881).
  • nixtla.snowflake helpers — a package for driving the Snowflake TimeGPT integration from Python, exposing detect_anomalies, load_actuals and to_anomalies_df (#870).
  • Start datetime information — requests now carry start-datetime metadata for each series (#859).
  • Breaking: detect_anomalies_online() gained finetuned_model_id and model_parameters mid-signature, to match the parameter order of forecast() and cross_validation(). Callers passing arguments positionally past finetune_loss must switch to keywords (#883).
  • Deprecation ahead of 1.0: the anomaly-detection methods are being renamed and detect_anomalies() changes meaning. Batch detect_anomalies() is removed in 1.0 with no drop-in replacement; detect_anomalies_online() takes over the name, unchanged in behavior. The Snowflake anomaly path (nixtla.snowflake.detect_anomalies(), NIXTLA_DETECT_ANOMALIES and its UDTF) makes the same move, so h and detection_size become required PARAMS entries. Every affected entry point now emits a FutureWarning (#896).
  • Cross-validation correctness fix — actual values returned in the cross-validation output were incorrect and are now right; re-verify any evaluation metrics computed with v0.8.0 (#866).

New Features

Breaking Change

Bug Fixes

Documentations/Web

Dependencies

Improvements

Full Changelog: v0.8.0...v0.9.0