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name: persistence-update description: "Persist, reload, update, and forecast pmdarima ARIMA models and pipelines safely, including transformer state, exogenous alignment, and version compatibility." disable-model-invocation: true metadata: disco-role: operating license: MIT

Persistence and update

Use this route when a fitted ARIMA, AutoARIMA, or pmdarima.pipeline.Pipeline must be serialized, reloaded, refreshed with new observations, or forecast after a refresh. Keep the artifact coupled to the producer environment and treat pickle/joblib deserialization as a trusted-code operation.

Route

1. Establish the fitted object's class and fitted state, pmdarima/Python and dependency versions, transformer configuration, exogenous schema, training row count/range, forecast-horizon contract, and artifact checksum. Read the API reference for source-level contracts.
2. Fit the complete pipeline, including endogenous and exogenous transformers, and smoke-test predict before persistence. Keep y and every X row in temporal alignment; for forecasts, provide one future X row per period and the same feature width.
3. Persist only a trusted object with pickle or joblib. Stage writes in a trusted temporary path on the same filesystem, validate a same-environment reload and known-shape forecast, then atomically replace the artifact of record. Never load an untrusted or arbitrary path.
4. For a small, ordered batch whose schema and model structure remain valid, pass raw new observations to Pipeline.update(y, X=..., maxiter=...) or ARIMA.update(...). Pipeline.update mutates the fitted pipeline but returns the final estimator in pmdarima 2.1.1. Preserve fitted transformer semantics: updatable stages advance, ordinary stages only transform, and the final ARIMA receives aligned transformed data.
5. Prefer a clean refit (and possibly order search) after drift, corrected history, schema/feature meaning changes, changed transformation domains or seasonality, repeated updates, or non-convergence. An update is not a new order search or a substitute for validation.

Read workflows for fit/predict/update, trusted round-trip, metadata, atomic replacement, refit decisions, and alignment. Read troubleshooting before recovering load, exogenous, transformer, or optimizer failures.

Bundled checks

• scripts/pipeline_roundtrip.py fits a deterministic small Box-Cox pipeline, records a compact version/schema manifest, stages and validates its own temporary artifact, atomically promotes it, reloads it, and asserts forecast shape and equality.
• scripts/update_forecast.py fits a small Box-Cox-plus-Fourier pipeline, updates it with raw observations using bounded maxiter, asserts Fourier state advancement and forecast shape, then validates and round-trips the artifact it created.

Both scripts accept --help, work from arbitrary current directories, use local deterministic data, default to temporary paths, and never accept an input artifact path.

Provenance boundary

This route describes pmdarima 2.1.1 source behavior at commit 4c2dfccb28f64d2c00a5e10b59c1d1a3e16576a9. Verify the installed package and dependency versions before applying any persisted artifact; an inspection environment can legitimately report a different development version.

Local references

• API reference — signatures, state, shape, transformer, and persistence contracts.
• Workflows — bounded operational sequences and the atomic promotion policy.
• Troubleshooting — installation, trust, compatibility, alignment, domain, and update recovery.