> ## Documentation Index > Fetch the complete documentation index at: https://docs.ionworks.com/llms.txt > Use this file to discover all available pages before exploring further. # 2026 06 29 ## A rebuilt execution engine for data fitting The pipeline's parallelisation layer has been rebuilt as a dedicated execution engine. `DataFit.fit` is now `DataFit.run` on this engine, which drives optimizers (ask/tell), point evaluation, multistart coordination, and progress reporting through a single set of executor protocols (serial, multiprocessing, and — on the backend — Ray over a warm actor pool). The old `distributed.py` Joblib configuration zoo and its `num_workers` / `parallel` schema fields are retired in favour of engine-owned parallelism, and backend datafit jobs now run through a thin `datafit.run()` host with classified-failure error mapping and per-generation progress streaming. ## Name-based measurement lookup `client.resolve_measurement(cell_specification, cell_instance, measurement)` resolves a `measurement_id` from human-readable names, walking the spec → instance → measurement hierarchy with server-side filtering at each level. Scripts no longer need to hand-walk three list endpoints and repeat name-matching boilerplate just to get an id. `parameterized_model.create_or_get` also lands, giving parameterized models the re-runnable create-or-resolve behaviour the other cell resources already had. ## Clearer errors for model failures and duplicates Two opaque "An unexpected error occurred" cases — a fit whose model setup needs geometry the user didn't supply, and a custom model with no discretisation recipe — now surface as a clear `ModelError` naming what failed. Separately, attempting to create a resource that already exists now returns a `409 CONFLICT` (with the existing id) instead of a `500`, both via a catch-all for Postgres unique-constraint violations and per-path translation at every insert site, so duplicate-creation attempts no longer page on-call. **Improvements** * "Save as template" for an optimization now builds the template server-side via a new `POST /optimization_templates/from-optimization` endpoint that copies an optimization's saved config directly into the template. **Fixes** * Completed validation/datafit results no longer sporadically show "Failed to load plot data." for one of a pair of plots. A job's metadata is rewritten in place as it runs (checkpoints, then the final write that adds the validation plot config), but the in-process metadata cache assumed metadata was immutable after completion; it now self-heals stale entries, and per-job storage blobs are written no-cache so a stale early write can't win. * `CycleAgeing` experiments passed as a lazy `DataLoader` (`experiment="from data"`) now resolve their `db:` measurement references server-side, instead of surviving to the credential-less fit worker and failing there. **Improvements** * A bare element-wise cost (`SSE`/`MSE`/`RMSE`/`MAE`/`Max`) applied to a multi-variable objective now warns when variable lengths mismatch — e.g. a model-axis dQ/dV variable against a data-axis voltage variable — instead of silently broadcasting to a meaningless residual. * All 1-D interpolant calculations now accept a `"pchip"` interpolator (monotone cubic), the right choice for sparse, order-of-magnitude `D(sto)` tables such as half-cell GITT per-pulse diffusivity. **Fixes** * The MSMR half-cell logistic value and derivative are now evaluated through a single per-species-stabilized helper whose exponent is always ≤ 0, so it can never overflow. * The object path (`iwp.Pipeline.from_schema(...).run()`) now rebuilds a serialized model dict in objective options the same way the config/server path does, so both paths agree. * A custom model with serialised geometry/mesh now survives stdlib `pickle` / raw multiprocessing multistart — the previous anonymous-subclass approach could only be serialised by value (cloudpickle/Ray). **Improvements** * `client.resolve_measurement` and `parameterized_model.create_or_get` (both introduced above), plus `Model.config` for inspecting a model's stored configuration. * Passing a bare pandas/polars DataFrame to a schema `data` field (objective `data_input`, `OCPDataInterpolant.data`, the Arrhenius calculations' `data`) is now auto-wrapped correctly on serialization, instead of failing server-side validation with the opaque "Required field 'data' missing". **Improvements** * Arbin protocols now support **subschedules** (mapped to a UCP subroutine with the referenced `.subsdx` registered and parsed recursively), **counter loops**, and **temperature add-ins**, so schedules that previously crashed on upload with "Unsupported step type: SubSchedule" now parse and simulate end-to-end. **Fixes** * BioLogic `.mps` simulation fixes: the loop counter is off by one no longer (EC-Lab's `ctrl_repeat` does not count the first pass, so a loop now runs `ctrl_repeat + 1` times), plus BCD/EIS support and drive-cycle fixes, each reproduced against the reported setting files before fixing. * User-correctable protocol and configuration errors across the Protocol Simulator and pipeline libraries now raise specific domain error types (`ProtocolConfigurationError`, `UserConfigurationError`) instead of generic `ValueError` / `RuntimeError`, so they surface to the user rather than paging on-call. **Improvements** * The `process-data` reader gotchas are now documented: selecting the `record` sheet for multi-sheet Neware BTSDA `.xlsx` files, and current-unit handling — alongside the one-call `read.time_series_and_steps` entry point.