Skip to main content

Pydantic schemas for building Ionworks pipeline configurations

Project description

Ionworks Schema

This is a read-only mirror. The source of truth is a private repo.

Pydantic schemas for building Ionworks pipeline configurations.

Overview

Ionworks Schema (ionworks_schema) provides the schema for constructing Ionworks pipeline configurations. Use these classes to define pipelines (data fits, calculations, entries, validations) in Python with validation, then export JSON to submit via the Ionworks API. Pipeline concepts, objectives, and workflows are described in the Pipeline documentation and in the Ionworks documentation.

Pipelines are executed by submitting configurations to the Ionworks API. Use the ionworks-api Python client to create and run jobs: pip install ionworks-api.

Installation

pip install ionworks-schema

Quick start

Build a pipeline configuration with schema classes, export to JSON, and submit with the Ionworks API client:

import ionworks_schema as iws
import json

# Define a parameter to fit (name, initial_value, bounds)
parameter = iws.Parameter(
    name="Positive electrode capacity [A.h]",
    initial_value=1.0,
    bounds=(0.5, 2.0),
)

# Objective: MSMR half-cell fit; data can be "db:<measurement_id>" for uploaded data (use objectives submodule)
objective = iws.objectives.MSMRHalfCell(
    data_input="db:your-measurement-id",
    options={"model": {"electrode": "positive"}},
)

data_fit = iws.DataFit(
    objectives={"ocp": objective},
    parameters={"Positive electrode capacity [A.h]": parameter},
)

pipeline = iws.Pipeline(elements={"fit": data_fit})

# Export to JSON for API submission
config = pipeline.to_config()
with open("pipeline_config.json", "w") as f:
    json.dump(config, f, indent=2)

# Submit via ionworks-api (requires credentials and project ID — see ionworks-api README)
# from ionworks import Ionworks
# client = Ionworks()
# job = client.pipeline.create(config)
# client.pipeline.wait_for_completion(job.id, timeout=600)

Schema classes and pipeline elements

Schema classes mirror the pipeline configuration format consumed by the Ionworks pipeline and API. Runtime behavior and options are documented in the Pipeline user guide and in the ionworkspipeline package (e.g. parsers, data_fits, objectives).

A pipeline is a top-level Pipeline with a dictionary of named elements. Each element has an element_type: entry, data_fit, calculation, or validation.

Role Schema class Description
Top-level Pipeline Pipeline configuration with named elements.
Entry DirectEntry Supply fixed parameter values (no fitting or calculation).
Data fit DataFit, ArrayDataFit Fit model parameters to data; contain objectives and parameters.
Calculation ionworks_schema.calculations Run calculations (e.g. OCP, diffusivity, geometry). See submodule for available classes.
Objectives MSMRHalfCell, MSMRFullCell, CurrentDriven, CycleAgeing, CalendarAgeing, EIS, Pulse, Resistance, ElectrodeBalancing, OCPHalfCell, and others Used inside DataFit.objectives to define what to fit. Import from ionworks_schema.objectives (e.g. iws.objectives.MSMRHalfCell).
Parameters Parameter name, initial_value, bounds (and optional prior, etc.). Used in DataFit.parameters; dict key is the parameter name.
Priors Prior Used in DataFit.priors. Import from ionworks_schema.priors (e.g. iws.priors.Prior).
Library Material, Library Built-in material library for initial parameter values.

Material library

Access built-in materials with validated parameter values for use as initial values or entries:

import ionworks_schema as iws

# List available materials
materials = iws.Library.list_materials()

# Get a specific material (e.g. NMC - Verbrugge 2017)
material = iws.Material.from_library("NMC - Verbrugge 2017")
print(material.parameter_values)

Parameter names and interpretation are described in the Pipeline documentation.

Resources

Note

This package provides configuration schemas only. To run pipelines, export JSON with pipeline.to_config() and submit it via the Ionworks API using the ionworks-api client.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ionworks_schema-0.10.0.tar.gz (606.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ionworks_schema-0.10.0-py3-none-any.whl (83.5 kB view details)

Uploaded Python 3

File details

Details for the file ionworks_schema-0.10.0.tar.gz.

File metadata

  • Download URL: ionworks_schema-0.10.0.tar.gz
  • Upload date:
  • Size: 606.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for ionworks_schema-0.10.0.tar.gz
Algorithm Hash digest
SHA256 9e6865b57ed63b54a3cf06ee5fe8602876a24c15c14782481cd40e52d105fe7f
MD5 b8dd538d60beccea148ae6cd6b3cbc02
BLAKE2b-256 d022f6d5e4cf758f4d83d1bd4fb1a892f5155d00647e7d9afe417e8066a08a46

See more details on using hashes here.

File details

Details for the file ionworks_schema-0.10.0-py3-none-any.whl.

File metadata

File hashes

Hashes for ionworks_schema-0.10.0-py3-none-any.whl
Algorithm Hash digest
SHA256 0312896cc97b4614d584fe9019bc892d8d57592cd61265bd507957effb8b1470
MD5 593c8517b17c169e6dd8082271a414bf
BLAKE2b-256 455d055c14583dcfccd2897dfd48df7087e7d0911c4726d550881bb483672cf8

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page