Shared Pydantic schemas for the Storywrangler platform
Project description
storywrangler-schemas
Shared Pydantic schemas for the Storywrangler platform. Both the backend API and the storywrangler SDK import from this package — neither owns a copy of the models.
Implements the Storywrangler Specification v0.0.3.
Installation
pip install storywrangler-schemas
Most users should install storywrangler instead, which includes this package as a dependency.
What's inside
Registry models (storywrangler_schemas.registry)
| Model | Purpose |
|---|---|
DatasetCreate |
Full registration payload (domain, format, transform, entity mapping, lineage, ...) |
EndpointSchemaConfig |
Output shape declaration (types-counts, time-series) |
TransformConfig |
Query slice axes (time dimension, filter dimensions, hash bucket) |
EntityMappingConfig |
Entity ID resolution config (local column + namespace) |
EntityRow |
One row in the entity mapping table |
ManifestConfig |
Coverage index (availability, partition index) |
OwnershipConfig |
Owner group, contact, lifecycle status |
LineageConfig |
Sources, upstream datasets, pipeline repo, archival DOI |
Hash bucket assignment (storywrangler_schemas.hashing)
Canonical murmur3_32 hash function shared between the backend query layer and data pipelines:
from storywrangler_schemas.hashing import assign_bucket
bucket = assign_bucket("hello", num_buckets=16) # deterministic int in [0, 16)
Standards (storywrangler_schemas.standards)
Entity ID validation, namespace registry, and spec URL helpers.
Project details
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