Dataset management and data casting tools for the iad toolbox, published as ialdev-dataman and imported as iad.dataman.

Use this package to describe datasets with resource models, discover YAML-backed dataset definitions, build data collections, apply read/transformation pipelines, and create sink repositories for generated outputs.

pip install ialdev-dataman

Requires Python >=3.10, NumPy >=1.26.4,<2, and pandas >=2.0.0.

• Dataset resource models: DataSourceRM, SchemeRM, DatasetRM, and CollectionRM.
• Factory helpers: create_caster, create_collection, and create_sink.
• Data collection APIs: DataCollection, SinkRepo, CollectTable, and CollectSeries.
• YAML/Pydantic helpers through iad.dataman.pydantools.
• Transform utilities for reading files into structured tables and applying image/data transforms.

from iad.dataman import create_caster, create_collection

caster = create_caster(
    source="/data/images",
    scheme="{scene}/{frame}.png",
    filters={"scene": "scene_001"},
)
collection = create_collection(datasets=[caster])

from iad.dataman.models import DataSourceRM, DatasetRM, SchemeRM
from iad.dataman.resman import ModelsManager

manager = ModelsManager()
manager.register_models(DataSourceRM, SchemeRM, DatasetRM)

from iad.dataman.pydantools import YamlModel

class DatasetConfig(YamlModel):
    name: str
    root: str