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Imported as `iad.dataman` — data casting, resource models, and dataset bridge

Project description

ialdev-dataman

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.

Install

pip install ialdev-dataman

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

Highlights

  • 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.

Examples

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

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