write_resource_batch

Warning

🚧 Sprout is still in active development and evolving quickly, so the documentation and functionality may not work as described and could undergo substantial changes 🚧

write_resource_batch(
    data: pl.DataFrame,
    resource_properties: ResourceProperties,
    package_path: Path | None = None,
)

Writes the tidied, original data into the resource’s batch data folder.

Writes the original data that is in a Tidy format and read as a pl.DataFrame into the resource location available from the path property of the resource_properties. This will save a timestamped, unique file name to store it as a backup. See the design docs for an explanation of this batch file. Data is always checked against the properties before writing it to the batch folder.

Parameters

data : pl.DataFrame

A Polars DataFrame object with the data to write to the batch folder.

resource_properties : ResourceProperties

The properties object for the specific resource. Use read_properties() to read the properties for the resource and get_resource_properties() to get the correct resource properties.

package_path : Path | None = None

The path to the data package root folder (where datapackage.json is located). Defaults to the current working directory.

Returns

Path

The path to the written Parquet resource file.

Raises

ExceptionGroup

A group of CheckErrors, if resource properties are incorrect.

# TODO

Add exception for data check when implemented.

Examples

import seedcase_sprout as sp

with sp.ExamplePackage():
    resource_properties = sp.read_properties().resources[0]
    sp.write_resource_batch(
        data=sp.example_data(),
        resource_properties=resource_properties,
    )

PosixPath('/tmp/tmp9f_zjxa0/example-package/resources/example-resource/batch/2025-05-30T105407Z-0138ef47-ffe7-4a0e-9515-ffeb299a008a.parquet')