kedro_datasets.polars.LazyPolarsDataset

class kedro_datasets.polars.LazyPolarsDataset(*, filepath, file_format, load_args=None, save_args=None, version=None, credentials=None, fs_args=None, metadata=None)[source]

LazyPolarsDataset loads/saves data from/to a data file using an underlying filesystem (e.g.: local, S3, GCS). It uses Polars to handle the type of read/write target. It uses lazy loading with Polars Lazy API, but it can save both Lazy and Eager Polars DataFrames.

Example usage for the YAML API:

cars:
  type: polars.LazyPolarsDataset
  filepath: data/01_raw/company/cars.csv
  load_args:
    sep: ","
    parse_dates: False
  save_args:
    has_header: False
    null_value: "somenullstring"

motorbikes:
  type: polars.LazyPolarsDataset
  filepath: s3://your_bucket/data/02_intermediate/company/motorbikes.csv
  credentials: dev_s3

Example usage for the Python API:

from kedro_datasets.polars import LazyPolarsDataset
import polars as pl

data = pl.DataFrame({"col1": [1, 2], "col2": [4, 5], "col3": [5, 6]})

dataset = LazyPolarsDataset(filepath=tmp_path / "test.csv", file_format="csv")
dataset.save(data)
reloaded = dataset.load()
assert data.frame_equal(reloaded.collect())

Attributes

DEFAULT_LOAD_ARGS

DEFAULT_SAVE_ARGS

Methods

exists()

Checks whether a data set's output already exists by calling the provided _exists() method.

from_config(name, config[, load_version, ...])

Create a data set instance using the configuration provided.

load()

Loads data by delegation to the provided load method.

release()

Release any cached data.

resolve_load_version()

Compute the version the dataset should be loaded with.

resolve_save_version()

Compute the version the dataset should be saved with.

save(data)

Saves data by delegation to the provided save method.
DEFAULT_LOAD_ARGS: ClassVar[dict[str, Any]] = {}
DEFAULT_SAVE_ARGS: ClassVar[dict[str, Any]] = {}
__init__(*, filepath, file_format, load_args=None, save_args=None, version=None, credentials=None, fs_args=None, metadata=None)[source]

Creates a new instance of LazyPolarsDataset pointing to a concrete data file on a specific filesystem.

Parameters:

  • filepath (str) – Filepath in POSIX format to a file prefixed with a protocol like s3://. If prefix is not provided, file protocol (local filesystem) will be used. The prefix should be any protocol supported by fsspec. Key assumption: The first argument of either load/save method points to a filepath/buffer/io type location. There are some read/write targets such as ‘clipboard’ or ‘records’ that will fail since they do not take a filepath like argument.

  • file_format (str) – String which is used to match the appropriate load/save method on a best effort basis. For example if ‘csv’ is passed the polars.read_csv and polars.DataFrame.write_csv methods will be identified. An error will be raised unless at least one matching read_{file_format} or write_{file_format}.

  • load_args (Optional[dict[str, Any]]) – polars options for loading files. Here you can find all available arguments: https://pola-rs.github.io/polars/py-polars/html/reference/io.html All defaults are preserved.

  • save_args (Optional[dict[str, Any]]) – Polars options for saving files. Here you can find all available arguments: https://pola-rs.github.io/polars/py-polars/html/reference/io.html All defaults are preserved.

  • version (Optional[Version]) – If specified, should be an instance of kedro.io.core.Version. If its load attribute is None, the latest version will be loaded. If its save attribute is None, save version will be autogenerated.

  • credentials (Optional[dict[str, Any]]) – Credentials required to get access to the underlying filesystem. E.g. for GCSFileSystem it should look like {“token”: None}.

  • fs_args (Optional[dict[str, Any]]) – Extra arguments to pass into underlying filesystem class constructor (e.g. {“project”: “my-project”} for GCSFileSystem), as well as to pass to the filesystem’s open method through nested keys open_args_load and open_args_save. Here you can find all available arguments for open: https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.open All defaults are preserved, except mode, which is set to r when loading and to w when saving.

  • metadata (Optional[dict[str, Any]]) – Any arbitrary metadata. This is ignored by Kedro, but may be consumed by users or external plugins.

Raises:

DatasetError – Will be raised if at least less than one appropriate read or write methods are identified.

exists()

Checks whether a data set’s output already exists by calling the provided _exists() method.

Return type:

bool

Returns:

Flag indicating whether the output already exists.

Raises:

DatasetError – when underlying exists method raises error.

classmethod from_config(name, config, load_version=None, save_version=None)

Create a data set instance using the configuration provided.

Parameters:

  • name (str) – Data set name.

  • config (dict[str, Any]) – Data set config dictionary.

  • load_version (str | None) – Version string to be used for load operation if the data set is versioned. Has no effect on the data set if versioning was not enabled.

  • save_version (str | None) – Version string to be used for save operation if the data set is versioned. Has no effect on the data set if versioning was not enabled.

Return type:

AbstractDataset

Returns:

An instance of an AbstractDataset subclass.

Raises:

DatasetError – When the function fails to create the data set from its config.

load()

Loads data by delegation to the provided load method.

Return type:

TypeVar(_DO)

Returns:

Data returned by the provided load method.

Raises:

DatasetError – When underlying load method raises error.

release()

Release any cached data.

Raises:

DatasetError – when underlying release method raises error.

Return type:

None

resolve_load_version()

Compute the version the dataset should be loaded with.

Return type:

str | None

resolve_save_version()

Compute the version the dataset should be saved with.

Return type:

str | None

save(data)

Saves data by delegation to the provided save method.

Parameters:

data (TypeVar(_DI)) – the value to be saved by provided save method.

Raises:

  • DatasetError – when underlying save method raises error.

  • FileNotFoundError – when save method got file instead of dir, on Windows.

  • NotADirectoryError – when save method got file instead of dir, on Unix.

Return type:

None