kedro_datasets.polars.CSVDataset

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

CSVDataset loads/saves data from/to a CSV file using an underlying filesystem (e.g.: local, S3, GCS). It uses polars to handle the CSV file.

Example usage for the YAML API:

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

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

Example usage for the Python API:

 import sys

 import polars as pl
 import pytest
 from kedro_datasets.polars import CSVDataset

 if sys.platform.startswith("win"):
...     pytest.skip("this doctest fails on Windows CI runner")
...
 data = pl.DataFrame({"col1": [1, 2], "col2": [4, 5], "col3": [5, 6]})

 dataset = CSVDataset(filepath=tmp_path / "test.csv")
 dataset.save(data)
 reloaded = dataset.load()
 assert data.equals(reloaded)

Attributes

DEFAULT_FS_ARGS

DEFAULT_LOAD_ARGS

DEFAULT_SAVE_ARGS

Methods

exists()

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

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

Create a dataset 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_FS_ARGS: dict[str, Any] = {'open_args_save': {'mode': 'w'}}
DEFAULT_LOAD_ARGS: dict[str, Any] = {'rechunk': True}
DEFAULT_SAVE_ARGS: dict[str, Any] = {}
__init__(*, filepath, load_args=None, save_args=None, version=None, credentials=None, fs_args=None, metadata=None)[source]

Creates a new instance of CSVDataset pointing to a concrete CSV file on a specific filesystem.

Parameters:

  • filepath (str) – Filepath in POSIX format to a CSV file prefixed with a protocol s3://. If prefix is not provided, file protocol (local filesystem) will be used. The prefix should be any protocol supported by fsspec. Note: http(s) doesn’t support versioning.

  • load_args (Optional[dict[str, Any]]) – Polars options for loading CSV files. Here you can find all available arguments: https://pola-rs.github.io/polars/py-polars/html/reference/api/polars.read_csv.html#polars.read_csv All defaults are preserved, but we explicitly use rechunk=True for seaborn compatibility.

  • save_args (Optional[dict[str, Any]]) – Polars options for saving CSV files. Here you can find all available arguments: https://pola-rs.github.io/polars/py-polars/html/reference/api/polars.DataFrame.write_csv.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). Defaults are preserved, apart from the open_args_save mode which is set to w.

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

exists()

Checks whether a dataset’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 dataset instance using the configuration provided.

Parameters:

  • name (str) – Data set name.

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

  • load_version (Optional[str]) – Version string to be used for load operation if the dataset is versioned. Has no effect on the dataset if versioning was not enabled.

  • save_version (Optional[str]) – Version string to be used for save operation if the dataset is versioned. Has no effect on the dataset if versioning was not enabled.

Return type:

AbstractDataset

Returns:

An instance of an AbstractDataset subclass.

Raises:

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

load()[source]

Loads data by delegation to the provided load method.

Return type:

DataFrame

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:

Optional[str]

resolve_save_version()

Compute the version the dataset should be saved with.

Return type:

Optional[str]

save(data)[source]

Saves data by delegation to the provided save method.

Parameters:

data (DataFrame) – 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