CSVDataset¶
CSVDataset loads and saves data to/from CSV files using Polars.
kedro_datasets.polars.CSVDataset ¶
CSVDataset(
*,
filepath,
load_args=None,
save_args=None,
version=None,
credentials=None,
fs_args=None,
metadata=None
)
Bases: AbstractVersionedDataset[DataFrame, DataFrame]
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.
Examples:
Using 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
Using 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)
Parameters:
-
filepath(str | PathLike) –Filepath as a string or path-like object in POSIX format to a CSV file prefixed with a protocol
s3://. If prefix is not provided,fileprotocol (local filesystem) will be used. The prefix should be any protocol supported byfsspec. Note:http(s)doesn't support versioning. -
load_args(dict[str, Any] | None, default:None) –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=Trueforseaborncompatibility. -
save_args(dict[str, Any] | None, default:None) –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(Version | None, default:None) –If specified, should be an instance of
kedro.io.core.Version. If itsloadattribute is None, the latest version will be loaded. If itssaveattribute is None, save version will be autogenerated. -
credentials(dict[str, Any] | None, default:None) –Credentials required to get access to the underlying filesystem. E.g. for
GCSFileSystemit should look like{"token": None}. -
fs_args(dict[str, Any] | None, default:None) –Extra arguments to pass into underlying filesystem class constructor (e.g.
{"project": "my-project"}forGCSFileSystem). Defaults are preserved, apart from theopen_args_savemodewhich is set tow. -
metadata(dict[str, Any] | None, default:None) –Any arbitrary metadata. This is ignored by Kedro, but may be consumed by users or external plugins.
Source code in kedro_datasets/polars/csv_dataset.py
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DEFAULT_FS_ARGS
class-attribute
instance-attribute
¶
DEFAULT_FS_ARGS = {
"open_args_save": {"mode": "w", "encoding": "utf-8"}
}
_fs_open_args_load
instance-attribute
¶
_fs_open_args_load = {
None: get("open_args_load", {}),
None: _fs_open_args_load or {},
}
_fs_open_args_save
instance-attribute
¶
_fs_open_args_save = {
None: get("open_args_save", {}),
None: _fs_open_args_save or {},
}
_describe ¶
_describe()
Source code in kedro_datasets/polars/csv_dataset.py
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_exists ¶
_exists()
Source code in kedro_datasets/polars/csv_dataset.py
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_invalidate_cache ¶
_invalidate_cache()
Invalidate underlying filesystem caches.
Source code in kedro_datasets/polars/csv_dataset.py
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_release ¶
_release()
Source code in kedro_datasets/polars/csv_dataset.py
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load ¶
load()
Source code in kedro_datasets/polars/csv_dataset.py
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preview ¶
preview(nrows=5)
Generate a preview of the dataset with a specified number of rows.
Parameters:
-
nrows(int, default:5) –The number of rows to include in the preview. Defaults to 5.
Returns:
-
dict–A dictionary containing the data in a split format.
Source code in kedro_datasets/polars/csv_dataset.py
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save ¶
save(data)
Source code in kedro_datasets/polars/csv_dataset.py
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