class documentation
class FeatherDataSet(AbstractVersionedDataSet[
FeatherDataSet loads and saves data to a feather file using an underlying filesystem (e.g.: local, S3, GCS). The underlying functionality is supported by pandas, so it supports all allowed pandas options for loading and saving csv files.
Example usage for the YAML API:
cars: type: pandas.FeatherDataSet filepath: data/01_raw/company/cars.feather load_args: columns: ['col1', 'col2', 'col3'] use_threads: True motorbikes: type: pandas.FeatherDataSet filepath: s3://your_bucket/data/02_intermediate/company/motorbikes.feather credentials: dev_s3
Example usage for the Python API:
>>> from kedro.extras.datasets.pandas import FeatherDataSet >>> import pandas as pd >>> >>> data = pd.DataFrame({'col1': [1, 2], 'col2': [4, 5], >>> 'col3': [5, 6]}) >>> >>> data_set = FeatherDataSet(filepath="test.feather") >>> >>> data_set.save(data) >>> reloaded = data_set.load() >>> >>> assert data.equals(reloaded)
Method | __init__ |
Creates a new instance of FeatherDataSet pointing to a concrete filepath. |
Constant | DEFAULT |
Undocumented |
Constant | DEFAULT |
Undocumented |
Method | _describe |
Undocumented |
Method | _exists |
Undocumented |
Method | _invalidate |
Invalidate underlying filesystem caches. |
Method | _load |
Undocumented |
Method | _release |
Undocumented |
Method | _save |
Undocumented |
Instance Variable | _fs |
Undocumented |
Instance Variable | _load |
Undocumented |
Instance Variable | _protocol |
Undocumented |
Instance Variable | _save |
Undocumented |
Instance Variable | _storage |
Undocumented |
Inherited from AbstractVersionedDataSet
:
Method | exists |
Checks whether a data set's output already exists by calling the provided _exists() method. |
Method | load |
Loads data by delegation to the provided load method. |
Method | resolve |
Compute the version the dataset should be loaded with. |
Method | resolve |
Compute the version the dataset should be saved with. |
Method | save |
Saves data by delegation to the provided save method. |
Method | _fetch |
Undocumented |
Method | _fetch |
Generate and cache the current save version |
Method | _get |
Undocumented |
Method | _get |
Undocumented |
Method | _get |
Undocumented |
Instance Variable | _exists |
Undocumented |
Instance Variable | _filepath |
Undocumented |
Instance Variable | _glob |
Undocumented |
Instance Variable | _version |
Undocumented |
Instance Variable | _version |
Undocumented |
Inherited from AbstractDataSet
(via AbstractVersionedDataSet
):
Class Method | from |
Create a data set instance using the configuration provided. |
Method | __str__ |
Undocumented |
Method | release |
Release any cached data. |
Method | _copy |
Undocumented |
Property | _logger |
Undocumented |
def __init__(self, filepath:
str
, load_args: Dict[ str, Any]
= None, save_args: Dict[ str, Any]
= None, version: Version
= None, credentials: Dict[ str, Any]
= None, fs_args: Dict[ str, Any]
= None):
(source)
¶
Creates a new instance of FeatherDataSet pointing to a concrete filepath.
Parameters | |
filepath:str | Filepath in POSIX format to a feather 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.
Note: http(s) doesn't support versioning. |
loadDict[ | Pandas options for loading feather files. Here you can find all available arguments: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_feather.html All defaults are preserved. |
saveDict[ | Pandas options for saving feather files. Here you can find all available arguments: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_feather.html All defaults are preserved. |
version: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:Dict[ | Credentials required to get access to the underlying filesystem.
E.g. for GCSFileSystem it should look like {"token": None} . |
fsDict[ | Extra arguments to pass into underlying filesystem class constructor
(e.g. {"project": "my-project"} for GCSFileSystem). |