kedro_datasets.geopandas.GenericDataset

class kedro_datasets.geopandas.GenericDataset(*, filepath, file_format='file', load_args=None, save_args=None, version=None, credentials=None, fs_args=None, metadata=None)[source]

GenericDataset loads/saves data to a file using an underlying filesystem (eg: local, S3, GCS). The underlying functionality is supported by geopandas, so it supports all allowed geopandas (pandas) options for loading and saving files.

Example:

 import geopandas as gpd
 from kedro_datasets.geopandas import GenericDataset
 from shapely.geometry import Point

 data = gpd.GeoDataFrame(
...     {"col1": [1, 2], "col2": [4, 5], "col3": [5, 6]},
...     geometry=[Point(1, 1), Point(2, 4)],
... )
 dataset = GenericDataset(filepath=tmp_path / "test.geojson")
 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.

invalidate_cache()

Invalidate underlying filesystem cache.

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': 'wb'}}
DEFAULT_LOAD_ARGS: dict[str, Any] = {}
DEFAULT_SAVE_ARGS: dict[str, Any] = {}
__init__(*, filepath, file_format='file', load_args=None, save_args=None, version=None, credentials=None, fs_args=None, metadata=None)[source]

Creates a new instance of GenericDataset pointing to a concrete file on a specific filesystem fsspec.

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. Note: http(s) doesn’t support versioning.

  • file_format (str) – String which is used to match the appropriate load/save method on a best effort basis. For example if ‘parquet’ is passed in the geopandas.read_parquet and geopandas.DataFrame.to_parquet will be identified. An error will be raised unless at least one matching read_{file_format} or to_{file_format} method is identified. Defaults to ‘file’.

  • load_args (Optional[dict[str, Any]]) – GeoPandas options for loading files. Here you can find all available arguments: https://geopandas.org/en/stable/docs/reference/api/geopandas.read_file.html

  • save_args (Optional[dict[str, Any]]) – GeoPandas options for saving files. Here you can find all available arguments: https://geopandas.org/en/stable/docs/reference/api/geopandas.GeoDataFrame.to_file.html

  • 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

  • credentials (Optional[dict[str, Any]]) – credentials required to access the underlying filesystem. Eg. for GCFileSystem it would 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 wb when saving.

  • 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.

invalidate_cache()[source]

Invalidate underlying filesystem cache.

Return type:

None

load()[source]

Loads data by delegation to the provided load method.

Return type:

GeoDataFrame | dict[str, GeoDataFrame]

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 (GeoDataFrame) – 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