feat(datasets): add pandas.DeltaSharingDataset

kedro-datasets/docs/source/api/kedro_datasets_experimental.rst

@@ -19,3 +19,4 @@ kedro_datasets_experimental
    prophet.ProphetModelDataset
    pytorch.PyTorchDataset
    rioxarray.GeoTIFFDataset
+   pandas.DeltaSharingDataset

kedro-datasets/kedro_datasets_experimental/pandas/__init__.py

@@ -0,0 +1,14 @@
+"""``AbstractDataset`` implementations that produce pandas DataFrames."""
+
+from typing import Any
+
+import lazy_loader as lazy
+
+DeltaSharingDataset: Any
+
+__getattr__, __dir__, __all__ = lazy.attach(
+    __name__,
+    submod_attrs={
+        "delta_sharing_dataset": ["DeltaSharingDataset"],
+    },
+)

kedro-datasets/kedro_datasets_experimental/pandas/delta_sharing_dataset.py

@@ -0,0 +1,157 @@
+from __future__ import annotations
+
+from typing import Any
+
+import delta_sharing
+import pandas as pd
+from kedro.io.core import AbstractDataset, DatasetError
+
+from kedro_datasets._typing import TablePreview
+
+
+class DeltaSharingDataset(AbstractDataset):
+    """``DeltaSharingDataset`` loads data from a Delta Sharing shared table using the Delta Sharing open protocol.
+    This dataset handles loading data into a Pandas DataFrame. Saving to Delta Sharing is not supported.
+
+    Delta Sharing is an open protocol for secure real-time exchange of large datasets, which enables
+    organizations to share data in real time regardless of which computing platforms they use. It is a
+    simple REST protocol that securely shares access to part of a cloud dataset and leverages modern cloud
+    storage systems, such as S3, ADLS, or GCS, to reliably transfer data.
+
+    Example usage for the YAML API:
+
+    .. code-block:: yaml
+
+        my_delta_sharing_dataset:
+          type: pandas.DeltaSharingDataset
+          share: <share-name>
+          schema: <schema-name>
+          table: <table-name>
+          credentials:
+            profile_file: <profile-file-path>
+          load_args:
+            version: <version>
+            limit: <limit>
+            use_delta_format: <use_delta_format>
+
+    Example usage for the Python API:
+
+    .. code-block:: pycon
+
+        >>> from kedro_datasets_experimental.pandas import DeltaSharingDataset
+        >>>
+        >>> credentials = {"profile_file": "conf/local/config.share"}
+        >>> load_args = {"version": 1, "limit": 10, "use_delta_format": True}
+        >>> dataset = DeltaSharingDataset(
+        ...     share="example_share",
+        ...     schema="example_schema",
+        ...     table="example_table",
+        ...     credentials=credentials,
+        ...     load_args=load_args,
+        ... )
+        >>> data = dataset.load()
+        >>> print(data)
+    """
+
+    DEFAULT_LOAD_ARGS: dict[str, Any] = {
+        "version": None,  # Load the latest version by default
+        "limit": None,  # No limit by default
+        "use_delta_format": False  # Default to not using Delta format
+    }
+
+    def __init__( # noqa: PLR0913
+        self,
+        *,
+        share: str,
+        schema: str,
+        table: str,
+        credentials: dict[str, Any],
+        load_args: dict[str, Any] | None = None
+    ) -> None:
+        """Creates a new instance of ``DeltaSharingDataset``.
+
+        Args:
+            share (str): Share name in Delta Sharing.
+            schema (str): Schema name in Delta Sharing.
+            table (str): Table name in Delta Sharing.
+            credentials (dict[str, Any]): Credentials for accessing the Delta Sharing profile. Must include:
+                - `profile_file` (str): Path to the Delta Sharing profile file.
+            load_args (dict[str, Any], optional): Additional options for loading data.
+                - `version` (int, optional): A non-negative integer specifying the version of the table snapshot to load.
+                Defaults to None, which loads the latest version. This parameter allows you to access historical versions of the shared table.
+                - `limit` (int, optional): A non-negative integer specifying the maximum number of rows to load.
+                - `use_delta_format` (bool, optional): Whether to use the Delta format for loading data. Defaults to False.
+
+        Raises:
+            DatasetError: If the profile file is not specified in credentials.
+        """
+        self.share = share
+        self.schema = schema
+        self.table = table
+        self.profile_file = credentials.get("profile_file")
+
+        # Merge the provided load_args with DEFAULT_LOAD_ARGS
+        self._load_args = {**self.DEFAULT_LOAD_ARGS, **(load_args or {})}
+        self.version = self._load_args["version"]
+        self.limit = self._load_args["limit"]
+        self.use_delta_format = self._load_args["use_delta_format"]
+
+        if not self.profile_file:
+            raise DatasetError("Profile file must be specified in credentials.")
+
+        self.table_path = f"{self.share}.{self.schema}.{self.table}"
+        self.table_url = f"{self.profile_file}#{self.table_path}"
+
+    def _load(self) -> pd.DataFrame:
+        """Load data from the Delta Sharing shared table into a Pandas DataFrame.
+
+        Returns:
+            pd.DataFrame: Loaded data.
+        """
+        return delta_sharing.load_as_pandas(
+            self.table_url,
+            version=self.version,
+            limit=self.limit,
+            use_delta_format=self.use_delta_format
+        )
+
+    def _save(self, data: pd.DataFrame) -> None:
+        """Saving to Delta Sharing shared tables is not supported.
+
+        Args:
+            data (pd.DataFrame): Data to save.
+
+        Raises:
+            DatasetError: Saving to Delta Sharing shared tables is not supported.
+        """
+        raise DatasetError("Saving to Delta Sharing shared tables is not supported.")
+
+    def preview(self, nrows: int = 5) -> TablePreview:
+        """Generate a preview of the dataset with a specified number of rows.
+
+        Args:
+            nrows (int, optional): The number of rows to include in the preview. Defaults to 5.
+
+        Returns:
+            TablePreview: A dictionary containing the data in a split format.
+        """
+        dataset_copy = self._copy()
+        dataset_copy.limit = nrows
+        data = dataset_copy._load()
+        return data.to_dict(orient="split")
+
+    def _describe(self) -> dict[str, Any]:
+        """Describe the dataset configuration.
+
+        Returns:
+            dict[str, Any]: Dataset configuration.
+        """
+        return {
+            "share": self.share,
+            "schema": self.schema,
+            "table": self.table,
+            "profile_file": self.profile_file,
+            "version": self.version,
+            "limit": self.limit,
+            "use_delta_format": self.use_delta_format
+        }

kedro-datasets/pyproject.toml

@@ -191,6 +191,7 @@ pytorch = ["kedro-datasets[pytorch-dataset]"]
 rioxarray-geotiffdataset = ["rioxarray>=0.15.0"]
 rioxarray = ["kedro-datasets[rioxarray-geotiffdataset]"]
 
+delta-sharing = ["kedro-datasets[delta-sharing-dataset]"]
 # Docs requirements
 docs = [
     "kedro-sphinx-theme==2024.4.0",
@@ -294,6 +295,7 @@ experimental = [
     "rioxarray",
     "torch",
     "prophet>=1.1.5",
+    "delta-sharing"
 ]
 
 # All requirements