Source code for kedro.extras.datasets.pandas.excel_dataset

"""``ExcelDataSet`` loads/saves data from/to a Excel file using an underlying
filesystem (e.g.: local, S3, GCS). It uses pandas to handle the Excel file.
import logging
from copy import deepcopy
from io import BytesIO
from pathlib import PurePosixPath
from typing import Any, Dict, Union

import fsspec
import pandas as pd

from import (

logger = logging.getLogger(__name__)

# NOTE: kedro.extras.datasets will be removed in Kedro 0.19.0.
# Any contribution to datasets should be made in kedro-datasets
# in kedro-plugins (

[docs]class ExcelDataSet( AbstractVersionedDataSet[ Union[pd.DataFrame, Dict[str, pd.DataFrame]], Union[pd.DataFrame, Dict[str, pd.DataFrame]], ] ): """``ExcelDataSet`` loads/saves data from/to a Excel file using an underlying filesystem (e.g.: local, S3, GCS). It uses pandas to handle the Excel file. Example usage for the `YAML API <\ data_catalog.html#use-the-data-catalog-with-the-yaml-api>`_: .. code-block:: yaml rockets: type: pandas.ExcelDataSet filepath: gcs://your_bucket/rockets.xlsx fs_args: project: my-project credentials: my_gcp_credentials save_args: sheet_name: Sheet1 load_args: sheet_name: Sheet1 shuttles: type: pandas.ExcelDataSet filepath: data/01_raw/shuttles.xlsx Example usage for the `Python API <\ data_catalog.html#use-the-data-catalog-with-the-code-api>`_: :: >>> from kedro.extras.datasets.pandas import ExcelDataSet >>> import pandas as pd >>> >>> data = pd.DataFrame({'col1': [1, 2], 'col2': [4, 5], >>> 'col3': [5, 6]}) >>> >>> data_set = ExcelDataSet(filepath="test.xlsx") >>> >>> reloaded = data_set.load() >>> assert data.equals(reloaded) To save a multi-sheet Excel file, no special ``save_args`` are required. Instead, return a dictionary of ``Dict[str, pd.DataFrame]`` where the string keys are your sheet names. Example usage for the `YAML API <\ data_catalog.html#use-the-data-catalog-with-the-yaml-api>`_ for a multi-sheet Excel file: .. code-block:: yaml trains: type: pandas.ExcelDataSet filepath: data/02_intermediate/company/trains.xlsx load_args: sheet_name: [Sheet1, Sheet2, Sheet3] Example usage for the `Python API <\ data_catalog.html#use-the-data-catalog-with-the-code-api>`_ for a multi-sheet Excel file: :: >>> from kedro.extras.datasets.pandas import ExcelDataSet >>> import pandas as pd >>> >>> dataframe = pd.DataFrame({'col1': [1, 2], 'col2': [4, 5], >>> 'col3': [5, 6]}) >>> another_dataframe = pd.DataFrame({"x": [10, 20], "y": ["hello", "world"]}) >>> multiframe = {"Sheet1": dataframe, "Sheet2": another_dataframe} >>> data_set = ExcelDataSet(filepath="test.xlsx", load_args = {"sheet_name": None}) >>> >>> reloaded = data_set.load() >>> assert multiframe["Sheet1"].equals(reloaded["Sheet1"]) >>> assert multiframe["Sheet2"].equals(reloaded["Sheet2"]) """ DEFAULT_LOAD_ARGS = {"engine": "openpyxl"} DEFAULT_SAVE_ARGS = {"index": False} # pylint: disable=too-many-arguments
[docs] def __init__( self, filepath: str, engine: str = "openpyxl", 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, ) -> None: """Creates a new instance of ``ExcelDataSet`` pointing to a concrete Excel file on a specific filesystem. Args: filepath: Filepath in POSIX format to a Excel 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. engine: The engine used to write to Excel files. The default engine is 'openpyxl'. load_args: Pandas options for loading Excel files. Here you can find all available arguments: All defaults are preserved, but "engine", which is set to "openpyxl". Supports multi-sheet Excel files (include `sheet_name = None` in `load_args`). save_args: Pandas options for saving Excel files. Here you can find all available arguments: All defaults are preserved, but "index", which is set to False. If you would like to specify options for the `ExcelWriter`, you can include them under the "writer" key. Here you can find all available arguments: version: If specified, should be an instance of ````. If its ``load`` attribute is None, the latest version will be loaded. If its ``save`` attribute is None, save version will be autogenerated. credentials: Credentials required to get access to the underlying filesystem. E.g. for ``GCSFileSystem`` it should look like `{"token": None}`. fs_args: Extra arguments to pass into underlying filesystem class constructor (e.g. `{"project": "my-project"}` for ``GCSFileSystem``). Raises: DataSetError: If versioning is enabled while in append mode. """ _fs_args = deepcopy(fs_args) or {} _credentials = deepcopy(credentials) or {} protocol, path = get_protocol_and_path(filepath, version) if protocol == "file": _fs_args.setdefault("auto_mkdir", True) self._protocol = protocol self._storage_options = {**_credentials, **_fs_args} self._fs = fsspec.filesystem(self._protocol, **self._storage_options) super().__init__( filepath=PurePosixPath(path), version=version, exists_function=self._fs.exists, glob_function=self._fs.glob, ) # Handle default load arguments self._load_args = deepcopy(self.DEFAULT_LOAD_ARGS) if load_args is not None: self._load_args.update(load_args) # Handle default save arguments self._save_args = deepcopy(self.DEFAULT_SAVE_ARGS) if save_args is not None: self._save_args.update(save_args) self._writer_args = self._save_args.pop("writer", {}) # type: ignore self._writer_args.setdefault("engine", engine or "openpyxl") # type: ignore if version and self._writer_args.get("mode") == "a": # type: ignore raise DataSetError( "'ExcelDataSet' doesn't support versioning in append mode." ) if "storage_options" in self._save_args or "storage_options" in self._load_args: logger.warning( "Dropping 'storage_options' for %s, " "please specify them under 'fs_args' or 'credentials'.", self._filepath, ) self._save_args.pop("storage_options", None) self._load_args.pop("storage_options", None)
def _describe(self) -> Dict[str, Any]: return { "filepath": self._filepath, "protocol": self._protocol, "load_args": self._load_args, "save_args": self._save_args, "writer_args": self._writer_args, "version": self._version, } def _load(self) -> Union[pd.DataFrame, Dict[str, pd.DataFrame]]: load_path = str(self._get_load_path()) if self._protocol == "file": # file:// protocol seems to misbehave on Windows # (<urlopen error file not on local host>), # so we don't join that back to the filepath; # storage_options also don't work with local paths return pd.read_excel(load_path, **self._load_args) load_path = f"{self._protocol}{PROTOCOL_DELIMITER}{load_path}" return pd.read_excel( load_path, storage_options=self._storage_options, **self._load_args ) def _save(self, data: Union[pd.DataFrame, Dict[str, pd.DataFrame]]) -> None: output = BytesIO() save_path = get_filepath_str(self._get_save_path(), self._protocol) # pylint: disable=abstract-class-instantiated with pd.ExcelWriter(output, **self._writer_args) as writer: if isinstance(data, dict): for sheet_name, sheet_data in data.items(): sheet_data.to_excel( writer, sheet_name=sheet_name, **self._save_args ) else: data.to_excel(writer, **self._save_args) with, mode="wb") as fs_file: fs_file.write(output.getvalue()) self._invalidate_cache() def _exists(self) -> bool: try: load_path = get_filepath_str(self._get_load_path(), self._protocol) except DataSetError: return False return self._fs.exists(load_path) def _release(self) -> None: super()._release() self._invalidate_cache() def _invalidate_cache(self) -> None: """Invalidate underlying filesystem caches.""" filepath = get_filepath_str(self._filepath, self._protocol) self._fs.invalidate_cache(filepath)