"""``XMLDataset`` loads/saves data from/to a XML file using an underlying
filesystem (e.g.: local, S3, GCS). It uses pandas to handle the XML file.
"""
import logging
from copy import deepcopy
from io import BytesIO
from pathlib import PurePosixPath
from typing import Any
import fsspec
import pandas as pd
from kedro.io.core import (
PROTOCOL_DELIMITER,
AbstractVersionedDataset,
DatasetError,
Version,
get_filepath_str,
get_protocol_and_path,
)
logger = logging.getLogger(__name__)
[docs]
class XMLDataset(AbstractVersionedDataset[pd.DataFrame, pd.DataFrame]):
"""``XMLDataset`` loads/saves data from/to a XML file using an underlying
filesystem (e.g.: local, S3, GCS). It uses pandas to handle the XML file.
Example usage for the
`Python API <https://kedro.readthedocs.io/en/stable/data/\
advanced_data_catalog_usage.html>`_:
.. code-block:: pycon
>>> from kedro_datasets.pandas import XMLDataset
>>> import pandas as pd
>>>
>>> data = pd.DataFrame({"col1": [1, 2], "col2": [4, 5], "col3": [5, 6]})
>>>
>>> dataset = XMLDataset(filepath=tmp_path / "test.xml")
>>> dataset.save(data)
>>> reloaded = dataset.load()
>>> assert data.equals(reloaded)
"""
DEFAULT_LOAD_ARGS: dict[str, Any] = {}
DEFAULT_SAVE_ARGS: dict[str, Any] = {"index": False}
[docs]
def __init__( # noqa: PLR0913
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,
metadata: dict[str, Any] = None,
) -> None:
"""Creates a new instance of ``XMLDataset`` pointing to a concrete XML file
on a specific filesystem.
Args:
filepath: Filepath in POSIX format to a XML 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.
load_args: Pandas options for loading XML files.
Here you can find all available arguments:
https://pandas.pydata.org/docs/reference/api/pandas.read_xml.html
All defaults are preserved.
save_args: Pandas options for saving XML files.
Here you can find all available arguments:
https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_xml.html
All defaults are preserved, but "index", which is set to False.
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: 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``).
metadata: Any arbitrary metadata.
This is ignored by Kedro, but may be consumed by users or external plugins.
"""
_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)
self.metadata = metadata
super().__init__(
filepath=PurePosixPath(path),
version=version,
exists_function=self._fs.exists,
glob_function=self._fs.glob,
)
# Handle default load and save arguments
self._load_args = deepcopy(self.DEFAULT_LOAD_ARGS)
if load_args is not None:
self._load_args.update(load_args)
self._save_args = deepcopy(self.DEFAULT_SAVE_ARGS)
if save_args is not None:
self._save_args.update(save_args)
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,
"version": self._version,
}
def _load(self) -> 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_xml(load_path, **self._load_args)
load_path = f"{self._protocol}{PROTOCOL_DELIMITER}{load_path}"
return pd.read_xml(
load_path, storage_options=self._storage_options, **self._load_args
)
def _save(self, data: pd.DataFrame) -> None:
save_path = get_filepath_str(self._get_save_path(), self._protocol)
buf = BytesIO()
data.to_xml(path_or_buffer=buf, **self._save_args)
with self._fs.open(save_path, mode="wb") as fs_file:
fs_file.write(buf.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)
