1105 行
35 KiB
Python
1105 行
35 KiB
Python
"""
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:mod:`pandas.io.xml` is a module for reading XML.
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"""
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from __future__ import annotations
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import io
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from typing import (
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Any,
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Callable,
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Sequence,
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)
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from pandas._typing import (
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TYPE_CHECKING,
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CompressionOptions,
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ConvertersArg,
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DtypeArg,
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FilePath,
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ParseDatesArg,
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ReadBuffer,
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StorageOptions,
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XMLParsers,
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)
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from pandas.compat._optional import import_optional_dependency
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from pandas.errors import (
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AbstractMethodError,
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ParserError,
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)
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from pandas.util._decorators import (
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deprecate_nonkeyword_arguments,
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doc,
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)
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from pandas.core.dtypes.common import is_list_like
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from pandas.core.shared_docs import _shared_docs
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from pandas.io.common import (
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file_exists,
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get_handle,
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infer_compression,
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is_fsspec_url,
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is_url,
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stringify_path,
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)
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from pandas.io.parsers import TextParser
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if TYPE_CHECKING:
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from xml.etree.ElementTree import Element
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from lxml.etree import (
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_Element,
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_XSLTResultTree,
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)
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from pandas import DataFrame
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@doc(
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storage_options=_shared_docs["storage_options"],
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decompression_options=_shared_docs["decompression_options"] % "path_or_buffer",
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)
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class _XMLFrameParser:
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"""
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Internal subclass to parse XML into DataFrames.
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Parameters
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----------
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path_or_buffer : a valid JSON str, path object or file-like object
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Any valid string path is acceptable. The string could be a URL. Valid
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URL schemes include http, ftp, s3, and file.
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xpath : str or regex
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The XPath expression to parse required set of nodes for
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migration to `Data Frame`. `etree` supports limited XPath.
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namespaces : dict
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The namespaces defined in XML document (`xmlns:namespace='URI')
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as dicts with key being namespace and value the URI.
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elems_only : bool
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Parse only the child elements at the specified `xpath`.
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attrs_only : bool
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Parse only the attributes at the specified `xpath`.
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names : list
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Column names for Data Frame of parsed XML data.
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dtype : dict
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Data type for data or columns. E.g. {{'a': np.float64,
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'b': np.int32, 'c': 'Int64'}}
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.. versionadded:: 1.5.0
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converters : dict, optional
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Dict of functions for converting values in certain columns. Keys can
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either be integers or column labels.
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.. versionadded:: 1.5.0
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parse_dates : bool or list of int or names or list of lists or dict
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Converts either index or select columns to datetimes
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.. versionadded:: 1.5.0
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encoding : str
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Encoding of xml object or document.
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stylesheet : str or file-like
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URL, file, file-like object, or a raw string containing XSLT,
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`etree` does not support XSLT but retained for consistency.
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iterparse : dict, optional
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Dict with row element as key and list of descendant elements
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and/or attributes as value to be retrieved in iterparsing of
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XML document.
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.. versionadded:: 1.5.0
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{decompression_options}
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.. versionchanged:: 1.4.0 Zstandard support.
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{storage_options}
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See also
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--------
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pandas.io.xml._EtreeFrameParser
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pandas.io.xml._LxmlFrameParser
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Notes
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-----
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To subclass this class effectively you must override the following methods:`
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* :func:`parse_data`
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* :func:`_parse_nodes`
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* :func:`_iterparse_nodes`
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* :func:`_parse_doc`
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* :func:`_validate_names`
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* :func:`_validate_path`
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See each method's respective documentation for details on their
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functionality.
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"""
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def __init__(
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self,
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path_or_buffer: FilePath | ReadBuffer[bytes] | ReadBuffer[str],
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xpath: str,
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namespaces: dict[str, str] | None,
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elems_only: bool,
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attrs_only: bool,
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names: Sequence[str] | None,
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dtype: DtypeArg | None,
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converters: ConvertersArg | None,
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parse_dates: ParseDatesArg | None,
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encoding: str | None,
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stylesheet: FilePath | ReadBuffer[bytes] | ReadBuffer[str] | None,
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iterparse: dict[str, list[str]] | None,
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compression: CompressionOptions,
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storage_options: StorageOptions,
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) -> None:
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self.path_or_buffer = path_or_buffer
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self.xpath = xpath
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self.namespaces = namespaces
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self.elems_only = elems_only
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self.attrs_only = attrs_only
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self.names = names
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self.dtype = dtype
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self.converters = converters
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self.parse_dates = parse_dates
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self.encoding = encoding
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self.stylesheet = stylesheet
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self.iterparse = iterparse
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self.is_style = None
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self.compression = compression
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self.storage_options = storage_options
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def parse_data(self) -> list[dict[str, str | None]]:
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"""
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Parse xml data.
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This method will call the other internal methods to
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validate xpath, names, parse and return specific nodes.
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"""
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raise AbstractMethodError(self)
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def _parse_nodes(self, elems: list[Any]) -> list[dict[str, str | None]]:
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"""
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Parse xml nodes.
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This method will parse the children and attributes of elements
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in xpath, conditionally for only elements, only attributes
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or both while optionally renaming node names.
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Raises
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------
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ValueError
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* If only elements and only attributes are specified.
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Notes
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-----
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Namespace URIs will be removed from return node values. Also,
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elements with missing children or attributes compared to siblings
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will have optional keys filled with None values.
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"""
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dicts: list[dict[str, str | None]]
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if self.elems_only and self.attrs_only:
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raise ValueError("Either element or attributes can be parsed not both.")
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elif self.elems_only:
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if self.names:
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dicts = [
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{
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**(
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{el.tag: el.text.strip()}
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if el.text and not el.text.isspace()
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else {}
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),
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**{
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nm: ch.text.strip() if ch.text else None
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for nm, ch in zip(self.names, el.findall("*"))
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},
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}
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for el in elems
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]
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else:
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dicts = [
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{
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ch.tag: ch.text.strip() if ch.text else None
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for ch in el.findall("*")
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}
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for el in elems
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]
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elif self.attrs_only:
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dicts = [
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{k: v.strip() if v else None for k, v in el.attrib.items()}
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for el in elems
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]
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else:
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if self.names:
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dicts = [
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{
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**el.attrib,
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**(
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{el.tag: el.text.strip()}
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if el.text and not el.text.isspace()
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else {}
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),
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**{
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nm: ch.text.strip() if ch.text else None
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for nm, ch in zip(self.names, el.findall("*"))
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},
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}
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for el in elems
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]
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else:
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dicts = [
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{
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**el.attrib,
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**(
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{el.tag: el.text.strip()}
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if el.text and not el.text.isspace()
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else {}
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),
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**{
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ch.tag: ch.text.strip() if ch.text else None
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for ch in el.findall("*")
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},
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}
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for el in elems
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]
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dicts = [
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{k.split("}")[1] if "}" in k else k: v for k, v in d.items()} for d in dicts
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]
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keys = list(dict.fromkeys([k for d in dicts for k in d.keys()]))
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dicts = [{k: d[k] if k in d.keys() else None for k in keys} for d in dicts]
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if self.names:
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dicts = [{nm: v for nm, v in zip(self.names, d.values())} for d in dicts]
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return dicts
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def _iterparse_nodes(self, iterparse: Callable) -> list[dict[str, str | None]]:
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"""
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Iterparse xml nodes.
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This method will read in local disk, decompressed XML files for elements
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and underlying descendants using iterparse, a method to iterate through
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an XML tree without holding entire XML tree in memory.
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Raises
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------
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TypeError
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* If `iterparse` is not a dict or its dict value is not list-like.
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ParserError
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* If `path_or_buffer` is not a physical, decompressed file on disk.
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* If no data is returned from selected items in `iterparse`.
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Notes
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-----
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Namespace URIs will be removed from return node values. Also,
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elements with missing children or attributes in submitted list
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will have optional keys filled with None values.
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"""
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dicts: list[dict[str, str | None]] = []
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row: dict[str, str | None] | None = None
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if not isinstance(self.iterparse, dict):
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raise TypeError(
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f"{type(self.iterparse).__name__} is not a valid type for iterparse"
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)
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row_node = next(iter(self.iterparse.keys())) if self.iterparse else ""
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if not is_list_like(self.iterparse[row_node]):
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raise TypeError(
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f"{type(self.iterparse[row_node])} is not a valid type "
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"for value in iterparse"
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)
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if (
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not isinstance(self.path_or_buffer, str)
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or is_url(self.path_or_buffer)
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or is_fsspec_url(self.path_or_buffer)
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or self.path_or_buffer.startswith(("<?xml", "<"))
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or infer_compression(self.path_or_buffer, "infer") is not None
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):
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raise ParserError(
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"iterparse is designed for large XML files that are fully extracted on "
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"local disk and not as compressed files or online sources."
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)
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for event, elem in iterparse(self.path_or_buffer, events=("start", "end")):
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curr_elem = elem.tag.split("}")[1] if "}" in elem.tag else elem.tag
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if event == "start":
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if curr_elem == row_node:
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row = {}
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if row is not None:
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if self.names:
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for col, nm in zip(self.iterparse[row_node], self.names):
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if curr_elem == col:
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elem_val = elem.text.strip() if elem.text else None
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if row.get(nm) != elem_val and nm not in row:
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row[nm] = elem_val
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if col in elem.attrib:
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if elem.attrib[col] not in row.values() and nm not in row:
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row[nm] = elem.attrib[col]
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else:
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for col in self.iterparse[row_node]:
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if curr_elem == col:
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row[col] = elem.text.strip() if elem.text else None
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if col in elem.attrib:
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row[col] = elem.attrib[col]
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if event == "end":
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if curr_elem == row_node and row is not None:
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dicts.append(row)
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row = None
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elem.clear()
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if hasattr(elem, "getprevious"):
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while (
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elem.getprevious() is not None and elem.getparent() is not None
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):
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del elem.getparent()[0]
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if dicts == []:
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raise ParserError("No result from selected items in iterparse.")
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keys = list(dict.fromkeys([k for d in dicts for k in d.keys()]))
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dicts = [{k: d[k] if k in d.keys() else None for k in keys} for d in dicts]
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if self.names:
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dicts = [{nm: v for nm, v in zip(self.names, d.values())} for d in dicts]
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return dicts
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def _validate_path(self) -> None:
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"""
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Validate xpath.
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This method checks for syntax, evaluation, or empty nodes return.
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Raises
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------
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SyntaxError
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* If xpah is not supported or issues with namespaces.
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ValueError
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* If xpah does not return any nodes.
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"""
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raise AbstractMethodError(self)
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def _validate_names(self) -> None:
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"""
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Validate names.
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This method will check if names is a list-like and aligns
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with length of parse nodes.
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Raises
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------
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ValueError
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* If value is not a list and less then length of nodes.
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"""
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raise AbstractMethodError(self)
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def _parse_doc(
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self, raw_doc: FilePath | ReadBuffer[bytes] | ReadBuffer[str]
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) -> Element | _Element:
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"""
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Build tree from path_or_buffer.
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This method will parse XML object into tree
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either from string/bytes or file location.
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"""
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raise AbstractMethodError(self)
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class _EtreeFrameParser(_XMLFrameParser):
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"""
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Internal class to parse XML into DataFrames with the Python
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standard library XML module: `xml.etree.ElementTree`.
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"""
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def parse_data(self) -> list[dict[str, str | None]]:
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from xml.etree.ElementTree import iterparse
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if self.stylesheet is not None:
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raise ValueError(
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"To use stylesheet, you need lxml installed and selected as parser."
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)
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if self.iterparse is None:
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self.xml_doc = self._parse_doc(self.path_or_buffer)
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self._validate_path()
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elems = self.xml_doc.findall(self.xpath, namespaces=self.namespaces)
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self._validate_names()
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xml_dicts: list[dict[str, str | None]] = (
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self._parse_nodes(elems)
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if self.iterparse is None
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else self._iterparse_nodes(iterparse)
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)
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return xml_dicts
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def _validate_path(self) -> None:
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"""
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Notes
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-----
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`etree` supports limited XPath. If user attempts a more complex
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expression syntax error will raise.
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"""
|
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msg = (
|
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"xpath does not return any nodes. "
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"If document uses namespaces denoted with "
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"xmlns, be sure to define namespaces and "
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"use them in xpath."
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)
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try:
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elems = self.xml_doc.find(self.xpath, namespaces=self.namespaces)
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if elems is None:
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raise ValueError(msg)
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if elems is not None and elems.find("*") is None and elems.attrib is None:
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raise ValueError(msg)
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except (KeyError, SyntaxError):
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raise SyntaxError(
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"You have used an incorrect or unsupported XPath "
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"expression for etree library or you used an "
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"undeclared namespace prefix."
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)
|
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def _validate_names(self) -> None:
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children: list[Any]
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|
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if self.names:
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if self.iterparse:
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children = self.iterparse[next(iter(self.iterparse))]
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else:
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parent = self.xml_doc.find(self.xpath, namespaces=self.namespaces)
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children = parent.findall("*") if parent else []
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|
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if is_list_like(self.names):
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if len(self.names) < len(children):
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raise ValueError(
|
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"names does not match length of child elements in xpath."
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)
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else:
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raise TypeError(
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f"{type(self.names).__name__} is not a valid type for names"
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)
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def _parse_doc(
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self, raw_doc: FilePath | ReadBuffer[bytes] | ReadBuffer[str]
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) -> Element:
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from xml.etree.ElementTree import (
|
|
XMLParser,
|
|
parse,
|
|
)
|
|
|
|
handle_data = get_data_from_filepath(
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filepath_or_buffer=raw_doc,
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encoding=self.encoding,
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compression=self.compression,
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storage_options=self.storage_options,
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)
|
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with preprocess_data(handle_data) as xml_data:
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curr_parser = XMLParser(encoding=self.encoding)
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doc = parse(xml_data, parser=curr_parser)
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return doc.getroot()
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|
|
|
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class _LxmlFrameParser(_XMLFrameParser):
|
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"""
|
|
Internal class to parse XML into DataFrames with third-party
|
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full-featured XML library, `lxml`, that supports
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XPath 1.0 and XSLT 1.0.
|
|
"""
|
|
|
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def parse_data(self) -> list[dict[str, str | None]]:
|
|
"""
|
|
Parse xml data.
|
|
|
|
This method will call the other internal methods to
|
|
validate xpath, names, optionally parse and run XSLT,
|
|
and parse original or transformed XML and return specific nodes.
|
|
"""
|
|
from lxml.etree import iterparse
|
|
|
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if self.iterparse is None:
|
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self.xml_doc = self._parse_doc(self.path_or_buffer)
|
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|
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if self.stylesheet:
|
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self.xsl_doc = self._parse_doc(self.stylesheet)
|
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self.xml_doc = self._transform_doc()
|
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|
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self._validate_path()
|
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elems = self.xml_doc.xpath(self.xpath, namespaces=self.namespaces)
|
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|
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self._validate_names()
|
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|
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xml_dicts: list[dict[str, str | None]] = (
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self._parse_nodes(elems)
|
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if self.iterparse is None
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else self._iterparse_nodes(iterparse)
|
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)
|
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|
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return xml_dicts
|
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|
|
def _validate_path(self) -> None:
|
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|
|
msg = (
|
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"xpath does not return any nodes. "
|
|
"Be sure row level nodes are in xpath. "
|
|
"If document uses namespaces denoted with "
|
|
"xmlns, be sure to define namespaces and "
|
|
"use them in xpath."
|
|
)
|
|
|
|
elems = self.xml_doc.xpath(self.xpath, namespaces=self.namespaces)
|
|
children = self.xml_doc.xpath(self.xpath + "/*", namespaces=self.namespaces)
|
|
attrs = self.xml_doc.xpath(self.xpath + "/@*", namespaces=self.namespaces)
|
|
|
|
if elems == []:
|
|
raise ValueError(msg)
|
|
|
|
if elems != [] and attrs == [] and children == []:
|
|
raise ValueError(msg)
|
|
|
|
def _validate_names(self) -> None:
|
|
children: list[Any]
|
|
|
|
if self.names:
|
|
if self.iterparse:
|
|
children = self.iterparse[next(iter(self.iterparse))]
|
|
else:
|
|
children = self.xml_doc.xpath(
|
|
self.xpath + "[1]/*", namespaces=self.namespaces
|
|
)
|
|
|
|
if is_list_like(self.names):
|
|
if len(self.names) < len(children):
|
|
raise ValueError(
|
|
"names does not match length of child elements in xpath."
|
|
)
|
|
else:
|
|
raise TypeError(
|
|
f"{type(self.names).__name__} is not a valid type for names"
|
|
)
|
|
|
|
def _parse_doc(
|
|
self, raw_doc: FilePath | ReadBuffer[bytes] | ReadBuffer[str]
|
|
) -> _Element:
|
|
from lxml.etree import (
|
|
XMLParser,
|
|
fromstring,
|
|
parse,
|
|
)
|
|
|
|
handle_data = get_data_from_filepath(
|
|
filepath_or_buffer=raw_doc,
|
|
encoding=self.encoding,
|
|
compression=self.compression,
|
|
storage_options=self.storage_options,
|
|
)
|
|
|
|
with preprocess_data(handle_data) as xml_data:
|
|
curr_parser = XMLParser(encoding=self.encoding)
|
|
|
|
if isinstance(xml_data, io.StringIO):
|
|
if self.encoding is None:
|
|
raise TypeError(
|
|
"Can not pass encoding None when input is StringIO."
|
|
)
|
|
|
|
doc = fromstring(
|
|
xml_data.getvalue().encode(self.encoding), parser=curr_parser
|
|
)
|
|
else:
|
|
doc = parse(xml_data, parser=curr_parser)
|
|
|
|
return doc
|
|
|
|
def _transform_doc(self) -> _XSLTResultTree:
|
|
"""
|
|
Transform original tree using stylesheet.
|
|
|
|
This method will transform original xml using XSLT script into
|
|
am ideally flatter xml document for easier parsing and migration
|
|
to Data Frame.
|
|
"""
|
|
from lxml.etree import XSLT
|
|
|
|
transformer = XSLT(self.xsl_doc)
|
|
new_doc = transformer(self.xml_doc)
|
|
|
|
return new_doc
|
|
|
|
|
|
def get_data_from_filepath(
|
|
filepath_or_buffer: FilePath | bytes | ReadBuffer[bytes] | ReadBuffer[str],
|
|
encoding: str | None,
|
|
compression: CompressionOptions,
|
|
storage_options: StorageOptions,
|
|
) -> str | bytes | ReadBuffer[bytes] | ReadBuffer[str]:
|
|
"""
|
|
Extract raw XML data.
|
|
|
|
The method accepts three input types:
|
|
1. filepath (string-like)
|
|
2. file-like object (e.g. open file object, StringIO)
|
|
3. XML string or bytes
|
|
|
|
This method turns (1) into (2) to simplify the rest of the processing.
|
|
It returns input types (2) and (3) unchanged.
|
|
"""
|
|
if not isinstance(filepath_or_buffer, bytes):
|
|
filepath_or_buffer = stringify_path(filepath_or_buffer)
|
|
|
|
if (
|
|
isinstance(filepath_or_buffer, str)
|
|
and not filepath_or_buffer.startswith(("<?xml", "<"))
|
|
) and (
|
|
not isinstance(filepath_or_buffer, str)
|
|
or is_url(filepath_or_buffer)
|
|
or is_fsspec_url(filepath_or_buffer)
|
|
or file_exists(filepath_or_buffer)
|
|
):
|
|
with get_handle(
|
|
filepath_or_buffer,
|
|
"r",
|
|
encoding=encoding,
|
|
compression=compression,
|
|
storage_options=storage_options,
|
|
) as handle_obj:
|
|
filepath_or_buffer = (
|
|
# error: Incompatible types in assignment (expression has type
|
|
# "Union[str, IO[str]]", variable has type "Union[Union[str,
|
|
# PathLike[str]], bytes, ReadBuffer[bytes], ReadBuffer[str]]")
|
|
handle_obj.handle.read() # type: ignore[assignment]
|
|
if hasattr(handle_obj.handle, "read")
|
|
else handle_obj.handle
|
|
)
|
|
|
|
return filepath_or_buffer
|
|
|
|
|
|
def preprocess_data(data) -> io.StringIO | io.BytesIO:
|
|
"""
|
|
Convert extracted raw data.
|
|
|
|
This method will return underlying data of extracted XML content.
|
|
The data either has a `read` attribute (e.g. a file object or a
|
|
StringIO/BytesIO) or is a string or bytes that is an XML document.
|
|
"""
|
|
|
|
if isinstance(data, str):
|
|
data = io.StringIO(data)
|
|
|
|
elif isinstance(data, bytes):
|
|
data = io.BytesIO(data)
|
|
|
|
return data
|
|
|
|
|
|
def _data_to_frame(data, **kwargs) -> DataFrame:
|
|
"""
|
|
Convert parsed data to Data Frame.
|
|
|
|
This method will bind xml dictionary data of keys and values
|
|
into named columns of Data Frame using the built-in TextParser
|
|
class that build Data Frame and infers specific dtypes.
|
|
"""
|
|
|
|
tags = next(iter(data))
|
|
nodes = [list(d.values()) for d in data]
|
|
|
|
try:
|
|
with TextParser(nodes, names=tags, **kwargs) as tp:
|
|
return tp.read()
|
|
except ParserError:
|
|
raise ParserError(
|
|
"XML document may be too complex for import. "
|
|
"Try to flatten document and use distinct "
|
|
"element and attribute names."
|
|
)
|
|
|
|
|
|
def _parse(
|
|
path_or_buffer: FilePath | ReadBuffer[bytes] | ReadBuffer[str],
|
|
xpath: str,
|
|
namespaces: dict[str, str] | None,
|
|
elems_only: bool,
|
|
attrs_only: bool,
|
|
names: Sequence[str] | None,
|
|
dtype: DtypeArg | None,
|
|
converters: ConvertersArg | None,
|
|
parse_dates: ParseDatesArg | None,
|
|
encoding: str | None,
|
|
parser: XMLParsers,
|
|
stylesheet: FilePath | ReadBuffer[bytes] | ReadBuffer[str] | None,
|
|
iterparse: dict[str, list[str]] | None,
|
|
compression: CompressionOptions,
|
|
storage_options: StorageOptions,
|
|
**kwargs,
|
|
) -> DataFrame:
|
|
"""
|
|
Call internal parsers.
|
|
|
|
This method will conditionally call internal parsers:
|
|
LxmlFrameParser and/or EtreeParser.
|
|
|
|
Raises
|
|
------
|
|
ImportError
|
|
* If lxml is not installed if selected as parser.
|
|
|
|
ValueError
|
|
* If parser is not lxml or etree.
|
|
"""
|
|
|
|
p: _EtreeFrameParser | _LxmlFrameParser
|
|
|
|
if parser == "lxml":
|
|
lxml = import_optional_dependency("lxml.etree", errors="ignore")
|
|
|
|
if lxml is not None:
|
|
p = _LxmlFrameParser(
|
|
path_or_buffer,
|
|
xpath,
|
|
namespaces,
|
|
elems_only,
|
|
attrs_only,
|
|
names,
|
|
dtype,
|
|
converters,
|
|
parse_dates,
|
|
encoding,
|
|
stylesheet,
|
|
iterparse,
|
|
compression,
|
|
storage_options,
|
|
)
|
|
else:
|
|
raise ImportError("lxml not found, please install or use the etree parser.")
|
|
|
|
elif parser == "etree":
|
|
p = _EtreeFrameParser(
|
|
path_or_buffer,
|
|
xpath,
|
|
namespaces,
|
|
elems_only,
|
|
attrs_only,
|
|
names,
|
|
dtype,
|
|
converters,
|
|
parse_dates,
|
|
encoding,
|
|
stylesheet,
|
|
iterparse,
|
|
compression,
|
|
storage_options,
|
|
)
|
|
else:
|
|
raise ValueError("Values for parser can only be lxml or etree.")
|
|
|
|
data_dicts = p.parse_data()
|
|
|
|
return _data_to_frame(
|
|
data=data_dicts,
|
|
dtype=dtype,
|
|
converters=converters,
|
|
parse_dates=parse_dates,
|
|
**kwargs,
|
|
)
|
|
|
|
|
|
@deprecate_nonkeyword_arguments(version=None, allowed_args=["path_or_buffer"])
|
|
@doc(
|
|
storage_options=_shared_docs["storage_options"],
|
|
decompression_options=_shared_docs["decompression_options"] % "path_or_buffer",
|
|
)
|
|
def read_xml(
|
|
path_or_buffer: FilePath | ReadBuffer[bytes] | ReadBuffer[str],
|
|
xpath: str = "./*",
|
|
namespaces: dict[str, str] | None = None,
|
|
elems_only: bool = False,
|
|
attrs_only: bool = False,
|
|
names: Sequence[str] | None = None,
|
|
dtype: DtypeArg | None = None,
|
|
converters: ConvertersArg | None = None,
|
|
parse_dates: ParseDatesArg | None = None,
|
|
# encoding can not be None for lxml and StringIO input
|
|
encoding: str | None = "utf-8",
|
|
parser: XMLParsers = "lxml",
|
|
stylesheet: FilePath | ReadBuffer[bytes] | ReadBuffer[str] | None = None,
|
|
iterparse: dict[str, list[str]] | None = None,
|
|
compression: CompressionOptions = "infer",
|
|
storage_options: StorageOptions = None,
|
|
) -> DataFrame:
|
|
r"""
|
|
Read XML document into a ``DataFrame`` object.
|
|
|
|
.. versionadded:: 1.3.0
|
|
|
|
Parameters
|
|
----------
|
|
path_or_buffer : str, path object, or file-like object
|
|
String, path object (implementing ``os.PathLike[str]``), or file-like
|
|
object implementing a ``read()`` function. The string can be any valid XML
|
|
string or a path. The string can further be a URL. Valid URL schemes
|
|
include http, ftp, s3, and file.
|
|
|
|
xpath : str, optional, default './\*'
|
|
The XPath to parse required set of nodes for migration to DataFrame.
|
|
XPath should return a collection of elements and not a single
|
|
element. Note: The ``etree`` parser supports limited XPath
|
|
expressions. For more complex XPath, use ``lxml`` which requires
|
|
installation.
|
|
|
|
namespaces : dict, optional
|
|
The namespaces defined in XML document as dicts with key being
|
|
namespace prefix and value the URI. There is no need to include all
|
|
namespaces in XML, only the ones used in ``xpath`` expression.
|
|
Note: if XML document uses default namespace denoted as
|
|
`xmlns='<URI>'` without a prefix, you must assign any temporary
|
|
namespace prefix such as 'doc' to the URI in order to parse
|
|
underlying nodes and/or attributes. For example, ::
|
|
|
|
namespaces = {{"doc": "https://example.com"}}
|
|
|
|
elems_only : bool, optional, default False
|
|
Parse only the child elements at the specified ``xpath``. By default,
|
|
all child elements and non-empty text nodes are returned.
|
|
|
|
attrs_only : bool, optional, default False
|
|
Parse only the attributes at the specified ``xpath``.
|
|
By default, all attributes are returned.
|
|
|
|
names : list-like, optional
|
|
Column names for DataFrame of parsed XML data. Use this parameter to
|
|
rename original element names and distinguish same named elements and
|
|
attributes.
|
|
|
|
dtype : Type name or dict of column -> type, optional
|
|
Data type for data or columns. E.g. {{'a': np.float64, 'b': np.int32,
|
|
'c': 'Int64'}}
|
|
Use `str` or `object` together with suitable `na_values` settings
|
|
to preserve and not interpret dtype.
|
|
If converters are specified, they will be applied INSTEAD
|
|
of dtype conversion.
|
|
|
|
.. versionadded:: 1.5.0
|
|
|
|
converters : dict, optional
|
|
Dict of functions for converting values in certain columns. Keys can either
|
|
be integers or column labels.
|
|
|
|
.. versionadded:: 1.5.0
|
|
|
|
parse_dates : bool or list of int or names or list of lists or dict, default False
|
|
Identifiers to parse index or columns to datetime. The behavior is as follows:
|
|
|
|
* boolean. If True -> try parsing the index.
|
|
* list of int or names. e.g. If [1, 2, 3] -> try parsing columns 1, 2, 3
|
|
each as a separate date column.
|
|
* list of lists. e.g. If [[1, 3]] -> combine columns 1 and 3 and parse as
|
|
a single date column.
|
|
* dict, e.g. {{'foo' : [1, 3]}} -> parse columns 1, 3 as date and call
|
|
result 'foo'
|
|
|
|
.. versionadded:: 1.5.0
|
|
|
|
encoding : str, optional, default 'utf-8'
|
|
Encoding of XML document.
|
|
|
|
parser : {{'lxml','etree'}}, default 'lxml'
|
|
Parser module to use for retrieval of data. Only 'lxml' and
|
|
'etree' are supported. With 'lxml' more complex XPath searches
|
|
and ability to use XSLT stylesheet are supported.
|
|
|
|
stylesheet : str, path object or file-like object
|
|
A URL, file-like object, or a raw string containing an XSLT script.
|
|
This stylesheet should flatten complex, deeply nested XML documents
|
|
for easier parsing. To use this feature you must have ``lxml`` module
|
|
installed and specify 'lxml' as ``parser``. The ``xpath`` must
|
|
reference nodes of transformed XML document generated after XSLT
|
|
transformation and not the original XML document. Only XSLT 1.0
|
|
scripts and not later versions is currently supported.
|
|
|
|
iterparse : dict, optional
|
|
The nodes or attributes to retrieve in iterparsing of XML document
|
|
as a dict with key being the name of repeating element and value being
|
|
list of elements or attribute names that are descendants of the repeated
|
|
element. Note: If this option is used, it will replace ``xpath`` parsing
|
|
and unlike xpath, descendants do not need to relate to each other but can
|
|
exist any where in document under the repeating element. This memory-
|
|
efficient method should be used for very large XML files (500MB, 1GB, or 5GB+).
|
|
For example, ::
|
|
|
|
iterparse = {{"row_element": ["child_elem", "attr", "grandchild_elem"]}}
|
|
|
|
.. versionadded:: 1.5.0
|
|
|
|
{decompression_options}
|
|
|
|
.. versionchanged:: 1.4.0 Zstandard support.
|
|
|
|
{storage_options}
|
|
|
|
Returns
|
|
-------
|
|
df
|
|
A DataFrame.
|
|
|
|
See Also
|
|
--------
|
|
read_json : Convert a JSON string to pandas object.
|
|
read_html : Read HTML tables into a list of DataFrame objects.
|
|
|
|
Notes
|
|
-----
|
|
This method is best designed to import shallow XML documents in
|
|
following format which is the ideal fit for the two-dimensions of a
|
|
``DataFrame`` (row by column). ::
|
|
|
|
<root>
|
|
<row>
|
|
<column1>data</column1>
|
|
<column2>data</column2>
|
|
<column3>data</column3>
|
|
...
|
|
</row>
|
|
<row>
|
|
...
|
|
</row>
|
|
...
|
|
</root>
|
|
|
|
As a file format, XML documents can be designed any way including
|
|
layout of elements and attributes as long as it conforms to W3C
|
|
specifications. Therefore, this method is a convenience handler for
|
|
a specific flatter design and not all possible XML structures.
|
|
|
|
However, for more complex XML documents, ``stylesheet`` allows you to
|
|
temporarily redesign original document with XSLT (a special purpose
|
|
language) for a flatter version for migration to a DataFrame.
|
|
|
|
This function will *always* return a single :class:`DataFrame` or raise
|
|
exceptions due to issues with XML document, ``xpath``, or other
|
|
parameters.
|
|
|
|
See the :ref:`read_xml documentation in the IO section of the docs
|
|
<io.read_xml>` for more information in using this method to parse XML
|
|
files to DataFrames.
|
|
|
|
Examples
|
|
--------
|
|
>>> xml = '''<?xml version='1.0' encoding='utf-8'?>
|
|
... <data xmlns="http://example.com">
|
|
... <row>
|
|
... <shape>square</shape>
|
|
... <degrees>360</degrees>
|
|
... <sides>4.0</sides>
|
|
... </row>
|
|
... <row>
|
|
... <shape>circle</shape>
|
|
... <degrees>360</degrees>
|
|
... <sides/>
|
|
... </row>
|
|
... <row>
|
|
... <shape>triangle</shape>
|
|
... <degrees>180</degrees>
|
|
... <sides>3.0</sides>
|
|
... </row>
|
|
... </data>'''
|
|
|
|
>>> df = pd.read_xml(xml)
|
|
>>> df
|
|
shape degrees sides
|
|
0 square 360 4.0
|
|
1 circle 360 NaN
|
|
2 triangle 180 3.0
|
|
|
|
>>> xml = '''<?xml version='1.0' encoding='utf-8'?>
|
|
... <data>
|
|
... <row shape="square" degrees="360" sides="4.0"/>
|
|
... <row shape="circle" degrees="360"/>
|
|
... <row shape="triangle" degrees="180" sides="3.0"/>
|
|
... </data>'''
|
|
|
|
>>> df = pd.read_xml(xml, xpath=".//row")
|
|
>>> df
|
|
shape degrees sides
|
|
0 square 360 4.0
|
|
1 circle 360 NaN
|
|
2 triangle 180 3.0
|
|
|
|
>>> xml = '''<?xml version='1.0' encoding='utf-8'?>
|
|
... <doc:data xmlns:doc="https://example.com">
|
|
... <doc:row>
|
|
... <doc:shape>square</doc:shape>
|
|
... <doc:degrees>360</doc:degrees>
|
|
... <doc:sides>4.0</doc:sides>
|
|
... </doc:row>
|
|
... <doc:row>
|
|
... <doc:shape>circle</doc:shape>
|
|
... <doc:degrees>360</doc:degrees>
|
|
... <doc:sides/>
|
|
... </doc:row>
|
|
... <doc:row>
|
|
... <doc:shape>triangle</doc:shape>
|
|
... <doc:degrees>180</doc:degrees>
|
|
... <doc:sides>3.0</doc:sides>
|
|
... </doc:row>
|
|
... </doc:data>'''
|
|
|
|
>>> df = pd.read_xml(xml,
|
|
... xpath="//doc:row",
|
|
... namespaces={{"doc": "https://example.com"}})
|
|
>>> df
|
|
shape degrees sides
|
|
0 square 360 4.0
|
|
1 circle 360 NaN
|
|
2 triangle 180 3.0
|
|
"""
|
|
|
|
return _parse(
|
|
path_or_buffer=path_or_buffer,
|
|
xpath=xpath,
|
|
namespaces=namespaces,
|
|
elems_only=elems_only,
|
|
attrs_only=attrs_only,
|
|
names=names,
|
|
dtype=dtype,
|
|
converters=converters,
|
|
parse_dates=parse_dates,
|
|
encoding=encoding,
|
|
parser=parser,
|
|
stylesheet=stylesheet,
|
|
iterparse=iterparse,
|
|
compression=compression,
|
|
storage_options=storage_options,
|
|
)
|