1231 lines
38 KiB
Python
1231 lines
38 KiB
Python
"""
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:mod:`pandas.io.html` is a module containing functionality for dealing with
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HTML IO.
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"""
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from __future__ import annotations
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from collections import abc
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import numbers
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import re
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from typing import (
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TYPE_CHECKING,
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Iterable,
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Literal,
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Pattern,
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Sequence,
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cast,
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)
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from pandas._libs import lib
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from pandas._typing import (
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BaseBuffer,
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DtypeBackend,
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FilePath,
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ReadBuffer,
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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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EmptyDataError,
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)
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from pandas.util._validators import check_dtype_backend
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from pandas.core.dtypes.common import is_list_like
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from pandas import isna
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from pandas.core.indexes.base import Index
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from pandas.core.indexes.multi import MultiIndex
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from pandas.core.series import Series
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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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is_url,
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stringify_path,
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urlopen,
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validate_header_arg,
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)
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from pandas.io.formats.printing import pprint_thing
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from pandas.io.parsers import TextParser
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if TYPE_CHECKING:
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from pandas import DataFrame
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_IMPORTS = False
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_HAS_BS4 = False
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_HAS_LXML = False
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_HAS_HTML5LIB = False
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def _importers() -> None:
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# import things we need
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# but make this done on a first use basis
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global _IMPORTS
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if _IMPORTS:
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return
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global _HAS_BS4, _HAS_LXML, _HAS_HTML5LIB
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bs4 = import_optional_dependency("bs4", errors="ignore")
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_HAS_BS4 = bs4 is not None
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lxml = import_optional_dependency("lxml.etree", errors="ignore")
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_HAS_LXML = lxml is not None
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html5lib = import_optional_dependency("html5lib", errors="ignore")
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_HAS_HTML5LIB = html5lib is not None
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_IMPORTS = True
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#############
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# READ HTML #
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#############
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_RE_WHITESPACE = re.compile(r"[\r\n]+|\s{2,}")
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def _remove_whitespace(s: str, regex: Pattern = _RE_WHITESPACE) -> str:
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"""
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Replace extra whitespace inside of a string with a single space.
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Parameters
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----------
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s : str or unicode
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The string from which to remove extra whitespace.
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regex : re.Pattern
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The regular expression to use to remove extra whitespace.
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Returns
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-------
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subd : str or unicode
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`s` with all extra whitespace replaced with a single space.
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"""
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return regex.sub(" ", s.strip())
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def _get_skiprows(skiprows: int | Sequence[int] | slice | None) -> int | Sequence[int]:
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"""
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Get an iterator given an integer, slice or container.
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Parameters
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----------
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skiprows : int, slice, container
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The iterator to use to skip rows; can also be a slice.
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Raises
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------
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TypeError
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* If `skiprows` is not a slice, integer, or Container
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Returns
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-------
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it : iterable
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A proper iterator to use to skip rows of a DataFrame.
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"""
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if isinstance(skiprows, slice):
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start, step = skiprows.start or 0, skiprows.step or 1
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return list(range(start, skiprows.stop, step))
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elif isinstance(skiprows, numbers.Integral) or is_list_like(skiprows):
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return cast("int | Sequence[int]", skiprows)
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elif skiprows is None:
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return 0
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raise TypeError(f"{type(skiprows).__name__} is not a valid type for skipping rows")
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def _read(obj: FilePath | BaseBuffer, encoding: str | None) -> str | bytes:
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"""
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Try to read from a url, file or string.
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Parameters
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----------
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obj : str, unicode, path object, or file-like object
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Returns
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-------
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raw_text : str
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"""
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text: str | bytes
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if (
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is_url(obj)
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or hasattr(obj, "read")
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or (isinstance(obj, str) and file_exists(obj))
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):
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with get_handle(obj, "r", encoding=encoding) as handles:
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text = handles.handle.read()
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elif isinstance(obj, (str, bytes)):
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text = obj
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else:
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raise TypeError(f"Cannot read object of type '{type(obj).__name__}'")
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return text
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class _HtmlFrameParser:
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"""
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Base class for parsers that parse HTML into DataFrames.
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Parameters
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----------
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io : str or file-like
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This can be either a string of raw HTML, a valid URL using the HTTP,
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FTP, or FILE protocols or a file-like object.
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match : str or regex
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The text to match in the document.
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attrs : dict
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List of HTML <table> element attributes to match.
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encoding : str
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Encoding to be used by parser
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displayed_only : bool
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Whether or not items with "display:none" should be ignored
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extract_links : {None, "all", "header", "body", "footer"}
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Table elements in the specified section(s) with <a> tags will have their
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href extracted.
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.. versionadded:: 1.5.0
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Attributes
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----------
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io : str or file-like
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raw HTML, URL, or file-like object
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match : regex
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The text to match in the raw HTML
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attrs : dict-like
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A dictionary of valid table attributes to use to search for table
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elements.
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encoding : str
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Encoding to be used by parser
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displayed_only : bool
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Whether or not items with "display:none" should be ignored
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extract_links : {None, "all", "header", "body", "footer"}
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Table elements in the specified section(s) with <a> tags will have their
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href extracted.
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.. versionadded:: 1.5.0
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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:`_build_doc`
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* :func:`_attr_getter`
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* :func:`_href_getter`
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* :func:`_text_getter`
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* :func:`_parse_td`
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* :func:`_parse_thead_tr`
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* :func:`_parse_tbody_tr`
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* :func:`_parse_tfoot_tr`
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* :func:`_parse_tables`
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* :func:`_equals_tag`
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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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io: FilePath | ReadBuffer[str] | ReadBuffer[bytes],
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match: str | Pattern,
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attrs: dict[str, str] | None,
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encoding: str,
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displayed_only: bool,
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extract_links: Literal[None, "header", "footer", "body", "all"],
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) -> None:
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self.io = io
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self.match = match
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self.attrs = attrs
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self.encoding = encoding
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self.displayed_only = displayed_only
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self.extract_links = extract_links
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def parse_tables(self):
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"""
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Parse and return all tables from the DOM.
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Returns
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-------
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list of parsed (header, body, footer) tuples from tables.
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"""
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tables = self._parse_tables(self._build_doc(), self.match, self.attrs)
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return (self._parse_thead_tbody_tfoot(table) for table in tables)
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def _attr_getter(self, obj, attr):
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"""
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Return the attribute value of an individual DOM node.
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Parameters
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----------
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obj : node-like
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A DOM node.
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attr : str or unicode
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The attribute, such as "colspan"
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Returns
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-------
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str or unicode
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The attribute value.
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"""
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# Both lxml and BeautifulSoup have the same implementation:
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return obj.get(attr)
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def _href_getter(self, obj):
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"""
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Return a href if the DOM node contains a child <a> or None.
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Parameters
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----------
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obj : node-like
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A DOM node.
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Returns
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-------
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href : str or unicode
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The href from the <a> child of the DOM node.
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"""
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raise AbstractMethodError(self)
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def _text_getter(self, obj):
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"""
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Return the text of an individual DOM node.
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Parameters
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----------
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obj : node-like
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A DOM node.
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Returns
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-------
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text : str or unicode
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The text from an individual DOM node.
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"""
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raise AbstractMethodError(self)
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def _parse_td(self, obj):
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"""
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Return the td elements from a row element.
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Parameters
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----------
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obj : node-like
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A DOM <tr> node.
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Returns
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-------
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list of node-like
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These are the elements of each row, i.e., the columns.
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"""
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raise AbstractMethodError(self)
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def _parse_thead_tr(self, table):
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"""
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Return the list of thead row elements from the parsed table element.
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Parameters
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----------
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table : a table element that contains zero or more thead elements.
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Returns
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-------
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list of node-like
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These are the <tr> row elements of a table.
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"""
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raise AbstractMethodError(self)
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def _parse_tbody_tr(self, table):
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"""
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Return the list of tbody row elements from the parsed table element.
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HTML5 table bodies consist of either 0 or more <tbody> elements (which
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only contain <tr> elements) or 0 or more <tr> elements. This method
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checks for both structures.
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Parameters
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----------
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table : a table element that contains row elements.
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Returns
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-------
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list of node-like
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These are the <tr> row elements of a table.
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"""
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raise AbstractMethodError(self)
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def _parse_tfoot_tr(self, table):
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"""
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Return the list of tfoot row elements from the parsed table element.
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Parameters
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----------
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table : a table element that contains row elements.
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Returns
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-------
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list of node-like
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These are the <tr> row elements of a table.
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"""
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raise AbstractMethodError(self)
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def _parse_tables(self, doc, match, attrs):
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"""
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Return all tables from the parsed DOM.
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Parameters
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----------
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doc : the DOM from which to parse the table element.
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match : str or regular expression
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The text to search for in the DOM tree.
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attrs : dict
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A dictionary of table attributes that can be used to disambiguate
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multiple tables on a page.
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Raises
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------
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ValueError : `match` does not match any text in the document.
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Returns
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-------
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list of node-like
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HTML <table> elements to be parsed into raw data.
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"""
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raise AbstractMethodError(self)
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def _equals_tag(self, obj, tag):
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"""
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Return whether an individual DOM node matches a tag
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Parameters
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----------
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obj : node-like
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A DOM node.
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tag : str
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Tag name to be checked for equality.
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Returns
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-------
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boolean
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Whether `obj`'s tag name is `tag`
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"""
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raise AbstractMethodError(self)
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def _build_doc(self):
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"""
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Return a tree-like object that can be used to iterate over the DOM.
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Returns
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-------
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node-like
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The DOM from which to parse the table element.
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"""
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raise AbstractMethodError(self)
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def _parse_thead_tbody_tfoot(self, table_html):
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"""
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Given a table, return parsed header, body, and foot.
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Parameters
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----------
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table_html : node-like
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Returns
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-------
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tuple of (header, body, footer), each a list of list-of-text rows.
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Notes
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-----
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Header and body are lists-of-lists. Top level list is a list of
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rows. Each row is a list of str text.
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Logic: Use <thead>, <tbody>, <tfoot> elements to identify
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header, body, and footer, otherwise:
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- Put all rows into body
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- Move rows from top of body to header only if
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all elements inside row are <th>
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- Move rows from bottom of body to footer only if
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all elements inside row are <th>
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"""
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header_rows = self._parse_thead_tr(table_html)
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body_rows = self._parse_tbody_tr(table_html)
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footer_rows = self._parse_tfoot_tr(table_html)
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def row_is_all_th(row):
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return all(self._equals_tag(t, "th") for t in self._parse_td(row))
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if not header_rows:
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# The table has no <thead>. Move the top all-<th> rows from
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# body_rows to header_rows. (This is a common case because many
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# tables in the wild have no <thead> or <tfoot>
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while body_rows and row_is_all_th(body_rows[0]):
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header_rows.append(body_rows.pop(0))
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header = self._expand_colspan_rowspan(header_rows, section="header")
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body = self._expand_colspan_rowspan(body_rows, section="body")
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footer = self._expand_colspan_rowspan(footer_rows, section="footer")
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return header, body, footer
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def _expand_colspan_rowspan(
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self, rows, section: Literal["header", "footer", "body"]
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):
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"""
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Given a list of <tr>s, return a list of text rows.
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Parameters
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----------
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rows : list of node-like
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List of <tr>s
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section : the section that the rows belong to (header, body or footer).
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|
Returns
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-------
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list of list
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Each returned row is a list of str text, or tuple (text, link)
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if extract_links is not None.
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|
|
Notes
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-----
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Any cell with ``rowspan`` or ``colspan`` will have its contents copied
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to subsequent cells.
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"""
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all_texts = [] # list of rows, each a list of str
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text: str | tuple
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remainder: list[
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tuple[int, str | tuple, int]
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] = [] # list of (index, text, nrows)
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for tr in rows:
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texts = [] # the output for this row
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next_remainder = []
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index = 0
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tds = self._parse_td(tr)
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for td in tds:
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# Append texts from previous rows with rowspan>1 that come
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# before this <td>
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while remainder and remainder[0][0] <= index:
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prev_i, prev_text, prev_rowspan = remainder.pop(0)
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texts.append(prev_text)
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if prev_rowspan > 1:
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next_remainder.append((prev_i, prev_text, prev_rowspan - 1))
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index += 1
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# Append the text from this <td>, colspan times
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text = _remove_whitespace(self._text_getter(td))
|
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if self.extract_links in ("all", section):
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href = self._href_getter(td)
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text = (text, href)
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rowspan = int(self._attr_getter(td, "rowspan") or 1)
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colspan = int(self._attr_getter(td, "colspan") or 1)
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for _ in range(colspan):
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texts.append(text)
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if rowspan > 1:
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next_remainder.append((index, text, rowspan - 1))
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index += 1
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# Append texts from previous rows at the final position
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for prev_i, prev_text, prev_rowspan in remainder:
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texts.append(prev_text)
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if prev_rowspan > 1:
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next_remainder.append((prev_i, prev_text, prev_rowspan - 1))
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all_texts.append(texts)
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remainder = next_remainder
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|
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# Append rows that only appear because the previous row had non-1
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# rowspan
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|
while remainder:
|
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next_remainder = []
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texts = []
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for prev_i, prev_text, prev_rowspan in remainder:
|
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texts.append(prev_text)
|
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if prev_rowspan > 1:
|
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next_remainder.append((prev_i, prev_text, prev_rowspan - 1))
|
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all_texts.append(texts)
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remainder = next_remainder
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return all_texts
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|
|
def _handle_hidden_tables(self, tbl_list, attr_name):
|
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"""
|
|
Return list of tables, potentially removing hidden elements
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|
|
|
Parameters
|
|
----------
|
|
tbl_list : list of node-like
|
|
Type of list elements will vary depending upon parser used
|
|
attr_name : str
|
|
Name of the accessor for retrieving HTML attributes
|
|
|
|
Returns
|
|
-------
|
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list of node-like
|
|
Return type matches `tbl_list`
|
|
"""
|
|
if not self.displayed_only:
|
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return tbl_list
|
|
|
|
return [
|
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x
|
|
for x in tbl_list
|
|
if "display:none"
|
|
not in getattr(x, attr_name).get("style", "").replace(" ", "")
|
|
]
|
|
|
|
|
|
class _BeautifulSoupHtml5LibFrameParser(_HtmlFrameParser):
|
|
"""
|
|
HTML to DataFrame parser that uses BeautifulSoup under the hood.
|
|
|
|
See Also
|
|
--------
|
|
pandas.io.html._HtmlFrameParser
|
|
pandas.io.html._LxmlFrameParser
|
|
|
|
Notes
|
|
-----
|
|
Documentation strings for this class are in the base class
|
|
:class:`pandas.io.html._HtmlFrameParser`.
|
|
"""
|
|
|
|
def __init__(self, *args, **kwargs) -> None:
|
|
super().__init__(*args, **kwargs)
|
|
from bs4 import SoupStrainer
|
|
|
|
self._strainer = SoupStrainer("table")
|
|
|
|
def _parse_tables(self, doc, match, attrs):
|
|
element_name = self._strainer.name
|
|
tables = doc.find_all(element_name, attrs=attrs)
|
|
|
|
if not tables:
|
|
raise ValueError("No tables found")
|
|
|
|
result = []
|
|
unique_tables = set()
|
|
tables = self._handle_hidden_tables(tables, "attrs")
|
|
|
|
for table in tables:
|
|
if self.displayed_only:
|
|
for elem in table.find_all(style=re.compile(r"display:\s*none")):
|
|
elem.decompose()
|
|
|
|
if table not in unique_tables and table.find(string=match) is not None:
|
|
result.append(table)
|
|
unique_tables.add(table)
|
|
|
|
if not result:
|
|
raise ValueError(f"No tables found matching pattern {repr(match.pattern)}")
|
|
return result
|
|
|
|
def _href_getter(self, obj) -> str | None:
|
|
a = obj.find("a", href=True)
|
|
return None if not a else a["href"]
|
|
|
|
def _text_getter(self, obj):
|
|
return obj.text
|
|
|
|
def _equals_tag(self, obj, tag):
|
|
return obj.name == tag
|
|
|
|
def _parse_td(self, row):
|
|
return row.find_all(("td", "th"), recursive=False)
|
|
|
|
def _parse_thead_tr(self, table):
|
|
return table.select("thead tr")
|
|
|
|
def _parse_tbody_tr(self, table):
|
|
from_tbody = table.select("tbody tr")
|
|
from_root = table.find_all("tr", recursive=False)
|
|
# HTML spec: at most one of these lists has content
|
|
return from_tbody + from_root
|
|
|
|
def _parse_tfoot_tr(self, table):
|
|
return table.select("tfoot tr")
|
|
|
|
def _setup_build_doc(self):
|
|
raw_text = _read(self.io, self.encoding)
|
|
if not raw_text:
|
|
raise ValueError(f"No text parsed from document: {self.io}")
|
|
return raw_text
|
|
|
|
def _build_doc(self):
|
|
from bs4 import BeautifulSoup
|
|
|
|
bdoc = self._setup_build_doc()
|
|
if isinstance(bdoc, bytes) and self.encoding is not None:
|
|
udoc = bdoc.decode(self.encoding)
|
|
from_encoding = None
|
|
else:
|
|
udoc = bdoc
|
|
from_encoding = self.encoding
|
|
|
|
soup = BeautifulSoup(udoc, features="html5lib", from_encoding=from_encoding)
|
|
|
|
for br in soup.find_all("br"):
|
|
br.replace_with("\n" + br.text)
|
|
|
|
return soup
|
|
|
|
|
|
def _build_xpath_expr(attrs) -> str:
|
|
"""
|
|
Build an xpath expression to simulate bs4's ability to pass in kwargs to
|
|
search for attributes when using the lxml parser.
|
|
|
|
Parameters
|
|
----------
|
|
attrs : dict
|
|
A dict of HTML attributes. These are NOT checked for validity.
|
|
|
|
Returns
|
|
-------
|
|
expr : unicode
|
|
An XPath expression that checks for the given HTML attributes.
|
|
"""
|
|
# give class attribute as class_ because class is a python keyword
|
|
if "class_" in attrs:
|
|
attrs["class"] = attrs.pop("class_")
|
|
|
|
s = " and ".join([f"@{k}={repr(v)}" for k, v in attrs.items()])
|
|
return f"[{s}]"
|
|
|
|
|
|
_re_namespace = {"re": "http://exslt.org/regular-expressions"}
|
|
|
|
|
|
class _LxmlFrameParser(_HtmlFrameParser):
|
|
"""
|
|
HTML to DataFrame parser that uses lxml under the hood.
|
|
|
|
Warning
|
|
-------
|
|
This parser can only handle HTTP, FTP, and FILE urls.
|
|
|
|
See Also
|
|
--------
|
|
_HtmlFrameParser
|
|
_BeautifulSoupLxmlFrameParser
|
|
|
|
Notes
|
|
-----
|
|
Documentation strings for this class are in the base class
|
|
:class:`_HtmlFrameParser`.
|
|
"""
|
|
|
|
def _href_getter(self, obj) -> str | None:
|
|
href = obj.xpath(".//a/@href")
|
|
return None if not href else href[0]
|
|
|
|
def _text_getter(self, obj):
|
|
return obj.text_content()
|
|
|
|
def _parse_td(self, row):
|
|
# Look for direct children only: the "row" element here may be a
|
|
# <thead> or <tfoot> (see _parse_thead_tr).
|
|
return row.xpath("./td|./th")
|
|
|
|
def _parse_tables(self, doc, match, kwargs):
|
|
pattern = match.pattern
|
|
|
|
# 1. check all descendants for the given pattern and only search tables
|
|
# GH 49929
|
|
xpath_expr = f"//table[.//text()[re:test(., {repr(pattern)})]]"
|
|
|
|
# if any table attributes were given build an xpath expression to
|
|
# search for them
|
|
if kwargs:
|
|
xpath_expr += _build_xpath_expr(kwargs)
|
|
|
|
tables = doc.xpath(xpath_expr, namespaces=_re_namespace)
|
|
|
|
tables = self._handle_hidden_tables(tables, "attrib")
|
|
if self.displayed_only:
|
|
for table in tables:
|
|
# lxml utilizes XPATH 1.0 which does not have regex
|
|
# support. As a result, we find all elements with a style
|
|
# attribute and iterate them to check for display:none
|
|
for elem in table.xpath(".//*[@style]"):
|
|
if "display:none" in elem.attrib.get("style", "").replace(" ", ""):
|
|
elem.getparent().remove(elem)
|
|
|
|
if not tables:
|
|
raise ValueError(f"No tables found matching regex {repr(pattern)}")
|
|
return tables
|
|
|
|
def _equals_tag(self, obj, tag):
|
|
return obj.tag == tag
|
|
|
|
def _build_doc(self):
|
|
"""
|
|
Raises
|
|
------
|
|
ValueError
|
|
* If a URL that lxml cannot parse is passed.
|
|
|
|
Exception
|
|
* Any other ``Exception`` thrown. For example, trying to parse a
|
|
URL that is syntactically correct on a machine with no internet
|
|
connection will fail.
|
|
|
|
See Also
|
|
--------
|
|
pandas.io.html._HtmlFrameParser._build_doc
|
|
"""
|
|
from lxml.etree import XMLSyntaxError
|
|
from lxml.html import (
|
|
HTMLParser,
|
|
fromstring,
|
|
parse,
|
|
)
|
|
|
|
parser = HTMLParser(recover=True, encoding=self.encoding)
|
|
|
|
try:
|
|
if is_url(self.io):
|
|
with urlopen(self.io) as f:
|
|
r = parse(f, parser=parser)
|
|
else:
|
|
# try to parse the input in the simplest way
|
|
r = parse(self.io, parser=parser)
|
|
try:
|
|
r = r.getroot()
|
|
except AttributeError:
|
|
pass
|
|
except (UnicodeDecodeError, OSError) as e:
|
|
# if the input is a blob of html goop
|
|
if not is_url(self.io):
|
|
r = fromstring(self.io, parser=parser)
|
|
|
|
try:
|
|
r = r.getroot()
|
|
except AttributeError:
|
|
pass
|
|
else:
|
|
raise e
|
|
else:
|
|
if not hasattr(r, "text_content"):
|
|
raise XMLSyntaxError("no text parsed from document", 0, 0, 0)
|
|
|
|
for br in r.xpath("*//br"):
|
|
br.tail = "\n" + (br.tail or "")
|
|
|
|
return r
|
|
|
|
def _parse_thead_tr(self, table):
|
|
rows = []
|
|
|
|
for thead in table.xpath(".//thead"):
|
|
rows.extend(thead.xpath("./tr"))
|
|
|
|
# HACK: lxml does not clean up the clearly-erroneous
|
|
# <thead><th>foo</th><th>bar</th></thead>. (Missing <tr>). Add
|
|
# the <thead> and _pretend_ it's a <tr>; _parse_td() will find its
|
|
# children as though it's a <tr>.
|
|
#
|
|
# Better solution would be to use html5lib.
|
|
elements_at_root = thead.xpath("./td|./th")
|
|
if elements_at_root:
|
|
rows.append(thead)
|
|
|
|
return rows
|
|
|
|
def _parse_tbody_tr(self, table):
|
|
from_tbody = table.xpath(".//tbody//tr")
|
|
from_root = table.xpath("./tr")
|
|
# HTML spec: at most one of these lists has content
|
|
return from_tbody + from_root
|
|
|
|
def _parse_tfoot_tr(self, table):
|
|
return table.xpath(".//tfoot//tr")
|
|
|
|
|
|
def _expand_elements(body) -> None:
|
|
data = [len(elem) for elem in body]
|
|
lens = Series(data)
|
|
lens_max = lens.max()
|
|
not_max = lens[lens != lens_max]
|
|
|
|
empty = [""]
|
|
for ind, length in not_max.items():
|
|
body[ind] += empty * (lens_max - length)
|
|
|
|
|
|
def _data_to_frame(**kwargs):
|
|
head, body, foot = kwargs.pop("data")
|
|
header = kwargs.pop("header")
|
|
kwargs["skiprows"] = _get_skiprows(kwargs["skiprows"])
|
|
if head:
|
|
body = head + body
|
|
|
|
# Infer header when there is a <thead> or top <th>-only rows
|
|
if header is None:
|
|
if len(head) == 1:
|
|
header = 0
|
|
else:
|
|
# ignore all-empty-text rows
|
|
header = [i for i, row in enumerate(head) if any(text for text in row)]
|
|
|
|
if foot:
|
|
body += foot
|
|
|
|
# fill out elements of body that are "ragged"
|
|
_expand_elements(body)
|
|
with TextParser(body, header=header, **kwargs) as tp:
|
|
return tp.read()
|
|
|
|
|
|
_valid_parsers = {
|
|
"lxml": _LxmlFrameParser,
|
|
None: _LxmlFrameParser,
|
|
"html5lib": _BeautifulSoupHtml5LibFrameParser,
|
|
"bs4": _BeautifulSoupHtml5LibFrameParser,
|
|
}
|
|
|
|
|
|
def _parser_dispatch(flavor: str | None) -> type[_HtmlFrameParser]:
|
|
"""
|
|
Choose the parser based on the input flavor.
|
|
|
|
Parameters
|
|
----------
|
|
flavor : str
|
|
The type of parser to use. This must be a valid backend.
|
|
|
|
Returns
|
|
-------
|
|
cls : _HtmlFrameParser subclass
|
|
The parser class based on the requested input flavor.
|
|
|
|
Raises
|
|
------
|
|
ValueError
|
|
* If `flavor` is not a valid backend.
|
|
ImportError
|
|
* If you do not have the requested `flavor`
|
|
"""
|
|
valid_parsers = list(_valid_parsers.keys())
|
|
if flavor not in valid_parsers:
|
|
raise ValueError(
|
|
f"{repr(flavor)} is not a valid flavor, valid flavors are {valid_parsers}"
|
|
)
|
|
|
|
if flavor in ("bs4", "html5lib"):
|
|
if not _HAS_HTML5LIB:
|
|
raise ImportError("html5lib not found, please install it")
|
|
if not _HAS_BS4:
|
|
raise ImportError("BeautifulSoup4 (bs4) not found, please install it")
|
|
# Although we call this above, we want to raise here right before use.
|
|
bs4 = import_optional_dependency("bs4") # noqa:F841
|
|
|
|
else:
|
|
if not _HAS_LXML:
|
|
raise ImportError("lxml not found, please install it")
|
|
return _valid_parsers[flavor]
|
|
|
|
|
|
def _print_as_set(s) -> str:
|
|
arg = ", ".join([pprint_thing(el) for el in s])
|
|
return f"{{{arg}}}"
|
|
|
|
|
|
def _validate_flavor(flavor):
|
|
if flavor is None:
|
|
flavor = "lxml", "bs4"
|
|
elif isinstance(flavor, str):
|
|
flavor = (flavor,)
|
|
elif isinstance(flavor, abc.Iterable):
|
|
if not all(isinstance(flav, str) for flav in flavor):
|
|
raise TypeError(
|
|
f"Object of type {repr(type(flavor).__name__)} "
|
|
f"is not an iterable of strings"
|
|
)
|
|
else:
|
|
msg = repr(flavor) if isinstance(flavor, str) else str(flavor)
|
|
msg += " is not a valid flavor"
|
|
raise ValueError(msg)
|
|
|
|
flavor = tuple(flavor)
|
|
valid_flavors = set(_valid_parsers)
|
|
flavor_set = set(flavor)
|
|
|
|
if not flavor_set & valid_flavors:
|
|
raise ValueError(
|
|
f"{_print_as_set(flavor_set)} is not a valid set of flavors, valid "
|
|
f"flavors are {_print_as_set(valid_flavors)}"
|
|
)
|
|
return flavor
|
|
|
|
|
|
def _parse(flavor, io, match, attrs, encoding, displayed_only, extract_links, **kwargs):
|
|
flavor = _validate_flavor(flavor)
|
|
compiled_match = re.compile(match) # you can pass a compiled regex here
|
|
|
|
retained = None
|
|
for flav in flavor:
|
|
parser = _parser_dispatch(flav)
|
|
p = parser(io, compiled_match, attrs, encoding, displayed_only, extract_links)
|
|
|
|
try:
|
|
tables = p.parse_tables()
|
|
except ValueError as caught:
|
|
# if `io` is an io-like object, check if it's seekable
|
|
# and try to rewind it before trying the next parser
|
|
if hasattr(io, "seekable") and io.seekable():
|
|
io.seek(0)
|
|
elif hasattr(io, "seekable") and not io.seekable():
|
|
# if we couldn't rewind it, let the user know
|
|
raise ValueError(
|
|
f"The flavor {flav} failed to parse your input. "
|
|
"Since you passed a non-rewindable file "
|
|
"object, we can't rewind it to try "
|
|
"another parser. Try read_html() with a different flavor."
|
|
) from caught
|
|
|
|
retained = caught
|
|
else:
|
|
break
|
|
else:
|
|
assert retained is not None # for mypy
|
|
raise retained
|
|
|
|
ret = []
|
|
for table in tables:
|
|
try:
|
|
df = _data_to_frame(data=table, **kwargs)
|
|
# Cast MultiIndex header to an Index of tuples when extracting header
|
|
# links and replace nan with None (therefore can't use mi.to_flat_index()).
|
|
# This maintains consistency of selection (e.g. df.columns.str[1])
|
|
if extract_links in ("all", "header") and isinstance(
|
|
df.columns, MultiIndex
|
|
):
|
|
df.columns = Index(
|
|
((col[0], None if isna(col[1]) else col[1]) for col in df.columns),
|
|
tupleize_cols=False,
|
|
)
|
|
|
|
ret.append(df)
|
|
except EmptyDataError: # empty table
|
|
continue
|
|
return ret
|
|
|
|
|
|
def read_html(
|
|
io: FilePath | ReadBuffer[str],
|
|
*,
|
|
match: str | Pattern = ".+",
|
|
flavor: str | None = None,
|
|
header: int | Sequence[int] | None = None,
|
|
index_col: int | Sequence[int] | None = None,
|
|
skiprows: int | Sequence[int] | slice | None = None,
|
|
attrs: dict[str, str] | None = None,
|
|
parse_dates: bool = False,
|
|
thousands: str | None = ",",
|
|
encoding: str | None = None,
|
|
decimal: str = ".",
|
|
converters: dict | None = None,
|
|
na_values: Iterable[object] | None = None,
|
|
keep_default_na: bool = True,
|
|
displayed_only: bool = True,
|
|
extract_links: Literal[None, "header", "footer", "body", "all"] = None,
|
|
dtype_backend: DtypeBackend | lib.NoDefault = lib.no_default,
|
|
) -> list[DataFrame]:
|
|
r"""
|
|
Read HTML tables into a ``list`` of ``DataFrame`` objects.
|
|
|
|
Parameters
|
|
----------
|
|
io : str, path object, or file-like object
|
|
String, path object (implementing ``os.PathLike[str]``), or file-like
|
|
object implementing a string ``read()`` function.
|
|
The string can represent a URL or the HTML itself. Note that
|
|
lxml only accepts the http, ftp and file url protocols. If you have a
|
|
URL that starts with ``'https'`` you might try removing the ``'s'``.
|
|
|
|
match : str or compiled regular expression, optional
|
|
The set of tables containing text matching this regex or string will be
|
|
returned. Unless the HTML is extremely simple you will probably need to
|
|
pass a non-empty string here. Defaults to '.+' (match any non-empty
|
|
string). The default value will return all tables contained on a page.
|
|
This value is converted to a regular expression so that there is
|
|
consistent behavior between Beautiful Soup and lxml.
|
|
|
|
flavor : str, optional
|
|
The parsing engine to use. 'bs4' and 'html5lib' are synonymous with
|
|
each other, they are both there for backwards compatibility. The
|
|
default of ``None`` tries to use ``lxml`` to parse and if that fails it
|
|
falls back on ``bs4`` + ``html5lib``.
|
|
|
|
header : int or list-like, optional
|
|
The row (or list of rows for a :class:`~pandas.MultiIndex`) to use to
|
|
make the columns headers.
|
|
|
|
index_col : int or list-like, optional
|
|
The column (or list of columns) to use to create the index.
|
|
|
|
skiprows : int, list-like or slice, optional
|
|
Number of rows to skip after parsing the column integer. 0-based. If a
|
|
sequence of integers or a slice is given, will skip the rows indexed by
|
|
that sequence. Note that a single element sequence means 'skip the nth
|
|
row' whereas an integer means 'skip n rows'.
|
|
|
|
attrs : dict, optional
|
|
This is a dictionary of attributes that you can pass to use to identify
|
|
the table in the HTML. These are not checked for validity before being
|
|
passed to lxml or Beautiful Soup. However, these attributes must be
|
|
valid HTML table attributes to work correctly. For example, ::
|
|
|
|
attrs = {'id': 'table'}
|
|
|
|
is a valid attribute dictionary because the 'id' HTML tag attribute is
|
|
a valid HTML attribute for *any* HTML tag as per `this document
|
|
<https://html.spec.whatwg.org/multipage/dom.html#global-attributes>`__. ::
|
|
|
|
attrs = {'asdf': 'table'}
|
|
|
|
is *not* a valid attribute dictionary because 'asdf' is not a valid
|
|
HTML attribute even if it is a valid XML attribute. Valid HTML 4.01
|
|
table attributes can be found `here
|
|
<http://www.w3.org/TR/REC-html40/struct/tables.html#h-11.2>`__. A
|
|
working draft of the HTML 5 spec can be found `here
|
|
<https://html.spec.whatwg.org/multipage/tables.html>`__. It contains the
|
|
latest information on table attributes for the modern web.
|
|
|
|
parse_dates : bool, optional
|
|
See :func:`~read_csv` for more details.
|
|
|
|
thousands : str, optional
|
|
Separator to use to parse thousands. Defaults to ``','``.
|
|
|
|
encoding : str, optional
|
|
The encoding used to decode the web page. Defaults to ``None``.``None``
|
|
preserves the previous encoding behavior, which depends on the
|
|
underlying parser library (e.g., the parser library will try to use
|
|
the encoding provided by the document).
|
|
|
|
decimal : str, default '.'
|
|
Character to recognize as decimal point (e.g. use ',' for European
|
|
data).
|
|
|
|
converters : dict, default None
|
|
Dict of functions for converting values in certain columns. Keys can
|
|
either be integers or column labels, values are functions that take one
|
|
input argument, the cell (not column) content, and return the
|
|
transformed content.
|
|
|
|
na_values : iterable, default None
|
|
Custom NA values.
|
|
|
|
keep_default_na : bool, default True
|
|
If na_values are specified and keep_default_na is False the default NaN
|
|
values are overridden, otherwise they're appended to.
|
|
|
|
displayed_only : bool, default True
|
|
Whether elements with "display: none" should be parsed.
|
|
|
|
extract_links : {None, "all", "header", "body", "footer"}
|
|
Table elements in the specified section(s) with <a> tags will have their
|
|
href extracted.
|
|
|
|
.. versionadded:: 1.5.0
|
|
|
|
dtype_backend : {"numpy_nullable", "pyarrow"}, defaults to NumPy backed DataFrames
|
|
Which dtype_backend to use, e.g. whether a DataFrame should have NumPy
|
|
arrays, nullable dtypes are used for all dtypes that have a nullable
|
|
implementation when "numpy_nullable" is set, pyarrow is used for all
|
|
dtypes if "pyarrow" is set.
|
|
|
|
The dtype_backends are still experimential.
|
|
|
|
.. versionadded:: 2.0
|
|
|
|
Returns
|
|
-------
|
|
dfs
|
|
A list of DataFrames.
|
|
|
|
See Also
|
|
--------
|
|
read_csv : Read a comma-separated values (csv) file into DataFrame.
|
|
|
|
Notes
|
|
-----
|
|
Before using this function you should read the :ref:`gotchas about the
|
|
HTML parsing libraries <io.html.gotchas>`.
|
|
|
|
Expect to do some cleanup after you call this function. For example, you
|
|
might need to manually assign column names if the column names are
|
|
converted to NaN when you pass the `header=0` argument. We try to assume as
|
|
little as possible about the structure of the table and push the
|
|
idiosyncrasies of the HTML contained in the table to the user.
|
|
|
|
This function searches for ``<table>`` elements and only for ``<tr>``
|
|
and ``<th>`` rows and ``<td>`` elements within each ``<tr>`` or ``<th>``
|
|
element in the table. ``<td>`` stands for "table data". This function
|
|
attempts to properly handle ``colspan`` and ``rowspan`` attributes.
|
|
If the function has a ``<thead>`` argument, it is used to construct
|
|
the header, otherwise the function attempts to find the header within
|
|
the body (by putting rows with only ``<th>`` elements into the header).
|
|
|
|
Similar to :func:`~read_csv` the `header` argument is applied
|
|
**after** `skiprows` is applied.
|
|
|
|
This function will *always* return a list of :class:`DataFrame` *or*
|
|
it will fail, e.g., it will *not* return an empty list.
|
|
|
|
Examples
|
|
--------
|
|
See the :ref:`read_html documentation in the IO section of the docs
|
|
<io.read_html>` for some examples of reading in HTML tables.
|
|
"""
|
|
_importers()
|
|
|
|
# Type check here. We don't want to parse only to fail because of an
|
|
# invalid value of an integer skiprows.
|
|
if isinstance(skiprows, numbers.Integral) and skiprows < 0:
|
|
raise ValueError(
|
|
"cannot skip rows starting from the end of the "
|
|
"data (you passed a negative value)"
|
|
)
|
|
if extract_links not in [None, "header", "footer", "body", "all"]:
|
|
raise ValueError(
|
|
"`extract_links` must be one of "
|
|
'{None, "header", "footer", "body", "all"}, got '
|
|
f'"{extract_links}"'
|
|
)
|
|
validate_header_arg(header)
|
|
check_dtype_backend(dtype_backend)
|
|
|
|
io = stringify_path(io)
|
|
|
|
return _parse(
|
|
flavor=flavor,
|
|
io=io,
|
|
match=match,
|
|
header=header,
|
|
index_col=index_col,
|
|
skiprows=skiprows,
|
|
parse_dates=parse_dates,
|
|
thousands=thousands,
|
|
attrs=attrs,
|
|
encoding=encoding,
|
|
decimal=decimal,
|
|
converters=converters,
|
|
na_values=na_values,
|
|
keep_default_na=keep_default_na,
|
|
displayed_only=displayed_only,
|
|
extract_links=extract_links,
|
|
dtype_backend=dtype_backend,
|
|
)
|