""":mod:`pandas.io.html` is a module containing functionality for dealing with HTML IO. """ import os import re import numbers import collections from distutils.version import LooseVersion import numpy as np from pandas.core.dtypes.common import is_list_like from pandas.errors import EmptyDataError from pandas.io.common import _is_url, urlopen, _validate_header_arg from pandas.io.parsers import TextParser from pandas.compat import (lrange, lmap, u, string_types, iteritems, raise_with_traceback, binary_type) from pandas import Series import pandas.core.common as com from pandas.io.formats.printing import pprint_thing _IMPORTS = False _HAS_BS4 = False _HAS_LXML = False _HAS_HTML5LIB = False def _importers(): # import things we need # but make this done on a first use basis global _IMPORTS if _IMPORTS: return global _HAS_BS4, _HAS_LXML, _HAS_HTML5LIB try: import bs4 # noqa _HAS_BS4 = True except ImportError: pass try: import lxml # noqa _HAS_LXML = True except ImportError: pass try: import html5lib # noqa _HAS_HTML5LIB = True except ImportError: pass _IMPORTS = True ############# # READ HTML # ############# _RE_WHITESPACE = re.compile(r'[\r\n]+|\s{2,}') char_types = string_types + (binary_type,) def _remove_whitespace(s, regex=_RE_WHITESPACE): """Replace extra whitespace inside of a string with a single space. Parameters ---------- s : str or unicode The string from which to remove extra whitespace. regex : regex The regular expression to use to remove extra whitespace. Returns ------- subd : str or unicode `s` with all extra whitespace replaced with a single space. """ return regex.sub(' ', s.strip()) def _get_skiprows(skiprows): """Get an iterator given an integer, slice or container. Parameters ---------- skiprows : int, slice, container The iterator to use to skip rows; can also be a slice. Raises ------ TypeError * If `skiprows` is not a slice, integer, or Container Returns ------- it : iterable A proper iterator to use to skip rows of a DataFrame. """ if isinstance(skiprows, slice): return lrange(skiprows.start or 0, skiprows.stop, skiprows.step or 1) elif isinstance(skiprows, numbers.Integral) or is_list_like(skiprows): return skiprows elif skiprows is None: return 0 raise TypeError('%r is not a valid type for skipping rows' % type(skiprows).__name__) def _read(obj): """Try to read from a url, file or string. Parameters ---------- obj : str, unicode, or file-like Returns ------- raw_text : str """ if _is_url(obj): with urlopen(obj) as url: text = url.read() elif hasattr(obj, 'read'): text = obj.read() elif isinstance(obj, char_types): text = obj try: if os.path.isfile(text): with open(text, 'rb') as f: return f.read() except (TypeError, ValueError): pass else: raise TypeError("Cannot read object of type %r" % type(obj).__name__) return text class _HtmlFrameParser(object): """Base class for parsers that parse HTML into DataFrames. Parameters ---------- io : str or file-like This can be either a string of raw HTML, a valid URL using the HTTP, FTP, or FILE protocols or a file-like object. match : str or regex The text to match in the document. attrs : dict List of HTML element attributes to match. encoding : str Encoding to be used by parser displayed_only : bool Whether or not items with "display:none" should be ignored .. versionadded:: 0.23.0 Attributes ---------- io : str or file-like raw HTML, URL, or file-like object match : regex The text to match in the raw HTML attrs : dict-like A dictionary of valid table attributes to use to search for table elements. encoding : str Encoding to be used by parser displayed_only : bool Whether or not items with "display:none" should be ignored .. versionadded:: 0.23.0 Notes ----- To subclass this class effectively you must override the following methods: * :func:`_build_doc` * :func:`_text_getter` * :func:`_parse_td` * :func:`_parse_tables` * :func:`_parse_tr` * :func:`_parse_thead` * :func:`_parse_tbody` * :func:`_parse_tfoot` See each method's respective documentation for details on their functionality. """ def __init__(self, io, match, attrs, encoding, displayed_only): self.io = io self.match = match self.attrs = attrs self.encoding = encoding self.displayed_only = displayed_only def parse_tables(self): tables = self._parse_tables(self._build_doc(), self.match, self.attrs) return (self._build_table(table) for table in tables) def _parse_raw_data(self, rows): """Parse the raw data into a list of lists. Parameters ---------- rows : iterable of node-like A list of row elements. text_getter : callable A callable that gets the text from an individual node. This must be defined by subclasses. column_finder : callable A callable that takes a row node as input and returns a list of the column node in that row. This must be defined by subclasses. Returns ------- data : list of list of strings """ data = [[_remove_whitespace(self._text_getter(col)) for col in self._parse_td(row)] for row in rows] return data def _text_getter(self, obj): """Return the text of an individual DOM node. Parameters ---------- obj : node-like A DOM node. Returns ------- text : str or unicode The text from an individual DOM node. """ raise com.AbstractMethodError(self) def _parse_td(self, obj): """Return the td elements from a row element. Parameters ---------- obj : node-like Returns ------- columns : list of node-like These are the elements of each row, i.e., the columns. """ raise com.AbstractMethodError(self) def _parse_tables(self, doc, match, attrs): """Return all tables from the parsed DOM. Parameters ---------- doc : tree-like The DOM from which to parse the table element. match : str or regular expression The text to search for in the DOM tree. attrs : dict A dictionary of table attributes that can be used to disambiguate multiple tables on a page. Raises ------ ValueError * If `match` does not match any text in the document. Returns ------- tables : list of node-like A list of
elements to be parsed into raw data. """ raise com.AbstractMethodError(self) def _parse_tr(self, table): """Return the list of row elements from the parsed table element. Parameters ---------- table : node-like A table element that contains row elements. Returns ------- rows : list of node-like A list row elements of a table, usually or ... element. """ raise com.AbstractMethodError(self) def _parse_tbody(self, table): """Return the list of tbody elements from the parsed table element. Parameters ---------- table : node-like A table element that contains row elements. Returns ------- tbodys : list of node-like A list of ... elements """ raise com.AbstractMethodError(self) def _parse_tfoot(self, table): """Return the footer of the table if any. Parameters ---------- table : node-like A table element that contains row elements. Returns ------- tfoot : node-like A ... element. """ raise com.AbstractMethodError(self) def _build_doc(self): """Return a tree-like object that can be used to iterate over the DOM. Returns ------- obj : tree-like """ raise com.AbstractMethodError(self) def _build_table(self, table): header = self._parse_raw_thead(table) body = self._parse_raw_tbody(table) footer = self._parse_raw_tfoot(table) return header, body, footer def _parse_raw_thead(self, table): thead = self._parse_thead(table) res = [] if thead: trs = self._parse_tr(thead[0]) for tr in trs: cols = lmap(self._text_getter, self._parse_td(tr)) if any(col != '' for col in cols): res.append(cols) return res def _parse_raw_tfoot(self, table): tfoot = self._parse_tfoot(table) res = [] if tfoot: res = lmap(self._text_getter, self._parse_td(tfoot[0])) return np.atleast_1d( np.array(res).squeeze()) if res and len(res) == 1 else res def _parse_raw_tbody(self, table): tbodies = self._parse_tbody(table) raw_data = [] if tbodies: for tbody in tbodies: raw_data.extend(self._parse_tr(tbody)) else: raw_data.extend(self._parse_tr(table)) return self._parse_raw_data(raw_data) def _handle_hidden_tables(self, tbl_list, attr_name): """Returns list of tables, potentially removing hidden elements Parameters ---------- tbl_list : list of Tag or list of Element Type of list elements will vary depending upon parser used attr_name : str Name of the accessor for retrieving HTML attributes Returns ------- list of Tag or list of Element Return type matches `tbl_list` """ if not self.displayed_only: return tbl_list return [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): super(_BeautifulSoupHtml5LibFrameParser, self).__init__(*args, **kwargs) from bs4 import SoupStrainer self._strainer = SoupStrainer('table') def _text_getter(self, obj): return obj.text def _parse_td(self, row): return row.find_all(('td', 'th')) def _parse_tr(self, element): return element.find_all('tr') def _parse_th(self, element): return element.find_all('th') def _parse_thead(self, table): return table.find_all('thead') def _parse_tbody(self, table): return table.find_all('tbody') def _parse_tfoot(self, table): return table.find_all('tfoot') 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(text=match) is not None): result.append(table) unique_tables.add(table) if not result: raise ValueError("No tables found matching pattern {patt!r}" .format(patt=match.pattern)) return result def _setup_build_doc(self): raw_text = _read(self.io) if not raw_text: raise ValueError('No text parsed from document: {doc}' .format(doc=self.io)) return raw_text def _build_doc(self): from bs4 import BeautifulSoup return BeautifulSoup(self._setup_build_doc(), features='html5lib', from_encoding=self.encoding) def _build_xpath_expr(attrs): """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 = [u("@{key}={val!r}").format(key=k, val=v) for k, v in iteritems(attrs)] return u('[{expr}]').format(expr=' and '.join(s)) _re_namespace = {'re': 'http://exslt.org/regular-expressions'} _valid_schemes = 'http', 'file', 'ftp' 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 __init__(self, *args, **kwargs): super(_LxmlFrameParser, self).__init__(*args, **kwargs) def _text_getter(self, obj): return obj.text_content() def _parse_td(self, row): return row.xpath('.//td|.//th') def _parse_tr(self, table): return table.xpath('.//tr') def _parse_tables(self, doc, match, kwargs): pattern = match.pattern # 1. check all descendants for the given pattern and only search tables # 2. go up the tree until we find a table query = '//table//*[re:test(text(), {patt!r})]/ancestor::table' xpath_expr = u(query).format(patt=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("No tables found matching regex {patt!r}" .format(patt=pattern)) return tables 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.html import parse, fromstring, HTMLParser from lxml.etree import XMLSyntaxError 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, IOError) 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) return r def _parse_tbody(self, table): return table.xpath('.//tbody') def _parse_thead(self, table): return table.xpath('.//thead') def _parse_tfoot(self, table): return table.xpath('.//tfoot') def _parse_raw_thead(self, table): expr = './/thead' thead = table.xpath(expr) res = [] if thead: # Grab any directly descending table headers first ths = thead[0].xpath('./th') if ths: cols = [_remove_whitespace(x.text_content()) for x in ths] if any(col != '' for col in cols): res.append(cols) else: trs = self._parse_tr(thead[0]) for tr in trs: cols = [_remove_whitespace(x.text_content()) for x in self._parse_td(tr)] if any(col != '' for col in cols): res.append(cols) return res def _parse_raw_tfoot(self, table): expr = './/tfoot//th|//tfoot//td' return [_remove_whitespace(x.text_content()) for x in table.xpath(expr)] def _expand_elements(body): lens = Series(lmap(len, body)) lens_max = lens.max() not_max = lens[lens != lens_max] empty = [''] for ind, length in iteritems(not_max): 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: rows = lrange(len(head)) body = head + body if header is None: # special case when a table has
elements. """ raise com.AbstractMethodError(self) def _parse_thead(self, table): """Return the header of a table. Parameters ---------- table : node-like A table element that contains row elements. Returns ------- thead : node-like A
elements header = 0 if rows == [0] else rows if foot: body += [foot] # fill out elements of body that are "ragged" _expand_elements(body) tp = TextParser(body, header=header, **kwargs) df = tp.read() return df _valid_parsers = {'lxml': _LxmlFrameParser, None: _LxmlFrameParser, 'html5lib': _BeautifulSoupHtml5LibFrameParser, 'bs4': _BeautifulSoupHtml5LibFrameParser} def _parser_dispatch(flavor): """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('{invalid!r} is not a valid flavor, valid flavors ' 'are {valid}' .format(invalid=flavor, valid=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") import bs4 if LooseVersion(bs4.__version__) <= LooseVersion('4.2.0'): raise ValueError("A minimum version of BeautifulSoup 4.2.1 " "is required") else: if not _HAS_LXML: raise ImportError("lxml not found, please install it") return _valid_parsers[flavor] def _print_as_set(s): return '{{arg}}'.format(arg=', '.join(pprint_thing(el) for el in s)) def _validate_flavor(flavor): if flavor is None: flavor = 'lxml', 'bs4' elif isinstance(flavor, string_types): flavor = flavor, elif isinstance(flavor, collections.Iterable): if not all(isinstance(flav, string_types) for flav in flavor): raise TypeError('Object of type {typ!r} is not an iterable of ' 'strings' .format(typ=type(flavor).__name__)) else: fmt = '{flavor!r}' if isinstance(flavor, string_types) else '{flavor}' fmt += ' is not a valid flavor' raise ValueError(fmt.format(flavor=flavor)) flavor = tuple(flavor) valid_flavors = set(_valid_parsers) flavor_set = set(flavor) if not flavor_set & valid_flavors: raise ValueError('{invalid} is not a valid set of flavors, valid ' 'flavors are {valid}' .format(invalid=_print_as_set(flavor_set), valid=_print_as_set(valid_flavors))) return flavor def _parse(flavor, io, match, attrs, encoding, displayed_only, **kwargs): flavor = _validate_flavor(flavor) compiled_match = re.compile(match) # you can pass a compiled regex here # hack around python 3 deleting the exception variable retained = None for flav in flavor: parser = _parser_dispatch(flav) p = parser(io, compiled_match, attrs, encoding, displayed_only) try: tables = p.parse_tables() except Exception 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('The flavor {} 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.'.format(flav)) retained = caught else: break else: raise_with_traceback(retained) ret = [] for table in tables: try: ret.append(_data_to_frame(data=table, **kwargs)) except EmptyDataError: # empty table continue return ret def read_html(io, match='.+', flavor=None, header=None, index_col=None, skiprows=None, attrs=None, parse_dates=False, tupleize_cols=None, thousands=',', encoding=None, decimal='.', converters=None, na_values=None, keep_default_na=True, displayed_only=True): r"""Read HTML tables into a ``list`` of ``DataFrame`` objects. Parameters ---------- io : str or file-like A URL, a file-like object, or a raw string containing HTML. 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 or None, container of strings 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 or None, 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 or None, optional The column (or list of columns) to use to create the index. skiprows : int or list-like or slice or None, optional 0-based. Number of rows to skip after parsing the column integer. 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 or None, 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 `__. :: 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 `__. A working draft of the HTML 5 spec can be found `here `__. It contains the latest information on table attributes for the modern web. parse_dates : bool, optional See :func:`~pandas.read_csv` for more details. tupleize_cols : bool, optional If ``False`` try to parse multiple header rows into a :class:`~pandas.MultiIndex`, otherwise return raw tuples. Defaults to ``False``. .. deprecated:: 0.21.0 This argument will be removed and will always convert to MultiIndex thousands : str, optional Separator to use to parse thousands. Defaults to ``','``. encoding : str or None, 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). .. versionadded:: 0.19.0 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. .. versionadded:: 0.19.0 na_values : iterable, default None Custom NA values .. versionadded:: 0.19.0 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 .. versionadded:: 0.19.0 display_only : bool, default True Whether elements with "display: none" should be parsed .. versionadded:: 0.23.0 Returns ------- dfs : list of DataFrames Notes ----- Before using this function you should read the :ref:`gotchas about the HTML parsing libraries `. 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 ```` elements and only for ```` and ```` or ``
`` rows and ```` elements within each ``
`` element in the table. ```` stands for "table data". Similar to :func:`~pandas.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 ` for some examples of reading in HTML tables. See Also -------- pandas.read_csv """ _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)') _validate_header_arg(header) return _parse(flavor=flavor, io=io, match=match, header=header, index_col=index_col, skiprows=skiprows, parse_dates=parse_dates, tupleize_cols=tupleize_cols, thousands=thousands, attrs=attrs, encoding=encoding, decimal=decimal, converters=converters, na_values=na_values, keep_default_na=keep_default_na, displayed_only=displayed_only)