from functools import partial from importlib import reload from io import BytesIO, StringIO import os import re import threading from urllib.error import URLError import numpy as np from numpy.random import rand import pytest from pandas.compat import is_platform_windows from pandas.errors import ParserError import pandas.util._test_decorators as td from pandas import DataFrame, Index, MultiIndex, Series, Timestamp, date_range, read_csv import pandas._testing as tm from pandas.io.common import file_path_to_url import pandas.io.html from pandas.io.html import read_html HERE = os.path.dirname(__file__) @pytest.fixture( params=[ "chinese_utf-16.html", "chinese_utf-32.html", "chinese_utf-8.html", "letz_latin1.html", ] ) def html_encoding_file(request, datapath): """Parametrized fixture for HTML encoding test filenames.""" return datapath("io", "data", "html_encoding", request.param) def assert_framelist_equal(list1, list2, *args, **kwargs): assert len(list1) == len(list2), ( "lists are not of equal size " "len(list1) == {0}, " "len(list2) == {1}".format(len(list1), len(list2)) ) msg = "not all list elements are DataFrames" both_frames = all( map( lambda x, y: isinstance(x, DataFrame) and isinstance(y, DataFrame), list1, list2, ) ) assert both_frames, msg for frame_i, frame_j in zip(list1, list2): tm.assert_frame_equal(frame_i, frame_j, *args, **kwargs) assert not frame_i.empty, "frames are both empty" @td.skip_if_no("bs4") def test_bs4_version_fails(monkeypatch, datapath): import bs4 monkeypatch.setattr(bs4, "__version__", "4.2") with pytest.raises(ImportError, match="Pandas requires version"): read_html(datapath("io", "data", "html", "spam.html"), flavor="bs4") def test_invalid_flavor(): url = "google.com" flavor = "invalid flavor" msg = r"\{" + flavor + r"\} is not a valid set of flavors" with pytest.raises(ValueError, match=msg): read_html(url, "google", flavor=flavor) @td.skip_if_no("bs4") @td.skip_if_no("lxml") def test_same_ordering(datapath): filename = datapath("io", "data", "html", "valid_markup.html") dfs_lxml = read_html(filename, index_col=0, flavor=["lxml"]) dfs_bs4 = read_html(filename, index_col=0, flavor=["bs4"]) assert_framelist_equal(dfs_lxml, dfs_bs4) @pytest.mark.parametrize( "flavor", [ pytest.param("bs4", marks=td.skip_if_no("bs4")), pytest.param("lxml", marks=td.skip_if_no("lxml")), ], scope="class", ) class TestReadHtml: @pytest.fixture(autouse=True) def set_files(self, datapath): self.spam_data = datapath("io", "data", "html", "spam.html") self.spam_data_kwargs = {} self.spam_data_kwargs["encoding"] = "UTF-8" self.banklist_data = datapath("io", "data", "html", "banklist.html") @pytest.fixture(autouse=True, scope="function") def set_defaults(self, flavor, request): self.read_html = partial(read_html, flavor=flavor) yield def test_to_html_compat(self): df = ( tm.makeCustomDataframe( 4, 3, data_gen_f=lambda *args: rand(), c_idx_names=False, r_idx_names=False, ) .applymap("{0:.3f}".format) .astype(float) ) out = df.to_html() res = self.read_html(out, attrs={"class": "dataframe"}, index_col=0)[0] tm.assert_frame_equal(res, df) @tm.network def test_banklist_url(self): url = "http://www.fdic.gov/bank/individual/failed/banklist.html" df1 = self.read_html( url, "First Federal Bank of Florida", attrs={"id": "table"} ) df2 = self.read_html(url, "Metcalf Bank", attrs={"id": "table"}) assert_framelist_equal(df1, df2) @tm.network def test_spam_url(self): url = ( "https://raw.githubusercontent.com/pandas-dev/pandas/master/" "pandas/tests/io/data/html/spam.html" ) df1 = self.read_html(url, ".*Water.*") df2 = self.read_html(url, "Unit") assert_framelist_equal(df1, df2) @pytest.mark.slow def test_banklist(self): df1 = self.read_html(self.banklist_data, ".*Florida.*", attrs={"id": "table"}) df2 = self.read_html(self.banklist_data, "Metcalf Bank", attrs={"id": "table"}) assert_framelist_equal(df1, df2) def test_spam(self): df1 = self.read_html(self.spam_data, ".*Water.*") df2 = self.read_html(self.spam_data, "Unit") assert_framelist_equal(df1, df2) assert df1[0].iloc[0, 0] == "Proximates" assert df1[0].columns[0] == "Nutrient" def test_spam_no_match(self): dfs = self.read_html(self.spam_data) for df in dfs: assert isinstance(df, DataFrame) def test_banklist_no_match(self): dfs = self.read_html(self.banklist_data, attrs={"id": "table"}) for df in dfs: assert isinstance(df, DataFrame) def test_spam_header(self): df = self.read_html(self.spam_data, ".*Water.*", header=2)[0] assert df.columns[0] == "Proximates" assert not df.empty def test_skiprows_int(self): df1 = self.read_html(self.spam_data, ".*Water.*", skiprows=1) df2 = self.read_html(self.spam_data, "Unit", skiprows=1) assert_framelist_equal(df1, df2) def test_skiprows_range(self): df1 = self.read_html(self.spam_data, ".*Water.*", skiprows=range(2))[0] df2 = self.read_html(self.spam_data, "Unit", skiprows=range(2))[0] tm.assert_frame_equal(df1, df2) def test_skiprows_list(self): df1 = self.read_html(self.spam_data, ".*Water.*", skiprows=[1, 2]) df2 = self.read_html(self.spam_data, "Unit", skiprows=[2, 1]) assert_framelist_equal(df1, df2) def test_skiprows_set(self): df1 = self.read_html(self.spam_data, ".*Water.*", skiprows={1, 2}) df2 = self.read_html(self.spam_data, "Unit", skiprows={2, 1}) assert_framelist_equal(df1, df2) def test_skiprows_slice(self): df1 = self.read_html(self.spam_data, ".*Water.*", skiprows=1) df2 = self.read_html(self.spam_data, "Unit", skiprows=1) assert_framelist_equal(df1, df2) def test_skiprows_slice_short(self): df1 = self.read_html(self.spam_data, ".*Water.*", skiprows=slice(2)) df2 = self.read_html(self.spam_data, "Unit", skiprows=slice(2)) assert_framelist_equal(df1, df2) def test_skiprows_slice_long(self): df1 = self.read_html(self.spam_data, ".*Water.*", skiprows=slice(2, 5)) df2 = self.read_html(self.spam_data, "Unit", skiprows=slice(4, 1, -1)) assert_framelist_equal(df1, df2) def test_skiprows_ndarray(self): df1 = self.read_html(self.spam_data, ".*Water.*", skiprows=np.arange(2)) df2 = self.read_html(self.spam_data, "Unit", skiprows=np.arange(2)) assert_framelist_equal(df1, df2) def test_skiprows_invalid(self): with pytest.raises(TypeError, match=("is not a valid type for skipping rows")): self.read_html(self.spam_data, ".*Water.*", skiprows="asdf") def test_index(self): df1 = self.read_html(self.spam_data, ".*Water.*", index_col=0) df2 = self.read_html(self.spam_data, "Unit", index_col=0) assert_framelist_equal(df1, df2) def test_header_and_index_no_types(self): df1 = self.read_html(self.spam_data, ".*Water.*", header=1, index_col=0) df2 = self.read_html(self.spam_data, "Unit", header=1, index_col=0) assert_framelist_equal(df1, df2) def test_header_and_index_with_types(self): df1 = self.read_html(self.spam_data, ".*Water.*", header=1, index_col=0) df2 = self.read_html(self.spam_data, "Unit", header=1, index_col=0) assert_framelist_equal(df1, df2) def test_infer_types(self): # 10892 infer_types removed df1 = self.read_html(self.spam_data, ".*Water.*", index_col=0) df2 = self.read_html(self.spam_data, "Unit", index_col=0) assert_framelist_equal(df1, df2) def test_string_io(self): with open(self.spam_data, **self.spam_data_kwargs) as f: data1 = StringIO(f.read()) with open(self.spam_data, **self.spam_data_kwargs) as f: data2 = StringIO(f.read()) df1 = self.read_html(data1, ".*Water.*") df2 = self.read_html(data2, "Unit") assert_framelist_equal(df1, df2) def test_string(self): with open(self.spam_data, **self.spam_data_kwargs) as f: data = f.read() df1 = self.read_html(data, ".*Water.*") df2 = self.read_html(data, "Unit") assert_framelist_equal(df1, df2) def test_file_like(self): with open(self.spam_data, **self.spam_data_kwargs) as f: df1 = self.read_html(f, ".*Water.*") with open(self.spam_data, **self.spam_data_kwargs) as f: df2 = self.read_html(f, "Unit") assert_framelist_equal(df1, df2) @tm.network def test_bad_url_protocol(self): with pytest.raises(URLError): self.read_html("git://github.com", match=".*Water.*") @tm.network @pytest.mark.slow def test_invalid_url(self): try: with pytest.raises(URLError): self.read_html("http://www.a23950sdfa908sd.com", match=".*Water.*") except ValueError as e: assert "No tables found" in str(e) @pytest.mark.slow def test_file_url(self): url = self.banklist_data dfs = self.read_html( file_path_to_url(os.path.abspath(url)), "First", attrs={"id": "table"} ) assert isinstance(dfs, list) for df in dfs: assert isinstance(df, DataFrame) @pytest.mark.slow def test_invalid_table_attrs(self): url = self.banklist_data with pytest.raises(ValueError, match="No tables found"): self.read_html( url, "First Federal Bank of Florida", attrs={"id": "tasdfable"} ) def _bank_data(self, *args, **kwargs): return self.read_html( self.banklist_data, "Metcalf", attrs={"id": "table"}, *args, **kwargs ) @pytest.mark.slow def test_multiindex_header(self): df = self._bank_data(header=[0, 1])[0] assert isinstance(df.columns, MultiIndex) @pytest.mark.slow def test_multiindex_index(self): df = self._bank_data(index_col=[0, 1])[0] assert isinstance(df.index, MultiIndex) @pytest.mark.slow def test_multiindex_header_index(self): df = self._bank_data(header=[0, 1], index_col=[0, 1])[0] assert isinstance(df.columns, MultiIndex) assert isinstance(df.index, MultiIndex) @pytest.mark.slow def test_multiindex_header_skiprows_tuples(self): df = self._bank_data(header=[0, 1], skiprows=1)[0] assert isinstance(df.columns, MultiIndex) @pytest.mark.slow def test_multiindex_header_skiprows(self): df = self._bank_data(header=[0, 1], skiprows=1)[0] assert isinstance(df.columns, MultiIndex) @pytest.mark.slow def test_multiindex_header_index_skiprows(self): df = self._bank_data(header=[0, 1], index_col=[0, 1], skiprows=1)[0] assert isinstance(df.index, MultiIndex) assert isinstance(df.columns, MultiIndex) @pytest.mark.slow def test_regex_idempotency(self): url = self.banklist_data dfs = self.read_html( file_path_to_url(os.path.abspath(url)), match=re.compile(re.compile("Florida")), attrs={"id": "table"}, ) assert isinstance(dfs, list) for df in dfs: assert isinstance(df, DataFrame) def test_negative_skiprows(self): msg = r"\(you passed a negative value\)" with pytest.raises(ValueError, match=msg): self.read_html(self.spam_data, "Water", skiprows=-1) @tm.network def test_multiple_matches(self): url = "https://docs.python.org/2/" dfs = self.read_html(url, match="Python") assert len(dfs) > 1 @tm.network def test_python_docs_table(self): url = "https://docs.python.org/2/" dfs = self.read_html(url, match="Python") zz = [df.iloc[0, 0][0:4] for df in dfs] assert sorted(zz) == sorted(["Repo", "What"]) @pytest.mark.slow def test_thousands_macau_stats(self, datapath): all_non_nan_table_index = -2 macau_data = datapath("io", "data", "html", "macau.html") dfs = self.read_html(macau_data, index_col=0, attrs={"class": "style1"}) df = dfs[all_non_nan_table_index] assert not any(s.isna().any() for _, s in df.items()) @pytest.mark.slow def test_thousands_macau_index_col(self, datapath, request): # https://github.com/pandas-dev/pandas/issues/29622 # This tests fails for bs4 >= 4.8.0 - so handle xfail accordingly if self.read_html.keywords.get("flavor") == "bs4" and td.safe_import( "bs4", "4.8.0" ): reason = "fails for bs4 version >= 4.8.0" request.node.add_marker(pytest.mark.xfail(reason=reason)) all_non_nan_table_index = -2 macau_data = datapath("io", "data", "html", "macau.html") dfs = self.read_html(macau_data, index_col=0, header=0) df = dfs[all_non_nan_table_index] assert not any(s.isna().any() for _, s in df.items()) def test_empty_tables(self): """ Make sure that read_html ignores empty tables. """ html = """
A B
1 2
""" result = self.read_html(html) assert len(result) == 1 def test_multiple_tbody(self): # GH-20690 # Read all tbody tags within a single table. result = self.read_html( """
A B
1 2
3 4
""" )[0] expected = DataFrame(data=[[1, 2], [3, 4]], columns=["A", "B"]) tm.assert_frame_equal(result, expected) def test_header_and_one_column(self): """ Don't fail with bs4 when there is a header and only one column as described in issue #9178 """ result = self.read_html( """
Header
first
""" )[0] expected = DataFrame(data={"Header": "first"}, index=[0]) tm.assert_frame_equal(result, expected) def test_thead_without_tr(self): """ Ensure parser adds within on malformed HTML. """ result = self.read_html( """
Country Municipality Year
Ukraine Odessa 1944
""" )[0] expected = DataFrame( data=[["Ukraine", "Odessa", 1944]], columns=["Country", "Municipality", "Year"], ) tm.assert_frame_equal(result, expected) def test_tfoot_read(self): """ Make sure that read_html reads tfoot, containing td or th. Ignores empty tfoot """ data_template = """ {footer}
A B
bodyA bodyB
""" expected1 = DataFrame(data=[["bodyA", "bodyB"]], columns=["A", "B"]) expected2 = DataFrame( data=[["bodyA", "bodyB"], ["footA", "footB"]], columns=["A", "B"] ) data1 = data_template.format(footer="") data2 = data_template.format(footer="footAfootB") result1 = self.read_html(data1)[0] result2 = self.read_html(data2)[0] tm.assert_frame_equal(result1, expected1) tm.assert_frame_equal(result2, expected2) def test_parse_header_of_non_string_column(self): # GH5048: if header is specified explicitly, an int column should be # parsed as int while its header is parsed as str result = self.read_html( """
S I
text 1944
""", header=0, )[0] expected = DataFrame([["text", 1944]], columns=("S", "I")) tm.assert_frame_equal(result, expected) def test_nyse_wsj_commas_table(self, datapath): data = datapath("io", "data", "html", "nyse_wsj.html") df = self.read_html(data, index_col=0, header=0, attrs={"class": "mdcTable"})[0] expected = Index( [ "Issue(Roll over for charts and headlines)", "Volume", "Price", "Chg", "% Chg", ] ) nrows = 100 assert df.shape[0] == nrows tm.assert_index_equal(df.columns, expected) @pytest.mark.slow def test_banklist_header(self, datapath): from pandas.io.html import _remove_whitespace def try_remove_ws(x): try: return _remove_whitespace(x) except AttributeError: return x df = self.read_html(self.banklist_data, "Metcalf", attrs={"id": "table"})[0] ground_truth = read_csv( datapath("io", "data", "csv", "banklist.csv"), converters={"Updated Date": Timestamp, "Closing Date": Timestamp}, ) assert df.shape == ground_truth.shape old = [ "First Vietnamese American BankIn Vietnamese", "Westernbank Puerto RicoEn Espanol", "R-G Premier Bank of Puerto RicoEn Espanol", "EurobankEn Espanol", "Sanderson State BankEn Espanol", "Washington Mutual Bank(Including its subsidiary Washington " "Mutual Bank FSB)", "Silver State BankEn Espanol", "AmTrade International BankEn Espanol", "Hamilton Bank, NAEn Espanol", "The Citizens Savings BankPioneer Community Bank, Inc.", ] new = [ "First Vietnamese American Bank", "Westernbank Puerto Rico", "R-G Premier Bank of Puerto Rico", "Eurobank", "Sanderson State Bank", "Washington Mutual Bank", "Silver State Bank", "AmTrade International Bank", "Hamilton Bank, NA", "The Citizens Savings Bank", ] dfnew = df.applymap(try_remove_ws).replace(old, new) gtnew = ground_truth.applymap(try_remove_ws) converted = dfnew._convert(datetime=True, numeric=True) date_cols = ["Closing Date", "Updated Date"] converted[date_cols] = converted[date_cols]._convert(datetime=True, coerce=True) tm.assert_frame_equal(converted, gtnew) @pytest.mark.slow def test_gold_canyon(self): gc = "Gold Canyon" with open(self.banklist_data, "r") as f: raw_text = f.read() assert gc in raw_text df = self.read_html(self.banklist_data, "Gold Canyon", attrs={"id": "table"})[0] assert gc in df.to_string() def test_different_number_of_cols(self): expected = self.read_html( """
C_l0_g0 C_l0_g1 C_l0_g2 C_l0_g3 C_l0_g4
R_l0_g0 0.763 0.233 nan nan nan
R_l0_g1 0.244 0.285 0.392 0.137 0.222
""", index_col=0, )[0] result = self.read_html( """
C_l0_g0 C_l0_g1 C_l0_g2 C_l0_g3 C_l0_g4
R_l0_g0 0.763 0.233
R_l0_g1 0.244 0.285 0.392 0.137 0.222
""", index_col=0, )[0] tm.assert_frame_equal(result, expected) def test_colspan_rowspan_1(self): # GH17054 result = self.read_html( """
A B C
a b c
""" )[0] expected = DataFrame([["a", "b", "c"]], columns=["A", "B", "C"]) tm.assert_frame_equal(result, expected) def test_colspan_rowspan_copy_values(self): # GH17054 # In ASCII, with lowercase letters being copies: # # X x Y Z W # A B b z C result = self.read_html( """
X Y Z W
A B C
""", header=0, )[0] expected = DataFrame( data=[["A", "B", "B", "Z", "C"]], columns=["X", "X.1", "Y", "Z", "W"] ) tm.assert_frame_equal(result, expected) def test_colspan_rowspan_both_not_1(self): # GH17054 # In ASCII, with lowercase letters being copies: # # A B b b C # a b b b D result = self.read_html( """
A B C
D
""", header=0, )[0] expected = DataFrame( data=[["A", "B", "B", "B", "D"]], columns=["A", "B", "B.1", "B.2", "C"] ) tm.assert_frame_equal(result, expected) def test_rowspan_at_end_of_row(self): # GH17054 # In ASCII, with lowercase letters being copies: # # A B # C b result = self.read_html( """
A B
C
""", header=0, )[0] expected = DataFrame(data=[["C", "B"]], columns=["A", "B"]) tm.assert_frame_equal(result, expected) def test_rowspan_only_rows(self): # GH17054 result = self.read_html( """
A B
""", header=0, )[0] expected = DataFrame(data=[["A", "B"], ["A", "B"]], columns=["A", "B"]) tm.assert_frame_equal(result, expected) def test_header_inferred_from_rows_with_only_th(self): # GH17054 result = self.read_html( """
A B
a b
1 2
""" )[0] columns = MultiIndex(levels=[["A", "B"], ["a", "b"]], codes=[[0, 1], [0, 1]]) expected = DataFrame(data=[[1, 2]], columns=columns) tm.assert_frame_equal(result, expected) def test_parse_dates_list(self): df = DataFrame({"date": date_range("1/1/2001", periods=10)}) expected = df.to_html() res = self.read_html(expected, parse_dates=[1], index_col=0) tm.assert_frame_equal(df, res[0]) res = self.read_html(expected, parse_dates=["date"], index_col=0) tm.assert_frame_equal(df, res[0]) def test_parse_dates_combine(self): raw_dates = Series(date_range("1/1/2001", periods=10)) df = DataFrame( { "date": raw_dates.map(lambda x: str(x.date())), "time": raw_dates.map(lambda x: str(x.time())), } ) res = self.read_html( df.to_html(), parse_dates={"datetime": [1, 2]}, index_col=1 ) newdf = DataFrame({"datetime": raw_dates}) tm.assert_frame_equal(newdf, res[0]) def test_computer_sales_page(self, datapath): data = datapath("io", "data", "html", "computer_sales_page.html") msg = ( r"Passed header=\[0,1\] are too many " r"rows for this multi_index of columns" ) with pytest.raises(ParserError, match=msg): self.read_html(data, header=[0, 1]) data = datapath("io", "data", "html", "computer_sales_page.html") assert self.read_html(data, header=[1, 2]) def test_wikipedia_states_table(self, datapath): data = datapath("io", "data", "html", "wikipedia_states.html") assert os.path.isfile(data), f"{repr(data)} is not a file" assert os.path.getsize(data), f"{repr(data)} is an empty file" result = self.read_html(data, "Arizona", header=1)[0] assert result["sq mi"].dtype == np.dtype("float64") def test_parser_error_on_empty_header_row(self): msg = ( r"Passed header=\[0,1\] are too many " r"rows for this multi_index of columns" ) with pytest.raises(ParserError, match=msg): self.read_html( """
AB
ab
""", header=[0, 1], ) def test_decimal_rows(self): # GH 12907 result = self.read_html( """
Header
1100#101
""", decimal="#", )[0] expected = DataFrame(data={"Header": 1100.101}, index=[0]) assert result["Header"].dtype == np.dtype("float64") tm.assert_frame_equal(result, expected) def test_bool_header_arg(self): # GH 6114 for arg in [True, False]: with pytest.raises(TypeError): self.read_html(self.spam_data, header=arg) def test_converters(self): # GH 13461 result = self.read_html( """
a
0.763
0.244
""", converters={"a": str}, )[0] expected = DataFrame({"a": ["0.763", "0.244"]}) tm.assert_frame_equal(result, expected) def test_na_values(self): # GH 13461 result = self.read_html( """
a
0.763
0.244
""", na_values=[0.244], )[0] expected = DataFrame({"a": [0.763, np.nan]}) tm.assert_frame_equal(result, expected) def test_keep_default_na(self): html_data = """
a
N/A
NA
""" expected_df = DataFrame({"a": ["N/A", "NA"]}) html_df = self.read_html(html_data, keep_default_na=False)[0] tm.assert_frame_equal(expected_df, html_df) expected_df = DataFrame({"a": [np.nan, np.nan]}) html_df = self.read_html(html_data, keep_default_na=True)[0] tm.assert_frame_equal(expected_df, html_df) def test_preserve_empty_rows(self): result = self.read_html( """
A B
a b
""" )[0] expected = DataFrame(data=[["a", "b"], [np.nan, np.nan]], columns=["A", "B"]) tm.assert_frame_equal(result, expected) def test_ignore_empty_rows_when_inferring_header(self): result = self.read_html( """
AB
ab
12
""" )[0] columns = MultiIndex(levels=[["A", "B"], ["a", "b"]], codes=[[0, 1], [0, 1]]) expected = DataFrame(data=[[1, 2]], columns=columns) tm.assert_frame_equal(result, expected) def test_multiple_header_rows(self): # Issue #13434 expected_df = DataFrame( data=[("Hillary", 68, "D"), ("Bernie", 74, "D"), ("Donald", 69, "R")] ) expected_df.columns = [ ["Unnamed: 0_level_0", "Age", "Party"], ["Name", "Unnamed: 1_level_1", "Unnamed: 2_level_1"], ] html = expected_df.to_html(index=False) html_df = self.read_html(html)[0] tm.assert_frame_equal(expected_df, html_df) def test_works_on_valid_markup(self, datapath): filename = datapath("io", "data", "html", "valid_markup.html") dfs = self.read_html(filename, index_col=0) assert isinstance(dfs, list) assert isinstance(dfs[0], DataFrame) @pytest.mark.slow def test_fallback_success(self, datapath): banklist_data = datapath("io", "data", "html", "banklist.html") self.read_html(banklist_data, ".*Water.*", flavor=["lxml", "html5lib"]) def test_to_html_timestamp(self): rng = date_range("2000-01-01", periods=10) df = DataFrame(np.random.randn(10, 4), index=rng) result = df.to_html() assert "2000-01-01" in result @pytest.mark.parametrize( "displayed_only,exp0,exp1", [ (True, DataFrame(["foo"]), None), (False, DataFrame(["foo bar baz qux"]), DataFrame(["foo"])), ], ) def test_displayed_only(self, displayed_only, exp0, exp1): # GH 20027 data = StringIO( """
foo bar baz qux
foo
""" ) dfs = self.read_html(data, displayed_only=displayed_only) tm.assert_frame_equal(dfs[0], exp0) if exp1 is not None: tm.assert_frame_equal(dfs[1], exp1) else: assert len(dfs) == 1 # Should not parse hidden table def test_encode(self, html_encoding_file): base_path = os.path.basename(html_encoding_file) root = os.path.splitext(base_path)[0] _, encoding = root.split("_") try: with open(html_encoding_file, "rb") as fobj: from_string = self.read_html( fobj.read(), encoding=encoding, index_col=0 ).pop() with open(html_encoding_file, "rb") as fobj: from_file_like = self.read_html( BytesIO(fobj.read()), encoding=encoding, index_col=0 ).pop() from_filename = self.read_html( html_encoding_file, encoding=encoding, index_col=0 ).pop() tm.assert_frame_equal(from_string, from_file_like) tm.assert_frame_equal(from_string, from_filename) except Exception: # seems utf-16/32 fail on windows if is_platform_windows(): if "16" in encoding or "32" in encoding: pytest.skip() raise def test_parse_failure_unseekable(self): # Issue #17975 if self.read_html.keywords.get("flavor") == "lxml": pytest.skip("Not applicable for lxml") class UnseekableStringIO(StringIO): def seekable(self): return False bad = UnseekableStringIO( """
spameggs
""" ) assert self.read_html(bad) with pytest.raises(ValueError, match="passed a non-rewindable file object"): self.read_html(bad) def test_parse_failure_rewinds(self): # Issue #17975 class MockFile: def __init__(self, data): self.data = data self.at_end = False def read(self, size=None): data = "" if self.at_end else self.data self.at_end = True return data def seek(self, offset): self.at_end = False def seekable(self): return True good = MockFile("
spam
eggs
") bad = MockFile("
spameggs
") assert self.read_html(good) assert self.read_html(bad) @pytest.mark.slow def test_importcheck_thread_safety(self, datapath): # see gh-16928 class ErrorThread(threading.Thread): def run(self): try: super().run() except Exception as err: self.err = err else: self.err = None # force import check by reinitalising global vars in html.py reload(pandas.io.html) filename = datapath("io", "data", "html", "valid_markup.html") helper_thread1 = ErrorThread(target=self.read_html, args=(filename,)) helper_thread2 = ErrorThread(target=self.read_html, args=(filename,)) helper_thread1.start() helper_thread2.start() while helper_thread1.is_alive() or helper_thread2.is_alive(): pass assert None is helper_thread1.err is helper_thread2.err