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1627 lines
53 KiB
1627 lines
53 KiB
from collections.abc import Iterator
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from functools import partial
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from io import (
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BytesIO,
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StringIO,
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)
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import os
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from pathlib import Path
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import re
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import threading
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from urllib.error import URLError
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import numpy as np
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import pytest
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from pandas.compat import is_platform_windows
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import pandas.util._test_decorators as td
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import pandas as pd
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from pandas import (
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NA,
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DataFrame,
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MultiIndex,
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Series,
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Timestamp,
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date_range,
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read_csv,
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read_html,
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to_datetime,
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)
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import pandas._testing as tm
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from pandas.core.arrays import (
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ArrowStringArray,
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StringArray,
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)
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from pandas.io.common import file_path_to_url
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@pytest.fixture(
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params=[
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"chinese_utf-16.html",
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"chinese_utf-32.html",
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"chinese_utf-8.html",
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"letz_latin1.html",
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]
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)
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def html_encoding_file(request, datapath):
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"""Parametrized fixture for HTML encoding test filenames."""
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return datapath("io", "data", "html_encoding", request.param)
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def assert_framelist_equal(list1, list2, *args, **kwargs):
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assert len(list1) == len(list2), (
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"lists are not of equal size "
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f"len(list1) == {len(list1)}, "
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f"len(list2) == {len(list2)}"
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)
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msg = "not all list elements are DataFrames"
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both_frames = all(
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map(
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lambda x, y: isinstance(x, DataFrame) and isinstance(y, DataFrame),
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list1,
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list2,
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)
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)
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assert both_frames, msg
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for frame_i, frame_j in zip(list1, list2):
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tm.assert_frame_equal(frame_i, frame_j, *args, **kwargs)
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assert not frame_i.empty, "frames are both empty"
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def test_bs4_version_fails(monkeypatch, datapath):
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bs4 = pytest.importorskip("bs4")
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pytest.importorskip("html5lib")
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monkeypatch.setattr(bs4, "__version__", "4.2")
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with pytest.raises(ImportError, match="Pandas requires version"):
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read_html(datapath("io", "data", "html", "spam.html"), flavor="bs4")
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def test_invalid_flavor():
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url = "google.com"
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flavor = "invalid flavor"
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msg = r"\{" + flavor + r"\} is not a valid set of flavors"
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with pytest.raises(ValueError, match=msg):
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read_html(StringIO(url), match="google", flavor=flavor)
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def test_same_ordering(datapath):
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pytest.importorskip("bs4")
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pytest.importorskip("lxml")
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pytest.importorskip("html5lib")
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filename = datapath("io", "data", "html", "valid_markup.html")
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dfs_lxml = read_html(filename, index_col=0, flavor=["lxml"])
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dfs_bs4 = read_html(filename, index_col=0, flavor=["bs4"])
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assert_framelist_equal(dfs_lxml, dfs_bs4)
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@pytest.mark.parametrize(
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"flavor",
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[
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pytest.param("bs4", marks=[td.skip_if_no("bs4"), td.skip_if_no("html5lib")]),
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pytest.param("lxml", marks=td.skip_if_no("lxml")),
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],
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)
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class TestReadHtml:
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def test_literal_html_deprecation(self):
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# GH 53785
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msg = (
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"Passing literal html to 'read_html' is deprecated and "
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"will be removed in a future version. To read from a "
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"literal string, wrap it in a 'StringIO' object."
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)
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with tm.assert_produces_warning(FutureWarning, match=msg):
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self.read_html(
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"""<table>
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<thead>
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<tr>
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<th>A</th>
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<th>B</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td>1</td>
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<td>2</td>
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</tr>
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</tbody>
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<tbody>
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<tr>
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<td>3</td>
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<td>4</td>
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</tr>
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</tbody>
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</table>"""
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)
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@pytest.fixture
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def spam_data(self, datapath):
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return datapath("io", "data", "html", "spam.html")
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@pytest.fixture
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def banklist_data(self, datapath):
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return datapath("io", "data", "html", "banklist.html")
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@pytest.fixture(autouse=True)
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def set_defaults(self, flavor):
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self.read_html = partial(read_html, flavor=flavor)
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yield
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def test_to_html_compat(self):
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df = (
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tm.makeCustomDataframe(
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4,
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3,
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data_gen_f=lambda *args: np.random.default_rng(2).random(),
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c_idx_names=False,
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r_idx_names=False,
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)
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# pylint: disable-next=consider-using-f-string
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.map("{:.3f}".format).astype(float)
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)
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out = df.to_html()
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res = self.read_html(StringIO(out), attrs={"class": "dataframe"}, index_col=0)[
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0
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]
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tm.assert_frame_equal(res, df)
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def test_dtype_backend(self, string_storage, dtype_backend):
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# GH#50286
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df = DataFrame(
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{
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"a": Series([1, np.nan, 3], dtype="Int64"),
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"b": Series([1, 2, 3], dtype="Int64"),
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"c": Series([1.5, np.nan, 2.5], dtype="Float64"),
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"d": Series([1.5, 2.0, 2.5], dtype="Float64"),
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"e": [True, False, None],
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"f": [True, False, True],
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"g": ["a", "b", "c"],
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"h": ["a", "b", None],
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}
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)
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if string_storage == "python":
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string_array = StringArray(np.array(["a", "b", "c"], dtype=np.object_))
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string_array_na = StringArray(np.array(["a", "b", NA], dtype=np.object_))
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else:
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pa = pytest.importorskip("pyarrow")
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string_array = ArrowStringArray(pa.array(["a", "b", "c"]))
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string_array_na = ArrowStringArray(pa.array(["a", "b", None]))
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out = df.to_html(index=False)
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with pd.option_context("mode.string_storage", string_storage):
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result = self.read_html(StringIO(out), dtype_backend=dtype_backend)[0]
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expected = DataFrame(
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{
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"a": Series([1, np.nan, 3], dtype="Int64"),
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"b": Series([1, 2, 3], dtype="Int64"),
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"c": Series([1.5, np.nan, 2.5], dtype="Float64"),
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"d": Series([1.5, 2.0, 2.5], dtype="Float64"),
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"e": Series([True, False, NA], dtype="boolean"),
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"f": Series([True, False, True], dtype="boolean"),
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"g": string_array,
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"h": string_array_na,
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}
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)
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if dtype_backend == "pyarrow":
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import pyarrow as pa
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from pandas.arrays import ArrowExtensionArray
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expected = DataFrame(
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{
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col: ArrowExtensionArray(pa.array(expected[col], from_pandas=True))
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for col in expected.columns
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}
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)
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tm.assert_frame_equal(result, expected)
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@pytest.mark.network
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@pytest.mark.single_cpu
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def test_banklist_url(self, httpserver, banklist_data):
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with open(banklist_data, encoding="utf-8") as f:
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httpserver.serve_content(content=f.read())
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df1 = self.read_html(
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# lxml cannot find attrs leave out for now
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httpserver.url,
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match="First Federal Bank of Florida", # attrs={"class": "dataTable"}
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)
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# lxml cannot find attrs leave out for now
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df2 = self.read_html(
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httpserver.url,
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match="Metcalf Bank",
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) # attrs={"class": "dataTable"})
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assert_framelist_equal(df1, df2)
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@pytest.mark.network
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@pytest.mark.single_cpu
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def test_spam_url(self, httpserver, spam_data):
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with open(spam_data, encoding="utf-8") as f:
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httpserver.serve_content(content=f.read())
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df1 = self.read_html(httpserver.url, match=".*Water.*")
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df2 = self.read_html(httpserver.url, match="Unit")
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assert_framelist_equal(df1, df2)
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@pytest.mark.slow
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def test_banklist(self, banklist_data):
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df1 = self.read_html(banklist_data, match=".*Florida.*", attrs={"id": "table"})
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df2 = self.read_html(banklist_data, match="Metcalf Bank", attrs={"id": "table"})
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assert_framelist_equal(df1, df2)
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def test_spam(self, spam_data):
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df1 = self.read_html(spam_data, match=".*Water.*")
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df2 = self.read_html(spam_data, match="Unit")
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assert_framelist_equal(df1, df2)
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assert df1[0].iloc[0, 0] == "Proximates"
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assert df1[0].columns[0] == "Nutrient"
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def test_spam_no_match(self, spam_data):
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dfs = self.read_html(spam_data)
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for df in dfs:
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assert isinstance(df, DataFrame)
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def test_banklist_no_match(self, banklist_data):
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dfs = self.read_html(banklist_data, attrs={"id": "table"})
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for df in dfs:
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assert isinstance(df, DataFrame)
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def test_spam_header(self, spam_data):
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df = self.read_html(spam_data, match=".*Water.*", header=2)[0]
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assert df.columns[0] == "Proximates"
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assert not df.empty
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def test_skiprows_int(self, spam_data):
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df1 = self.read_html(spam_data, match=".*Water.*", skiprows=1)
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df2 = self.read_html(spam_data, match="Unit", skiprows=1)
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assert_framelist_equal(df1, df2)
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def test_skiprows_range(self, spam_data):
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df1 = self.read_html(spam_data, match=".*Water.*", skiprows=range(2))
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df2 = self.read_html(spam_data, match="Unit", skiprows=range(2))
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assert_framelist_equal(df1, df2)
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def test_skiprows_list(self, spam_data):
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df1 = self.read_html(spam_data, match=".*Water.*", skiprows=[1, 2])
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df2 = self.read_html(spam_data, match="Unit", skiprows=[2, 1])
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assert_framelist_equal(df1, df2)
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def test_skiprows_set(self, spam_data):
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df1 = self.read_html(spam_data, match=".*Water.*", skiprows={1, 2})
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df2 = self.read_html(spam_data, match="Unit", skiprows={2, 1})
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assert_framelist_equal(df1, df2)
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def test_skiprows_slice(self, spam_data):
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df1 = self.read_html(spam_data, match=".*Water.*", skiprows=1)
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df2 = self.read_html(spam_data, match="Unit", skiprows=1)
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assert_framelist_equal(df1, df2)
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def test_skiprows_slice_short(self, spam_data):
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df1 = self.read_html(spam_data, match=".*Water.*", skiprows=slice(2))
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df2 = self.read_html(spam_data, match="Unit", skiprows=slice(2))
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assert_framelist_equal(df1, df2)
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def test_skiprows_slice_long(self, spam_data):
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df1 = self.read_html(spam_data, match=".*Water.*", skiprows=slice(2, 5))
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df2 = self.read_html(spam_data, match="Unit", skiprows=slice(4, 1, -1))
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assert_framelist_equal(df1, df2)
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def test_skiprows_ndarray(self, spam_data):
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df1 = self.read_html(spam_data, match=".*Water.*", skiprows=np.arange(2))
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df2 = self.read_html(spam_data, match="Unit", skiprows=np.arange(2))
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assert_framelist_equal(df1, df2)
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def test_skiprows_invalid(self, spam_data):
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with pytest.raises(TypeError, match=("is not a valid type for skipping rows")):
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self.read_html(spam_data, match=".*Water.*", skiprows="asdf")
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def test_index(self, spam_data):
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df1 = self.read_html(spam_data, match=".*Water.*", index_col=0)
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df2 = self.read_html(spam_data, match="Unit", index_col=0)
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assert_framelist_equal(df1, df2)
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def test_header_and_index_no_types(self, spam_data):
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df1 = self.read_html(spam_data, match=".*Water.*", header=1, index_col=0)
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df2 = self.read_html(spam_data, match="Unit", header=1, index_col=0)
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assert_framelist_equal(df1, df2)
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def test_header_and_index_with_types(self, spam_data):
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df1 = self.read_html(spam_data, match=".*Water.*", header=1, index_col=0)
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df2 = self.read_html(spam_data, match="Unit", header=1, index_col=0)
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assert_framelist_equal(df1, df2)
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def test_infer_types(self, spam_data):
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# 10892 infer_types removed
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df1 = self.read_html(spam_data, match=".*Water.*", index_col=0)
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df2 = self.read_html(spam_data, match="Unit", index_col=0)
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assert_framelist_equal(df1, df2)
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def test_string_io(self, spam_data):
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with open(spam_data, encoding="UTF-8") as f:
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data1 = StringIO(f.read())
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with open(spam_data, encoding="UTF-8") as f:
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data2 = StringIO(f.read())
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df1 = self.read_html(data1, match=".*Water.*")
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df2 = self.read_html(data2, match="Unit")
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assert_framelist_equal(df1, df2)
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def test_string(self, spam_data):
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with open(spam_data, encoding="UTF-8") as f:
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data = f.read()
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df1 = self.read_html(StringIO(data), match=".*Water.*")
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df2 = self.read_html(StringIO(data), match="Unit")
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assert_framelist_equal(df1, df2)
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def test_file_like(self, spam_data):
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with open(spam_data, encoding="UTF-8") as f:
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df1 = self.read_html(f, match=".*Water.*")
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with open(spam_data, encoding="UTF-8") as f:
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df2 = self.read_html(f, match="Unit")
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assert_framelist_equal(df1, df2)
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@pytest.mark.network
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@pytest.mark.single_cpu
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def test_bad_url_protocol(self, httpserver):
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httpserver.serve_content("urlopen error unknown url type: git", code=404)
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with pytest.raises(URLError, match="urlopen error unknown url type: git"):
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self.read_html("git://github.com", match=".*Water.*")
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@pytest.mark.slow
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|
@pytest.mark.network
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|
@pytest.mark.single_cpu
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def test_invalid_url(self, httpserver):
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httpserver.serve_content("Name or service not known", code=404)
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with pytest.raises((URLError, ValueError), match="HTTP Error 404: NOT FOUND"):
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self.read_html(httpserver.url, match=".*Water.*")
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|
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|
@pytest.mark.slow
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|
def test_file_url(self, banklist_data):
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url = banklist_data
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dfs = self.read_html(
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file_path_to_url(os.path.abspath(url)), match="First", attrs={"id": "table"}
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)
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assert isinstance(dfs, list)
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for df in dfs:
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assert isinstance(df, DataFrame)
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|
|
|
@pytest.mark.slow
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|
def test_invalid_table_attrs(self, banklist_data):
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url = banklist_data
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with pytest.raises(ValueError, match="No tables found"):
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self.read_html(
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url, match="First Federal Bank of Florida", attrs={"id": "tasdfable"}
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)
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|
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def _bank_data(self, path, **kwargs):
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return self.read_html(path, match="Metcalf", attrs={"id": "table"}, **kwargs)
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|
|
|
@pytest.mark.slow
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|
def test_multiindex_header(self, banklist_data):
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|
df = self._bank_data(banklist_data, header=[0, 1])[0]
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|
assert isinstance(df.columns, MultiIndex)
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|
|
|
@pytest.mark.slow
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|
def test_multiindex_index(self, banklist_data):
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|
df = self._bank_data(banklist_data, index_col=[0, 1])[0]
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assert isinstance(df.index, MultiIndex)
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|
|
|
@pytest.mark.slow
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|
def test_multiindex_header_index(self, banklist_data):
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df = self._bank_data(banklist_data, header=[0, 1], index_col=[0, 1])[0]
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assert isinstance(df.columns, MultiIndex)
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assert isinstance(df.index, MultiIndex)
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|
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|
@pytest.mark.slow
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|
def test_multiindex_header_skiprows_tuples(self, banklist_data):
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df = self._bank_data(banklist_data, header=[0, 1], skiprows=1)[0]
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assert isinstance(df.columns, MultiIndex)
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|
|
|
@pytest.mark.slow
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|
def test_multiindex_header_skiprows(self, banklist_data):
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df = self._bank_data(banklist_data, header=[0, 1], skiprows=1)[0]
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assert isinstance(df.columns, MultiIndex)
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|
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|
@pytest.mark.slow
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|
def test_multiindex_header_index_skiprows(self, banklist_data):
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|
df = self._bank_data(
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banklist_data, header=[0, 1], index_col=[0, 1], skiprows=1
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)[0]
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assert isinstance(df.index, MultiIndex)
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assert isinstance(df.columns, MultiIndex)
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|
|
|
@pytest.mark.slow
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|
def test_regex_idempotency(self, banklist_data):
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url = banklist_data
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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, spam_data):
|
|
msg = r"\(you passed a negative value\)"
|
|
with pytest.raises(ValueError, match=msg):
|
|
self.read_html(spam_data, match="Water", skiprows=-1)
|
|
|
|
@pytest.fixture
|
|
def python_docs(self):
|
|
return """
|
|
<table class="contentstable" align="center"><tr>
|
|
<td width="50%">
|
|
<p class="biglink"><a class="biglink" href="whatsnew/2.7.html">What's new in Python 2.7?</a><br/>
|
|
<span class="linkdescr">or <a href="whatsnew/index.html">all "What's new" documents</a> since 2.0</span></p>
|
|
<p class="biglink"><a class="biglink" href="tutorial/index.html">Tutorial</a><br/>
|
|
<span class="linkdescr">start here</span></p>
|
|
<p class="biglink"><a class="biglink" href="library/index.html">Library Reference</a><br/>
|
|
<span class="linkdescr">keep this under your pillow</span></p>
|
|
<p class="biglink"><a class="biglink" href="reference/index.html">Language Reference</a><br/>
|
|
<span class="linkdescr">describes syntax and language elements</span></p>
|
|
<p class="biglink"><a class="biglink" href="using/index.html">Python Setup and Usage</a><br/>
|
|
<span class="linkdescr">how to use Python on different platforms</span></p>
|
|
<p class="biglink"><a class="biglink" href="howto/index.html">Python HOWTOs</a><br/>
|
|
<span class="linkdescr">in-depth documents on specific topics</span></p>
|
|
</td><td width="50%">
|
|
<p class="biglink"><a class="biglink" href="installing/index.html">Installing Python Modules</a><br/>
|
|
<span class="linkdescr">installing from the Python Package Index & other sources</span></p>
|
|
<p class="biglink"><a class="biglink" href="distributing/index.html">Distributing Python Modules</a><br/>
|
|
<span class="linkdescr">publishing modules for installation by others</span></p>
|
|
<p class="biglink"><a class="biglink" href="extending/index.html">Extending and Embedding</a><br/>
|
|
<span class="linkdescr">tutorial for C/C++ programmers</span></p>
|
|
<p class="biglink"><a class="biglink" href="c-api/index.html">Python/C API</a><br/>
|
|
<span class="linkdescr">reference for C/C++ programmers</span></p>
|
|
<p class="biglink"><a class="biglink" href="faq/index.html">FAQs</a><br/>
|
|
<span class="linkdescr">frequently asked questions (with answers!)</span></p>
|
|
</td></tr>
|
|
</table>
|
|
|
|
<p><strong>Indices and tables:</strong></p>
|
|
<table class="contentstable" align="center"><tr>
|
|
<td width="50%">
|
|
<p class="biglink"><a class="biglink" href="py-modindex.html">Python Global Module Index</a><br/>
|
|
<span class="linkdescr">quick access to all modules</span></p>
|
|
<p class="biglink"><a class="biglink" href="genindex.html">General Index</a><br/>
|
|
<span class="linkdescr">all functions, classes, terms</span></p>
|
|
<p class="biglink"><a class="biglink" href="glossary.html">Glossary</a><br/>
|
|
<span class="linkdescr">the most important terms explained</span></p>
|
|
</td><td width="50%">
|
|
<p class="biglink"><a class="biglink" href="search.html">Search page</a><br/>
|
|
<span class="linkdescr">search this documentation</span></p>
|
|
<p class="biglink"><a class="biglink" href="contents.html">Complete Table of Contents</a><br/>
|
|
<span class="linkdescr">lists all sections and subsections</span></p>
|
|
</td></tr>
|
|
</table>
|
|
""" # noqa: E501
|
|
|
|
@pytest.mark.network
|
|
@pytest.mark.single_cpu
|
|
def test_multiple_matches(self, python_docs, httpserver):
|
|
httpserver.serve_content(content=python_docs)
|
|
dfs = self.read_html(httpserver.url, match="Python")
|
|
assert len(dfs) > 1
|
|
|
|
@pytest.mark.network
|
|
@pytest.mark.single_cpu
|
|
def test_python_docs_table(self, python_docs, httpserver):
|
|
httpserver.serve_content(content=python_docs)
|
|
dfs = self.read_html(httpserver.url, match="Python")
|
|
zz = [df.iloc[0, 0][0:4] for df in dfs]
|
|
assert sorted(zz) == ["Pyth", "What"]
|
|
|
|
def test_empty_tables(self):
|
|
"""
|
|
Make sure that read_html ignores empty tables.
|
|
"""
|
|
html = """
|
|
<table>
|
|
<thead>
|
|
<tr>
|
|
<th>A</th>
|
|
<th>B</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td>1</td>
|
|
<td>2</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
<table>
|
|
<tbody>
|
|
</tbody>
|
|
</table>
|
|
"""
|
|
result = self.read_html(StringIO(html))
|
|
assert len(result) == 1
|
|
|
|
def test_multiple_tbody(self):
|
|
# GH-20690
|
|
# Read all tbody tags within a single table.
|
|
result = self.read_html(
|
|
StringIO(
|
|
"""<table>
|
|
<thead>
|
|
<tr>
|
|
<th>A</th>
|
|
<th>B</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td>1</td>
|
|
<td>2</td>
|
|
</tr>
|
|
</tbody>
|
|
<tbody>
|
|
<tr>
|
|
<td>3</td>
|
|
<td>4</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>"""
|
|
)
|
|
)[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(
|
|
StringIO(
|
|
"""<table>
|
|
<thead>
|
|
<tr>
|
|
<th>Header</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td>first</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>"""
|
|
)
|
|
)[0]
|
|
|
|
expected = DataFrame(data={"Header": "first"}, index=[0])
|
|
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
def test_thead_without_tr(self):
|
|
"""
|
|
Ensure parser adds <tr> within <thead> on malformed HTML.
|
|
"""
|
|
result = self.read_html(
|
|
StringIO(
|
|
"""<table>
|
|
<thead>
|
|
<tr>
|
|
<th>Country</th>
|
|
<th>Municipality</th>
|
|
<th>Year</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td>Ukraine</td>
|
|
<th>Odessa</th>
|
|
<td>1944</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>"""
|
|
)
|
|
)[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 = """<table>
|
|
<thead>
|
|
<tr>
|
|
<th>A</th>
|
|
<th>B</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td>bodyA</td>
|
|
<td>bodyB</td>
|
|
</tr>
|
|
</tbody>
|
|
<tfoot>
|
|
{footer}
|
|
</tfoot>
|
|
</table>"""
|
|
|
|
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="<tr><td>footA</td><th>footB</th></tr>")
|
|
|
|
result1 = self.read_html(StringIO(data1))[0]
|
|
result2 = self.read_html(StringIO(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(
|
|
StringIO(
|
|
"""
|
|
<table>
|
|
<tr>
|
|
<td>S</td>
|
|
<td>I</td>
|
|
</tr>
|
|
<tr>
|
|
<td>text</td>
|
|
<td>1944</td>
|
|
</tr>
|
|
</table>
|
|
"""
|
|
),
|
|
header=0,
|
|
)[0]
|
|
|
|
expected = DataFrame([["text", 1944]], columns=("S", "I"))
|
|
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
@pytest.mark.slow
|
|
def test_banklist_header(self, banklist_data, 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(banklist_data, match="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 Bank In Vietnamese",
|
|
"Westernbank Puerto Rico En Espanol",
|
|
"R-G Premier Bank of Puerto Rico En Espanol",
|
|
"Eurobank En Espanol",
|
|
"Sanderson State Bank En Espanol",
|
|
"Washington Mutual Bank (Including its subsidiary Washington "
|
|
"Mutual Bank FSB)",
|
|
"Silver State Bank En Espanol",
|
|
"AmTrade International Bank En Espanol",
|
|
"Hamilton Bank, NA En Espanol",
|
|
"The Citizens Savings Bank Pioneer 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.map(try_remove_ws).replace(old, new)
|
|
gtnew = ground_truth.map(try_remove_ws)
|
|
converted = dfnew
|
|
date_cols = ["Closing Date", "Updated Date"]
|
|
converted[date_cols] = converted[date_cols].apply(to_datetime)
|
|
tm.assert_frame_equal(converted, gtnew)
|
|
|
|
@pytest.mark.slow
|
|
def test_gold_canyon(self, banklist_data):
|
|
gc = "Gold Canyon"
|
|
with open(banklist_data, encoding="utf-8") as f:
|
|
raw_text = f.read()
|
|
|
|
assert gc in raw_text
|
|
df = self.read_html(banklist_data, match="Gold Canyon", attrs={"id": "table"})[
|
|
0
|
|
]
|
|
assert gc in df.to_string()
|
|
|
|
def test_different_number_of_cols(self):
|
|
expected = self.read_html(
|
|
StringIO(
|
|
"""<table>
|
|
<thead>
|
|
<tr style="text-align: right;">
|
|
<th></th>
|
|
<th>C_l0_g0</th>
|
|
<th>C_l0_g1</th>
|
|
<th>C_l0_g2</th>
|
|
<th>C_l0_g3</th>
|
|
<th>C_l0_g4</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<th>R_l0_g0</th>
|
|
<td> 0.763</td>
|
|
<td> 0.233</td>
|
|
<td> nan</td>
|
|
<td> nan</td>
|
|
<td> nan</td>
|
|
</tr>
|
|
<tr>
|
|
<th>R_l0_g1</th>
|
|
<td> 0.244</td>
|
|
<td> 0.285</td>
|
|
<td> 0.392</td>
|
|
<td> 0.137</td>
|
|
<td> 0.222</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>"""
|
|
),
|
|
index_col=0,
|
|
)[0]
|
|
|
|
result = self.read_html(
|
|
StringIO(
|
|
"""<table>
|
|
<thead>
|
|
<tr style="text-align: right;">
|
|
<th></th>
|
|
<th>C_l0_g0</th>
|
|
<th>C_l0_g1</th>
|
|
<th>C_l0_g2</th>
|
|
<th>C_l0_g3</th>
|
|
<th>C_l0_g4</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<th>R_l0_g0</th>
|
|
<td> 0.763</td>
|
|
<td> 0.233</td>
|
|
</tr>
|
|
<tr>
|
|
<th>R_l0_g1</th>
|
|
<td> 0.244</td>
|
|
<td> 0.285</td>
|
|
<td> 0.392</td>
|
|
<td> 0.137</td>
|
|
<td> 0.222</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>"""
|
|
),
|
|
index_col=0,
|
|
)[0]
|
|
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
def test_colspan_rowspan_1(self):
|
|
# GH17054
|
|
result = self.read_html(
|
|
StringIO(
|
|
"""
|
|
<table>
|
|
<tr>
|
|
<th>A</th>
|
|
<th colspan="1">B</th>
|
|
<th rowspan="1">C</th>
|
|
</tr>
|
|
<tr>
|
|
<td>a</td>
|
|
<td>b</td>
|
|
<td>c</td>
|
|
</tr>
|
|
</table>
|
|
"""
|
|
)
|
|
)[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(
|
|
StringIO(
|
|
"""
|
|
<table>
|
|
<tr>
|
|
<td colspan="2">X</td>
|
|
<td>Y</td>
|
|
<td rowspan="2">Z</td>
|
|
<td>W</td>
|
|
</tr>
|
|
<tr>
|
|
<td>A</td>
|
|
<td colspan="2">B</td>
|
|
<td>C</td>
|
|
</tr>
|
|
</table>
|
|
"""
|
|
),
|
|
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(
|
|
StringIO(
|
|
"""
|
|
<table>
|
|
<tr>
|
|
<td rowspan="2">A</td>
|
|
<td rowspan="2" colspan="3">B</td>
|
|
<td>C</td>
|
|
</tr>
|
|
<tr>
|
|
<td>D</td>
|
|
</tr>
|
|
</table>
|
|
"""
|
|
),
|
|
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(
|
|
StringIO(
|
|
"""
|
|
<table>
|
|
<tr>
|
|
<td>A</td>
|
|
<td rowspan="2">B</td>
|
|
</tr>
|
|
<tr>
|
|
<td>C</td>
|
|
</tr>
|
|
</table>
|
|
"""
|
|
),
|
|
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(
|
|
StringIO(
|
|
"""
|
|
<table>
|
|
<tr>
|
|
<td rowspan="3">A</td>
|
|
<td rowspan="3">B</td>
|
|
</tr>
|
|
</table>
|
|
"""
|
|
),
|
|
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(
|
|
StringIO(
|
|
"""
|
|
<table>
|
|
<tr>
|
|
<th>A</th>
|
|
<th>B</th>
|
|
</tr>
|
|
<tr>
|
|
<th>a</th>
|
|
<th>b</th>
|
|
</tr>
|
|
<tr>
|
|
<td>1</td>
|
|
<td>2</td>
|
|
</tr>
|
|
</table>
|
|
"""
|
|
)
|
|
)[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(StringIO(expected), parse_dates=[1], index_col=0)
|
|
tm.assert_frame_equal(df, res[0])
|
|
res = self.read_html(StringIO(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(
|
|
StringIO(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_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, match="Arizona", header=1)[0]
|
|
assert result.shape == (60, 12)
|
|
assert "Unnamed" in result.columns[-1]
|
|
assert result["sq mi"].dtype == np.dtype("float64")
|
|
assert np.allclose(result.loc[0, "sq mi"], 665384.04)
|
|
|
|
def test_wikipedia_states_multiindex(self, datapath):
|
|
data = datapath("io", "data", "html", "wikipedia_states.html")
|
|
result = self.read_html(data, match="Arizona", index_col=0)[0]
|
|
assert result.shape == (60, 11)
|
|
assert "Unnamed" in result.columns[-1][1]
|
|
assert result.columns.nlevels == 2
|
|
assert np.allclose(result.loc["Alaska", ("Total area[2]", "sq mi")], 665384.04)
|
|
|
|
def test_parser_error_on_empty_header_row(self):
|
|
result = self.read_html(
|
|
StringIO(
|
|
"""
|
|
<table>
|
|
<thead>
|
|
<tr><th></th><th></tr>
|
|
<tr><th>A</th><th>B</th></tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr><td>a</td><td>b</td></tr>
|
|
</tbody>
|
|
</table>
|
|
"""
|
|
),
|
|
header=[0, 1],
|
|
)
|
|
expected = DataFrame(
|
|
[["a", "b"]],
|
|
columns=MultiIndex.from_tuples(
|
|
[("Unnamed: 0_level_0", "A"), ("Unnamed: 1_level_0", "B")]
|
|
),
|
|
)
|
|
tm.assert_frame_equal(result[0], expected)
|
|
|
|
def test_decimal_rows(self):
|
|
# GH 12907
|
|
result = self.read_html(
|
|
StringIO(
|
|
"""<html>
|
|
<body>
|
|
<table>
|
|
<thead>
|
|
<tr>
|
|
<th>Header</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td>1100#101</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
</body>
|
|
</html>"""
|
|
),
|
|
decimal="#",
|
|
)[0]
|
|
|
|
expected = DataFrame(data={"Header": 1100.101}, index=[0])
|
|
|
|
assert result["Header"].dtype == np.dtype("float64")
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
@pytest.mark.parametrize("arg", [True, False])
|
|
def test_bool_header_arg(self, spam_data, arg):
|
|
# GH 6114
|
|
msg = re.escape(
|
|
"Passing a bool to header is invalid. Use header=None for no header or "
|
|
"header=int or list-like of ints to specify the row(s) making up the "
|
|
"column names"
|
|
)
|
|
with pytest.raises(TypeError, match=msg):
|
|
self.read_html(spam_data, header=arg)
|
|
|
|
def test_converters(self):
|
|
# GH 13461
|
|
result = self.read_html(
|
|
StringIO(
|
|
"""<table>
|
|
<thead>
|
|
<tr>
|
|
<th>a</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td> 0.763</td>
|
|
</tr>
|
|
<tr>
|
|
<td> 0.244</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>"""
|
|
),
|
|
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(
|
|
StringIO(
|
|
"""<table>
|
|
<thead>
|
|
<tr>
|
|
<th>a</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td> 0.763</td>
|
|
</tr>
|
|
<tr>
|
|
<td> 0.244</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>"""
|
|
),
|
|
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 = """<table>
|
|
<thead>
|
|
<tr>
|
|
<th>a</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td> N/A</td>
|
|
</tr>
|
|
<tr>
|
|
<td> NA</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>"""
|
|
|
|
expected_df = DataFrame({"a": ["N/A", "NA"]})
|
|
html_df = self.read_html(StringIO(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(StringIO(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(
|
|
StringIO(
|
|
"""
|
|
<table>
|
|
<tr>
|
|
<th>A</th>
|
|
<th>B</th>
|
|
</tr>
|
|
<tr>
|
|
<td>a</td>
|
|
<td>b</td>
|
|
</tr>
|
|
<tr>
|
|
<td></td>
|
|
<td></td>
|
|
</tr>
|
|
</table>
|
|
"""
|
|
)
|
|
)[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(
|
|
StringIO(
|
|
"""
|
|
<table>
|
|
<thead>
|
|
<tr><th></th><th></tr>
|
|
<tr><th>A</th><th>B</th></tr>
|
|
<tr><th>a</th><th>b</th></tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr><td>1</td><td>2</td></tr>
|
|
</tbody>
|
|
</table>
|
|
"""
|
|
)
|
|
)[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(StringIO(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, match=".*Water.*", flavor=["lxml", "html5lib"])
|
|
|
|
def test_to_html_timestamp(self):
|
|
rng = date_range("2000-01-01", periods=10)
|
|
df = DataFrame(np.random.default_rng(2).standard_normal((10, 4)), index=rng)
|
|
|
|
result = df.to_html()
|
|
assert "2000-01-01" in result
|
|
|
|
def test_to_html_borderless(self):
|
|
df = DataFrame([{"A": 1, "B": 2}])
|
|
out_border_default = df.to_html()
|
|
out_border_true = df.to_html(border=True)
|
|
out_border_explicit_default = df.to_html(border=1)
|
|
out_border_nondefault = df.to_html(border=2)
|
|
out_border_zero = df.to_html(border=0)
|
|
|
|
out_border_false = df.to_html(border=False)
|
|
|
|
assert ' border="1"' in out_border_default
|
|
assert out_border_true == out_border_default
|
|
assert out_border_default == out_border_explicit_default
|
|
assert out_border_default != out_border_nondefault
|
|
assert ' border="2"' in out_border_nondefault
|
|
assert ' border="0"' not in out_border_zero
|
|
assert " border" not in out_border_false
|
|
assert out_border_zero == out_border_false
|
|
|
|
@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 = """<html>
|
|
<body>
|
|
<table>
|
|
<tr>
|
|
<td>
|
|
foo
|
|
<span style="display:none;text-align:center">bar</span>
|
|
<span style="display:none">baz</span>
|
|
<span style="display: none">qux</span>
|
|
</td>
|
|
</tr>
|
|
</table>
|
|
<table style="display: none">
|
|
<tr>
|
|
<td>foo</td>
|
|
</tr>
|
|
</table>
|
|
</body>
|
|
</html>"""
|
|
|
|
dfs = self.read_html(StringIO(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
|
|
|
|
@pytest.mark.parametrize("displayed_only", [True, False])
|
|
def test_displayed_only_with_many_elements(self, displayed_only):
|
|
html_table = """
|
|
<table>
|
|
<tr>
|
|
<th>A</th>
|
|
<th>B</th>
|
|
</tr>
|
|
<tr>
|
|
<td>1</td>
|
|
<td>2</td>
|
|
</tr>
|
|
<tr>
|
|
<td><span style="display:none"></span>4</td>
|
|
<td>5</td>
|
|
</tr>
|
|
</table>
|
|
"""
|
|
result = read_html(StringIO(html_table), displayed_only=displayed_only)[0]
|
|
expected = DataFrame({"A": [1, 4], "B": [2, 5]})
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
@pytest.mark.filterwarnings(
|
|
"ignore:You provided Unicode markup but also provided a value for "
|
|
"from_encoding.*:UserWarning"
|
|
)
|
|
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(
|
|
"""
|
|
<table><tr><td>spam<foobr />eggs</td></tr></table>"""
|
|
)
|
|
|
|
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) -> None:
|
|
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
|
|
|
|
# GH 49036 pylint checks for presence of __next__ for iterators
|
|
def __next__(self):
|
|
...
|
|
|
|
def __iter__(self) -> Iterator:
|
|
# `is_file_like` depends on the presence of
|
|
# the __iter__ attribute.
|
|
return self
|
|
|
|
good = MockFile("<table><tr><td>spam<br />eggs</td></tr></table>")
|
|
bad = MockFile("<table><tr><td>spam<foobr />eggs</td></tr></table>")
|
|
|
|
assert self.read_html(good)
|
|
assert self.read_html(bad)
|
|
|
|
@pytest.mark.slow
|
|
@pytest.mark.single_cpu
|
|
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
|
|
|
|
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
|
|
|
|
def test_parse_path_object(self, datapath):
|
|
# GH 37705
|
|
file_path_string = datapath("io", "data", "html", "spam.html")
|
|
file_path = Path(file_path_string)
|
|
df1 = self.read_html(file_path_string)[0]
|
|
df2 = self.read_html(file_path)[0]
|
|
tm.assert_frame_equal(df1, df2)
|
|
|
|
def test_parse_br_as_space(self):
|
|
# GH 29528: pd.read_html() convert <br> to space
|
|
result = self.read_html(
|
|
StringIO(
|
|
"""
|
|
<table>
|
|
<tr>
|
|
<th>A</th>
|
|
</tr>
|
|
<tr>
|
|
<td>word1<br>word2</td>
|
|
</tr>
|
|
</table>
|
|
"""
|
|
)
|
|
)[0]
|
|
|
|
expected = DataFrame(data=[["word1 word2"]], columns=["A"])
|
|
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
@pytest.mark.parametrize("arg", ["all", "body", "header", "footer"])
|
|
def test_extract_links(self, arg):
|
|
gh_13141_data = """
|
|
<table>
|
|
<tr>
|
|
<th>HTTP</th>
|
|
<th>FTP</th>
|
|
<th><a href="https://en.wiktionary.org/wiki/linkless">Linkless</a></th>
|
|
</tr>
|
|
<tr>
|
|
<td><a href="https://en.wikipedia.org/">Wikipedia</a></td>
|
|
<td>SURROUNDING <a href="ftp://ftp.us.debian.org/">Debian</a> TEXT</td>
|
|
<td>Linkless</td>
|
|
</tr>
|
|
<tfoot>
|
|
<tr>
|
|
<td><a href="https://en.wikipedia.org/wiki/Page_footer">Footer</a></td>
|
|
<td>
|
|
Multiple <a href="1">links:</a> <a href="2">Only first captured.</a>
|
|
</td>
|
|
</tr>
|
|
</tfoot>
|
|
</table>
|
|
"""
|
|
|
|
gh_13141_expected = {
|
|
"head_ignore": ["HTTP", "FTP", "Linkless"],
|
|
"head_extract": [
|
|
("HTTP", None),
|
|
("FTP", None),
|
|
("Linkless", "https://en.wiktionary.org/wiki/linkless"),
|
|
],
|
|
"body_ignore": ["Wikipedia", "SURROUNDING Debian TEXT", "Linkless"],
|
|
"body_extract": [
|
|
("Wikipedia", "https://en.wikipedia.org/"),
|
|
("SURROUNDING Debian TEXT", "ftp://ftp.us.debian.org/"),
|
|
("Linkless", None),
|
|
],
|
|
"footer_ignore": [
|
|
"Footer",
|
|
"Multiple links: Only first captured.",
|
|
None,
|
|
],
|
|
"footer_extract": [
|
|
("Footer", "https://en.wikipedia.org/wiki/Page_footer"),
|
|
("Multiple links: Only first captured.", "1"),
|
|
None,
|
|
],
|
|
}
|
|
|
|
data_exp = gh_13141_expected["body_ignore"]
|
|
foot_exp = gh_13141_expected["footer_ignore"]
|
|
head_exp = gh_13141_expected["head_ignore"]
|
|
if arg == "all":
|
|
data_exp = gh_13141_expected["body_extract"]
|
|
foot_exp = gh_13141_expected["footer_extract"]
|
|
head_exp = gh_13141_expected["head_extract"]
|
|
elif arg == "body":
|
|
data_exp = gh_13141_expected["body_extract"]
|
|
elif arg == "footer":
|
|
foot_exp = gh_13141_expected["footer_extract"]
|
|
elif arg == "header":
|
|
head_exp = gh_13141_expected["head_extract"]
|
|
|
|
result = self.read_html(StringIO(gh_13141_data), extract_links=arg)[0]
|
|
expected = DataFrame([data_exp, foot_exp], columns=head_exp)
|
|
expected = expected.fillna(np.nan)
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
def test_extract_links_bad(self, spam_data):
|
|
msg = (
|
|
"`extract_links` must be one of "
|
|
'{None, "header", "footer", "body", "all"}, got "incorrect"'
|
|
)
|
|
with pytest.raises(ValueError, match=msg):
|
|
read_html(spam_data, extract_links="incorrect")
|
|
|
|
def test_extract_links_all_no_header(self):
|
|
# GH 48316
|
|
data = """
|
|
<table>
|
|
<tr>
|
|
<td>
|
|
<a href='https://google.com'>Google.com</a>
|
|
</td>
|
|
</tr>
|
|
</table>
|
|
"""
|
|
result = self.read_html(StringIO(data), extract_links="all")[0]
|
|
expected = DataFrame([[("Google.com", "https://google.com")]])
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
def test_invalid_dtype_backend(self):
|
|
msg = (
|
|
"dtype_backend numpy is invalid, only 'numpy_nullable' and "
|
|
"'pyarrow' are allowed."
|
|
)
|
|
with pytest.raises(ValueError, match=msg):
|
|
read_html("test", dtype_backend="numpy")
|
|
|
|
def test_style_tag(self):
|
|
# GH 48316
|
|
data = """
|
|
<table>
|
|
<tr>
|
|
<th>
|
|
<style>.style</style>
|
|
A
|
|
</th>
|
|
<th>B</th>
|
|
</tr>
|
|
<tr>
|
|
<td>A1</td>
|
|
<td>B1</td>
|
|
</tr>
|
|
<tr>
|
|
<td>A2</td>
|
|
<td>B2</td>
|
|
</tr>
|
|
</table>
|
|
"""
|
|
result = self.read_html(StringIO(data))[0]
|
|
expected = DataFrame(data=[["A1", "B1"], ["A2", "B2"]], columns=["A", "B"])
|
|
tm.assert_frame_equal(result, expected)
|
|
|