Inzynierka/Lib/site-packages/pandas/tests/io/test_html.py

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2023-06-02 12:51:02 +02:00
from functools import partial
from importlib import reload
from io import (
BytesIO,
StringIO,
)
import os
from pathlib import Path
import re
import threading
from typing import Iterator
from urllib.error import URLError
import numpy as np
import pytest
from pandas.compat import is_platform_windows
import pandas.util._test_decorators as td
import pandas as pd
from pandas import (
NA,
DataFrame,
MultiIndex,
Series,
Timestamp,
date_range,
read_csv,
to_datetime,
)
import pandas._testing as tm
from pandas.core.arrays import (
ArrowStringArray,
StringArray,
)
from pandas.io.common import file_path_to_url
import pandas.io.html
from pandas.io.html import read_html
@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 "
f"len(list1) == {len(list1)}, "
f"len(list2) == {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")
@td.skip_if_no("html5lib")
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, match="google", flavor=flavor)
@td.skip_if_no("bs4")
@td.skip_if_no("lxml")
@td.skip_if_no("html5lib")
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"), td.skip_if_no("html5lib")]),
pytest.param("lxml", marks=td.skip_if_no("lxml")),
],
)
class TestReadHtml:
@pytest.fixture
def spam_data(self, datapath):
return datapath("io", "data", "html", "spam.html")
@pytest.fixture
def banklist_data(self, datapath):
return datapath("io", "data", "html", "banklist.html")
@pytest.fixture(autouse=True)
def set_defaults(self, flavor):
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: np.random.rand(),
c_idx_names=False,
r_idx_names=False,
)
# pylint: disable-next=consider-using-f-string
.applymap("{:.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)
def test_dtype_backend(self, string_storage, dtype_backend):
# GH#50286
df = DataFrame(
{
"a": Series([1, np.nan, 3], dtype="Int64"),
"b": Series([1, 2, 3], dtype="Int64"),
"c": Series([1.5, np.nan, 2.5], dtype="Float64"),
"d": Series([1.5, 2.0, 2.5], dtype="Float64"),
"e": [True, False, None],
"f": [True, False, True],
"g": ["a", "b", "c"],
"h": ["a", "b", None],
}
)
if string_storage == "python":
string_array = StringArray(np.array(["a", "b", "c"], dtype=np.object_))
string_array_na = StringArray(np.array(["a", "b", NA], dtype=np.object_))
else:
pa = pytest.importorskip("pyarrow")
string_array = ArrowStringArray(pa.array(["a", "b", "c"]))
string_array_na = ArrowStringArray(pa.array(["a", "b", None]))
out = df.to_html(index=False)
with pd.option_context("mode.string_storage", string_storage):
result = self.read_html(out, dtype_backend=dtype_backend)[0]
expected = DataFrame(
{
"a": Series([1, np.nan, 3], dtype="Int64"),
"b": Series([1, 2, 3], dtype="Int64"),
"c": Series([1.5, np.nan, 2.5], dtype="Float64"),
"d": Series([1.5, 2.0, 2.5], dtype="Float64"),
"e": Series([True, False, NA], dtype="boolean"),
"f": Series([True, False, True], dtype="boolean"),
"g": string_array,
"h": string_array_na,
}
)
if dtype_backend == "pyarrow":
import pyarrow as pa
from pandas.arrays import ArrowExtensionArray
expected = DataFrame(
{
col: ArrowExtensionArray(pa.array(expected[col], from_pandas=True))
for col in expected.columns
}
)
tm.assert_frame_equal(result, expected)
@pytest.mark.network
@tm.network(
url=(
"https://www.fdic.gov/resources/resolutions/"
"bank-failures/failed-bank-list/index.html"
),
check_before_test=True,
)
def test_banklist_url(self):
url = "https://www.fdic.gov/resources/resolutions/bank-failures/failed-bank-list/index.html" # noqa E501
df1 = self.read_html(
# lxml cannot find attrs leave out for now
url,
match="First Federal Bank of Florida", # attrs={"class": "dataTable"}
)
# lxml cannot find attrs leave out for now
df2 = self.read_html(
url,
match="Metcalf Bank",
) # attrs={"class": "dataTable"})
assert_framelist_equal(df1, df2)
@pytest.mark.network
@tm.network(
url=(
"https://raw.githubusercontent.com/pandas-dev/pandas/main/"
"pandas/tests/io/data/html/spam.html"
),
check_before_test=True,
)
def test_spam_url(self):
url = (
"https://raw.githubusercontent.com/pandas-dev/pandas/main/"
"pandas/tests/io/data/html/spam.html"
)
df1 = self.read_html(url, match=".*Water.*")
df2 = self.read_html(url, match="Unit")
assert_framelist_equal(df1, df2)
@pytest.mark.slow
def test_banklist(self, banklist_data):
df1 = self.read_html(banklist_data, match=".*Florida.*", attrs={"id": "table"})
df2 = self.read_html(banklist_data, match="Metcalf Bank", attrs={"id": "table"})
assert_framelist_equal(df1, df2)
def test_spam(self, spam_data):
df1 = self.read_html(spam_data, match=".*Water.*")
df2 = self.read_html(spam_data, match="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, spam_data):
dfs = self.read_html(spam_data)
for df in dfs:
assert isinstance(df, DataFrame)
def test_banklist_no_match(self, banklist_data):
dfs = self.read_html(banklist_data, attrs={"id": "table"})
for df in dfs:
assert isinstance(df, DataFrame)
def test_spam_header(self, spam_data):
df = self.read_html(spam_data, match=".*Water.*", header=2)[0]
assert df.columns[0] == "Proximates"
assert not df.empty
def test_skiprows_int(self, spam_data):
df1 = self.read_html(spam_data, match=".*Water.*", skiprows=1)
df2 = self.read_html(spam_data, match="Unit", skiprows=1)
assert_framelist_equal(df1, df2)
def test_skiprows_range(self, spam_data):
df1 = self.read_html(spam_data, match=".*Water.*", skiprows=range(2))
df2 = self.read_html(spam_data, match="Unit", skiprows=range(2))
assert_framelist_equal(df1, df2)
def test_skiprows_list(self, spam_data):
df1 = self.read_html(spam_data, match=".*Water.*", skiprows=[1, 2])
df2 = self.read_html(spam_data, match="Unit", skiprows=[2, 1])
assert_framelist_equal(df1, df2)
def test_skiprows_set(self, spam_data):
df1 = self.read_html(spam_data, match=".*Water.*", skiprows={1, 2})
df2 = self.read_html(spam_data, match="Unit", skiprows={2, 1})
assert_framelist_equal(df1, df2)
def test_skiprows_slice(self, spam_data):
df1 = self.read_html(spam_data, match=".*Water.*", skiprows=1)
df2 = self.read_html(spam_data, match="Unit", skiprows=1)
assert_framelist_equal(df1, df2)
def test_skiprows_slice_short(self, spam_data):
df1 = self.read_html(spam_data, match=".*Water.*", skiprows=slice(2))
df2 = self.read_html(spam_data, match="Unit", skiprows=slice(2))
assert_framelist_equal(df1, df2)
def test_skiprows_slice_long(self, spam_data):
df1 = self.read_html(spam_data, match=".*Water.*", skiprows=slice(2, 5))
df2 = self.read_html(spam_data, match="Unit", skiprows=slice(4, 1, -1))
assert_framelist_equal(df1, df2)
def test_skiprows_ndarray(self, spam_data):
df1 = self.read_html(spam_data, match=".*Water.*", skiprows=np.arange(2))
df2 = self.read_html(spam_data, match="Unit", skiprows=np.arange(2))
assert_framelist_equal(df1, df2)
def test_skiprows_invalid(self, spam_data):
with pytest.raises(TypeError, match=("is not a valid type for skipping rows")):
self.read_html(spam_data, match=".*Water.*", skiprows="asdf")
def test_index(self, spam_data):
df1 = self.read_html(spam_data, match=".*Water.*", index_col=0)
df2 = self.read_html(spam_data, match="Unit", index_col=0)
assert_framelist_equal(df1, df2)
def test_header_and_index_no_types(self, spam_data):
df1 = self.read_html(spam_data, match=".*Water.*", header=1, index_col=0)
df2 = self.read_html(spam_data, match="Unit", header=1, index_col=0)
assert_framelist_equal(df1, df2)
def test_header_and_index_with_types(self, spam_data):
df1 = self.read_html(spam_data, match=".*Water.*", header=1, index_col=0)
df2 = self.read_html(spam_data, match="Unit", header=1, index_col=0)
assert_framelist_equal(df1, df2)
def test_infer_types(self, spam_data):
# 10892 infer_types removed
df1 = self.read_html(spam_data, match=".*Water.*", index_col=0)
df2 = self.read_html(spam_data, match="Unit", index_col=0)
assert_framelist_equal(df1, df2)
def test_string_io(self, spam_data):
with open(spam_data, encoding="UTF-8") as f:
data1 = StringIO(f.read())
with open(spam_data, encoding="UTF-8") as f:
data2 = StringIO(f.read())
df1 = self.read_html(data1, match=".*Water.*")
df2 = self.read_html(data2, match="Unit")
assert_framelist_equal(df1, df2)
def test_string(self, spam_data):
with open(spam_data, encoding="UTF-8") as f:
data = f.read()
df1 = self.read_html(data, match=".*Water.*")
df2 = self.read_html(data, match="Unit")
assert_framelist_equal(df1, df2)
def test_file_like(self, spam_data):
with open(spam_data, encoding="UTF-8") as f:
df1 = self.read_html(f, match=".*Water.*")
with open(spam_data, encoding="UTF-8") as f:
df2 = self.read_html(f, match="Unit")
assert_framelist_equal(df1, df2)
@pytest.mark.network
@tm.network
def test_bad_url_protocol(self):
with pytest.raises(URLError, match="urlopen error unknown url type: git"):
self.read_html("git://github.com", match=".*Water.*")
@pytest.mark.slow
@pytest.mark.network
@tm.network
def test_invalid_url(self):
msg = (
"Name or service not known|Temporary failure in name resolution|"
"No tables found"
)
with pytest.raises((URLError, ValueError), match=msg):
self.read_html("http://www.a23950sdfa908sd.com", match=".*Water.*")
@pytest.mark.slow
def test_file_url(self, banklist_data):
url = banklist_data
dfs = self.read_html(
file_path_to_url(os.path.abspath(url)), match="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, banklist_data):
url = banklist_data
with pytest.raises(ValueError, match="No tables found"):
self.read_html(
url, match="First Federal Bank of Florida", attrs={"id": "tasdfable"}
)
def _bank_data(self, path, **kwargs):
return self.read_html(path, match="Metcalf", attrs={"id": "table"}, **kwargs)
@pytest.mark.slow
def test_multiindex_header(self, banklist_data):
df = self._bank_data(banklist_data, header=[0, 1])[0]
assert isinstance(df.columns, MultiIndex)
@pytest.mark.slow
def test_multiindex_index(self, banklist_data):
df = self._bank_data(banklist_data, index_col=[0, 1])[0]
assert isinstance(df.index, MultiIndex)
@pytest.mark.slow
def test_multiindex_header_index(self, banklist_data):
df = self._bank_data(banklist_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, banklist_data):
df = self._bank_data(banklist_data, header=[0, 1], skiprows=1)[0]
assert isinstance(df.columns, MultiIndex)
@pytest.mark.slow
def test_multiindex_header_skiprows(self, banklist_data):
df = self._bank_data(banklist_data, header=[0, 1], skiprows=1)[0]
assert isinstance(df.columns, MultiIndex)
@pytest.mark.slow
def test_multiindex_header_index_skiprows(self, banklist_data):
df = self._bank_data(
banklist_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, banklist_data):
url = 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, 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.mark.network
@tm.network(url="https://docs.python.org/2/", check_before_test=True)
def test_multiple_matches(self):
url = "https://docs.python.org/2/"
dfs = self.read_html(url, match="Python")
assert len(dfs) > 1
@pytest.mark.network
@tm.network(url="https://docs.python.org/2/", check_before_test=True)
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"])
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(html)
assert len(result) == 1
def test_multiple_tbody(self):
# GH-20690
# Read all tbody tags within a single table.
result = self.read_html(
"""<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(
"""<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(
"""<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(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(
"""
<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.applymap(try_remove_ws).replace(old, new)
gtnew = ground_truth.applymap(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) 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(
"""<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(
"""<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(
"""
<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(
"""
<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(
"""
<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(
"""
<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(
"""
<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(
"""
<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(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_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(
"""
<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(
"""<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(
"""<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(
"""<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(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(
"""
<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(
"""
<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(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.randn(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 = StringIO(
"""<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(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.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
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
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(
"""
<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(gh_13141_data, extract_links=arg)[0]
expected = DataFrame([data_exp, foot_exp], columns=head_exp)
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(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")