from collections.abc import Iterator
from functools import partial
from io import (
BytesIO,
StringIO,
)
import os
from pathlib import Path
import re
import threading
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,
read_html,
to_datetime,
)
import pandas._testing as tm
from pandas.core.arrays import (
ArrowStringArray,
StringArray,
)
from pandas.io.common import file_path_to_url
@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"
def test_bs4_version_fails(monkeypatch, datapath):
bs4 = pytest.importorskip("bs4")
pytest.importorskip("html5lib")
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(StringIO(url), match="google", flavor=flavor)
def test_same_ordering(datapath):
pytest.importorskip("bs4")
pytest.importorskip("lxml")
pytest.importorskip("html5lib")
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.fixture(
params=[
pytest.param("bs4", marks=[td.skip_if_no("bs4"), td.skip_if_no("html5lib")]),
pytest.param("lxml", marks=td.skip_if_no("lxml")),
],
)
def flavor_read_html(request):
return partial(read_html, flavor=request.param)
class TestReadHtml:
def test_literal_html_deprecation(self, flavor_read_html):
# GH 53785
msg = (
"Passing literal html to 'read_html' is deprecated and "
"will be removed in a future version. To read from a "
"literal string, wrap it in a 'StringIO' object."
)
with tm.assert_produces_warning(FutureWarning, match=msg):
flavor_read_html(
"""
"""
)
@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")
def test_to_html_compat(self, flavor_read_html):
df = (
DataFrame(
np.random.default_rng(2).random((4, 3)),
columns=pd.Index(list("abc"), dtype=object),
)
# pylint: disable-next=consider-using-f-string
.map("{:.3f}".format).astype(float)
)
out = df.to_html()
res = flavor_read_html(
StringIO(out), attrs={"class": "dataframe"}, index_col=0
)[0]
tm.assert_frame_equal(res, df)
def test_dtype_backend(self, string_storage, dtype_backend, flavor_read_html):
# 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_))
elif dtype_backend == "pyarrow":
pa = pytest.importorskip("pyarrow")
from pandas.arrays import ArrowExtensionArray
string_array = ArrowExtensionArray(pa.array(["a", "b", "c"]))
string_array_na = ArrowExtensionArray(pa.array(["a", "b", None]))
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 = flavor_read_html(StringIO(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
@pytest.mark.single_cpu
def test_banklist_url(self, httpserver, banklist_data, flavor_read_html):
with open(banklist_data, encoding="utf-8") as f:
httpserver.serve_content(content=f.read())
df1 = flavor_read_html(
# lxml cannot find attrs leave out for now
httpserver.url,
match="First Federal Bank of Florida", # attrs={"class": "dataTable"}
)
# lxml cannot find attrs leave out for now
df2 = flavor_read_html(
httpserver.url,
match="Metcalf Bank",
) # attrs={"class": "dataTable"})
assert_framelist_equal(df1, df2)
@pytest.mark.network
@pytest.mark.single_cpu
def test_spam_url(self, httpserver, spam_data, flavor_read_html):
with open(spam_data, encoding="utf-8") as f:
httpserver.serve_content(content=f.read())
df1 = flavor_read_html(httpserver.url, match=".*Water.*")
df2 = flavor_read_html(httpserver.url, match="Unit")
assert_framelist_equal(df1, df2)
@pytest.mark.slow
def test_banklist(self, banklist_data, flavor_read_html):
df1 = flavor_read_html(
banklist_data, match=".*Florida.*", attrs={"id": "table"}
)
df2 = flavor_read_html(
banklist_data, match="Metcalf Bank", attrs={"id": "table"}
)
assert_framelist_equal(df1, df2)
def test_spam(self, spam_data, flavor_read_html):
df1 = flavor_read_html(spam_data, match=".*Water.*")
df2 = flavor_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, flavor_read_html):
dfs = flavor_read_html(spam_data)
for df in dfs:
assert isinstance(df, DataFrame)
def test_banklist_no_match(self, banklist_data, flavor_read_html):
dfs = flavor_read_html(banklist_data, attrs={"id": "table"})
for df in dfs:
assert isinstance(df, DataFrame)
def test_spam_header(self, spam_data, flavor_read_html):
df = flavor_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, flavor_read_html):
df1 = flavor_read_html(spam_data, match=".*Water.*", skiprows=1)
df2 = flavor_read_html(spam_data, match="Unit", skiprows=1)
assert_framelist_equal(df1, df2)
def test_skiprows_range(self, spam_data, flavor_read_html):
df1 = flavor_read_html(spam_data, match=".*Water.*", skiprows=range(2))
df2 = flavor_read_html(spam_data, match="Unit", skiprows=range(2))
assert_framelist_equal(df1, df2)
def test_skiprows_list(self, spam_data, flavor_read_html):
df1 = flavor_read_html(spam_data, match=".*Water.*", skiprows=[1, 2])
df2 = flavor_read_html(spam_data, match="Unit", skiprows=[2, 1])
assert_framelist_equal(df1, df2)
def test_skiprows_set(self, spam_data, flavor_read_html):
df1 = flavor_read_html(spam_data, match=".*Water.*", skiprows={1, 2})
df2 = flavor_read_html(spam_data, match="Unit", skiprows={2, 1})
assert_framelist_equal(df1, df2)
def test_skiprows_slice(self, spam_data, flavor_read_html):
df1 = flavor_read_html(spam_data, match=".*Water.*", skiprows=1)
df2 = flavor_read_html(spam_data, match="Unit", skiprows=1)
assert_framelist_equal(df1, df2)
def test_skiprows_slice_short(self, spam_data, flavor_read_html):
df1 = flavor_read_html(spam_data, match=".*Water.*", skiprows=slice(2))
df2 = flavor_read_html(spam_data, match="Unit", skiprows=slice(2))
assert_framelist_equal(df1, df2)
def test_skiprows_slice_long(self, spam_data, flavor_read_html):
df1 = flavor_read_html(spam_data, match=".*Water.*", skiprows=slice(2, 5))
df2 = flavor_read_html(spam_data, match="Unit", skiprows=slice(4, 1, -1))
assert_framelist_equal(df1, df2)
def test_skiprows_ndarray(self, spam_data, flavor_read_html):
df1 = flavor_read_html(spam_data, match=".*Water.*", skiprows=np.arange(2))
df2 = flavor_read_html(spam_data, match="Unit", skiprows=np.arange(2))
assert_framelist_equal(df1, df2)
def test_skiprows_invalid(self, spam_data, flavor_read_html):
with pytest.raises(TypeError, match=("is not a valid type for skipping rows")):
flavor_read_html(spam_data, match=".*Water.*", skiprows="asdf")
def test_index(self, spam_data, flavor_read_html):
df1 = flavor_read_html(spam_data, match=".*Water.*", index_col=0)
df2 = flavor_read_html(spam_data, match="Unit", index_col=0)
assert_framelist_equal(df1, df2)
def test_header_and_index_no_types(self, spam_data, flavor_read_html):
df1 = flavor_read_html(spam_data, match=".*Water.*", header=1, index_col=0)
df2 = flavor_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, flavor_read_html):
df1 = flavor_read_html(spam_data, match=".*Water.*", header=1, index_col=0)
df2 = flavor_read_html(spam_data, match="Unit", header=1, index_col=0)
assert_framelist_equal(df1, df2)
def test_infer_types(self, spam_data, flavor_read_html):
# 10892 infer_types removed
df1 = flavor_read_html(spam_data, match=".*Water.*", index_col=0)
df2 = flavor_read_html(spam_data, match="Unit", index_col=0)
assert_framelist_equal(df1, df2)
def test_string_io(self, spam_data, flavor_read_html):
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 = flavor_read_html(data1, match=".*Water.*")
df2 = flavor_read_html(data2, match="Unit")
assert_framelist_equal(df1, df2)
def test_string(self, spam_data, flavor_read_html):
with open(spam_data, encoding="UTF-8") as f:
data = f.read()
df1 = flavor_read_html(StringIO(data), match=".*Water.*")
df2 = flavor_read_html(StringIO(data), match="Unit")
assert_framelist_equal(df1, df2)
def test_file_like(self, spam_data, flavor_read_html):
with open(spam_data, encoding="UTF-8") as f:
df1 = flavor_read_html(f, match=".*Water.*")
with open(spam_data, encoding="UTF-8") as f:
df2 = flavor_read_html(f, match="Unit")
assert_framelist_equal(df1, df2)
@pytest.mark.network
@pytest.mark.single_cpu
def test_bad_url_protocol(self, httpserver, flavor_read_html):
httpserver.serve_content("urlopen error unknown url type: git", code=404)
with pytest.raises(URLError, match="urlopen error unknown url type: git"):
flavor_read_html("git://github.com", match=".*Water.*")
@pytest.mark.slow
@pytest.mark.network
@pytest.mark.single_cpu
def test_invalid_url(self, httpserver, flavor_read_html):
httpserver.serve_content("Name or service not known", code=404)
with pytest.raises((URLError, ValueError), match="HTTP Error 404: NOT FOUND"):
flavor_read_html(httpserver.url, match=".*Water.*")
@pytest.mark.slow
def test_file_url(self, banklist_data, flavor_read_html):
url = banklist_data
dfs = flavor_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, flavor_read_html):
url = banklist_data
with pytest.raises(ValueError, match="No tables found"):
flavor_read_html(
url, match="First Federal Bank of Florida", attrs={"id": "tasdfable"}
)
@pytest.mark.slow
def test_multiindex_header(self, banklist_data, flavor_read_html):
df = flavor_read_html(
banklist_data, match="Metcalf", attrs={"id": "table"}, header=[0, 1]
)[0]
assert isinstance(df.columns, MultiIndex)
@pytest.mark.slow
def test_multiindex_index(self, banklist_data, flavor_read_html):
df = flavor_read_html(
banklist_data, match="Metcalf", attrs={"id": "table"}, index_col=[0, 1]
)[0]
assert isinstance(df.index, MultiIndex)
@pytest.mark.slow
def test_multiindex_header_index(self, banklist_data, flavor_read_html):
df = flavor_read_html(
banklist_data,
match="Metcalf",
attrs={"id": "table"},
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, flavor_read_html):
df = flavor_read_html(
banklist_data,
match="Metcalf",
attrs={"id": "table"},
header=[0, 1],
skiprows=1,
)[0]
assert isinstance(df.columns, MultiIndex)
@pytest.mark.slow
def test_multiindex_header_skiprows(self, banklist_data, flavor_read_html):
df = flavor_read_html(
banklist_data,
match="Metcalf",
attrs={"id": "table"},
header=[0, 1],
skiprows=1,
)[0]
assert isinstance(df.columns, MultiIndex)
@pytest.mark.slow
def test_multiindex_header_index_skiprows(self, banklist_data, flavor_read_html):
df = flavor_read_html(
banklist_data,
match="Metcalf",
attrs={"id": "table"},
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, flavor_read_html):
url = banklist_data
dfs = flavor_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, flavor_read_html):
msg = r"\(you passed a negative value\)"
with pytest.raises(ValueError, match=msg):
flavor_read_html(spam_data, match="Water", skiprows=-1)
@pytest.fixture
def python_docs(self):
return """
What's new in Python 2.7?
or all "What's new" documents since 2.0
Tutorial
start here
Library Reference
keep this under your pillow
Language Reference
describes syntax and language elements
Python Setup and Usage
how to use Python on different platforms
Python HOWTOs
in-depth documents on specific topics
|
Installing Python Modules
installing from the Python Package Index & other sources
Distributing Python Modules
publishing modules for installation by others
Extending and Embedding
tutorial for C/C++ programmers
Python/C API
reference for C/C++ programmers
FAQs
frequently asked questions (with answers!)
|
Indices and tables:
Python Global Module Index
quick access to all modules
General Index
all functions, classes, terms
Glossary
the most important terms explained
|
Search page
search this documentation
Complete Table of Contents
lists all sections and subsections
|
""" # noqa: E501
@pytest.mark.network
@pytest.mark.single_cpu
def test_multiple_matches(self, python_docs, httpserver, flavor_read_html):
httpserver.serve_content(content=python_docs)
dfs = flavor_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, flavor_read_html):
httpserver.serve_content(content=python_docs)
dfs = flavor_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, flavor_read_html):
"""
Make sure that read_html ignores empty tables.
"""
html = """
"""
result = flavor_read_html(StringIO(html))
assert len(result) == 1
def test_multiple_tbody(self, flavor_read_html):
# GH-20690
# Read all tbody tags within a single table.
result = flavor_read_html(
StringIO(
""""""
)
)[0]
expected = DataFrame(data=[[1, 2], [3, 4]], columns=["A", "B"])
tm.assert_frame_equal(result, expected)
def test_header_and_one_column(self, flavor_read_html):
"""
Don't fail with bs4 when there is a header and only one column
as described in issue #9178
"""
result = flavor_read_html(
StringIO(
""""""
)
)[0]
expected = DataFrame(data={"Header": "first"}, index=[0])
tm.assert_frame_equal(result, expected)
def test_thead_without_tr(self, flavor_read_html):
"""
Ensure parser adds within on malformed HTML.
"""
result = flavor_read_html(
StringIO(
"""
Country |
Municipality |
Year |
Ukraine |
Odessa |
1944 |
"""
)
)[0]
expected = DataFrame(
data=[["Ukraine", "Odessa", 1944]],
columns=["Country", "Municipality", "Year"],
)
tm.assert_frame_equal(result, expected)
def test_tfoot_read(self, flavor_read_html):
"""
Make sure that read_html reads tfoot, containing td or th.
Ignores empty tfoot
"""
data_template = """"""
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="footA | footB |
")
result1 = flavor_read_html(StringIO(data1))[0]
result2 = flavor_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, flavor_read_html):
# GH5048: if header is specified explicitly, an int column should be
# parsed as int while its header is parsed as str
result = flavor_read_html(
StringIO(
"""
"""
),
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, flavor_read_html):
from pandas.io.html import _remove_whitespace
def try_remove_ws(x):
try:
return _remove_whitespace(x)
except AttributeError:
return x
df = flavor_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, flavor_read_html):
gc = "Gold Canyon"
with open(banklist_data, encoding="utf-8") as f:
raw_text = f.read()
assert gc in raw_text
df = flavor_read_html(
banklist_data, match="Gold Canyon", attrs={"id": "table"}
)[0]
assert gc in df.to_string()
def test_different_number_of_cols(self, flavor_read_html):
expected = flavor_read_html(
StringIO(
"""
|
C_l0_g0 |
C_l0_g1 |
C_l0_g2 |
C_l0_g3 |
C_l0_g4 |
R_l0_g0 |
0.763 |
0.233 |
nan |
nan |
nan |
R_l0_g1 |
0.244 |
0.285 |
0.392 |
0.137 |
0.222 |
"""
),
index_col=0,
)[0]
result = flavor_read_html(
StringIO(
"""
|
C_l0_g0 |
C_l0_g1 |
C_l0_g2 |
C_l0_g3 |
C_l0_g4 |
R_l0_g0 |
0.763 |
0.233 |
R_l0_g1 |
0.244 |
0.285 |
0.392 |
0.137 |
0.222 |
"""
),
index_col=0,
)[0]
tm.assert_frame_equal(result, expected)
def test_colspan_rowspan_1(self, flavor_read_html):
# GH17054
result = flavor_read_html(
StringIO(
"""
"""
)
)[0]
expected = DataFrame([["a", "b", "c"]], columns=["A", "B", "C"])
tm.assert_frame_equal(result, expected)
def test_colspan_rowspan_copy_values(self, flavor_read_html):
# GH17054
# In ASCII, with lowercase letters being copies:
#
# X x Y Z W
# A B b z C
result = flavor_read_html(
StringIO(
"""
"""
),
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, flavor_read_html):
# GH17054
# In ASCII, with lowercase letters being copies:
#
# A B b b C
# a b b b D
result = flavor_read_html(
StringIO(
"""
"""
),
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, flavor_read_html):
# GH17054
# In ASCII, with lowercase letters being copies:
#
# A B
# C b
result = flavor_read_html(
StringIO(
"""
"""
),
header=0,
)[0]
expected = DataFrame(data=[["C", "B"]], columns=["A", "B"])
tm.assert_frame_equal(result, expected)
def test_rowspan_only_rows(self, flavor_read_html):
# GH17054
result = flavor_read_html(
StringIO(
"""
"""
),
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, flavor_read_html):
# GH17054
result = flavor_read_html(
StringIO(
"""
"""
)
)[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, flavor_read_html):
df = DataFrame({"date": date_range("1/1/2001", periods=10)})
expected = df.to_html()
res = flavor_read_html(StringIO(expected), parse_dates=[1], index_col=0)
tm.assert_frame_equal(df, res[0])
res = flavor_read_html(StringIO(expected), parse_dates=["date"], index_col=0)
tm.assert_frame_equal(df, res[0])
def test_parse_dates_combine(self, flavor_read_html):
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 = flavor_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, flavor_read_html):
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 = flavor_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, flavor_read_html):
data = datapath("io", "data", "html", "wikipedia_states.html")
result = flavor_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, flavor_read_html):
result = flavor_read_html(
StringIO(
"""
"""
),
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, flavor_read_html):
# GH 12907
result = flavor_read_html(
StringIO(
"""
"""
),
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, flavor_read_html):
# 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):
flavor_read_html(spam_data, header=arg)
def test_converters(self, flavor_read_html):
# GH 13461
result = flavor_read_html(
StringIO(
""""""
),
converters={"a": str},
)[0]
expected = DataFrame({"a": ["0.763", "0.244"]})
tm.assert_frame_equal(result, expected)
def test_na_values(self, flavor_read_html):
# GH 13461
result = flavor_read_html(
StringIO(
""""""
),
na_values=[0.244],
)[0]
expected = DataFrame({"a": [0.763, np.nan]})
tm.assert_frame_equal(result, expected)
def test_keep_default_na(self, flavor_read_html):
html_data = """"""
expected_df = DataFrame({"a": ["N/A", "NA"]})
html_df = flavor_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 = flavor_read_html(StringIO(html_data), keep_default_na=True)[0]
tm.assert_frame_equal(expected_df, html_df)
def test_preserve_empty_rows(self, flavor_read_html):
result = flavor_read_html(
StringIO(
"""
"""
)
)[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, flavor_read_html):
result = flavor_read_html(
StringIO(
"""
"""
)
)[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, flavor_read_html):
# 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 = flavor_read_html(StringIO(html))[0]
tm.assert_frame_equal(expected_df, html_df)
def test_works_on_valid_markup(self, datapath, flavor_read_html):
filename = datapath("io", "data", "html", "valid_markup.html")
dfs = flavor_read_html(filename, index_col=0)
assert isinstance(dfs, list)
assert isinstance(dfs[0], DataFrame)
@pytest.mark.slow
def test_fallback_success(self, datapath, flavor_read_html):
banklist_data = datapath("io", "data", "html", "banklist.html")
flavor_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, flavor_read_html):
# GH 20027
data = """
"""
dfs = flavor_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, flavor_read_html):
html_table = """
"""
result = flavor_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, flavor_read_html):
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 = flavor_read_html(
fobj.read(), encoding=encoding, index_col=0
).pop()
with open(html_encoding_file, "rb") as fobj:
from_file_like = flavor_read_html(
BytesIO(fobj.read()), encoding=encoding, index_col=0
).pop()
from_filename = flavor_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, flavor_read_html):
# Issue #17975
if flavor_read_html.keywords.get("flavor") == "lxml":
pytest.skip("Not applicable for lxml")
class UnseekableStringIO(StringIO):
def seekable(self):
return False
bad = UnseekableStringIO(
"""
"""
)
assert flavor_read_html(bad)
with pytest.raises(ValueError, match="passed a non-rewindable file object"):
flavor_read_html(bad)
def test_parse_failure_rewinds(self, flavor_read_html):
# 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("")
bad = MockFile("")
assert flavor_read_html(good)
assert flavor_read_html(bad)
@pytest.mark.slow
@pytest.mark.single_cpu
def test_importcheck_thread_safety(self, datapath, flavor_read_html):
# 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=flavor_read_html, args=(filename,))
helper_thread2 = ErrorThread(target=flavor_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, flavor_read_html):
# GH 37705
file_path_string = datapath("io", "data", "html", "spam.html")
file_path = Path(file_path_string)
df1 = flavor_read_html(file_path_string)[0]
df2 = flavor_read_html(file_path)[0]
tm.assert_frame_equal(df1, df2)
def test_parse_br_as_space(self, flavor_read_html):
# GH 29528: pd.read_html() convert
to space
result = flavor_read_html(
StringIO(
"""
"""
)
)[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, flavor_read_html):
gh_13141_data = """
"""
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 = flavor_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, flavor_read_html):
# GH 48316
data = """
"""
result = flavor_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, flavor_read_html):
# GH 48316
data = """
"""
result = flavor_read_html(StringIO(data))[0]
expected = DataFrame(data=[["A1", "B1"], ["A2", "B2"]], columns=["A", "B"])
tm.assert_frame_equal(result, expected)