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Updated script that can be controled by Nodejs web app

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2024-11-25 12:24:18 +07:00
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lib/python3.13/site-packages/pandas/tests/io/parser/common/__init__.py Normal file
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lib/python3.13/site-packages/pandas/tests/io/parser/common/test_chunksize.py Normal file
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"""
Tests that work on both the Python and C engines but do not have a
specific classification into the other test modules.
"""
from io import StringIO
import numpy as np
import pytest
from pandas._libs import parsers as libparsers
from pandas.errors import DtypeWarning
from pandas import (
DataFrame,
concat,
)
import pandas._testing as tm
pytestmark = pytest.mark.filterwarnings(
"ignore:Passing a BlockManager to DataFrame:DeprecationWarning"
)
@pytest.mark.parametrize("index_col", [0, "index"])
def test_read_chunksize_with_index(all_parsers, index_col):
parser = all_parsers
data = """index,A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15
qux,12,13,14,15
foo2,12,13,14,15
bar2,12,13,14,15
"""
expected = DataFrame(
[
["foo", 2, 3, 4, 5],
["bar", 7, 8, 9, 10],
["baz", 12, 13, 14, 15],
["qux", 12, 13, 14, 15],
["foo2", 12, 13, 14, 15],
["bar2", 12, 13, 14, 15],
],
columns=["index", "A", "B", "C", "D"],
)
expected = expected.set_index("index")
if parser.engine == "pyarrow":
msg = "The 'chunksize' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
with parser.read_csv(StringIO(data), index_col=0, chunksize=2) as reader:
list(reader)
return
with parser.read_csv(StringIO(data), index_col=0, chunksize=2) as reader:
chunks = list(reader)
tm.assert_frame_equal(chunks[0], expected[:2])
tm.assert_frame_equal(chunks[1], expected[2:4])
tm.assert_frame_equal(chunks[2], expected[4:])
@pytest.mark.parametrize("chunksize", [1.3, "foo", 0])
def test_read_chunksize_bad(all_parsers, chunksize):
data = """index,A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15
qux,12,13,14,15
foo2,12,13,14,15
bar2,12,13,14,15
"""
parser = all_parsers
msg = r"'chunksize' must be an integer >=1"
if parser.engine == "pyarrow":
msg = "The 'chunksize' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
with parser.read_csv(StringIO(data), chunksize=chunksize) as _:
pass
@pytest.mark.parametrize("chunksize", [2, 8])
def test_read_chunksize_and_nrows(all_parsers, chunksize):
# see gh-15755
data = """index,A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15
qux,12,13,14,15
foo2,12,13,14,15
bar2,12,13,14,15
"""
parser = all_parsers
kwargs = {"index_col": 0, "nrows": 5}
if parser.engine == "pyarrow":
msg = "The 'nrows' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
parser.read_csv(StringIO(data), **kwargs)
return
expected = parser.read_csv(StringIO(data), **kwargs)
with parser.read_csv(StringIO(data), chunksize=chunksize, **kwargs) as reader:
tm.assert_frame_equal(concat(reader), expected)
def test_read_chunksize_and_nrows_changing_size(all_parsers):
data = """index,A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15
qux,12,13,14,15
foo2,12,13,14,15
bar2,12,13,14,15
"""
parser = all_parsers
kwargs = {"index_col": 0, "nrows": 5}
if parser.engine == "pyarrow":
msg = "The 'nrows' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
parser.read_csv(StringIO(data), **kwargs)
return
expected = parser.read_csv(StringIO(data), **kwargs)
with parser.read_csv(StringIO(data), chunksize=8, **kwargs) as reader:
tm.assert_frame_equal(reader.get_chunk(size=2), expected.iloc[:2])
tm.assert_frame_equal(reader.get_chunk(size=4), expected.iloc[2:5])
with pytest.raises(StopIteration, match=""):
reader.get_chunk(size=3)
def test_get_chunk_passed_chunksize(all_parsers):
parser = all_parsers
data = """A,B,C
1,2,3
4,5,6
7,8,9
1,2,3"""
if parser.engine == "pyarrow":
msg = "The 'chunksize' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
with parser.read_csv(StringIO(data), chunksize=2) as reader:
reader.get_chunk()
return
with parser.read_csv(StringIO(data), chunksize=2) as reader:
result = reader.get_chunk()
expected = DataFrame([[1, 2, 3], [4, 5, 6]], columns=["A", "B", "C"])
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize("kwargs", [{}, {"index_col": 0}])
def test_read_chunksize_compat(all_parsers, kwargs):
# see gh-12185
data = """index,A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15
qux,12,13,14,15
foo2,12,13,14,15
bar2,12,13,14,15
"""
parser = all_parsers
result = parser.read_csv(StringIO(data), **kwargs)
if parser.engine == "pyarrow":
msg = "The 'chunksize' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
with parser.read_csv(StringIO(data), chunksize=2, **kwargs) as reader:
concat(reader)
return
with parser.read_csv(StringIO(data), chunksize=2, **kwargs) as reader:
via_reader = concat(reader)
tm.assert_frame_equal(via_reader, result)
def test_read_chunksize_jagged_names(all_parsers):
# see gh-23509
parser = all_parsers
data = "\n".join(["0"] * 7 + [",".join(["0"] * 10)])
expected = DataFrame([[0] + [np.nan] * 9] * 7 + [[0] * 10])
if parser.engine == "pyarrow":
msg = "The 'chunksize' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
with parser.read_csv(
StringIO(data), names=range(10), chunksize=4
) as reader:
concat(reader)
return
with parser.read_csv(StringIO(data), names=range(10), chunksize=4) as reader:
result = concat(reader)
tm.assert_frame_equal(result, expected)
def test_chunk_begins_with_newline_whitespace(all_parsers):
# see gh-10022
parser = all_parsers
data = "\n hello\nworld\n"
result = parser.read_csv(StringIO(data), header=None)
expected = DataFrame([" hello", "world"])
tm.assert_frame_equal(result, expected)
@pytest.mark.slow
def test_chunks_have_consistent_numerical_type(all_parsers, monkeypatch):
# mainly an issue with the C parser
heuristic = 2**3
parser = all_parsers
integers = [str(i) for i in range(heuristic - 1)]
data = "a\n" + "\n".join(integers + ["1.0", "2.0"] + integers)
# Coercions should work without warnings.
with monkeypatch.context() as m:
m.setattr(libparsers, "DEFAULT_BUFFER_HEURISTIC", heuristic)
result = parser.read_csv(StringIO(data))
assert type(result.a[0]) is np.float64
assert result.a.dtype == float
def test_warn_if_chunks_have_mismatched_type(all_parsers):
warning_type = None
parser = all_parsers
size = 10000
# see gh-3866: if chunks are different types and can't
# be coerced using numerical types, then issue warning.
if parser.engine == "c" and parser.low_memory:
warning_type = DtypeWarning
# Use larger size to hit warning path
size = 499999
integers = [str(i) for i in range(size)]
data = "a\n" + "\n".join(integers + ["a", "b"] + integers)
buf = StringIO(data)
if parser.engine == "pyarrow":
df = parser.read_csv(
buf,
)
else:
df = parser.read_csv_check_warnings(
warning_type,
r"Columns \(0\) have mixed types. "
"Specify dtype option on import or set low_memory=False.",
buf,
)
assert df.a.dtype == object
@pytest.mark.parametrize("iterator", [True, False])
def test_empty_with_nrows_chunksize(all_parsers, iterator):
# see gh-9535
parser = all_parsers
expected = DataFrame(columns=["foo", "bar"])
nrows = 10
data = StringIO("foo,bar\n")
if parser.engine == "pyarrow":
msg = (
"The '(nrows|chunksize)' option is not supported with the 'pyarrow' engine"
)
with pytest.raises(ValueError, match=msg):
if iterator:
with parser.read_csv(data, chunksize=nrows) as reader:
next(iter(reader))
else:
parser.read_csv(data, nrows=nrows)
return
if iterator:
with parser.read_csv(data, chunksize=nrows) as reader:
result = next(iter(reader))
else:
result = parser.read_csv(data, nrows=nrows)
tm.assert_frame_equal(result, expected)
def test_read_csv_memory_growth_chunksize(all_parsers):
# see gh-24805
#
# Let's just make sure that we don't crash
# as we iteratively process all chunks.
parser = all_parsers
with tm.ensure_clean() as path:
with open(path, "w", encoding="utf-8") as f:
for i in range(1000):
f.write(str(i) + "\n")
if parser.engine == "pyarrow":
msg = "The 'chunksize' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
with parser.read_csv(path, chunksize=20) as result:
for _ in result:
pass
return
with parser.read_csv(path, chunksize=20) as result:
for _ in result:
pass
def test_chunksize_with_usecols_second_block_shorter(all_parsers):
# GH#21211
parser = all_parsers
data = """1,2,3,4
5,6,7,8
9,10,11
"""
if parser.engine == "pyarrow":
msg = "The 'chunksize' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
parser.read_csv(
StringIO(data),
names=["a", "b"],
chunksize=2,
usecols=[0, 1],
header=None,
)
return
result_chunks = parser.read_csv(
StringIO(data),
names=["a", "b"],
chunksize=2,
usecols=[0, 1],
header=None,
)
expected_frames = [
DataFrame({"a": [1, 5], "b": [2, 6]}),
DataFrame({"a": [9], "b": [10]}, index=[2]),
]
for i, result in enumerate(result_chunks):
tm.assert_frame_equal(result, expected_frames[i])
def test_chunksize_second_block_shorter(all_parsers):
# GH#21211
parser = all_parsers
data = """a,b,c,d
1,2,3,4
5,6,7,8
9,10,11
"""
if parser.engine == "pyarrow":
msg = "The 'chunksize' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
parser.read_csv(StringIO(data), chunksize=2)
return
result_chunks = parser.read_csv(StringIO(data), chunksize=2)
expected_frames = [
DataFrame({"a": [1, 5], "b": [2, 6], "c": [3, 7], "d": [4, 8]}),
DataFrame({"a": [9], "b": [10], "c": [11], "d": [np.nan]}, index=[2]),
]
for i, result in enumerate(result_chunks):
tm.assert_frame_equal(result, expected_frames[i])

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lib/python3.13/site-packages/pandas/tests/io/parser/common/test_common_basic.py Normal file
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"""
Tests that work on both the Python and C engines but do not have a
specific classification into the other test modules.
"""
from datetime import datetime
from inspect import signature
from io import StringIO
import os
from pathlib import Path
import sys
import numpy as np
import pytest
from pandas.errors import (
EmptyDataError,
ParserError,
ParserWarning,
)
from pandas import (
DataFrame,
Index,
Timestamp,
compat,
)
import pandas._testing as tm
from pandas.io.parsers import TextFileReader
from pandas.io.parsers.c_parser_wrapper import CParserWrapper
pytestmark = pytest.mark.filterwarnings(
"ignore:Passing a BlockManager to DataFrame:DeprecationWarning"
)
xfail_pyarrow = pytest.mark.usefixtures("pyarrow_xfail")
skip_pyarrow = pytest.mark.usefixtures("pyarrow_skip")
def test_override_set_noconvert_columns():
# see gh-17351
#
# Usecols needs to be sorted in _set_noconvert_columns based
# on the test_usecols_with_parse_dates test from test_usecols.py
class MyTextFileReader(TextFileReader):
def __init__(self) -> None:
self._currow = 0
self.squeeze = False
class MyCParserWrapper(CParserWrapper):
def _set_noconvert_columns(self):
if self.usecols_dtype == "integer":
# self.usecols is a set, which is documented as unordered
# but in practice, a CPython set of integers is sorted.
# In other implementations this assumption does not hold.
# The following code simulates a different order, which
# before GH 17351 would cause the wrong columns to be
# converted via the parse_dates parameter
self.usecols = list(self.usecols)
self.usecols.reverse()
return CParserWrapper._set_noconvert_columns(self)
data = """a,b,c,d,e
0,1,2014-01-01,09:00,4
0,1,2014-01-02,10:00,4"""
parse_dates = [[1, 2]]
cols = {
"a": [0, 0],
"c_d": [Timestamp("2014-01-01 09:00:00"), Timestamp("2014-01-02 10:00:00")],
}
expected = DataFrame(cols, columns=["c_d", "a"])
parser = MyTextFileReader()
parser.options = {
"usecols": [0, 2, 3],
"parse_dates": parse_dates,
"delimiter": ",",
}
parser.engine = "c"
parser._engine = MyCParserWrapper(StringIO(data), **parser.options)
result = parser.read()
tm.assert_frame_equal(result, expected)
def test_read_csv_local(all_parsers, csv1):
prefix = "file:///" if compat.is_platform_windows() else "file://"
parser = all_parsers
fname = prefix + str(os.path.abspath(csv1))
result = parser.read_csv(fname, index_col=0, parse_dates=True)
# TODO: make unit check more specific
if parser.engine == "pyarrow":
result.index = result.index.as_unit("ns")
expected = DataFrame(
[
[0.980269, 3.685731, -0.364216805298, -1.159738],
[1.047916, -0.041232, -0.16181208307, 0.212549],
[0.498581, 0.731168, -0.537677223318, 1.346270],
[1.120202, 1.567621, 0.00364077397681, 0.675253],
[-0.487094, 0.571455, -1.6116394093, 0.103469],
[0.836649, 0.246462, 0.588542635376, 1.062782],
[-0.157161, 1.340307, 1.1957779562, -1.097007],
],
columns=["A", "B", "C", "D"],
index=Index(
[
datetime(2000, 1, 3),
datetime(2000, 1, 4),
datetime(2000, 1, 5),
datetime(2000, 1, 6),
datetime(2000, 1, 7),
datetime(2000, 1, 10),
datetime(2000, 1, 11),
],
name="index",
),
)
tm.assert_frame_equal(result, expected)
def test_1000_sep(all_parsers):
parser = all_parsers
data = """A|B|C
1|2,334|5
10|13|10.
"""
expected = DataFrame({"A": [1, 10], "B": [2334, 13], "C": [5, 10.0]})
if parser.engine == "pyarrow":
msg = "The 'thousands' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
parser.read_csv(StringIO(data), sep="|", thousands=",")
return
result = parser.read_csv(StringIO(data), sep="|", thousands=",")
tm.assert_frame_equal(result, expected)
@xfail_pyarrow # ValueError: Found non-unique column index
def test_unnamed_columns(all_parsers):
data = """A,B,C,,
1,2,3,4,5
6,7,8,9,10
11,12,13,14,15
"""
parser = all_parsers
expected = DataFrame(
[[1, 2, 3, 4, 5], [6, 7, 8, 9, 10], [11, 12, 13, 14, 15]],
dtype=np.int64,
columns=["A", "B", "C", "Unnamed: 3", "Unnamed: 4"],
)
result = parser.read_csv(StringIO(data))
tm.assert_frame_equal(result, expected)
def test_csv_mixed_type(all_parsers):
data = """A,B,C
a,1,2
b,3,4
c,4,5
"""
parser = all_parsers
expected = DataFrame({"A": ["a", "b", "c"], "B": [1, 3, 4], "C": [2, 4, 5]})
result = parser.read_csv(StringIO(data))
tm.assert_frame_equal(result, expected)
def test_read_csv_low_memory_no_rows_with_index(all_parsers):
# see gh-21141
parser = all_parsers
if not parser.low_memory:
pytest.skip("This is a low-memory specific test")
data = """A,B,C
1,1,1,2
2,2,3,4
3,3,4,5
"""
if parser.engine == "pyarrow":
msg = "The 'nrows' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
parser.read_csv(StringIO(data), low_memory=True, index_col=0, nrows=0)
return
result = parser.read_csv(StringIO(data), low_memory=True, index_col=0, nrows=0)
expected = DataFrame(columns=["A", "B", "C"])
tm.assert_frame_equal(result, expected)
def test_read_csv_dataframe(all_parsers, csv1):
parser = all_parsers
result = parser.read_csv(csv1, index_col=0, parse_dates=True)
# TODO: make unit check more specific
if parser.engine == "pyarrow":
result.index = result.index.as_unit("ns")
expected = DataFrame(
[
[0.980269, 3.685731, -0.364216805298, -1.159738],
[1.047916, -0.041232, -0.16181208307, 0.212549],
[0.498581, 0.731168, -0.537677223318, 1.346270],
[1.120202, 1.567621, 0.00364077397681, 0.675253],
[-0.487094, 0.571455, -1.6116394093, 0.103469],
[0.836649, 0.246462, 0.588542635376, 1.062782],
[-0.157161, 1.340307, 1.1957779562, -1.097007],
],
columns=["A", "B", "C", "D"],
index=Index(
[
datetime(2000, 1, 3),
datetime(2000, 1, 4),
datetime(2000, 1, 5),
datetime(2000, 1, 6),
datetime(2000, 1, 7),
datetime(2000, 1, 10),
datetime(2000, 1, 11),
],
name="index",
),
)
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize("nrows", [3, 3.0])
def test_read_nrows(all_parsers, nrows):
# see gh-10476
data = """index,A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15
qux,12,13,14,15
foo2,12,13,14,15
bar2,12,13,14,15
"""
expected = DataFrame(
[["foo", 2, 3, 4, 5], ["bar", 7, 8, 9, 10], ["baz", 12, 13, 14, 15]],
columns=["index", "A", "B", "C", "D"],
)
parser = all_parsers
if parser.engine == "pyarrow":
msg = "The 'nrows' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
parser.read_csv(StringIO(data), nrows=nrows)
return
result = parser.read_csv(StringIO(data), nrows=nrows)
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize("nrows", [1.2, "foo", -1])
def test_read_nrows_bad(all_parsers, nrows):
data = """index,A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15
qux,12,13,14,15
foo2,12,13,14,15
bar2,12,13,14,15
"""
msg = r"'nrows' must be an integer >=0"
parser = all_parsers
if parser.engine == "pyarrow":
msg = "The 'nrows' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
parser.read_csv(StringIO(data), nrows=nrows)
def test_nrows_skipfooter_errors(all_parsers):
msg = "'skipfooter' not supported with 'nrows'"
data = "a\n1\n2\n3\n4\n5\n6"
parser = all_parsers
with pytest.raises(ValueError, match=msg):
parser.read_csv(StringIO(data), skipfooter=1, nrows=5)
@skip_pyarrow
def test_missing_trailing_delimiters(all_parsers):
parser = all_parsers
data = """A,B,C,D
1,2,3,4
1,3,3,
1,4,5"""
result = parser.read_csv(StringIO(data))
expected = DataFrame(
[[1, 2, 3, 4], [1, 3, 3, np.nan], [1, 4, 5, np.nan]],
columns=["A", "B", "C", "D"],
)
tm.assert_frame_equal(result, expected)
def test_skip_initial_space(all_parsers):
data = (
'"09-Apr-2012", "01:10:18.300", 2456026.548822908, 12849, '
"1.00361, 1.12551, 330.65659, 0355626618.16711, 73.48821, "
"314.11625, 1917.09447, 179.71425, 80.000, 240.000, -350, "
"70.06056, 344.98370, 1, 1, -0.689265, -0.692787, "
"0.212036, 14.7674, 41.605, -9999.0, -9999.0, "
"-9999.0, -9999.0, -9999.0, -9999.0, 000, 012, 128"
)
parser = all_parsers
if parser.engine == "pyarrow":
msg = "The 'skipinitialspace' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
parser.read_csv(
StringIO(data),
names=list(range(33)),
header=None,
na_values=["-9999.0"],
skipinitialspace=True,
)
return
result = parser.read_csv(
StringIO(data),
names=list(range(33)),
header=None,
na_values=["-9999.0"],
skipinitialspace=True,
)
expected = DataFrame(
[
[
"09-Apr-2012",
"01:10:18.300",
2456026.548822908,
12849,
1.00361,
1.12551,
330.65659,
355626618.16711,
73.48821,
314.11625,
1917.09447,
179.71425,
80.0,
240.0,
-350,
70.06056,
344.9837,
1,
1,
-0.689265,
-0.692787,
0.212036,
14.7674,
41.605,
np.nan,
np.nan,
np.nan,
np.nan,
np.nan,
np.nan,
0,
12,
128,
]
]
)
tm.assert_frame_equal(result, expected)
@skip_pyarrow
def test_trailing_delimiters(all_parsers):
# see gh-2442
data = """A,B,C
1,2,3,
4,5,6,
7,8,9,"""
parser = all_parsers
result = parser.read_csv(StringIO(data), index_col=False)
expected = DataFrame({"A": [1, 4, 7], "B": [2, 5, 8], "C": [3, 6, 9]})
tm.assert_frame_equal(result, expected)
def test_escapechar(all_parsers):
# https://stackoverflow.com/questions/13824840/feature-request-for-
# pandas-read-csv
data = '''SEARCH_TERM,ACTUAL_URL
"bra tv board","http://www.ikea.com/se/sv/catalog/categories/departments/living_room/10475/?se%7cps%7cnonbranded%7cvardagsrum%7cgoogle%7ctv_bord"
"tv p\xc3\xa5 hjul","http://www.ikea.com/se/sv/catalog/categories/departments/living_room/10475/?se%7cps%7cnonbranded%7cvardagsrum%7cgoogle%7ctv_bord"
"SLAGBORD, \\"Bergslagen\\", IKEA:s 1700-tals series","http://www.ikea.com/se/sv/catalog/categories/departments/living_room/10475/?se%7cps%7cnonbranded%7cvardagsrum%7cgoogle%7ctv_bord"'''
parser = all_parsers
result = parser.read_csv(
StringIO(data), escapechar="\\", quotechar='"', encoding="utf-8"
)
assert result["SEARCH_TERM"][2] == 'SLAGBORD, "Bergslagen", IKEA:s 1700-tals series'
tm.assert_index_equal(result.columns, Index(["SEARCH_TERM", "ACTUAL_URL"]))
def test_ignore_leading_whitespace(all_parsers):
# see gh-3374, gh-6607
parser = all_parsers
data = " a b c\n 1 2 3\n 4 5 6\n 7 8 9"
if parser.engine == "pyarrow":
msg = "the 'pyarrow' engine does not support regex separators"
with pytest.raises(ValueError, match=msg):
parser.read_csv(StringIO(data), sep=r"\s+")
return
result = parser.read_csv(StringIO(data), sep=r"\s+")
expected = DataFrame({"a": [1, 4, 7], "b": [2, 5, 8], "c": [3, 6, 9]})
tm.assert_frame_equal(result, expected)
@skip_pyarrow
@pytest.mark.parametrize("usecols", [None, [0, 1], ["a", "b"]])
def test_uneven_lines_with_usecols(all_parsers, usecols):
# see gh-12203
parser = all_parsers
data = r"""a,b,c
0,1,2
3,4,5,6,7
8,9,10"""
if usecols is None:
# Make sure that an error is still raised
# when the "usecols" parameter is not provided.
msg = r"Expected \d+ fields in line \d+, saw \d+"
with pytest.raises(ParserError, match=msg):
parser.read_csv(StringIO(data))
else:
expected = DataFrame({"a": [0, 3, 8], "b": [1, 4, 9]})
result = parser.read_csv(StringIO(data), usecols=usecols)
tm.assert_frame_equal(result, expected)
@skip_pyarrow
@pytest.mark.parametrize(
"data,kwargs,expected",
[
# First, check to see that the response of parser when faced with no
# provided columns raises the correct error, with or without usecols.
("", {}, None),
("", {"usecols": ["X"]}, None),
(
",,",
{"names": ["Dummy", "X", "Dummy_2"], "usecols": ["X"]},
DataFrame(columns=["X"], index=[0], dtype=np.float64),
),
(
"",
{"names": ["Dummy", "X", "Dummy_2"], "usecols": ["X"]},
DataFrame(columns=["X"]),
),
],
)
def test_read_empty_with_usecols(all_parsers, data, kwargs, expected):
# see gh-12493
parser = all_parsers
if expected is None:
msg = "No columns to parse from file"
with pytest.raises(EmptyDataError, match=msg):
parser.read_csv(StringIO(data), **kwargs)
else:
result = parser.read_csv(StringIO(data), **kwargs)
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize(
"kwargs,expected",
[
# gh-8661, gh-8679: this should ignore six lines, including
# lines with trailing whitespace and blank lines.
(
{
"header": None,
"delim_whitespace": True,
"skiprows": [0, 1, 2, 3, 5, 6],
"skip_blank_lines": True,
},
DataFrame([[1.0, 2.0, 4.0], [5.1, np.nan, 10.0]]),
),
# gh-8983: test skipping set of rows after a row with trailing spaces.
(
{
"delim_whitespace": True,
"skiprows": [1, 2, 3, 5, 6],
"skip_blank_lines": True,
},
DataFrame({"A": [1.0, 5.1], "B": [2.0, np.nan], "C": [4.0, 10]}),
),
],
)
def test_trailing_spaces(all_parsers, kwargs, expected):
data = "A B C \nrandom line with trailing spaces \nskip\n1,2,3\n1,2.,4.\nrandom line with trailing tabs\t\t\t\n \n5.1,NaN,10.0\n" # noqa: E501
parser = all_parsers
depr_msg = "The 'delim_whitespace' keyword in pd.read_csv is deprecated"
if parser.engine == "pyarrow":
msg = "The 'delim_whitespace' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
with tm.assert_produces_warning(
FutureWarning, match=depr_msg, check_stacklevel=False
):
parser.read_csv(StringIO(data.replace(",", " ")), **kwargs)
return
with tm.assert_produces_warning(
FutureWarning, match=depr_msg, check_stacklevel=False
):
result = parser.read_csv(StringIO(data.replace(",", " ")), **kwargs)
tm.assert_frame_equal(result, expected)
def test_raise_on_sep_with_delim_whitespace(all_parsers):
# see gh-6607
data = "a b c\n1 2 3"
parser = all_parsers
depr_msg = "The 'delim_whitespace' keyword in pd.read_csv is deprecated"
with pytest.raises(ValueError, match="you can only specify one"):
with tm.assert_produces_warning(
FutureWarning, match=depr_msg, check_stacklevel=False
):
parser.read_csv(StringIO(data), sep=r"\s", delim_whitespace=True)
def test_read_filepath_or_buffer(all_parsers):
# see gh-43366
parser = all_parsers
with pytest.raises(TypeError, match="Expected file path name or file-like"):
parser.read_csv(filepath_or_buffer=b"input")
@pytest.mark.parametrize("delim_whitespace", [True, False])
def test_single_char_leading_whitespace(all_parsers, delim_whitespace):
# see gh-9710
parser = all_parsers
data = """\
MyColumn
a
b
a
b\n"""
expected = DataFrame({"MyColumn": list("abab")})
depr_msg = "The 'delim_whitespace' keyword in pd.read_csv is deprecated"
if parser.engine == "pyarrow":
msg = "The 'skipinitialspace' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
with tm.assert_produces_warning(
FutureWarning, match=depr_msg, check_stacklevel=False
):
parser.read_csv(
StringIO(data),
skipinitialspace=True,
delim_whitespace=delim_whitespace,
)
return
with tm.assert_produces_warning(
FutureWarning, match=depr_msg, check_stacklevel=False
):
result = parser.read_csv(
StringIO(data), skipinitialspace=True, delim_whitespace=delim_whitespace
)
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize(
"sep,skip_blank_lines,exp_data",
[
(",", True, [[1.0, 2.0, 4.0], [5.0, np.nan, 10.0], [-70.0, 0.4, 1.0]]),
(r"\s+", True, [[1.0, 2.0, 4.0], [5.0, np.nan, 10.0], [-70.0, 0.4, 1.0]]),
(
",",
False,
[
[1.0, 2.0, 4.0],
[np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan],
[5.0, np.nan, 10.0],
[np.nan, np.nan, np.nan],
[-70.0, 0.4, 1.0],
],
),
],
)
def test_empty_lines(all_parsers, sep, skip_blank_lines, exp_data, request):
parser = all_parsers
data = """\
A,B,C
1,2.,4.
5.,NaN,10.0
-70,.4,1
"""
if sep == r"\s+":
data = data.replace(",", " ")
if parser.engine == "pyarrow":
msg = "the 'pyarrow' engine does not support regex separators"
with pytest.raises(ValueError, match=msg):
parser.read_csv(
StringIO(data), sep=sep, skip_blank_lines=skip_blank_lines
)
return
result = parser.read_csv(StringIO(data), sep=sep, skip_blank_lines=skip_blank_lines)
expected = DataFrame(exp_data, columns=["A", "B", "C"])
tm.assert_frame_equal(result, expected)
@skip_pyarrow
def test_whitespace_lines(all_parsers):
parser = all_parsers
data = """
\t \t\t
\t
A,B,C
\t 1,2.,4.
5.,NaN,10.0
"""
expected = DataFrame([[1, 2.0, 4.0], [5.0, np.nan, 10.0]], columns=["A", "B", "C"])
result = parser.read_csv(StringIO(data))
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize(
"data,expected",
[
(
""" A B C D
a 1 2 3 4
b 1 2 3 4
c 1 2 3 4
""",
DataFrame(
[[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4]],
columns=["A", "B", "C", "D"],
index=["a", "b", "c"],
),
),
(
" a b c\n1 2 3 \n4 5 6\n 7 8 9",
DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9]], columns=["a", "b", "c"]),
),
],
)
def test_whitespace_regex_separator(all_parsers, data, expected):
# see gh-6607
parser = all_parsers
if parser.engine == "pyarrow":
msg = "the 'pyarrow' engine does not support regex separators"
with pytest.raises(ValueError, match=msg):
parser.read_csv(StringIO(data), sep=r"\s+")
return
result = parser.read_csv(StringIO(data), sep=r"\s+")
tm.assert_frame_equal(result, expected)
def test_sub_character(all_parsers, csv_dir_path):
# see gh-16893
filename = os.path.join(csv_dir_path, "sub_char.csv")
expected = DataFrame([[1, 2, 3]], columns=["a", "\x1ab", "c"])
parser = all_parsers
result = parser.read_csv(filename)
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize("filename", ["sé-es-vé.csv", "ru-sй.csv", "中文文件名.csv"])
def test_filename_with_special_chars(all_parsers, filename):
# see gh-15086.
parser = all_parsers
df = DataFrame({"a": [1, 2, 3]})
with tm.ensure_clean(filename) as path:
df.to_csv(path, index=False)
result = parser.read_csv(path)
tm.assert_frame_equal(result, df)
def test_read_table_same_signature_as_read_csv(all_parsers):
# GH-34976
parser = all_parsers
table_sign = signature(parser.read_table)
csv_sign = signature(parser.read_csv)
assert table_sign.parameters.keys() == csv_sign.parameters.keys()
assert table_sign.return_annotation == csv_sign.return_annotation
for key, csv_param in csv_sign.parameters.items():
table_param = table_sign.parameters[key]
if key == "sep":
assert csv_param.default == ","
assert table_param.default == "\t"
assert table_param.annotation == csv_param.annotation
assert table_param.kind == csv_param.kind
continue
assert table_param == csv_param
def test_read_table_equivalency_to_read_csv(all_parsers):
# see gh-21948
# As of 0.25.0, read_table is undeprecated
parser = all_parsers
data = "a\tb\n1\t2\n3\t4"
expected = parser.read_csv(StringIO(data), sep="\t")
result = parser.read_table(StringIO(data))
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize("read_func", ["read_csv", "read_table"])
def test_read_csv_and_table_sys_setprofile(all_parsers, read_func):
# GH#41069
parser = all_parsers
data = "a b\n0 1"
sys.setprofile(lambda *a, **k: None)
result = getattr(parser, read_func)(StringIO(data))
sys.setprofile(None)
expected = DataFrame({"a b": ["0 1"]})
tm.assert_frame_equal(result, expected)
@skip_pyarrow
def test_first_row_bom(all_parsers):
# see gh-26545
parser = all_parsers
data = '''\ufeff"Head1"\t"Head2"\t"Head3"'''
result = parser.read_csv(StringIO(data), delimiter="\t")
expected = DataFrame(columns=["Head1", "Head2", "Head3"])
tm.assert_frame_equal(result, expected)
@skip_pyarrow
def test_first_row_bom_unquoted(all_parsers):
# see gh-36343
parser = all_parsers
data = """\ufeffHead1\tHead2\tHead3"""
result = parser.read_csv(StringIO(data), delimiter="\t")
expected = DataFrame(columns=["Head1", "Head2", "Head3"])
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize("nrows", range(1, 6))
def test_blank_lines_between_header_and_data_rows(all_parsers, nrows):
# GH 28071
ref = DataFrame(
[[np.nan, np.nan], [np.nan, np.nan], [1, 2], [np.nan, np.nan], [3, 4]],
columns=list("ab"),
)
csv = "\nheader\n\na,b\n\n\n1,2\n\n3,4"
parser = all_parsers
if parser.engine == "pyarrow":
msg = "The 'nrows' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
parser.read_csv(
StringIO(csv), header=3, nrows=nrows, skip_blank_lines=False
)
return
df = parser.read_csv(StringIO(csv), header=3, nrows=nrows, skip_blank_lines=False)
tm.assert_frame_equal(df, ref[:nrows])
@skip_pyarrow
def test_no_header_two_extra_columns(all_parsers):
# GH 26218
column_names = ["one", "two", "three"]
ref = DataFrame([["foo", "bar", "baz"]], columns=column_names)
stream = StringIO("foo,bar,baz,bam,blah")
parser = all_parsers
df = parser.read_csv_check_warnings(
ParserWarning,
"Length of header or names does not match length of data. "
"This leads to a loss of data with index_col=False.",
stream,
header=None,
names=column_names,
index_col=False,
)
tm.assert_frame_equal(df, ref)
def test_read_csv_names_not_accepting_sets(all_parsers):
# GH 34946
data = """\
1,2,3
4,5,6\n"""
parser = all_parsers
with pytest.raises(ValueError, match="Names should be an ordered collection."):
parser.read_csv(StringIO(data), names=set("QAZ"))
def test_read_table_delim_whitespace_default_sep(all_parsers):
# GH: 35958
f = StringIO("a b c\n1 -2 -3\n4 5 6")
parser = all_parsers
depr_msg = "The 'delim_whitespace' keyword in pd.read_table is deprecated"
if parser.engine == "pyarrow":
msg = "The 'delim_whitespace' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
with tm.assert_produces_warning(
FutureWarning, match=depr_msg, check_stacklevel=False
):
parser.read_table(f, delim_whitespace=True)
return
with tm.assert_produces_warning(
FutureWarning, match=depr_msg, check_stacklevel=False
):
result = parser.read_table(f, delim_whitespace=True)
expected = DataFrame({"a": [1, 4], "b": [-2, 5], "c": [-3, 6]})
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize("delimiter", [",", "\t"])
def test_read_csv_delim_whitespace_non_default_sep(all_parsers, delimiter):
# GH: 35958
f = StringIO("a b c\n1 -2 -3\n4 5 6")
parser = all_parsers
msg = (
"Specified a delimiter with both sep and "
"delim_whitespace=True; you can only specify one."
)
depr_msg = "The 'delim_whitespace' keyword in pd.read_csv is deprecated"
with tm.assert_produces_warning(
FutureWarning, match=depr_msg, check_stacklevel=False
):
with pytest.raises(ValueError, match=msg):
parser.read_csv(f, delim_whitespace=True, sep=delimiter)
with pytest.raises(ValueError, match=msg):
parser.read_csv(f, delim_whitespace=True, delimiter=delimiter)
def test_read_csv_delimiter_and_sep_no_default(all_parsers):
# GH#39823
f = StringIO("a,b\n1,2")
parser = all_parsers
msg = "Specified a sep and a delimiter; you can only specify one."
with pytest.raises(ValueError, match=msg):
parser.read_csv(f, sep=" ", delimiter=".")
@pytest.mark.parametrize("kwargs", [{"delimiter": "\n"}, {"sep": "\n"}])
def test_read_csv_line_break_as_separator(kwargs, all_parsers):
# GH#43528
parser = all_parsers
data = """a,b,c
1,2,3
"""
msg = (
r"Specified \\n as separator or delimiter. This forces the python engine "
r"which does not accept a line terminator. Hence it is not allowed to use "
r"the line terminator as separator."
)
with pytest.raises(ValueError, match=msg):
parser.read_csv(StringIO(data), **kwargs)
@pytest.mark.parametrize("delimiter", [",", "\t"])
def test_read_table_delim_whitespace_non_default_sep(all_parsers, delimiter):
# GH: 35958
f = StringIO("a b c\n1 -2 -3\n4 5 6")
parser = all_parsers
msg = (
"Specified a delimiter with both sep and "
"delim_whitespace=True; you can only specify one."
)
depr_msg = "The 'delim_whitespace' keyword in pd.read_table is deprecated"
with tm.assert_produces_warning(
FutureWarning, match=depr_msg, check_stacklevel=False
):
with pytest.raises(ValueError, match=msg):
parser.read_table(f, delim_whitespace=True, sep=delimiter)
with pytest.raises(ValueError, match=msg):
parser.read_table(f, delim_whitespace=True, delimiter=delimiter)
@skip_pyarrow
def test_dict_keys_as_names(all_parsers):
# GH: 36928
data = "1,2"
keys = {"a": int, "b": int}.keys()
parser = all_parsers
result = parser.read_csv(StringIO(data), names=keys)
expected = DataFrame({"a": [1], "b": [2]})
tm.assert_frame_equal(result, expected)
@xfail_pyarrow # UnicodeDecodeError: 'utf-8' codec can't decode byte 0xed in position 0
def test_encoding_surrogatepass(all_parsers):
# GH39017
parser = all_parsers
content = b"\xed\xbd\xbf"
decoded = content.decode("utf-8", errors="surrogatepass")
expected = DataFrame({decoded: [decoded]}, index=[decoded * 2])
expected.index.name = decoded * 2
with tm.ensure_clean() as path:
Path(path).write_bytes(
content * 2 + b"," + content + b"\n" + content * 2 + b"," + content
)
df = parser.read_csv(path, encoding_errors="surrogatepass", index_col=0)
tm.assert_frame_equal(df, expected)
with pytest.raises(UnicodeDecodeError, match="'utf-8' codec can't decode byte"):
parser.read_csv(path)
def test_malformed_second_line(all_parsers):
# see GH14782
parser = all_parsers
data = "\na\nb\n"
result = parser.read_csv(StringIO(data), skip_blank_lines=False, header=1)
expected = DataFrame({"a": ["b"]})
tm.assert_frame_equal(result, expected)
@skip_pyarrow
def test_short_single_line(all_parsers):
# GH 47566
parser = all_parsers
columns = ["a", "b", "c"]
data = "1,2"
result = parser.read_csv(StringIO(data), header=None, names=columns)
expected = DataFrame({"a": [1], "b": [2], "c": [np.nan]})
tm.assert_frame_equal(result, expected)
@xfail_pyarrow # ValueError: Length mismatch: Expected axis has 2 elements
def test_short_multi_line(all_parsers):
# GH 47566
parser = all_parsers
columns = ["a", "b", "c"]
data = "1,2\n1,2"
result = parser.read_csv(StringIO(data), header=None, names=columns)
expected = DataFrame({"a": [1, 1], "b": [2, 2], "c": [np.nan, np.nan]})
tm.assert_frame_equal(result, expected)
def test_read_seek(all_parsers):
# GH48646
parser = all_parsers
prefix = "### DATA\n"
content = "nkey,value\ntables,rectangular\n"
with tm.ensure_clean() as path:
Path(path).write_text(prefix + content, encoding="utf-8")
with open(path, encoding="utf-8") as file:
file.readline()
actual = parser.read_csv(file)
expected = parser.read_csv(StringIO(content))
tm.assert_frame_equal(actual, expected)

91
lib/python3.13/site-packages/pandas/tests/io/parser/common/test_data_list.py Normal file
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@ -0,0 +1,91 @@
"""
Tests that work on both the Python and C engines but do not have a
specific classification into the other test modules.
"""
import csv
from io import StringIO
import pytest
from pandas import DataFrame
import pandas._testing as tm
from pandas.io.parsers import TextParser
pytestmark = pytest.mark.filterwarnings(
"ignore:Passing a BlockManager to DataFrame:DeprecationWarning"
)
xfail_pyarrow = pytest.mark.usefixtures("pyarrow_xfail")
@xfail_pyarrow
def test_read_data_list(all_parsers):
parser = all_parsers
kwargs = {"index_col": 0}
data = "A,B,C\nfoo,1,2,3\nbar,4,5,6"
data_list = [["A", "B", "C"], ["foo", "1", "2", "3"], ["bar", "4", "5", "6"]]
expected = parser.read_csv(StringIO(data), **kwargs)
with TextParser(data_list, chunksize=2, **kwargs) as parser:
result = parser.read()
tm.assert_frame_equal(result, expected)
def test_reader_list(all_parsers):
data = """index,A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15
qux,12,13,14,15
foo2,12,13,14,15
bar2,12,13,14,15
"""
parser = all_parsers
kwargs = {"index_col": 0}
lines = list(csv.reader(StringIO(data)))
with TextParser(lines, chunksize=2, **kwargs) as reader:
chunks = list(reader)
expected = parser.read_csv(StringIO(data), **kwargs)
tm.assert_frame_equal(chunks[0], expected[:2])
tm.assert_frame_equal(chunks[1], expected[2:4])
tm.assert_frame_equal(chunks[2], expected[4:])
def test_reader_list_skiprows(all_parsers):
data = """index,A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15
qux,12,13,14,15
foo2,12,13,14,15
bar2,12,13,14,15
"""
parser = all_parsers
kwargs = {"index_col": 0}
lines = list(csv.reader(StringIO(data)))
with TextParser(lines, chunksize=2, skiprows=[1], **kwargs) as reader:
chunks = list(reader)
expected = parser.read_csv(StringIO(data), **kwargs)
tm.assert_frame_equal(chunks[0], expected[1:3])
def test_read_csv_parse_simple_list(all_parsers):
parser = all_parsers
data = """foo
bar baz
qux foo
foo
bar"""
result = parser.read_csv(StringIO(data), header=None)
expected = DataFrame(["foo", "bar baz", "qux foo", "foo", "bar"])
tm.assert_frame_equal(result, expected)

72
lib/python3.13/site-packages/pandas/tests/io/parser/common/test_decimal.py Normal file
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@ -0,0 +1,72 @@
"""
Tests that work on both the Python and C engines but do not have a
specific classification into the other test modules.
"""
from io import StringIO
import pytest
from pandas import DataFrame
import pandas._testing as tm
pytestmark = pytest.mark.filterwarnings(
"ignore:Passing a BlockManager to DataFrame:DeprecationWarning"
)
@pytest.mark.parametrize(
"data,thousands,decimal",
[
(
"""A|B|C
1|2,334.01|5
10|13|10.
""",
",",
".",
),
(
"""A|B|C
1|2.334,01|5
10|13|10,
""",
".",
",",
),
],
)
def test_1000_sep_with_decimal(all_parsers, data, thousands, decimal):
parser = all_parsers
expected = DataFrame({"A": [1, 10], "B": [2334.01, 13], "C": [5, 10.0]})
if parser.engine == "pyarrow":
msg = "The 'thousands' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
parser.read_csv(
StringIO(data), sep="|", thousands=thousands, decimal=decimal
)
return
result = parser.read_csv(
StringIO(data), sep="|", thousands=thousands, decimal=decimal
)
tm.assert_frame_equal(result, expected)
def test_euro_decimal_format(all_parsers):
parser = all_parsers
data = """Id;Number1;Number2;Text1;Text2;Number3
1;1521,1541;187101,9543;ABC;poi;4,738797819
2;121,12;14897,76;DEF;uyt;0,377320872
3;878,158;108013,434;GHI;rez;2,735694704"""
result = parser.read_csv(StringIO(data), sep=";", decimal=",")
expected = DataFrame(
[
[1, 1521.1541, 187101.9543, "ABC", "poi", 4.738797819],
[2, 121.12, 14897.76, "DEF", "uyt", 0.377320872],
[3, 878.158, 108013.434, "GHI", "rez", 2.735694704],
],
columns=["Id", "Number1", "Number2", "Text1", "Text2", "Number3"],
)
tm.assert_frame_equal(result, expected)

478
lib/python3.13/site-packages/pandas/tests/io/parser/common/test_file_buffer_url.py Normal file
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@ -0,0 +1,478 @@
"""
Tests that work on both the Python and C engines but do not have a
specific classification into the other test modules.
"""
from io import (
BytesIO,
StringIO,
)
import os
import platform
from urllib.error import URLError
import uuid
import numpy as np
import pytest
from pandas.errors import (
EmptyDataError,
ParserError,
)
import pandas.util._test_decorators as td
from pandas import (
DataFrame,
Index,
)
import pandas._testing as tm
pytestmark = pytest.mark.filterwarnings(
"ignore:Passing a BlockManager to DataFrame:DeprecationWarning"
)
xfail_pyarrow = pytest.mark.usefixtures("pyarrow_xfail")
skip_pyarrow = pytest.mark.usefixtures("pyarrow_skip")
@pytest.mark.network
@pytest.mark.single_cpu
def test_url(all_parsers, csv_dir_path, httpserver):
parser = all_parsers
kwargs = {"sep": "\t"}
local_path = os.path.join(csv_dir_path, "salaries.csv")
with open(local_path, encoding="utf-8") as f:
httpserver.serve_content(content=f.read())
url_result = parser.read_csv(httpserver.url, **kwargs)
local_result = parser.read_csv(local_path, **kwargs)
tm.assert_frame_equal(url_result, local_result)
@pytest.mark.slow
def test_local_file(all_parsers, csv_dir_path):
parser = all_parsers
kwargs = {"sep": "\t"}
local_path = os.path.join(csv_dir_path, "salaries.csv")
local_result = parser.read_csv(local_path, **kwargs)
url = "file://localhost/" + local_path
try:
url_result = parser.read_csv(url, **kwargs)
tm.assert_frame_equal(url_result, local_result)
except URLError:
# Fails on some systems.
pytest.skip("Failing on: " + " ".join(platform.uname()))
@xfail_pyarrow # AssertionError: DataFrame.index are different
def test_path_path_lib(all_parsers):
parser = all_parsers
df = DataFrame(
1.1 * np.arange(120).reshape((30, 4)),
columns=Index(list("ABCD"), dtype=object),
index=Index([f"i-{i}" for i in range(30)], dtype=object),
)
result = tm.round_trip_pathlib(df.to_csv, lambda p: parser.read_csv(p, index_col=0))
tm.assert_frame_equal(df, result)
@xfail_pyarrow # AssertionError: DataFrame.index are different
def test_path_local_path(all_parsers):
parser = all_parsers
df = DataFrame(
1.1 * np.arange(120).reshape((30, 4)),
columns=Index(list("ABCD"), dtype=object),
index=Index([f"i-{i}" for i in range(30)], dtype=object),
)
result = tm.round_trip_localpath(
df.to_csv, lambda p: parser.read_csv(p, index_col=0)
)
tm.assert_frame_equal(df, result)
def test_nonexistent_path(all_parsers):
# gh-2428: pls no segfault
# gh-14086: raise more helpful FileNotFoundError
# GH#29233 "File foo" instead of "File b'foo'"
parser = all_parsers
path = f"{uuid.uuid4()}.csv"
msg = r"\[Errno 2\]"
with pytest.raises(FileNotFoundError, match=msg) as e:
parser.read_csv(path)
assert path == e.value.filename
@td.skip_if_windows # os.chmod does not work in windows
def test_no_permission(all_parsers):
# GH 23784
parser = all_parsers
msg = r"\[Errno 13\]"
with tm.ensure_clean() as path:
os.chmod(path, 0) # make file unreadable
# verify that this process cannot open the file (not running as sudo)
try:
with open(path, encoding="utf-8"):
pass
pytest.skip("Running as sudo.")
except PermissionError:
pass
with pytest.raises(PermissionError, match=msg) as e:
parser.read_csv(path)
assert path == e.value.filename
@pytest.mark.parametrize(
"data,kwargs,expected,msg",
[
# gh-10728: WHITESPACE_LINE
(
"a,b,c\n4,5,6\n ",
{},
DataFrame([[4, 5, 6]], columns=["a", "b", "c"]),
None,
),
# gh-10548: EAT_LINE_COMMENT
(
"a,b,c\n4,5,6\n#comment",
{"comment": "#"},
DataFrame([[4, 5, 6]], columns=["a", "b", "c"]),
None,
),
# EAT_CRNL_NOP
(
"a,b,c\n4,5,6\n\r",
{},
DataFrame([[4, 5, 6]], columns=["a", "b", "c"]),
None,
),
# EAT_COMMENT
(
"a,b,c\n4,5,6#comment",
{"comment": "#"},
DataFrame([[4, 5, 6]], columns=["a", "b", "c"]),
None,
),
# SKIP_LINE
(
"a,b,c\n4,5,6\nskipme",
{"skiprows": [2]},
DataFrame([[4, 5, 6]], columns=["a", "b", "c"]),
None,
),
# EAT_LINE_COMMENT
(
"a,b,c\n4,5,6\n#comment",
{"comment": "#", "skip_blank_lines": False},
DataFrame([[4, 5, 6]], columns=["a", "b", "c"]),
None,
),
# IN_FIELD
(
"a,b,c\n4,5,6\n ",
{"skip_blank_lines": False},
DataFrame([["4", 5, 6], [" ", None, None]], columns=["a", "b", "c"]),
None,
),
# EAT_CRNL
(
"a,b,c\n4,5,6\n\r",
{"skip_blank_lines": False},
DataFrame([[4, 5, 6], [None, None, None]], columns=["a", "b", "c"]),
None,
),
# ESCAPED_CHAR
(
"a,b,c\n4,5,6\n\\",
{"escapechar": "\\"},
None,
"(EOF following escape character)|(unexpected end of data)",
),
# ESCAPE_IN_QUOTED_FIELD
(
'a,b,c\n4,5,6\n"\\',
{"escapechar": "\\"},
None,
"(EOF inside string starting at row 2)|(unexpected end of data)",
),
# IN_QUOTED_FIELD
(
'a,b,c\n4,5,6\n"',
{"escapechar": "\\"},
None,
"(EOF inside string starting at row 2)|(unexpected end of data)",
),
],
ids=[
"whitespace-line",
"eat-line-comment",
"eat-crnl-nop",
"eat-comment",
"skip-line",
"eat-line-comment",
"in-field",
"eat-crnl",
"escaped-char",
"escape-in-quoted-field",
"in-quoted-field",
],
)
def test_eof_states(all_parsers, data, kwargs, expected, msg, request):
# see gh-10728, gh-10548
parser = all_parsers
if parser.engine == "pyarrow" and "comment" in kwargs:
msg = "The 'comment' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
parser.read_csv(StringIO(data), **kwargs)
return
if parser.engine == "pyarrow" and "\r" not in data:
# pandas.errors.ParserError: CSV parse error: Expected 3 columns, got 1:
# ValueError: skiprows argument must be an integer when using engine='pyarrow'
# AssertionError: Regex pattern did not match.
pytest.skip(reason="https://github.com/apache/arrow/issues/38676")
if expected is None:
with pytest.raises(ParserError, match=msg):
parser.read_csv(StringIO(data), **kwargs)
else:
result = parser.read_csv(StringIO(data), **kwargs)
tm.assert_frame_equal(result, expected)
def test_temporary_file(all_parsers):
# see gh-13398
parser = all_parsers
data = "0 0"
with tm.ensure_clean(mode="w+", return_filelike=True) as new_file:
new_file.write(data)
new_file.flush()
new_file.seek(0)
if parser.engine == "pyarrow":
msg = "the 'pyarrow' engine does not support regex separators"
with pytest.raises(ValueError, match=msg):
parser.read_csv(new_file, sep=r"\s+", header=None)
return
result = parser.read_csv(new_file, sep=r"\s+", header=None)
expected = DataFrame([[0, 0]])
tm.assert_frame_equal(result, expected)
def test_internal_eof_byte(all_parsers):
# see gh-5500
parser = all_parsers
data = "a,b\n1\x1a,2"
expected = DataFrame([["1\x1a", 2]], columns=["a", "b"])
result = parser.read_csv(StringIO(data))
tm.assert_frame_equal(result, expected)
def test_internal_eof_byte_to_file(all_parsers):
# see gh-16559
parser = all_parsers
data = b'c1,c2\r\n"test \x1a test", test\r\n'
expected = DataFrame([["test \x1a test", " test"]], columns=["c1", "c2"])
path = f"__{uuid.uuid4()}__.csv"
with tm.ensure_clean(path) as path:
with open(path, "wb") as f:
f.write(data)
result = parser.read_csv(path)
tm.assert_frame_equal(result, expected)
def test_file_handle_string_io(all_parsers):
# gh-14418
#
# Don't close user provided file handles.
parser = all_parsers
data = "a,b\n1,2"
fh = StringIO(data)
parser.read_csv(fh)
assert not fh.closed
def test_file_handles_with_open(all_parsers, csv1):
# gh-14418
#
# Don't close user provided file handles.
parser = all_parsers
for mode in ["r", "rb"]:
with open(csv1, mode, encoding="utf-8" if mode == "r" else None) as f:
parser.read_csv(f)
assert not f.closed
def test_invalid_file_buffer_class(all_parsers):
# see gh-15337
class InvalidBuffer:
pass
parser = all_parsers
msg = "Invalid file path or buffer object type"
with pytest.raises(ValueError, match=msg):
parser.read_csv(InvalidBuffer())
def test_invalid_file_buffer_mock(all_parsers):
# see gh-15337
parser = all_parsers
msg = "Invalid file path or buffer object type"
class Foo:
pass
with pytest.raises(ValueError, match=msg):
parser.read_csv(Foo())
def test_valid_file_buffer_seems_invalid(all_parsers):
# gh-16135: we want to ensure that "tell" and "seek"
# aren't actually being used when we call `read_csv`
#
# Thus, while the object may look "invalid" (these
# methods are attributes of the `StringIO` class),
# it is still a valid file-object for our purposes.
class NoSeekTellBuffer(StringIO):
def tell(self):
raise AttributeError("No tell method")
def seek(self, pos, whence=0):
raise AttributeError("No seek method")
data = "a\n1"
parser = all_parsers
expected = DataFrame({"a": [1]})
result = parser.read_csv(NoSeekTellBuffer(data))
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize("io_class", [StringIO, BytesIO])
@pytest.mark.parametrize("encoding", [None, "utf-8"])
def test_read_csv_file_handle(all_parsers, io_class, encoding):
"""
Test whether read_csv does not close user-provided file handles.
GH 36980
"""
parser = all_parsers
expected = DataFrame({"a": [1], "b": [2]})
content = "a,b\n1,2"
handle = io_class(content.encode("utf-8") if io_class == BytesIO else content)
tm.assert_frame_equal(parser.read_csv(handle, encoding=encoding), expected)
assert not handle.closed
def test_memory_map_compression(all_parsers, compression):
"""
Support memory map for compressed files.
GH 37621
"""
parser = all_parsers
expected = DataFrame({"a": [1], "b": [2]})
with tm.ensure_clean() as path:
expected.to_csv(path, index=False, compression=compression)
if parser.engine == "pyarrow":
msg = "The 'memory_map' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
parser.read_csv(path, memory_map=True, compression=compression)
return
result = parser.read_csv(path, memory_map=True, compression=compression)
tm.assert_frame_equal(
result,
expected,
)
def test_context_manager(all_parsers, datapath):
# make sure that opened files are closed
parser = all_parsers
path = datapath("io", "data", "csv", "iris.csv")
if parser.engine == "pyarrow":
msg = "The 'chunksize' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
parser.read_csv(path, chunksize=1)
return
reader = parser.read_csv(path, chunksize=1)
assert not reader.handles.handle.closed
try:
with reader:
next(reader)
assert False
except AssertionError:
assert reader.handles.handle.closed
def test_context_manageri_user_provided(all_parsers, datapath):
# make sure that user-provided handles are not closed
parser = all_parsers
with open(datapath("io", "data", "csv", "iris.csv"), encoding="utf-8") as path:
if parser.engine == "pyarrow":
msg = "The 'chunksize' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
parser.read_csv(path, chunksize=1)
return
reader = parser.read_csv(path, chunksize=1)
assert not reader.handles.handle.closed
try:
with reader:
next(reader)
assert False
except AssertionError:
assert not reader.handles.handle.closed
@skip_pyarrow # ParserError: Empty CSV file
def test_file_descriptor_leak(all_parsers, using_copy_on_write):
# GH 31488
parser = all_parsers
with tm.ensure_clean() as path:
with pytest.raises(EmptyDataError, match="No columns to parse from file"):
parser.read_csv(path)
def test_memory_map(all_parsers, csv_dir_path):
mmap_file = os.path.join(csv_dir_path, "test_mmap.csv")
parser = all_parsers
expected = DataFrame(
{"a": [1, 2, 3], "b": ["one", "two", "three"], "c": ["I", "II", "III"]}
)
if parser.engine == "pyarrow":
msg = "The 'memory_map' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
parser.read_csv(mmap_file, memory_map=True)
return
result = parser.read_csv(mmap_file, memory_map=True)
tm.assert_frame_equal(result, expected)

79
lib/python3.13/site-packages/pandas/tests/io/parser/common/test_float.py Normal file
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@ -0,0 +1,79 @@
"""
Tests that work on both the Python and C engines but do not have a
specific classification into the other test modules.
"""
from io import StringIO
import numpy as np
import pytest
from pandas.compat import is_platform_linux
from pandas import DataFrame
import pandas._testing as tm
pytestmark = pytest.mark.filterwarnings(
"ignore:Passing a BlockManager to DataFrame:DeprecationWarning"
)
xfail_pyarrow = pytest.mark.usefixtures("pyarrow_xfail")
skip_pyarrow = pytest.mark.usefixtures("pyarrow_skip")
@skip_pyarrow # ParserError: CSV parse error: Empty CSV file or block
def test_float_parser(all_parsers):
# see gh-9565
parser = all_parsers
data = "45e-1,4.5,45.,inf,-inf"
result = parser.read_csv(StringIO(data), header=None)
expected = DataFrame([[float(s) for s in data.split(",")]])
tm.assert_frame_equal(result, expected)
def test_scientific_no_exponent(all_parsers_all_precisions):
# see gh-12215
df = DataFrame.from_dict({"w": ["2e"], "x": ["3E"], "y": ["42e"], "z": ["632E"]})
data = df.to_csv(index=False)
parser, precision = all_parsers_all_precisions
df_roundtrip = parser.read_csv(StringIO(data), float_precision=precision)
tm.assert_frame_equal(df_roundtrip, df)
@pytest.mark.parametrize(
"neg_exp",
[
-617,
-100000,
pytest.param(-99999999999999999, marks=pytest.mark.skip_ubsan),
],
)
def test_very_negative_exponent(all_parsers_all_precisions, neg_exp):
# GH#38753
parser, precision = all_parsers_all_precisions
data = f"data\n10E{neg_exp}"
result = parser.read_csv(StringIO(data), float_precision=precision)
expected = DataFrame({"data": [0.0]})
tm.assert_frame_equal(result, expected)
@pytest.mark.skip_ubsan
@xfail_pyarrow # AssertionError: Attributes of DataFrame.iloc[:, 0] are different
@pytest.mark.parametrize("exp", [999999999999999999, -999999999999999999])
def test_too_many_exponent_digits(all_parsers_all_precisions, exp, request):
# GH#38753
parser, precision = all_parsers_all_precisions
data = f"data\n10E{exp}"
result = parser.read_csv(StringIO(data), float_precision=precision)
if precision == "round_trip":
if exp == 999999999999999999 and is_platform_linux():
mark = pytest.mark.xfail(reason="GH38794, on Linux gives object result")
request.applymarker(mark)
value = np.inf if exp > 0 else 0.0
expected = DataFrame({"data": [value]})
else:
expected = DataFrame({"data": [f"10E{exp}"]})
tm.assert_frame_equal(result, expected)

302
lib/python3.13/site-packages/pandas/tests/io/parser/common/test_index.py Normal file
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@ -0,0 +1,302 @@
"""
Tests that work on both the Python and C engines but do not have a
specific classification into the other test modules.
"""
from datetime import datetime
from io import StringIO
import os
import pytest
from pandas import (
DataFrame,
Index,
MultiIndex,
)
import pandas._testing as tm
pytestmark = pytest.mark.filterwarnings(
"ignore:Passing a BlockManager to DataFrame:DeprecationWarning"
)
xfail_pyarrow = pytest.mark.usefixtures("pyarrow_xfail")
skip_pyarrow = pytest.mark.usefixtures("pyarrow_skip")
@pytest.mark.parametrize(
"data,kwargs,expected",
[
(
"""foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15
qux,12,13,14,15
foo2,12,13,14,15
bar2,12,13,14,15
""",
{"index_col": 0, "names": ["index", "A", "B", "C", "D"]},
DataFrame(
[
[2, 3, 4, 5],
[7, 8, 9, 10],
[12, 13, 14, 15],
[12, 13, 14, 15],
[12, 13, 14, 15],
[12, 13, 14, 15],
],
index=Index(["foo", "bar", "baz", "qux", "foo2", "bar2"], name="index"),
columns=["A", "B", "C", "D"],
),
),
(
"""foo,one,2,3,4,5
foo,two,7,8,9,10
foo,three,12,13,14,15
bar,one,12,13,14,15
bar,two,12,13,14,15
""",
{"index_col": [0, 1], "names": ["index1", "index2", "A", "B", "C", "D"]},
DataFrame(
[
[2, 3, 4, 5],
[7, 8, 9, 10],
[12, 13, 14, 15],
[12, 13, 14, 15],
[12, 13, 14, 15],
],
index=MultiIndex.from_tuples(
[
("foo", "one"),
("foo", "two"),
("foo", "three"),
("bar", "one"),
("bar", "two"),
],
names=["index1", "index2"],
),
columns=["A", "B", "C", "D"],
),
),
],
)
def test_pass_names_with_index(all_parsers, data, kwargs, expected):
parser = all_parsers
result = parser.read_csv(StringIO(data), **kwargs)
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize("index_col", [[0, 1], [1, 0]])
def test_multi_index_no_level_names(all_parsers, index_col):
data = """index1,index2,A,B,C,D
foo,one,2,3,4,5
foo,two,7,8,9,10
foo,three,12,13,14,15
bar,one,12,13,14,15
bar,two,12,13,14,15
"""
headless_data = "\n".join(data.split("\n")[1:])
names = ["A", "B", "C", "D"]
parser = all_parsers
result = parser.read_csv(
StringIO(headless_data), index_col=index_col, header=None, names=names
)
expected = parser.read_csv(StringIO(data), index_col=index_col)
# No index names in headless data.
expected.index.names = [None] * 2
tm.assert_frame_equal(result, expected)
@skip_pyarrow
def test_multi_index_no_level_names_implicit(all_parsers):
parser = all_parsers
data = """A,B,C,D
foo,one,2,3,4,5
foo,two,7,8,9,10
foo,three,12,13,14,15
bar,one,12,13,14,15
bar,two,12,13,14,15
"""
result = parser.read_csv(StringIO(data))
expected = DataFrame(
[
[2, 3, 4, 5],
[7, 8, 9, 10],
[12, 13, 14, 15],
[12, 13, 14, 15],
[12, 13, 14, 15],
],
columns=["A", "B", "C", "D"],
index=MultiIndex.from_tuples(
[
("foo", "one"),
("foo", "two"),
("foo", "three"),
("bar", "one"),
("bar", "two"),
]
),
)
tm.assert_frame_equal(result, expected)
@xfail_pyarrow # TypeError: an integer is required
@pytest.mark.parametrize(
"data,expected,header",
[
("a,b", DataFrame(columns=["a", "b"]), [0]),
(
"a,b\nc,d",
DataFrame(columns=MultiIndex.from_tuples([("a", "c"), ("b", "d")])),
[0, 1],
),
],
)
@pytest.mark.parametrize("round_trip", [True, False])
def test_multi_index_blank_df(all_parsers, data, expected, header, round_trip):
# see gh-14545
parser = all_parsers
data = expected.to_csv(index=False) if round_trip else data
result = parser.read_csv(StringIO(data), header=header)
tm.assert_frame_equal(result, expected)
@xfail_pyarrow # AssertionError: DataFrame.columns are different
def test_no_unnamed_index(all_parsers):
parser = all_parsers
data = """ id c0 c1 c2
0 1 0 a b
1 2 0 c d
2 2 2 e f
"""
result = parser.read_csv(StringIO(data), sep=" ")
expected = DataFrame(
[[0, 1, 0, "a", "b"], [1, 2, 0, "c", "d"], [2, 2, 2, "e", "f"]],
columns=["Unnamed: 0", "id", "c0", "c1", "c2"],
)
tm.assert_frame_equal(result, expected)
def test_read_duplicate_index_explicit(all_parsers):
data = """index,A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15
qux,12,13,14,15
foo,12,13,14,15
bar,12,13,14,15
"""
parser = all_parsers
result = parser.read_csv(StringIO(data), index_col=0)
expected = DataFrame(
[
[2, 3, 4, 5],
[7, 8, 9, 10],
[12, 13, 14, 15],
[12, 13, 14, 15],
[12, 13, 14, 15],
[12, 13, 14, 15],
],
columns=["A", "B", "C", "D"],
index=Index(["foo", "bar", "baz", "qux", "foo", "bar"], name="index"),
)
tm.assert_frame_equal(result, expected)
@skip_pyarrow
def test_read_duplicate_index_implicit(all_parsers):
data = """A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15
qux,12,13,14,15
foo,12,13,14,15
bar,12,13,14,15
"""
parser = all_parsers
result = parser.read_csv(StringIO(data))
expected = DataFrame(
[
[2, 3, 4, 5],
[7, 8, 9, 10],
[12, 13, 14, 15],
[12, 13, 14, 15],
[12, 13, 14, 15],
[12, 13, 14, 15],
],
columns=["A", "B", "C", "D"],
index=Index(["foo", "bar", "baz", "qux", "foo", "bar"]),
)
tm.assert_frame_equal(result, expected)
@skip_pyarrow
def test_read_csv_no_index_name(all_parsers, csv_dir_path):
parser = all_parsers
csv2 = os.path.join(csv_dir_path, "test2.csv")
result = parser.read_csv(csv2, index_col=0, parse_dates=True)
expected = DataFrame(
[
[0.980269, 3.685731, -0.364216805298, -1.159738, "foo"],
[1.047916, -0.041232, -0.16181208307, 0.212549, "bar"],
[0.498581, 0.731168, -0.537677223318, 1.346270, "baz"],
[1.120202, 1.567621, 0.00364077397681, 0.675253, "qux"],
[-0.487094, 0.571455, -1.6116394093, 0.103469, "foo2"],
],
columns=["A", "B", "C", "D", "E"],
index=Index(
[
datetime(2000, 1, 3),
datetime(2000, 1, 4),
datetime(2000, 1, 5),
datetime(2000, 1, 6),
datetime(2000, 1, 7),
]
),
)
tm.assert_frame_equal(result, expected)
@skip_pyarrow
def test_empty_with_index(all_parsers):
# see gh-10184
data = "x,y"
parser = all_parsers
result = parser.read_csv(StringIO(data), index_col=0)
expected = DataFrame(columns=["y"], index=Index([], name="x"))
tm.assert_frame_equal(result, expected)
# CSV parse error: Empty CSV file or block: cannot infer number of columns
@skip_pyarrow
def test_empty_with_multi_index(all_parsers):
# see gh-10467
data = "x,y,z"
parser = all_parsers
result = parser.read_csv(StringIO(data), index_col=["x", "y"])
expected = DataFrame(
columns=["z"], index=MultiIndex.from_arrays([[]] * 2, names=["x", "y"])
)
tm.assert_frame_equal(result, expected)
# CSV parse error: Empty CSV file or block: cannot infer number of columns
@skip_pyarrow
def test_empty_with_reversed_multi_index(all_parsers):
data = "x,y,z"
parser = all_parsers
result = parser.read_csv(StringIO(data), index_col=[1, 0])
expected = DataFrame(
columns=["z"], index=MultiIndex.from_arrays([[]] * 2, names=["y", "x"])
)
tm.assert_frame_equal(result, expected)

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"""
Tests that work on both the Python and C engines but do not have a
specific classification into the other test modules.
"""
from io import StringIO
import numpy as np
import pytest
from pandas import (
DataFrame,
option_context,
)
import pandas._testing as tm
pytestmark = pytest.mark.filterwarnings(
"ignore:Passing a BlockManager to DataFrame:DeprecationWarning"
)
xfail_pyarrow = pytest.mark.usefixtures("pyarrow_xfail")
@xfail_pyarrow # AssertionError: DataFrame.index are different
@pytest.mark.parametrize("na_filter", [True, False])
def test_inf_parsing(all_parsers, na_filter):
parser = all_parsers
data = """\
,A
a,inf
b,-inf
c,+Inf
d,-Inf
e,INF
f,-INF
g,+INf
h,-INf
i,inF
j,-inF"""
expected = DataFrame(
{"A": [float("inf"), float("-inf")] * 5},
index=["a", "b", "c", "d", "e", "f", "g", "h", "i", "j"],
)
result = parser.read_csv(StringIO(data), index_col=0, na_filter=na_filter)
tm.assert_frame_equal(result, expected)
@xfail_pyarrow # AssertionError: DataFrame.index are different
@pytest.mark.parametrize("na_filter", [True, False])
def test_infinity_parsing(all_parsers, na_filter):
parser = all_parsers
data = """\
,A
a,Infinity
b,-Infinity
c,+Infinity
"""
expected = DataFrame(
{"A": [float("infinity"), float("-infinity"), float("+infinity")]},
index=["a", "b", "c"],
)
result = parser.read_csv(StringIO(data), index_col=0, na_filter=na_filter)
tm.assert_frame_equal(result, expected)
def test_read_csv_with_use_inf_as_na(all_parsers):
# https://github.com/pandas-dev/pandas/issues/35493
parser = all_parsers
data = "1.0\nNaN\n3.0"
msg = "use_inf_as_na option is deprecated"
warn = FutureWarning
if parser.engine == "pyarrow":
warn = (FutureWarning, DeprecationWarning)
with tm.assert_produces_warning(warn, match=msg, check_stacklevel=False):
with option_context("use_inf_as_na", True):
result = parser.read_csv(StringIO(data), header=None)
expected = DataFrame([1.0, np.nan, 3.0])
tm.assert_frame_equal(result, expected)

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"""
Tests that work on both the Python and C engines but do not have a
specific classification into the other test modules.
"""
from io import StringIO
import numpy as np
import pytest
from pandas import (
DataFrame,
Series,
)
import pandas._testing as tm
pytestmark = pytest.mark.filterwarnings(
"ignore:Passing a BlockManager to DataFrame:DeprecationWarning"
)
xfail_pyarrow = pytest.mark.usefixtures("pyarrow_xfail")
skip_pyarrow = pytest.mark.usefixtures("pyarrow_skip")
def test_int_conversion(all_parsers):
data = """A,B
1.0,1
2.0,2
3.0,3
"""
parser = all_parsers
result = parser.read_csv(StringIO(data))
expected = DataFrame([[1.0, 1], [2.0, 2], [3.0, 3]], columns=["A", "B"])
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize(
"data,kwargs,expected",
[
(
"A,B\nTrue,1\nFalse,2\nTrue,3",
{},
DataFrame([[True, 1], [False, 2], [True, 3]], columns=["A", "B"]),
),
(
"A,B\nYES,1\nno,2\nyes,3\nNo,3\nYes,3",
{"true_values": ["yes", "Yes", "YES"], "false_values": ["no", "NO", "No"]},
DataFrame(
[[True, 1], [False, 2], [True, 3], [False, 3], [True, 3]],
columns=["A", "B"],
),
),
(
"A,B\nTRUE,1\nFALSE,2\nTRUE,3",
{},
DataFrame([[True, 1], [False, 2], [True, 3]], columns=["A", "B"]),
),
(
"A,B\nfoo,bar\nbar,foo",
{"true_values": ["foo"], "false_values": ["bar"]},
DataFrame([[True, False], [False, True]], columns=["A", "B"]),
),
],
)
def test_parse_bool(all_parsers, data, kwargs, expected):
parser = all_parsers
result = parser.read_csv(StringIO(data), **kwargs)
tm.assert_frame_equal(result, expected)
def test_parse_integers_above_fp_precision(all_parsers):
data = """Numbers
17007000002000191
17007000002000191
17007000002000191
17007000002000191
17007000002000192
17007000002000192
17007000002000192
17007000002000192
17007000002000192
17007000002000194"""
parser = all_parsers
result = parser.read_csv(StringIO(data))
expected = DataFrame(
{
"Numbers": [
17007000002000191,
17007000002000191,
17007000002000191,
17007000002000191,
17007000002000192,
17007000002000192,
17007000002000192,
17007000002000192,
17007000002000192,
17007000002000194,
]
}
)
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize("sep", [" ", r"\s+"])
def test_integer_overflow_bug(all_parsers, sep):
# see gh-2601
data = "65248E10 11\n55555E55 22\n"
parser = all_parsers
if parser.engine == "pyarrow" and sep != " ":
msg = "the 'pyarrow' engine does not support regex separators"
with pytest.raises(ValueError, match=msg):
parser.read_csv(StringIO(data), header=None, sep=sep)
return
result = parser.read_csv(StringIO(data), header=None, sep=sep)
expected = DataFrame([[6.5248e14, 11], [5.5555e59, 22]])
tm.assert_frame_equal(result, expected)
def test_int64_min_issues(all_parsers):
# see gh-2599
parser = all_parsers
data = "A,B\n0,0\n0,"
result = parser.read_csv(StringIO(data))
expected = DataFrame({"A": [0, 0], "B": [0, np.nan]})
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize("conv", [None, np.int64, np.uint64])
def test_int64_overflow(all_parsers, conv, request):
data = """ID
00013007854817840016671868
00013007854817840016749251
00013007854817840016754630
00013007854817840016781876
00013007854817840017028824
00013007854817840017963235
00013007854817840018860166"""
parser = all_parsers
if conv is None:
# 13007854817840016671868 > UINT64_MAX, so this
# will overflow and return object as the dtype.
if parser.engine == "pyarrow":
mark = pytest.mark.xfail(reason="parses to float64")
request.applymarker(mark)
result = parser.read_csv(StringIO(data))
expected = DataFrame(
[
"00013007854817840016671868",
"00013007854817840016749251",
"00013007854817840016754630",
"00013007854817840016781876",
"00013007854817840017028824",
"00013007854817840017963235",
"00013007854817840018860166",
],
columns=["ID"],
)
tm.assert_frame_equal(result, expected)
else:
# 13007854817840016671868 > UINT64_MAX, so attempts
# to cast to either int64 or uint64 will result in
# an OverflowError being raised.
msg = "|".join(
[
"Python int too large to convert to C long",
"long too big to convert",
"int too big to convert",
]
)
err = OverflowError
if parser.engine == "pyarrow":
err = ValueError
msg = "The 'converters' option is not supported with the 'pyarrow' engine"
with pytest.raises(err, match=msg):
parser.read_csv(StringIO(data), converters={"ID": conv})
@skip_pyarrow # CSV parse error: Empty CSV file or block
@pytest.mark.parametrize(
"val", [np.iinfo(np.uint64).max, np.iinfo(np.int64).max, np.iinfo(np.int64).min]
)
def test_int64_uint64_range(all_parsers, val):
# These numbers fall right inside the int64-uint64
# range, so they should be parsed as string.
parser = all_parsers
result = parser.read_csv(StringIO(str(val)), header=None)
expected = DataFrame([val])
tm.assert_frame_equal(result, expected)
@skip_pyarrow # CSV parse error: Empty CSV file or block
@pytest.mark.parametrize(
"val", [np.iinfo(np.uint64).max + 1, np.iinfo(np.int64).min - 1]
)
def test_outside_int64_uint64_range(all_parsers, val):
# These numbers fall just outside the int64-uint64
# range, so they should be parsed as string.
parser = all_parsers
result = parser.read_csv(StringIO(str(val)), header=None)
expected = DataFrame([str(val)])
tm.assert_frame_equal(result, expected)
@xfail_pyarrow # gets float64 dtype instead of object
@pytest.mark.parametrize("exp_data", [[str(-1), str(2**63)], [str(2**63), str(-1)]])
def test_numeric_range_too_wide(all_parsers, exp_data):
# No numerical dtype can hold both negative and uint64
# values, so they should be cast as string.
parser = all_parsers
data = "\n".join(exp_data)
expected = DataFrame(exp_data)
result = parser.read_csv(StringIO(data), header=None)
tm.assert_frame_equal(result, expected)
def test_integer_precision(all_parsers):
# Gh 7072
s = """1,1;0;0;0;1;1;3844;3844;3844;1;1;1;1;1;1;0;0;1;1;0;0,,,4321583677327450765
5,1;0;0;0;1;1;843;843;843;1;1;1;1;1;1;0;0;1;1;0;0,64.0,;,4321113141090630389"""
parser = all_parsers
result = parser.read_csv(StringIO(s), header=None)[4]
expected = Series([4321583677327450765, 4321113141090630389], name=4)
tm.assert_series_equal(result, expected)

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"""
Tests that work on both the Python and C engines but do not have a
specific classification into the other test modules.
"""
from io import StringIO
import pytest
from pandas import (
DataFrame,
concat,
)
import pandas._testing as tm
pytestmark = pytest.mark.filterwarnings(
"ignore:Passing a BlockManager to DataFrame:DeprecationWarning"
)
def test_iterator(all_parsers):
# see gh-6607
data = """index,A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15
qux,12,13,14,15
foo2,12,13,14,15
bar2,12,13,14,15
"""
parser = all_parsers
kwargs = {"index_col": 0}
expected = parser.read_csv(StringIO(data), **kwargs)
if parser.engine == "pyarrow":
msg = "The 'iterator' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
parser.read_csv(StringIO(data), iterator=True, **kwargs)
return
with parser.read_csv(StringIO(data), iterator=True, **kwargs) as reader:
first_chunk = reader.read(3)
tm.assert_frame_equal(first_chunk, expected[:3])
last_chunk = reader.read(5)
tm.assert_frame_equal(last_chunk, expected[3:])
def test_iterator2(all_parsers):
parser = all_parsers
data = """A,B,C
foo,1,2,3
bar,4,5,6
baz,7,8,9
"""
if parser.engine == "pyarrow":
msg = "The 'iterator' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
parser.read_csv(StringIO(data), iterator=True)
return
with parser.read_csv(StringIO(data), iterator=True) as reader:
result = list(reader)
expected = DataFrame(
[[1, 2, 3], [4, 5, 6], [7, 8, 9]],
index=["foo", "bar", "baz"],
columns=["A", "B", "C"],
)
tm.assert_frame_equal(result[0], expected)
def test_iterator_stop_on_chunksize(all_parsers):
# gh-3967: stopping iteration when chunksize is specified
parser = all_parsers
data = """A,B,C
foo,1,2,3
bar,4,5,6
baz,7,8,9
"""
if parser.engine == "pyarrow":
msg = "The 'chunksize' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
parser.read_csv(StringIO(data), chunksize=1)
return
with parser.read_csv(StringIO(data), chunksize=1) as reader:
result = list(reader)
assert len(result) == 3
expected = DataFrame(
[[1, 2, 3], [4, 5, 6], [7, 8, 9]],
index=["foo", "bar", "baz"],
columns=["A", "B", "C"],
)
tm.assert_frame_equal(concat(result), expected)
@pytest.mark.parametrize(
"kwargs", [{"iterator": True, "chunksize": 1}, {"iterator": True}, {"chunksize": 1}]
)
def test_iterator_skipfooter_errors(all_parsers, kwargs):
msg = "'skipfooter' not supported for iteration"
parser = all_parsers
data = "a\n1\n2"
if parser.engine == "pyarrow":
msg = (
"The '(chunksize|iterator)' option is not supported with the "
"'pyarrow' engine"
)
with pytest.raises(ValueError, match=msg):
with parser.read_csv(StringIO(data), skipfooter=1, **kwargs) as _:
pass
def test_iteration_open_handle(all_parsers):
parser = all_parsers
kwargs = {"header": None}
with tm.ensure_clean() as path:
with open(path, "w", encoding="utf-8") as f:
f.write("AAA\nBBB\nCCC\nDDD\nEEE\nFFF\nGGG")
with open(path, encoding="utf-8") as f:
for line in f:
if "CCC" in line:
break
result = parser.read_csv(f, **kwargs)
expected = DataFrame({0: ["DDD", "EEE", "FFF", "GGG"]})
tm.assert_frame_equal(result, expected)

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"""
Tests that work on the Python, C and PyArrow engines but do not have a
specific classification into the other test modules.
"""
import codecs
import csv
from io import StringIO
import os
from pathlib import Path
import numpy as np
import pytest
from pandas.compat import PY311
from pandas.errors import (
EmptyDataError,
ParserError,
ParserWarning,
)
from pandas import DataFrame
import pandas._testing as tm
xfail_pyarrow = pytest.mark.usefixtures("pyarrow_xfail")
skip_pyarrow = pytest.mark.usefixtures("pyarrow_skip")
def test_empty_decimal_marker(all_parsers):
data = """A|B|C
1|2,334|5
10|13|10.
"""
# Parsers support only length-1 decimals
msg = "Only length-1 decimal markers supported"
parser = all_parsers
if parser.engine == "pyarrow":
msg = (
"only single character unicode strings can be "
"converted to Py_UCS4, got length 0"
)
with pytest.raises(ValueError, match=msg):
parser.read_csv(StringIO(data), decimal="")
def test_bad_stream_exception(all_parsers, csv_dir_path):
# see gh-13652
#
# This test validates that both the Python engine and C engine will
# raise UnicodeDecodeError instead of C engine raising ParserError
# and swallowing the exception that caused read to fail.
path = os.path.join(csv_dir_path, "sauron.SHIFT_JIS.csv")
codec = codecs.lookup("utf-8")
utf8 = codecs.lookup("utf-8")
parser = all_parsers
msg = "'utf-8' codec can't decode byte"
# Stream must be binary UTF8.
with open(path, "rb") as handle, codecs.StreamRecoder(
handle, utf8.encode, utf8.decode, codec.streamreader, codec.streamwriter
) as stream:
with pytest.raises(UnicodeDecodeError, match=msg):
parser.read_csv(stream)
def test_malformed(all_parsers):
# see gh-6607
parser = all_parsers
data = """ignore
A,B,C
1,2,3 # comment
1,2,3,4,5
2,3,4
"""
msg = "Expected 3 fields in line 4, saw 5"
err = ParserError
if parser.engine == "pyarrow":
msg = "The 'comment' option is not supported with the 'pyarrow' engine"
err = ValueError
with pytest.raises(err, match=msg):
parser.read_csv(StringIO(data), header=1, comment="#")
@pytest.mark.parametrize("nrows", [5, 3, None])
def test_malformed_chunks(all_parsers, nrows):
data = """ignore
A,B,C
skip
1,2,3
3,5,10 # comment
1,2,3,4,5
2,3,4
"""
parser = all_parsers
if parser.engine == "pyarrow":
msg = "The 'iterator' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
parser.read_csv(
StringIO(data),
header=1,
comment="#",
iterator=True,
chunksize=1,
skiprows=[2],
)
return
msg = "Expected 3 fields in line 6, saw 5"
with parser.read_csv(
StringIO(data), header=1, comment="#", iterator=True, chunksize=1, skiprows=[2]
) as reader:
with pytest.raises(ParserError, match=msg):
reader.read(nrows)
@xfail_pyarrow # does not raise
def test_catch_too_many_names(all_parsers):
# see gh-5156
data = """\
1,2,3
4,,6
7,8,9
10,11,12\n"""
parser = all_parsers
msg = (
"Too many columns specified: expected 4 and found 3"
if parser.engine == "c"
else "Number of passed names did not match "
"number of header fields in the file"
)
with pytest.raises(ValueError, match=msg):
parser.read_csv(StringIO(data), header=0, names=["a", "b", "c", "d"])
@skip_pyarrow # CSV parse error: Empty CSV file or block
@pytest.mark.parametrize("nrows", [0, 1, 2, 3, 4, 5])
def test_raise_on_no_columns(all_parsers, nrows):
parser = all_parsers
data = "\n" * nrows
msg = "No columns to parse from file"
with pytest.raises(EmptyDataError, match=msg):
parser.read_csv(StringIO(data))
def test_unexpected_keyword_parameter_exception(all_parsers):
# GH-34976
parser = all_parsers
msg = "{}\\(\\) got an unexpected keyword argument 'foo'"
with pytest.raises(TypeError, match=msg.format("read_csv")):
parser.read_csv("foo.csv", foo=1)
with pytest.raises(TypeError, match=msg.format("read_table")):
parser.read_table("foo.tsv", foo=1)
def test_suppress_error_output(all_parsers):
# see gh-15925
parser = all_parsers
data = "a\n1\n1,2,3\n4\n5,6,7"
expected = DataFrame({"a": [1, 4]})
result = parser.read_csv(StringIO(data), on_bad_lines="skip")
tm.assert_frame_equal(result, expected)
def test_error_bad_lines(all_parsers):
# see gh-15925
parser = all_parsers
data = "a\n1\n1,2,3\n4\n5,6,7"
msg = "Expected 1 fields in line 3, saw 3"
if parser.engine == "pyarrow":
# "CSV parse error: Expected 1 columns, got 3: 1,2,3"
pytest.skip(reason="https://github.com/apache/arrow/issues/38676")
with pytest.raises(ParserError, match=msg):
parser.read_csv(StringIO(data), on_bad_lines="error")
def test_warn_bad_lines(all_parsers):
# see gh-15925
parser = all_parsers
data = "a\n1\n1,2,3\n4\n5,6,7"
expected = DataFrame({"a": [1, 4]})
match_msg = "Skipping line"
expected_warning = ParserWarning
if parser.engine == "pyarrow":
match_msg = "Expected 1 columns, but found 3: 1,2,3"
expected_warning = (ParserWarning, DeprecationWarning)
with tm.assert_produces_warning(
expected_warning, match=match_msg, check_stacklevel=False
):
result = parser.read_csv(StringIO(data), on_bad_lines="warn")
tm.assert_frame_equal(result, expected)
def test_read_csv_wrong_num_columns(all_parsers):
# Too few columns.
data = """A,B,C,D,E,F
1,2,3,4,5,6
6,7,8,9,10,11,12
11,12,13,14,15,16
"""
parser = all_parsers
msg = "Expected 6 fields in line 3, saw 7"
if parser.engine == "pyarrow":
# Expected 6 columns, got 7: 6,7,8,9,10,11,12
pytest.skip(reason="https://github.com/apache/arrow/issues/38676")
with pytest.raises(ParserError, match=msg):
parser.read_csv(StringIO(data))
def test_null_byte_char(request, all_parsers):
# see gh-2741
data = "\x00,foo"
names = ["a", "b"]
parser = all_parsers
if parser.engine == "c" or (parser.engine == "python" and PY311):
if parser.engine == "python" and PY311:
request.applymarker(
pytest.mark.xfail(
reason="In Python 3.11, this is read as an empty character not null"
)
)
expected = DataFrame([[np.nan, "foo"]], columns=names)
out = parser.read_csv(StringIO(data), names=names)
tm.assert_frame_equal(out, expected)
else:
if parser.engine == "pyarrow":
# CSV parse error: Empty CSV file or block: "
# cannot infer number of columns"
pytest.skip(reason="https://github.com/apache/arrow/issues/38676")
else:
msg = "NULL byte detected"
with pytest.raises(ParserError, match=msg):
parser.read_csv(StringIO(data), names=names)
@pytest.mark.filterwarnings("always::ResourceWarning")
def test_open_file(request, all_parsers):
# GH 39024
parser = all_parsers
msg = "Could not determine delimiter"
err = csv.Error
if parser.engine == "c":
msg = "the 'c' engine does not support sep=None with delim_whitespace=False"
err = ValueError
elif parser.engine == "pyarrow":
msg = (
"the 'pyarrow' engine does not support sep=None with delim_whitespace=False"
)
err = ValueError
with tm.ensure_clean() as path:
file = Path(path)
file.write_bytes(b"\xe4\na\n1")
with tm.assert_produces_warning(None):
# should not trigger a ResourceWarning
with pytest.raises(err, match=msg):
parser.read_csv(file, sep=None, encoding_errors="replace")
def test_invalid_on_bad_line(all_parsers):
parser = all_parsers
data = "a\n1\n1,2,3\n4\n5,6,7"
with pytest.raises(ValueError, match="Argument abc is invalid for on_bad_lines"):
parser.read_csv(StringIO(data), on_bad_lines="abc")
def test_bad_header_uniform_error(all_parsers):
parser = all_parsers
data = "+++123456789...\ncol1,col2,col3,col4\n1,2,3,4\n"
msg = "Expected 2 fields in line 2, saw 4"
if parser.engine == "c":
msg = (
"Could not construct index. Requested to use 1 "
"number of columns, but 3 left to parse."
)
elif parser.engine == "pyarrow":
# "CSV parse error: Expected 1 columns, got 4: col1,col2,col3,col4"
pytest.skip(reason="https://github.com/apache/arrow/issues/38676")
with pytest.raises(ParserError, match=msg):
parser.read_csv(StringIO(data), index_col=0, on_bad_lines="error")
def test_on_bad_lines_warn_correct_formatting(all_parsers):
# see gh-15925
parser = all_parsers
data = """1,2
a,b
a,b,c
a,b,d
a,b
"""
expected = DataFrame({"1": "a", "2": ["b"] * 2})
match_msg = "Skipping line"
expected_warning = ParserWarning
if parser.engine == "pyarrow":
match_msg = "Expected 2 columns, but found 3: a,b,c"
expected_warning = (ParserWarning, DeprecationWarning)
with tm.assert_produces_warning(
expected_warning, match=match_msg, check_stacklevel=False
):
result = parser.read_csv(StringIO(data), on_bad_lines="warn")
tm.assert_frame_equal(result, expected)

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lib/python3.13/site-packages/pandas/tests/io/parser/common/test_verbose.py Normal file
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@ -0,0 +1,81 @@
"""
Tests that work on both the Python and C engines but do not have a
specific classification into the other test modules.
"""
from io import StringIO
import pytest
import pandas._testing as tm
depr_msg = "The 'verbose' keyword in pd.read_csv is deprecated"
def test_verbose_read(all_parsers, capsys):
parser = all_parsers
data = """a,b,c,d
one,1,2,3
one,1,2,3
,1,2,3
one,1,2,3
,1,2,3
,1,2,3
one,1,2,3
two,1,2,3"""
if parser.engine == "pyarrow":
msg = "The 'verbose' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
with tm.assert_produces_warning(
FutureWarning, match=depr_msg, check_stacklevel=False
):
parser.read_csv(StringIO(data), verbose=True)
return
# Engines are verbose in different ways.
with tm.assert_produces_warning(
FutureWarning, match=depr_msg, check_stacklevel=False
):
parser.read_csv(StringIO(data), verbose=True)
captured = capsys.readouterr()
if parser.engine == "c":
assert "Tokenization took:" in captured.out
assert "Parser memory cleanup took:" in captured.out
else: # Python engine
assert captured.out == "Filled 3 NA values in column a\n"
def test_verbose_read2(all_parsers, capsys):
parser = all_parsers
data = """a,b,c,d
one,1,2,3
two,1,2,3
three,1,2,3
four,1,2,3
five,1,2,3
,1,2,3
seven,1,2,3
eight,1,2,3"""
if parser.engine == "pyarrow":
msg = "The 'verbose' option is not supported with the 'pyarrow' engine"
with pytest.raises(ValueError, match=msg):
with tm.assert_produces_warning(
FutureWarning, match=depr_msg, check_stacklevel=False
):
parser.read_csv(StringIO(data), verbose=True, index_col=0)
return
with tm.assert_produces_warning(
FutureWarning, match=depr_msg, check_stacklevel=False
):
parser.read_csv(StringIO(data), verbose=True, index_col=0)
captured = capsys.readouterr()
# Engines are verbose in different ways.
if parser.engine == "c":
assert "Tokenization took:" in captured.out
assert "Parser memory cleanup took:" in captured.out
else: # Python engine
assert captured.out == "Filled 1 NA values in column a\n"