You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.

338 lines
10 KiB

This file contains ambiguous Unicode characters!

This file contains ambiguous Unicode characters that may be confused with others in your current locale. If your use case is intentional and legitimate, you can safely ignore this warning. Use the Escape button to highlight these characters.

"""
Tests encoding functionality during parsing
for all of the parsers defined in parsers.py
"""
from io import (
BytesIO,
TextIOWrapper,
)
import os
import tempfile
import uuid
import numpy as np
import pytest
from pandas import (
DataFrame,
read_csv,
)
import pandas._testing as tm
pytestmark = pytest.mark.filterwarnings(
"ignore:Passing a BlockManager to DataFrame:DeprecationWarning"
)
skip_pyarrow = pytest.mark.usefixtures("pyarrow_skip")
def test_bytes_io_input(all_parsers):
encoding = "cp1255"
parser = all_parsers
data = BytesIO("שלום:1234\n562:123".encode(encoding))
result = parser.read_csv(data, sep=":", encoding=encoding)
expected = DataFrame([[562, 123]], columns=["שלום", "1234"])
tm.assert_frame_equal(result, expected)
@skip_pyarrow # CSV parse error: Empty CSV file or block
def test_read_csv_unicode(all_parsers):
parser = all_parsers
data = BytesIO("\u0141aski, Jan;1".encode())
result = parser.read_csv(data, sep=";", encoding="utf-8", header=None)
expected = DataFrame([["\u0141aski, Jan", 1]])
tm.assert_frame_equal(result, expected)
@skip_pyarrow
@pytest.mark.parametrize("sep", [",", "\t"])
@pytest.mark.parametrize("encoding", ["utf-16", "utf-16le", "utf-16be"])
def test_utf16_bom_skiprows(all_parsers, sep, encoding):
# see gh-2298
parser = all_parsers
data = """skip this
skip this too
A,B,C
1,2,3
4,5,6""".replace(
",", sep
)
path = f"__{uuid.uuid4()}__.csv"
kwargs = {"sep": sep, "skiprows": 2}
utf8 = "utf-8"
with tm.ensure_clean(path) as path:
bytes_data = data.encode(encoding)
with open(path, "wb") as f:
f.write(bytes_data)
with TextIOWrapper(BytesIO(data.encode(utf8)), encoding=utf8) as bytes_buffer:
result = parser.read_csv(path, encoding=encoding, **kwargs)
expected = parser.read_csv(bytes_buffer, encoding=utf8, **kwargs)
tm.assert_frame_equal(result, expected)
def test_utf16_example(all_parsers, csv_dir_path):
path = os.path.join(csv_dir_path, "utf16_ex.txt")
parser = all_parsers
result = parser.read_csv(path, encoding="utf-16", sep="\t")
assert len(result) == 50
def test_unicode_encoding(all_parsers, csv_dir_path):
path = os.path.join(csv_dir_path, "unicode_series.csv")
parser = all_parsers
result = parser.read_csv(path, header=None, encoding="latin-1")
result = result.set_index(0)
got = result[1][1632]
expected = "\xc1 k\xf6ldum klaka (Cold Fever) (1994)"
assert got == expected
@pytest.mark.parametrize(
"data,kwargs,expected",
[
# Basic test
("a\n1", {}, DataFrame({"a": [1]})),
# "Regular" quoting
('"a"\n1', {"quotechar": '"'}, DataFrame({"a": [1]})),
# Test in a data row instead of header
("b\n1", {"names": ["a"]}, DataFrame({"a": ["b", "1"]})),
# Test in empty data row with skipping
("\n1", {"names": ["a"], "skip_blank_lines": True}, DataFrame({"a": [1]})),
# Test in empty data row without skipping
(
"\n1",
{"names": ["a"], "skip_blank_lines": False},
DataFrame({"a": [np.nan, 1]}),
),
],
)
def test_utf8_bom(all_parsers, data, kwargs, expected, request):
# see gh-4793
parser = all_parsers
bom = "\ufeff"
utf8 = "utf-8"
def _encode_data_with_bom(_data):
bom_data = (bom + _data).encode(utf8)
return BytesIO(bom_data)
if (
parser.engine == "pyarrow"
and data == "\n1"
and kwargs.get("skip_blank_lines", True)
):
# CSV parse error: Empty CSV file or block: cannot infer number of columns
pytest.skip(reason="https://github.com/apache/arrow/issues/38676")
result = parser.read_csv(_encode_data_with_bom(data), encoding=utf8, **kwargs)
tm.assert_frame_equal(result, expected)
def test_read_csv_utf_aliases(all_parsers, utf_value, encoding_fmt):
# see gh-13549
expected = DataFrame({"mb_num": [4.8], "multibyte": ["test"]})
parser = all_parsers
encoding = encoding_fmt.format(utf_value)
data = "mb_num,multibyte\n4.8,test".encode(encoding)
result = parser.read_csv(BytesIO(data), encoding=encoding)
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize(
"file_path,encoding",
[
(("io", "data", "csv", "test1.csv"), "utf-8"),
(("io", "parser", "data", "unicode_series.csv"), "latin-1"),
(("io", "parser", "data", "sauron.SHIFT_JIS.csv"), "shiftjis"),
],
)
def test_binary_mode_file_buffers(all_parsers, file_path, encoding, datapath):
# gh-23779: Python csv engine shouldn't error on files opened in binary.
# gh-31575: Python csv engine shouldn't error on files opened in raw binary.
parser = all_parsers
fpath = datapath(*file_path)
expected = parser.read_csv(fpath, encoding=encoding)
with open(fpath, encoding=encoding) as fa:
result = parser.read_csv(fa)
assert not fa.closed
tm.assert_frame_equal(expected, result)
with open(fpath, mode="rb") as fb:
result = parser.read_csv(fb, encoding=encoding)
assert not fb.closed
tm.assert_frame_equal(expected, result)
with open(fpath, mode="rb", buffering=0) as fb:
result = parser.read_csv(fb, encoding=encoding)
assert not fb.closed
tm.assert_frame_equal(expected, result)
@pytest.mark.parametrize("pass_encoding", [True, False])
def test_encoding_temp_file(all_parsers, utf_value, encoding_fmt, pass_encoding):
# see gh-24130
parser = all_parsers
encoding = encoding_fmt.format(utf_value)
if parser.engine == "pyarrow" and pass_encoding is True and utf_value in [16, 32]:
# FIXME: this is bad!
pytest.skip("These cases freeze")
expected = DataFrame({"foo": ["bar"]})
with tm.ensure_clean(mode="w+", encoding=encoding, return_filelike=True) as f:
f.write("foo\nbar")
f.seek(0)
result = parser.read_csv(f, encoding=encoding if pass_encoding else None)
tm.assert_frame_equal(result, expected)
def test_encoding_named_temp_file(all_parsers):
# see gh-31819
parser = all_parsers
encoding = "shift-jis"
title = "てすと"
data = "こむ"
expected = DataFrame({title: [data]})
with tempfile.NamedTemporaryFile() as f:
f.write(f"{title}\n{data}".encode(encoding))
f.seek(0)
result = parser.read_csv(f, encoding=encoding)
tm.assert_frame_equal(result, expected)
assert not f.closed
@pytest.mark.parametrize(
"encoding", ["utf-8", "utf-16", "utf-16-be", "utf-16-le", "utf-32"]
)
def test_parse_encoded_special_characters(encoding):
# GH16218 Verify parsing of data with encoded special characters
# Data contains a Unicode 'FULLWIDTH COLON' (U+FF1A) at position (0,"a")
data = "a\tb\nfoo\t0\nbar\t1\nbaz\t2" # noqa: RUF001
encoded_data = BytesIO(data.encode(encoding))
result = read_csv(encoded_data, delimiter="\t", encoding=encoding)
expected = DataFrame(
data=[["foo", 0], ["bar", 1], ["baz", 2]], # noqa: RUF001
columns=["a", "b"],
)
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize("encoding", ["utf-8", None, "utf-16", "cp1255", "latin-1"])
def test_encoding_memory_map(all_parsers, encoding):
# GH40986
parser = all_parsers
expected = DataFrame(
{
"name": ["Raphael", "Donatello", "Miguel Angel", "Leonardo"],
"mask": ["red", "purple", "orange", "blue"],
"weapon": ["sai", "bo staff", "nunchunk", "katana"],
}
)
with tm.ensure_clean() as file:
expected.to_csv(file, index=False, encoding=encoding)
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(file, encoding=encoding, memory_map=True)
return
df = parser.read_csv(file, encoding=encoding, memory_map=True)
tm.assert_frame_equal(df, expected)
def test_chunk_splits_multibyte_char(all_parsers):
"""
Chunk splits a multibyte character with memory_map=True
GH 43540
"""
parser = all_parsers
# DEFAULT_CHUNKSIZE = 262144, defined in parsers.pyx
df = DataFrame(data=["a" * 127] * 2048)
# Put two-bytes utf-8 encoded character "ą" at the end of chunk
# utf-8 encoding of "ą" is b'\xc4\x85'
df.iloc[2047] = "a" * 127 + "ą"
with tm.ensure_clean("bug-gh43540.csv") as fname:
df.to_csv(fname, index=False, header=False, encoding="utf-8")
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(fname, header=None, memory_map=True)
return
dfr = parser.read_csv(fname, header=None, memory_map=True)
tm.assert_frame_equal(dfr, df)
def test_readcsv_memmap_utf8(all_parsers):
"""
GH 43787
Test correct handling of UTF-8 chars when memory_map=True and encoding is UTF-8
"""
lines = []
line_length = 128
start_char = " "
end_char = "\U00010080"
# This for loop creates a list of 128-char strings
# consisting of consecutive Unicode chars
for lnum in range(ord(start_char), ord(end_char), line_length):
line = "".join([chr(c) for c in range(lnum, lnum + 0x80)]) + "\n"
try:
line.encode("utf-8")
except UnicodeEncodeError:
continue
lines.append(line)
parser = all_parsers
df = DataFrame(lines)
with tm.ensure_clean("utf8test.csv") as fname:
df.to_csv(fname, index=False, header=False, encoding="utf-8")
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(fname, header=None, memory_map=True, encoding="utf-8")
return
dfr = parser.read_csv(fname, header=None, memory_map=True, encoding="utf-8")
tm.assert_frame_equal(df, dfr)
@pytest.mark.usefixtures("pyarrow_xfail")
@pytest.mark.parametrize("mode", ["w+b", "w+t"])
def test_not_readable(all_parsers, mode):
# GH43439
parser = all_parsers
content = b"abcd"
if "t" in mode:
content = "abcd"
with tempfile.SpooledTemporaryFile(mode=mode, encoding="utf-8") as handle:
handle.write(content)
handle.seek(0)
df = parser.read_csv(handle)
expected = DataFrame([], columns=["abcd"])
tm.assert_frame_equal(df, expected)