316 lines
9.3 KiB
Python
316 lines
9.3 KiB
Python
"""
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Tests encoding functionality during parsing
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for all of the parsers defined in parsers.py
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"""
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from io import BytesIO
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import os
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import tempfile
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import numpy as np
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import pytest
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from pandas import (
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DataFrame,
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read_csv,
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)
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import pandas._testing as tm
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skip_pyarrow = pytest.mark.usefixtures("pyarrow_skip")
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@skip_pyarrow
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def test_bytes_io_input(all_parsers):
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encoding = "cp1255"
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parser = all_parsers
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data = BytesIO("שלום:1234\n562:123".encode(encoding))
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result = parser.read_csv(data, sep=":", encoding=encoding)
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expected = DataFrame([[562, 123]], columns=["שלום", "1234"])
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tm.assert_frame_equal(result, expected)
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@skip_pyarrow
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def test_read_csv_unicode(all_parsers):
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parser = all_parsers
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data = BytesIO("\u0141aski, Jan;1".encode())
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result = parser.read_csv(data, sep=";", encoding="utf-8", header=None)
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expected = DataFrame([["\u0141aski, Jan", 1]])
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tm.assert_frame_equal(result, expected)
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@skip_pyarrow
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@pytest.mark.parametrize("sep", [",", "\t"])
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@pytest.mark.parametrize("encoding", ["utf-16", "utf-16le", "utf-16be"])
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def test_utf16_bom_skiprows(all_parsers, sep, encoding):
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# see gh-2298
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parser = all_parsers
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data = """skip this
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skip this too
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A,B,C
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1,2,3
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4,5,6""".replace(
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",", sep
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)
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path = f"__{tm.rands(10)}__.csv"
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kwargs = {"sep": sep, "skiprows": 2}
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utf8 = "utf-8"
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with tm.ensure_clean(path) as path:
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from io import TextIOWrapper
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bytes_data = data.encode(encoding)
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with open(path, "wb") as f:
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f.write(bytes_data)
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bytes_buffer = BytesIO(data.encode(utf8))
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bytes_buffer = TextIOWrapper(bytes_buffer, encoding=utf8)
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result = parser.read_csv(path, encoding=encoding, **kwargs)
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expected = parser.read_csv(bytes_buffer, encoding=utf8, **kwargs)
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bytes_buffer.close()
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tm.assert_frame_equal(result, expected)
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@skip_pyarrow
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def test_utf16_example(all_parsers, csv_dir_path):
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path = os.path.join(csv_dir_path, "utf16_ex.txt")
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parser = all_parsers
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result = parser.read_csv(path, encoding="utf-16", sep="\t")
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assert len(result) == 50
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@skip_pyarrow
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def test_unicode_encoding(all_parsers, csv_dir_path):
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path = os.path.join(csv_dir_path, "unicode_series.csv")
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parser = all_parsers
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result = parser.read_csv(path, header=None, encoding="latin-1")
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result = result.set_index(0)
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got = result[1][1632]
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expected = "\xc1 k\xf6ldum klaka (Cold Fever) (1994)"
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assert got == expected
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@skip_pyarrow
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@pytest.mark.parametrize(
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"data,kwargs,expected",
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[
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# Basic test
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("a\n1", {}, DataFrame({"a": [1]})),
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# "Regular" quoting
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('"a"\n1', {"quotechar": '"'}, DataFrame({"a": [1]})),
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# Test in a data row instead of header
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("b\n1", {"names": ["a"]}, DataFrame({"a": ["b", "1"]})),
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# Test in empty data row with skipping
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("\n1", {"names": ["a"], "skip_blank_lines": True}, DataFrame({"a": [1]})),
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# Test in empty data row without skipping
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(
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"\n1",
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{"names": ["a"], "skip_blank_lines": False},
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DataFrame({"a": [np.nan, 1]}),
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),
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],
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)
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def test_utf8_bom(all_parsers, data, kwargs, expected):
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# see gh-4793
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parser = all_parsers
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bom = "\ufeff"
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utf8 = "utf-8"
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def _encode_data_with_bom(_data):
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bom_data = (bom + _data).encode(utf8)
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return BytesIO(bom_data)
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result = parser.read_csv(_encode_data_with_bom(data), encoding=utf8, **kwargs)
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tm.assert_frame_equal(result, expected)
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@skip_pyarrow
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def test_read_csv_utf_aliases(all_parsers, utf_value, encoding_fmt):
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# see gh-13549
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expected = DataFrame({"mb_num": [4.8], "multibyte": ["test"]})
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parser = all_parsers
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encoding = encoding_fmt.format(utf_value)
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data = "mb_num,multibyte\n4.8,test".encode(encoding)
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result = parser.read_csv(BytesIO(data), encoding=encoding)
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tm.assert_frame_equal(result, expected)
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@skip_pyarrow
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@pytest.mark.parametrize(
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"file_path,encoding",
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[
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(("io", "data", "csv", "test1.csv"), "utf-8"),
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(("io", "parser", "data", "unicode_series.csv"), "latin-1"),
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(("io", "parser", "data", "sauron.SHIFT_JIS.csv"), "shiftjis"),
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],
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)
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def test_binary_mode_file_buffers(
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all_parsers, csv_dir_path, file_path, encoding, datapath
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):
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# gh-23779: Python csv engine shouldn't error on files opened in binary.
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# gh-31575: Python csv engine shouldn't error on files opened in raw binary.
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parser = all_parsers
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fpath = datapath(*file_path)
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expected = parser.read_csv(fpath, encoding=encoding)
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with open(fpath, encoding=encoding) as fa:
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result = parser.read_csv(fa)
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assert not fa.closed
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tm.assert_frame_equal(expected, result)
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with open(fpath, mode="rb") as fb:
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result = parser.read_csv(fb, encoding=encoding)
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assert not fb.closed
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tm.assert_frame_equal(expected, result)
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with open(fpath, mode="rb", buffering=0) as fb:
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result = parser.read_csv(fb, encoding=encoding)
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assert not fb.closed
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tm.assert_frame_equal(expected, result)
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@skip_pyarrow
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@pytest.mark.parametrize("pass_encoding", [True, False])
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def test_encoding_temp_file(all_parsers, utf_value, encoding_fmt, pass_encoding):
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# see gh-24130
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parser = all_parsers
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encoding = encoding_fmt.format(utf_value)
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expected = DataFrame({"foo": ["bar"]})
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with tm.ensure_clean(mode="w+", encoding=encoding, return_filelike=True) as f:
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f.write("foo\nbar")
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f.seek(0)
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result = parser.read_csv(f, encoding=encoding if pass_encoding else None)
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tm.assert_frame_equal(result, expected)
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@skip_pyarrow
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def test_encoding_named_temp_file(all_parsers):
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# see gh-31819
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parser = all_parsers
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encoding = "shift-jis"
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title = "てすと"
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data = "こむ"
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expected = DataFrame({title: [data]})
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with tempfile.NamedTemporaryFile() as f:
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f.write(f"{title}\n{data}".encode(encoding))
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f.seek(0)
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result = parser.read_csv(f, encoding=encoding)
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tm.assert_frame_equal(result, expected)
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assert not f.closed
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@pytest.mark.parametrize(
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"encoding", ["utf-8", "utf-16", "utf-16-be", "utf-16-le", "utf-32"]
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)
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def test_parse_encoded_special_characters(encoding):
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# GH16218 Verify parsing of data with encoded special characters
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# Data contains a Unicode 'FULLWIDTH COLON' (U+FF1A) at position (0,"a")
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data = "a\tb\n：foo\t0\nbar\t1\nbaz\t2"
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encoded_data = BytesIO(data.encode(encoding))
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result = read_csv(encoded_data, delimiter="\t", encoding=encoding)
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expected = DataFrame(data=[["：foo", 0], ["bar", 1], ["baz", 2]], columns=["a", "b"])
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tm.assert_frame_equal(result, expected)
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@skip_pyarrow
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@pytest.mark.parametrize("encoding", ["utf-8", None, "utf-16", "cp1255", "latin-1"])
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def test_encoding_memory_map(all_parsers, encoding):
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# GH40986
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parser = all_parsers
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expected = DataFrame(
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{
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"name": ["Raphael", "Donatello", "Miguel Angel", "Leonardo"],
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"mask": ["red", "purple", "orange", "blue"],
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"weapon": ["sai", "bo staff", "nunchunk", "katana"],
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}
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)
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with tm.ensure_clean() as file:
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expected.to_csv(file, index=False, encoding=encoding)
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df = parser.read_csv(file, encoding=encoding, memory_map=True)
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tm.assert_frame_equal(df, expected)
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@skip_pyarrow
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def test_chunk_splits_multibyte_char(all_parsers):
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"""
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Chunk splits a multibyte character with memory_map=True
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GH 43540
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"""
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parser = all_parsers
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# DEFAULT_CHUNKSIZE = 262144, defined in parsers.pyx
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df = DataFrame(data=["a" * 127] * 2048)
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# Put two-bytes utf-8 encoded character "ą" at the end of chunk
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# utf-8 encoding of "ą" is b'\xc4\x85'
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df.iloc[2047] = "a" * 127 + "ą"
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with tm.ensure_clean("bug-gh43540.csv") as fname:
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df.to_csv(fname, index=False, header=False, encoding="utf-8")
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dfr = parser.read_csv(fname, header=None, memory_map=True, engine="c")
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tm.assert_frame_equal(dfr, df)
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@skip_pyarrow
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def test_readcsv_memmap_utf8(all_parsers):
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"""
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GH 43787
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Test correct handling of UTF-8 chars when memory_map=True and encoding is UTF-8
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"""
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lines = []
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line_length = 128
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start_char = " "
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end_char = "\U00010080"
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# This for loop creates a list of 128-char strings
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# consisting of consecutive Unicode chars
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for lnum in range(ord(start_char), ord(end_char), line_length):
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line = "".join([chr(c) for c in range(lnum, lnum + 0x80)]) + "\n"
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try:
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line.encode("utf-8")
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except UnicodeEncodeError:
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continue
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lines.append(line)
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parser = all_parsers
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df = DataFrame(lines)
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with tm.ensure_clean("utf8test.csv") as fname:
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df.to_csv(fname, index=False, header=False, encoding="utf-8")
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dfr = parser.read_csv(
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fname, header=None, memory_map=True, engine="c", encoding="utf-8"
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)
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tm.assert_frame_equal(df, dfr)
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@pytest.mark.usefixtures("pyarrow_xfail")
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@pytest.mark.parametrize("mode", ["w+b", "w+t"])
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def test_not_readable(all_parsers, mode):
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# GH43439
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parser = all_parsers
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content = b"abcd"
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if "t" in mode:
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content = "abcd"
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with tempfile.SpooledTemporaryFile(mode=mode) as handle:
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handle.write(content)
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handle.seek(0)
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df = parser.read_csv(handle)
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expected = DataFrame([], columns=["abcd"])
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tm.assert_frame_equal(df, expected)
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