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.
350 lines
11 KiB
350 lines
11 KiB
"""
|
|
Tests the TextReader class in parsers.pyx, which
|
|
is integral to the C engine in parsers.py
|
|
"""
|
|
from io import (
|
|
BytesIO,
|
|
StringIO,
|
|
)
|
|
import os
|
|
|
|
import numpy as np
|
|
import pytest
|
|
|
|
import pandas._libs.parsers as parser
|
|
from pandas._libs.parsers import TextReader
|
|
|
|
from pandas import DataFrame
|
|
import pandas._testing as tm
|
|
|
|
from pandas.io.parsers import (
|
|
TextFileReader,
|
|
read_csv,
|
|
)
|
|
from pandas.io.parsers.c_parser_wrapper import ensure_dtype_objs
|
|
|
|
|
|
class TestTextReader:
|
|
@pytest.fixture(autouse=True)
|
|
def setup_method(self, datapath):
|
|
self.dirpath = datapath("io", "parser", "data")
|
|
csv1_dirpath = datapath("io", "data", "csv")
|
|
self.csv1 = os.path.join(csv1_dirpath, "test1.csv")
|
|
self.csv2 = os.path.join(self.dirpath, "test2.csv")
|
|
self.xls1 = os.path.join(self.dirpath, "test.xls")
|
|
|
|
def test_file_handle(self):
|
|
with open(self.csv1, "rb") as f:
|
|
reader = TextReader(f)
|
|
reader.read()
|
|
|
|
def test_file_handle_mmap(self):
|
|
# this was never using memory_map=True
|
|
with open(self.csv1, "rb") as f:
|
|
reader = TextReader(f, header=None)
|
|
reader.read()
|
|
|
|
def test_StringIO(self):
|
|
with open(self.csv1, "rb") as f:
|
|
text = f.read()
|
|
src = BytesIO(text)
|
|
reader = TextReader(src, header=None)
|
|
reader.read()
|
|
|
|
def test_string_factorize(self):
|
|
# should this be optional?
|
|
data = "a\nb\na\nb\na"
|
|
reader = TextReader(StringIO(data), header=None)
|
|
result = reader.read()
|
|
assert len(set(map(id, result[0]))) == 2
|
|
|
|
def test_skipinitialspace(self):
|
|
data = "a, b\na, b\na, b\na, b"
|
|
|
|
reader = TextReader(StringIO(data), skipinitialspace=True, header=None)
|
|
result = reader.read()
|
|
|
|
tm.assert_numpy_array_equal(
|
|
result[0], np.array(["a", "a", "a", "a"], dtype=np.object_)
|
|
)
|
|
tm.assert_numpy_array_equal(
|
|
result[1], np.array(["b", "b", "b", "b"], dtype=np.object_)
|
|
)
|
|
|
|
def test_parse_booleans(self):
|
|
data = "True\nFalse\nTrue\nTrue"
|
|
|
|
reader = TextReader(StringIO(data), header=None)
|
|
result = reader.read()
|
|
|
|
assert result[0].dtype == np.bool_
|
|
|
|
def test_delimit_whitespace(self):
|
|
data = 'a b\na\t\t "b"\n"a"\t \t b'
|
|
|
|
reader = TextReader(StringIO(data), delim_whitespace=True, header=None)
|
|
result = reader.read()
|
|
|
|
tm.assert_numpy_array_equal(
|
|
result[0], np.array(["a", "a", "a"], dtype=np.object_)
|
|
)
|
|
tm.assert_numpy_array_equal(
|
|
result[1], np.array(["b", "b", "b"], dtype=np.object_)
|
|
)
|
|
|
|
def test_embedded_newline(self):
|
|
data = 'a\n"hello\nthere"\nthis'
|
|
|
|
reader = TextReader(StringIO(data), header=None)
|
|
result = reader.read()
|
|
|
|
expected = np.array(["a", "hello\nthere", "this"], dtype=np.object_)
|
|
tm.assert_numpy_array_equal(result[0], expected)
|
|
|
|
def test_euro_decimal(self):
|
|
data = "12345,67\n345,678"
|
|
|
|
reader = TextReader(StringIO(data), delimiter=":", decimal=",", header=None)
|
|
result = reader.read()
|
|
|
|
expected = np.array([12345.67, 345.678])
|
|
tm.assert_almost_equal(result[0], expected)
|
|
|
|
def test_integer_thousands(self):
|
|
data = "123,456\n12,500"
|
|
|
|
reader = TextReader(StringIO(data), delimiter=":", thousands=",", header=None)
|
|
result = reader.read()
|
|
|
|
expected = np.array([123456, 12500], dtype=np.int64)
|
|
tm.assert_almost_equal(result[0], expected)
|
|
|
|
def test_integer_thousands_alt(self):
|
|
data = "123.456\n12.500"
|
|
|
|
reader = TextFileReader(
|
|
StringIO(data), delimiter=":", thousands=".", header=None
|
|
)
|
|
result = reader.read()
|
|
|
|
expected = DataFrame([123456, 12500])
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
def test_skip_bad_lines(self, capsys):
|
|
# too many lines, see #2430 for why
|
|
data = "a:b:c\nd:e:f\ng:h:i\nj:k:l:m\nl:m:n\no:p:q:r"
|
|
|
|
reader = TextReader(StringIO(data), delimiter=":", header=None)
|
|
msg = r"Error tokenizing data\. C error: Expected 3 fields in line 4, saw 4"
|
|
with pytest.raises(parser.ParserError, match=msg):
|
|
reader.read()
|
|
|
|
reader = TextReader(
|
|
StringIO(data), delimiter=":", header=None, on_bad_lines=2 # Skip
|
|
)
|
|
result = reader.read()
|
|
expected = {
|
|
0: np.array(["a", "d", "g", "l"], dtype=object),
|
|
1: np.array(["b", "e", "h", "m"], dtype=object),
|
|
2: np.array(["c", "f", "i", "n"], dtype=object),
|
|
}
|
|
assert_array_dicts_equal(result, expected)
|
|
|
|
reader = TextReader(
|
|
StringIO(data), delimiter=":", header=None, on_bad_lines=1 # Warn
|
|
)
|
|
reader.read()
|
|
captured = capsys.readouterr()
|
|
|
|
assert "Skipping line 4" in captured.err
|
|
assert "Skipping line 6" in captured.err
|
|
|
|
def test_header_not_enough_lines(self):
|
|
data = "skip this\nskip this\na,b,c\n1,2,3\n4,5,6"
|
|
|
|
reader = TextReader(StringIO(data), delimiter=",", header=2)
|
|
header = reader.header
|
|
expected = [["a", "b", "c"]]
|
|
assert header == expected
|
|
|
|
recs = reader.read()
|
|
expected = {
|
|
0: np.array([1, 4], dtype=np.int64),
|
|
1: np.array([2, 5], dtype=np.int64),
|
|
2: np.array([3, 6], dtype=np.int64),
|
|
}
|
|
assert_array_dicts_equal(recs, expected)
|
|
|
|
def test_escapechar(self):
|
|
data = '\\"hello world"\n\\"hello world"\n\\"hello world"'
|
|
|
|
reader = TextReader(StringIO(data), delimiter=",", header=None, escapechar="\\")
|
|
result = reader.read()
|
|
expected = {0: np.array(['"hello world"'] * 3, dtype=object)}
|
|
assert_array_dicts_equal(result, expected)
|
|
|
|
def test_eof_has_eol(self):
|
|
# handling of new line at EOF
|
|
pass
|
|
|
|
def test_na_substitution(self):
|
|
pass
|
|
|
|
def test_numpy_string_dtype(self):
|
|
data = """\
|
|
a,1
|
|
aa,2
|
|
aaa,3
|
|
aaaa,4
|
|
aaaaa,5"""
|
|
|
|
def _make_reader(**kwds):
|
|
if "dtype" in kwds:
|
|
kwds["dtype"] = ensure_dtype_objs(kwds["dtype"])
|
|
return TextReader(StringIO(data), delimiter=",", header=None, **kwds)
|
|
|
|
reader = _make_reader(dtype="S5,i4")
|
|
result = reader.read()
|
|
|
|
assert result[0].dtype == "S5"
|
|
|
|
ex_values = np.array(["a", "aa", "aaa", "aaaa", "aaaaa"], dtype="S5")
|
|
assert (result[0] == ex_values).all()
|
|
assert result[1].dtype == "i4"
|
|
|
|
reader = _make_reader(dtype="S4")
|
|
result = reader.read()
|
|
assert result[0].dtype == "S4"
|
|
ex_values = np.array(["a", "aa", "aaa", "aaaa", "aaaa"], dtype="S4")
|
|
assert (result[0] == ex_values).all()
|
|
assert result[1].dtype == "S4"
|
|
|
|
def test_pass_dtype(self):
|
|
data = """\
|
|
one,two
|
|
1,a
|
|
2,b
|
|
3,c
|
|
4,d"""
|
|
|
|
def _make_reader(**kwds):
|
|
if "dtype" in kwds:
|
|
kwds["dtype"] = ensure_dtype_objs(kwds["dtype"])
|
|
return TextReader(StringIO(data), delimiter=",", **kwds)
|
|
|
|
reader = _make_reader(dtype={"one": "u1", 1: "S1"})
|
|
result = reader.read()
|
|
assert result[0].dtype == "u1"
|
|
assert result[1].dtype == "S1"
|
|
|
|
reader = _make_reader(dtype={"one": np.uint8, 1: object})
|
|
result = reader.read()
|
|
assert result[0].dtype == "u1"
|
|
assert result[1].dtype == "O"
|
|
|
|
reader = _make_reader(dtype={"one": np.dtype("u1"), 1: np.dtype("O")})
|
|
result = reader.read()
|
|
assert result[0].dtype == "u1"
|
|
assert result[1].dtype == "O"
|
|
|
|
def test_usecols(self):
|
|
data = """\
|
|
a,b,c
|
|
1,2,3
|
|
4,5,6
|
|
7,8,9
|
|
10,11,12"""
|
|
|
|
def _make_reader(**kwds):
|
|
return TextReader(StringIO(data), delimiter=",", **kwds)
|
|
|
|
reader = _make_reader(usecols=(1, 2))
|
|
result = reader.read()
|
|
|
|
exp = _make_reader().read()
|
|
assert len(result) == 2
|
|
assert (result[1] == exp[1]).all()
|
|
assert (result[2] == exp[2]).all()
|
|
|
|
def test_cr_delimited(self):
|
|
def _test(text, **kwargs):
|
|
nice_text = text.replace("\r", "\r\n")
|
|
result = TextReader(StringIO(text), **kwargs).read()
|
|
expected = TextReader(StringIO(nice_text), **kwargs).read()
|
|
assert_array_dicts_equal(result, expected)
|
|
|
|
data = "a,b,c\r1,2,3\r4,5,6\r7,8,9\r10,11,12"
|
|
_test(data, delimiter=",")
|
|
|
|
data = "a b c\r1 2 3\r4 5 6\r7 8 9\r10 11 12"
|
|
_test(data, delim_whitespace=True)
|
|
|
|
data = "a,b,c\r1,2,3\r4,5,6\r,88,9\r10,11,12"
|
|
_test(data, delimiter=",")
|
|
|
|
sample = (
|
|
"A,B,C,D,E,F,G,H,I,J,K,L,M,N,O\r"
|
|
"AAAAA,BBBBB,0,0,0,0,0,0,0,0,0,0,0,0,0\r"
|
|
",BBBBB,0,0,0,0,0,0,0,0,0,0,0,0,0"
|
|
)
|
|
_test(sample, delimiter=",")
|
|
|
|
data = "A B C\r 2 3\r4 5 6"
|
|
_test(data, delim_whitespace=True)
|
|
|
|
data = "A B C\r2 3\r4 5 6"
|
|
_test(data, delim_whitespace=True)
|
|
|
|
def test_empty_field_eof(self):
|
|
data = "a,b,c\n1,2,3\n4,,"
|
|
|
|
result = TextReader(StringIO(data), delimiter=",").read()
|
|
|
|
expected = {
|
|
0: np.array([1, 4], dtype=np.int64),
|
|
1: np.array(["2", ""], dtype=object),
|
|
2: np.array(["3", ""], dtype=object),
|
|
}
|
|
assert_array_dicts_equal(result, expected)
|
|
|
|
# GH5664
|
|
a = DataFrame([["b"], [np.nan]], columns=["a"], index=["a", "c"])
|
|
b = DataFrame([[1, 1, 1, 0], [1, 1, 1, 0]], columns=list("abcd"), index=[1, 1])
|
|
c = DataFrame(
|
|
[
|
|
[1, 2, 3, 4],
|
|
[6, np.nan, np.nan, np.nan],
|
|
[8, 9, 10, 11],
|
|
[13, 14, np.nan, np.nan],
|
|
],
|
|
columns=list("abcd"),
|
|
index=[0, 5, 7, 12],
|
|
)
|
|
|
|
for _ in range(100):
|
|
df = read_csv(StringIO("a,b\nc\n"), skiprows=0, names=["a"], engine="c")
|
|
tm.assert_frame_equal(df, a)
|
|
|
|
df = read_csv(
|
|
StringIO("1,1,1,1,0\n" * 2 + "\n" * 2), names=list("abcd"), engine="c"
|
|
)
|
|
tm.assert_frame_equal(df, b)
|
|
|
|
df = read_csv(
|
|
StringIO("0,1,2,3,4\n5,6\n7,8,9,10,11\n12,13,14"),
|
|
names=list("abcd"),
|
|
engine="c",
|
|
)
|
|
tm.assert_frame_equal(df, c)
|
|
|
|
def test_empty_csv_input(self):
|
|
# GH14867
|
|
with read_csv(
|
|
StringIO(), chunksize=20, header=None, names=["a", "b", "c"]
|
|
) as df:
|
|
assert isinstance(df, TextFileReader)
|
|
|
|
|
|
def assert_array_dicts_equal(left, right):
|
|
for k, v in left.items():
|
|
tm.assert_numpy_array_equal(np.asarray(v), np.asarray(right[k]))
|
|
|