ai-content-maker/.venv/Lib/site-packages/pandas/tests/io/parser/test_dialect.py

157 lines
4.2 KiB
Python

"""
Tests that dialects are properly handled during parsing
for all of the parsers defined in parsers.py
"""
import csv
from io import StringIO
import pytest
from pandas.errors import ParserWarning
from pandas import DataFrame
import pandas._testing as tm
pytestmark = pytest.mark.usefixtures("pyarrow_skip")
@pytest.fixture
def custom_dialect():
dialect_name = "weird"
dialect_kwargs = {
"doublequote": False,
"escapechar": "~",
"delimiter": ":",
"skipinitialspace": False,
"quotechar": "~",
"quoting": 3,
}
return dialect_name, dialect_kwargs
def test_dialect(all_parsers):
parser = all_parsers
data = """\
label1,label2,label3
index1,"a,c,e
index2,b,d,f
"""
dia = csv.excel()
dia.quoting = csv.QUOTE_NONE
df = parser.read_csv(StringIO(data), dialect=dia)
data = """\
label1,label2,label3
index1,a,c,e
index2,b,d,f
"""
exp = parser.read_csv(StringIO(data))
exp.replace("a", '"a', inplace=True)
tm.assert_frame_equal(df, exp)
def test_dialect_str(all_parsers):
dialect_name = "mydialect"
parser = all_parsers
data = """\
fruit:vegetable
apple:broccoli
pear:tomato
"""
exp = DataFrame({"fruit": ["apple", "pear"], "vegetable": ["broccoli", "tomato"]})
with tm.with_csv_dialect(dialect_name, delimiter=":"):
df = parser.read_csv(StringIO(data), dialect=dialect_name)
tm.assert_frame_equal(df, exp)
def test_invalid_dialect(all_parsers):
class InvalidDialect:
pass
data = "a\n1"
parser = all_parsers
msg = "Invalid dialect"
with pytest.raises(ValueError, match=msg):
parser.read_csv(StringIO(data), dialect=InvalidDialect)
@pytest.mark.parametrize(
"arg",
[None, "doublequote", "escapechar", "skipinitialspace", "quotechar", "quoting"],
)
@pytest.mark.parametrize("value", ["dialect", "default", "other"])
def test_dialect_conflict_except_delimiter(all_parsers, custom_dialect, arg, value):
# see gh-23761.
dialect_name, dialect_kwargs = custom_dialect
parser = all_parsers
expected = DataFrame({"a": [1], "b": [2]})
data = "a:b\n1:2"
warning_klass = None
kwds = {}
# arg=None tests when we pass in the dialect without any other arguments.
if arg is not None:
if "value" == "dialect": # No conflict --> no warning.
kwds[arg] = dialect_kwargs[arg]
elif "value" == "default": # Default --> no warning.
from pandas.io.parsers.base_parser import parser_defaults
kwds[arg] = parser_defaults[arg]
else: # Non-default + conflict with dialect --> warning.
warning_klass = ParserWarning
kwds[arg] = "blah"
with tm.with_csv_dialect(dialect_name, **dialect_kwargs):
result = parser.read_csv_check_warnings(
warning_klass,
"Conflicting values for",
StringIO(data),
dialect=dialect_name,
**kwds,
)
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize(
"kwargs,warning_klass",
[
({"sep": ","}, None), # sep is default --> sep_override=True
({"sep": "."}, ParserWarning), # sep isn't default --> sep_override=False
({"delimiter": ":"}, None), # No conflict
({"delimiter": None}, None), # Default arguments --> sep_override=True
({"delimiter": ","}, ParserWarning), # Conflict
({"delimiter": "."}, ParserWarning), # Conflict
],
ids=[
"sep-override-true",
"sep-override-false",
"delimiter-no-conflict",
"delimiter-default-arg",
"delimiter-conflict",
"delimiter-conflict2",
],
)
def test_dialect_conflict_delimiter(all_parsers, custom_dialect, kwargs, warning_klass):
# see gh-23761.
dialect_name, dialect_kwargs = custom_dialect
parser = all_parsers
expected = DataFrame({"a": [1], "b": [2]})
data = "a:b\n1:2"
with tm.with_csv_dialect(dialect_name, **dialect_kwargs):
result = parser.read_csv_check_warnings(
warning_klass,
"Conflicting values for 'delimiter'",
StringIO(data),
dialect=dialect_name,
**kwargs,
)
tm.assert_frame_equal(result, expected)