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CLN: C408 Unnecessary dict call - rewrite as a literal #38138 #38383

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merged 4 commits into from
Dec 9, 2020
Merged

CLN: C408 Unnecessary dict call - rewrite as a literal #38138 #38383

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f855954
last dict fixings
UrielMaD Dec 9, 2020
adc2ff8
last dict fixings
UrielMaD Dec 9, 2020
6adf501
last dict fixings
UrielMaD Dec 9, 2020
2970c67
last dict fixings
UrielMaD Dec 9, 2020
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118 changes: 59 additions & 59 deletions pandas/tests/io/generate_legacy_storage_files.py
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Original file line number Diff line number Diff line change
Expand Up @@ -142,16 +142,16 @@ def create_data():
"E": [0.0, 1, Timestamp("20100101"), "foo", 2.0],
}

scalars = dict(timestamp=Timestamp("20130101"), period=Period("2012", "M"))

index = dict(
int=Index(np.arange(10)),
date=date_range("20130101", periods=10),
period=period_range("2013-01-01", freq="M", periods=10),
float=Index(np.arange(10, dtype=np.float64)),
uint=Index(np.arange(10, dtype=np.uint64)),
timedelta=timedelta_range("00:00:00", freq="30T", periods=10),
)
scalars = {"timestamp": Timestamp("20130101"), "period": Period("2012", "M")}

index = {
"int": Index(np.arange(10)),
"date": date_range("20130101", periods=10),
"period": period_range("2013-01-01", freq="M", periods=10),
"float": Index(np.arange(10, dtype=np.float64)),
"uint": Index(np.arange(10, dtype=np.uint64)),
"timedelta": timedelta_range("00:00:00", freq="30T", periods=10),
}

index["range"] = RangeIndex(10)

Expand All @@ -160,8 +160,8 @@ def create_data():

index["interval"] = interval_range(0, periods=10)

mi = dict(
reg2=MultiIndex.from_tuples(
mi = {
"reg2": MultiIndex.from_tuples(
tuple(
zip(
*[
Expand All @@ -172,35 +172,35 @@ def create_data():
),
names=["first", "second"],
)
)
}

series = dict(
float=Series(data["A"]),
int=Series(data["B"]),
mixed=Series(data["E"]),
ts=Series(
series = {
"float": Series(data["A"]),
"int": Series(data["B"]),
"mixed": Series(data["E"]),
"ts": Series(
np.arange(10).astype(np.int64), index=date_range("20130101", periods=10)
),
mi=Series(
"mi": Series(
np.arange(5).astype(np.float64),
index=MultiIndex.from_tuples(
tuple(zip(*[[1, 1, 2, 2, 2], [3, 4, 3, 4, 5]])), names=["one", "two"]
),
),
dup=Series(np.arange(5).astype(np.float64), index=["A", "B", "C", "D", "A"]),
cat=Series(Categorical(["foo", "bar", "baz"])),
dt=Series(date_range("20130101", periods=5)),
dt_tz=Series(date_range("20130101", periods=5, tz="US/Eastern")),
period=Series([Period("2000Q1")] * 5),
)
"dup": Series(np.arange(5).astype(np.float64), index=["A", "B", "C", "D", "A"]),
"cat": Series(Categorical(["foo", "bar", "baz"])),
"dt": Series(date_range("20130101", periods=5)),
"dt_tz": Series(date_range("20130101", periods=5, tz="US/Eastern")),
"period": Series([Period("2000Q1")] * 5),
}

mixed_dup_df = DataFrame(data)
mixed_dup_df.columns = list("ABCDA")
frame = dict(
float=DataFrame({"A": series["float"], "B": series["float"] + 1}),
int=DataFrame({"A": series["int"], "B": series["int"] + 1}),
mixed=DataFrame({k: data[k] for k in ["A", "B", "C", "D"]}),
mi=DataFrame(
frame = {
"float": DataFrame({"A": series["float"], "B": series["float"] + 1}),
"int": DataFrame({"A": series["int"], "B": series["int"] + 1}),
"mixed": DataFrame({k: data[k] for k in ["A", "B", "C", "D"]}),
"mi": DataFrame(
{"A": np.arange(5).astype(np.float64), "B": np.arange(5).astype(np.int64)},
index=MultiIndex.from_tuples(
tuple(
Expand All @@ -214,45 +214,45 @@ def create_data():
names=["first", "second"],
),
),
dup=DataFrame(
"dup": DataFrame(
np.arange(15).reshape(5, 3).astype(np.float64), columns=["A", "B", "A"]
),
cat_onecol=DataFrame({"A": Categorical(["foo", "bar"])}),
cat_and_float=DataFrame(
"cat_onecol": DataFrame({"A": Categorical(["foo", "bar"])}),
"cat_and_float": DataFrame(
{
"A": Categorical(["foo", "bar", "baz"]),
"B": np.arange(3).astype(np.int64),
}
),
mixed_dup=mixed_dup_df,
dt_mixed_tzs=DataFrame(
"mixed_dup": mixed_dup_df,
"dt_mixed_tzs": DataFrame(
{
"A": Timestamp("20130102", tz="US/Eastern"),
"B": Timestamp("20130603", tz="CET"),
},
index=range(5),
),
dt_mixed2_tzs=DataFrame(
"dt_mixed2_tzs": DataFrame(
{
"A": Timestamp("20130102", tz="US/Eastern"),
"B": Timestamp("20130603", tz="CET"),
"C": Timestamp("20130603", tz="UTC"),
},
index=range(5),
),
)
}

cat = dict(
int8=Categorical(list("abcdefg")),
int16=Categorical(np.arange(1000)),
int32=Categorical(np.arange(10000)),
)
cat = {
"int8": Categorical(list("abcdefg")),
"int16": Categorical(np.arange(1000)),
"int32": Categorical(np.arange(10000)),
}

timestamp = dict(
normal=Timestamp("2011-01-01"),
nat=NaT,
tz=Timestamp("2011-01-01", tz="US/Eastern"),
)
timestamp = {
"normal": Timestamp("2011-01-01"),
"nat": NaT,
"tz": Timestamp("2011-01-01", tz="US/Eastern"),
}

timestamp["freq"] = Timestamp("2011-01-01", freq="D")
timestamp["both"] = Timestamp("2011-01-01", tz="Asia/Tokyo", freq="M")
Expand Down Expand Up @@ -282,18 +282,18 @@ def create_data():
"Minute": Minute(1),
}

return dict(
series=series,
frame=frame,
index=index,
scalars=scalars,
mi=mi,
sp_series=dict(float=_create_sp_series(), ts=_create_sp_tsseries()),
sp_frame=dict(float=_create_sp_frame()),
cat=cat,
timestamp=timestamp,
offsets=off,
)
return {
"series": series,
"frame": frame,
"index": index,
"scalars": scalars,
"mi": mi,
"sp_series": {"float": _create_sp_series(), "ts": _create_sp_tsseries()},
"sp_frame": {"float": _create_sp_frame()},
"cat": cat,
"timestamp": timestamp,
"offsets": off,
}


def create_pickle_data():
Expand Down
2 changes: 1 addition & 1 deletion pandas/tests/io/parser/test_comment.py
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Original file line number Diff line number Diff line change
Expand Up @@ -26,7 +26,7 @@ def test_comment(all_parsers, na_values):


@pytest.mark.parametrize(
"read_kwargs", [dict(), dict(lineterminator="*"), dict(delim_whitespace=True)]
"read_kwargs", [{}, {"lineterminator": "*"}, {"delim_whitespace": True}]
)
def test_line_comment(all_parsers, read_kwargs):
parser = all_parsers
Expand Down
30 changes: 15 additions & 15 deletions pandas/tests/io/parser/test_dialect.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,14 +17,14 @@
@pytest.fixture
def custom_dialect():
dialect_name = "weird"
dialect_kwargs = dict(
doublequote=False,
escapechar="~",
delimiter=":",
skipinitialspace=False,
quotechar="~",
quoting=3,
)
dialect_kwargs = {
"doublequote": False,
"escapechar": "~",
"delimiter": ":",
"skipinitialspace": False,
"quotechar": "~",
"quoting": 3,
}
return dialect_name, dialect_kwargs


Expand Down Expand Up @@ -91,7 +91,7 @@ def test_dialect_conflict_except_delimiter(all_parsers, custom_dialect, arg, val
data = "a:b\n1:2"

warning_klass = None
kwds = dict()
kwds = {}

# arg=None tests when we pass in the dialect without any other arguments.
if arg is not None:
Expand All @@ -114,12 +114,12 @@ def test_dialect_conflict_except_delimiter(all_parsers, custom_dialect, arg, val
@pytest.mark.parametrize(
"kwargs,warning_klass",
[
(dict(sep=","), None), # sep is default --> sep_override=True
(dict(sep="."), ParserWarning), # sep isn't default --> sep_override=False
(dict(delimiter=":"), None), # No conflict
(dict(delimiter=None), None), # Default arguments --> sep_override=True
(dict(delimiter=","), ParserWarning), # Conflict
(dict(delimiter="."), ParserWarning), # Conflict
({"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",
Expand Down
12 changes: 6 additions & 6 deletions pandas/tests/io/parser/test_encoding.py
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Original file line number Diff line number Diff line change
Expand Up @@ -47,7 +47,7 @@ def test_utf16_bom_skiprows(all_parsers, sep, encoding):
",", sep
)
path = f"__{tm.rands(10)}__.csv"
kwargs = dict(sep=sep, skiprows=2)
kwargs = {"sep": sep, "skiprows": 2}
utf8 = "utf-8"

with tm.ensure_clean(path) as path:
Expand Down Expand Up @@ -91,17 +91,17 @@ def test_unicode_encoding(all_parsers, csv_dir_path):
"data,kwargs,expected",
[
# Basic test
("a\n1", dict(), DataFrame({"a": [1]})),
("a\n1", {}, DataFrame({"a": [1]})),
# "Regular" quoting
('"a"\n1', dict(quotechar='"'), DataFrame({"a": [1]})),
('"a"\n1', {"quotechar": '"'}, DataFrame({"a": [1]})),
# Test in a data row instead of header
("b\n1", dict(names=["a"]), DataFrame({"a": ["b", "1"]})),
("b\n1", {"names": ["a"]}, DataFrame({"a": ["b", "1"]})),
# Test in empty data row with skipping
("\n1", dict(names=["a"], skip_blank_lines=True), DataFrame({"a": [1]})),
("\n1", {"names": ["a"], "skip_blank_lines": True}, DataFrame({"a": [1]})),
# Test in empty data row without skipping
(
"\n1",
dict(names=["a"], skip_blank_lines=False),
{"names": ["a"], "skip_blank_lines": False},
DataFrame({"a": [np.nan, 1]}),
),
],
Expand Down
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