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Merged
merged 3 commits into from
Mar 30, 2020
Merged

More Json parametrize #33148

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14be57d
empty_series fixture
WillAyd Mar 30, 2020
388cb72
float_frame usage
WillAyd Mar 30, 2020
5d4af6e
removed frame2
WillAyd Mar 30, 2020
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5 changes: 5 additions & 0 deletions pandas/conftest.py
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Original file line number Diff line number Diff line change
Expand Up @@ -521,6 +521,11 @@ def index_or_series_obj(request):
# ----------------------------------------------------------------
# DataFrames
# ----------------------------------------------------------------
@pytest.fixture
def empty_frame():
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This is scattered across a few modules right now that I didn't touch here; can use further here or in a follow up

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followup is fine.

return DataFrame()


@pytest.fixture
def float_frame():
"""
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29 changes: 10 additions & 19 deletions pandas/tests/io/json/test_pandas.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,6 @@
_tsd = tm.getTimeSeriesData()

_frame = DataFrame(_seriesd)
_frame2 = DataFrame(_seriesd, columns=["D", "C", "B", "A"])
_intframe = DataFrame({k: v.astype(np.int64) for k, v in _seriesd.items()})

_tsframe = DataFrame(_tsd)
Expand All @@ -44,20 +43,13 @@ def assert_json_roundtrip_equal(result, expected, orient):
class TestPandasContainer:
@pytest.fixture(autouse=True)
def setup(self):
self.empty_frame = DataFrame()
self.frame = _frame.copy()
self.frame2 = _frame2.copy()
self.intframe = _intframe.copy()
self.tsframe = _tsframe.copy()
self.mixed_frame = _mixed_frame.copy()
self.categorical = _cat_frame.copy()

yield

del self.empty_frame

del self.frame
del self.frame2
del self.intframe
del self.tsframe
del self.mixed_frame
Expand Down Expand Up @@ -126,19 +118,19 @@ def test_frame_non_unique_columns_raises(self, orient):
with pytest.raises(ValueError, match=msg):
df.to_json(orient=orient)

def test_frame_default_orient(self):
assert self.frame.to_json() == self.frame.to_json(orient="columns")
def test_frame_default_orient(self, float_frame):
assert float_frame.to_json() == float_frame.to_json(orient="columns")
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Note that float_frame and self.frame aren't 100% equivalent because the former has the columns labeled ABCD whereas the latter didn't provide labels. I don't think that distinction matters for these tests though


@pytest.mark.parametrize("dtype", [False, float])
@pytest.mark.parametrize("convert_axes", [True, False])
@pytest.mark.parametrize("numpy", [True, False])
def test_roundtrip_simple(self, orient, convert_axes, numpy, dtype):
data = self.frame.to_json(orient=orient)
def test_roundtrip_simple(self, orient, convert_axes, numpy, dtype, float_frame):
data = float_frame.to_json(orient=orient)
result = pd.read_json(
data, orient=orient, convert_axes=convert_axes, numpy=numpy, dtype=dtype
)

expected = self.frame.copy()
expected = float_frame

assert_json_roundtrip_equal(result, expected, orient)

Expand Down Expand Up @@ -226,12 +218,12 @@ def test_roundtrip_categorical(self, orient, convert_axes, numpy):

@pytest.mark.parametrize("convert_axes", [True, False])
@pytest.mark.parametrize("numpy", [True, False])
def test_roundtrip_empty(self, orient, convert_axes, numpy):
data = self.empty_frame.to_json(orient=orient)
def test_roundtrip_empty(self, orient, convert_axes, numpy, empty_frame):
data = empty_frame.to_json(orient=orient)
result = pd.read_json(
data, orient=orient, convert_axes=convert_axes, numpy=numpy
)
expected = self.empty_frame.copy()
expected = empty_frame.copy()

# TODO: both conditions below are probably bugs
if convert_axes:
Expand Down Expand Up @@ -738,11 +730,10 @@ def test_reconstruction_index(self):
result = read_json(df.to_json())
tm.assert_frame_equal(result, df)

def test_path(self):
def test_path(self, float_frame):
with tm.ensure_clean("test.json") as path:
for df in [
self.frame,
self.frame2,
float_frame,
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Similar to above comment, self.frame and self.frame2 are actually different in that the former uses default column labels whereas the latter used ABCD; I didn't think that distinction was worth creating a separate fixture or object within this test

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sure, but this is a historical accident, having a smaller set of common fixtures is better

self.intframe,
self.tsframe,
self.mixed_frame,
Expand Down
2 changes: 1 addition & 1 deletion pandas/tests/resample/conftest.py
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Original file line number Diff line number Diff line change
Expand Up @@ -153,7 +153,7 @@ def frame(index, _series_name, _static_values):


@pytest.fixture
def empty_frame(series):
def empty_frame_dti(series):
"""
Fixture for parametrization of empty DataFrame with date_range,
period_range and timedelta_range indexes
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22 changes: 10 additions & 12 deletions pandas/tests/resample/test_base.py
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Expand Up @@ -127,9 +127,9 @@ def test_resample_count_empty_series(freq, empty_series_dti, resample_method):

@all_ts
@pytest.mark.parametrize("freq", ["M", "D", "H"])
def test_resample_empty_dataframe(empty_frame, freq, resample_method):
def test_resample_empty_dataframe(empty_frame_dti, freq, resample_method):
# GH13212
df = empty_frame
df = empty_frame_dti
# count retains dimensions too
result = getattr(df.resample(freq), resample_method)()
if resample_method != "size":
Expand All @@ -149,15 +149,14 @@ def test_resample_empty_dataframe(empty_frame, freq, resample_method):

@all_ts
@pytest.mark.parametrize("freq", ["M", "D", "H"])
def test_resample_count_empty_dataframe(freq, empty_frame):
def test_resample_count_empty_dataframe(freq, empty_frame_dti):
# GH28427

empty_frame = empty_frame.copy()
empty_frame["a"] = []
empty_frame_dti["a"] = []

result = empty_frame.resample(freq).count()
result = empty_frame_dti.resample(freq).count()

index = _asfreq_compat(empty_frame.index, freq)
index = _asfreq_compat(empty_frame_dti.index, freq)

expected = pd.DataFrame({"a": []}, dtype="int64", index=index)

Expand All @@ -166,15 +165,14 @@ def test_resample_count_empty_dataframe(freq, empty_frame):

@all_ts
@pytest.mark.parametrize("freq", ["M", "D", "H"])
def test_resample_size_empty_dataframe(freq, empty_frame):
def test_resample_size_empty_dataframe(freq, empty_frame_dti):
# GH28427

empty_frame = empty_frame.copy()
empty_frame["a"] = []
empty_frame_dti["a"] = []

result = empty_frame.resample(freq).size()
result = empty_frame_dti.resample(freq).size()

index = _asfreq_compat(empty_frame.index, freq)
index = _asfreq_compat(empty_frame_dti.index, freq)

expected = pd.Series([], dtype="int64", index=index)

Expand Down