def test_dict_unflatten(self):
"""Test passing a spec as keywords."""
st._arrow_vega_lite_chart(df1,
x="foo",
boink_boop=100,
baz={"boz": "booz"})
proto = self.get_delta_from_queue().new_element.arrow_vega_lite_chart
pd.testing.assert_frame_equal(bytes_to_data_frame(proto.data.data),
df1,
check_dtype=False)
self.assertDictEqual(
json.loads(proto.spec),
merge_dicts(
autosize_spec,
{
"baz": {
"boz": "booz"
},
"boink": {
"boop": 100
},
"encoding": {
"x": "foo"
},
},
),
)
def test_st_arrow_table(self):
"""Test st._arrow_table."""
from streamlit.type_util import bytes_to_data_frame
df = pd.DataFrame([[1, 2], [3, 4]], columns=["col1", "col2"])
st._arrow_table(df)
proto = self.get_delta_from_queue().new_element.arrow_table
pd.testing.assert_frame_equal(bytes_to_data_frame(proto.data), df)
def test_st_arrow_dataframe(self):
"""Test st._arrow_dataframe."""
from streamlit.type_util import bytes_to_data_frame
df = pd.DataFrame({"one": [1, 2], "two": [11, 22]})
st._arrow_dataframe(df)
proto = self.get_delta_from_queue().new_element.arrow_data_frame
pd.testing.assert_frame_equal(bytes_to_data_frame(proto.data), df)
def test_data_in_spec(self):
"""Test passing data=df inside the spec."""
st._arrow_vega_lite_chart({"mark": "rect", "data": df1})
proto = self.get_delta_from_queue().new_element.arrow_vega_lite_chart
pd.testing.assert_frame_equal(bytes_to_data_frame(proto.data.data),
df1,
check_dtype=False)
self.assertDictEqual(json.loads(proto.spec),
merge_dicts(autosize_spec, {"mark": "rect"}))
def test_deltas_that_melt_dataframes(self):
deltas = self._get_deltas_that_melt_dataframes()
for delta in deltas:
element = delta(DATAFRAME)
element._arrow_add_rows(NEW_ROWS)
proto = bytes_to_data_frame(
self.get_delta_from_queue().arrow_add_rows.data.data)
pd.testing.assert_frame_equal(proto, MELTED_DATAFRAME)
def test_display_values(self):
df = pd.DataFrame([[1, 2, 3], [4, 5, 6]], )
styler = df.style.format("{:.2%}")
st._arrow_table(styler)
expected = pd.DataFrame([["100.00%", "200.00%", "300.00%"],
["400.00%", "500.00%", "600.00%"]], )
proto = self.get_delta_from_queue().new_element.arrow_table
pd.testing.assert_frame_equal(
bytes_to_data_frame(proto.styler.display_values), expected)
def test_no_args_add_rows(self):
"""Test that you can call _arrow_add_rows on a arrow_vega_lite_chart (without data)."""
chart = st._arrow_vega_lite_chart({"mark": "rect"})
proto = self.get_delta_from_queue().new_element.arrow_vega_lite_chart
self.assertEqual(proto.HasField("data"), False)
chart._arrow_add_rows(df1)
proto = self.get_delta_from_queue().arrow_add_rows
pd.testing.assert_frame_equal(
bytes_to_data_frame(proto.data.data), df1, check_dtype=False
)
def test_arrow_area_chart(self):
"""Test st._arrow_area_chart."""
df = pd.DataFrame([[20, 30, 50]], columns=["a", "b", "c"])
EXPECTED_DATAFRAME = pd.DataFrame(
[[0, "a", 20], [0, "b", 30], [0, "c", 50]],
index=[0, 1, 2],
columns=["index", "variable", "value"],
)
st._arrow_area_chart(df)
proto = self.get_delta_from_queue().new_element.arrow_vega_lite_chart
chart_spec = json.loads(proto.spec)
self.assertEqual(chart_spec["mark"], "area")
pd.testing.assert_frame_equal(
bytes_to_data_frame(proto.datasets[0].data.data),
EXPECTED_DATAFRAME,
)
def test_arrow_line_chart_with_generic_index(self):
"""Test st._arrow_line_chart with a generic index."""
df = pd.DataFrame([[20, 30, 50]], columns=["a", "b", "c"])
df.set_index("a", inplace=True)
EXPECTED_DATAFRAME = pd.DataFrame(
[[20, "b", 30], [20, "c", 50]],
index=[0, 1],
columns=["a", "variable", "value"],
)
st._arrow_line_chart(df)
proto = self.get_delta_from_queue().new_element.arrow_vega_lite_chart
chart_spec = json.loads(proto.spec)
self.assertEqual(chart_spec["mark"], "line")
pd.testing.assert_frame_equal(
bytes_to_data_frame(proto.datasets[0].data.data),
EXPECTED_DATAFRAME,
)
def test_st_arrow_line_chart(self):
"""Test st._arrow_line_chart."""
from streamlit.type_util import bytes_to_data_frame
df = pd.DataFrame([[10, 20, 30]], columns=["a", "b", "c"])
EXPECTED_DATAFRAME = pd.DataFrame(
[[0, "a", 10], [0, "b", 20], [0, "c", 30]],
index=[0, 1, 2],
columns=["index", "variable", "value"],
)
st._arrow_line_chart(df, width=640, height=480)
proto = self.get_delta_from_queue().new_element.arrow_vega_lite_chart
chart_spec = json.loads(proto.spec)
self.assertEqual(chart_spec["mark"], "line")
self.assertEqual(chart_spec["width"], 640)
self.assertEqual(chart_spec["height"], 480)
pd.testing.assert_frame_equal(
bytes_to_data_frame(proto.datasets[0].data.data),
EXPECTED_DATAFRAME,
)
def test_altair_chart(self):
"""Test that it can be called with args."""
df = pd.DataFrame([["A", "B", "C", "D"], [28, 55, 43, 91]],
index=["a", "b"]).T
chart = alt.Chart(df).mark_bar().encode(x="a", y="b")
EXPECTED_DATAFRAME = pd.DataFrame({
"a": ["A", "B", "C", "D"],
"b": [28, 55, 43, 91],
})
st._arrow_altair_chart(chart)
proto = self.get_delta_from_queue().new_element.arrow_vega_lite_chart
self.assertEqual(proto.HasField("data"), False)
self.assertEqual(len(proto.datasets), 1)
pd.testing.assert_frame_equal(
bytes_to_data_frame(proto.datasets[0].data.data),
EXPECTED_DATAFRAME)
spec_dict = json.loads(proto.spec)
self.assertEqual(
spec_dict["encoding"],
{
"y": {
"field": "b",
"type": "quantitative"
},
"x": {
"field": "a",
"type": "nominal"
},
},
)
self.assertEqual(spec_dict["data"], {"name": proto.datasets[0].name})
self.assertEqual(spec_dict["mark"], "bar")
self.assertTrue("config" in spec_dict)
self.assertTrue("encoding" in spec_dict)
def test_dataframe_data(self):
df = mock_data_frame()
st._arrow_table(df)
proto = self.get_delta_from_queue().new_element.arrow_table
pd.testing.assert_frame_equal(bytes_to_data_frame(proto.data), df)
