def test_st_arrow_altair_chart(self):
"""Test st._arrow_altair_chart."""
import altair as alt
df = pd.DataFrame(np.random.randn(3, 3), columns=["a", "b", "c"])
c = (alt.Chart(df).mark_circle().encode(x="a",
y="b",
size="c",
color="c").interactive())
st._arrow_altair_chart(c)
proto = self.get_delta_from_queue().new_element.arrow_vega_lite_chart
spec = json.loads(proto.spec)
# Checking Vega-Lite is a lot of work so rather than doing that, we
# just checked to see if the spec data name matches the dataset.
self.assertEqual(spec.get("data").get("name"), proto.datasets[0].name)
def test_date_column_utc_scale(self):
"""Test that columns with date values have UTC time scale"""
df = pd.DataFrame({
"index": [date(2019, 8, 9), date(2019, 8, 10)],
"numbers": [1, 10]
}).set_index("index")
chart = altair._generate_chart(ChartType.LINE, df)
st._arrow_altair_chart(chart)
proto = self.get_delta_from_queue().new_element.arrow_vega_lite_chart
spec_dict = json.loads(proto.spec)
# The x axis should have scale="utc", because it uses date values.
x_scale = _deep_get(spec_dict, "encoding", "x", "scale", "type")
self.assertEqual(x_scale, "utc")
# The y axis should _not_ have scale="utc", because it doesn't
# use date values.
y_scale = _deep_get(spec_dict, "encoding", "y", "scale", "type")
self.assertNotEqual(y_scale, "utc")
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)
# comment this one out to avoid this Cypress-Mapbox related error.
# ref: https://github.com/cypress-io/cypress/issues/4322
# st.pydeck_chart()
# st.map()
# 6 errors
try:
st._arrow_vega_lite_chart({}, use_container_width=True)
except Exception as e:
st.write(e)
try:
st._arrow_vega_lite_chart(data, {}, use_container_width=True)
except Exception as e:
st.write(e)
try:
st._arrow_vega_lite_chart(data, use_container_width=True)
except Exception as e:
st.write(e)
try:
st._arrow_vega_lite_chart(use_container_width=True)
except Exception as e:
st.write(e)
try:
st._arrow_altair_chart(use_container_width=True)
except Exception as e:
st.write(e)
# Copyright 2018-2021 Streamlit Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import streamlit as st import pandas as pd import numpy as np import altair as alt data = np.random.randn(200, 3) df = pd.DataFrame(data, columns=["a", "b", "c"]) chart = alt.Chart(df).mark_circle().encode(x="a", y="b", size="c", color="c") st._arrow_altair_chart(chart)
},
"encoding": {
"x": {
"field": "a",
"type": "quantitative"
},
"y": {
"field": "b",
"type": "quantitative"
},
},
},
use_container_width=True,
)
altair_element = st._arrow_altair_chart(
alt.Chart(df).mark_line(point=True).encode(x="a", y="b").interactive(),
use_container_width=True,
)
table_element._arrow_add_rows(df)
dataframe_element._arrow_add_rows(df)
chart_element_1._arrow_add_rows(df)
chart_element_2._arrow_add_rows(df)
vega_element_1._arrow_add_rows(df)
vega_element_2._arrow_add_rows(df)
vega_element_3._arrow_add_rows(foo=df)
altair_element._arrow_add_rows(df)
# Test that `_arrow_add_rows` errors out when the dataframe dimensions don't match.
# This should show an error!
dataframe_element = st._arrow_dataframe(df)
dataframe_element._arrow_add_rows(np.abs(np.random.randn(1, 6)))
