def test_dict_unflatten(self):
"""Test passing a spec as keywords."""
st._legacy_vega_lite_chart(df1,
x="foo",
boink_boop=100,
baz={"boz": "booz"})
c = self.get_delta_from_queue().new_element.vega_lite_chart
self.assertEqual(c.HasField("data"), True)
self.assertDictEqual(
json.loads(c.spec),
merge_dicts(
autosize_spec,
{
"baz": {
"boz": "booz"
},
"boink": {
"boop": 100
},
"encoding": {
"x": "foo"
},
},
),
)
def test_datasets_in_spec(self):
"""Test passing datasets={foo: df} inside the spec."""
st._legacy_vega_lite_chart({"mark": "rect", "datasets": {"foo": df1}})
c = self.get_delta_from_queue().new_element.vega_lite_chart
self.assertEqual(c.HasField("data"), False)
self.assertDictEqual(json.loads(c.spec),
merge_dicts(autosize_spec, {"mark": "rect"}))
def test_spec_in_arg1(self):
"""Test that it can be called spec as the 1st arg."""
st._legacy_vega_lite_chart({"mark": "rect"})
c = self.get_delta_from_queue().new_element.vega_lite_chart
self.assertEqual(c.HasField("data"), False)
self.assertDictEqual(json.loads(c.spec),
merge_dicts(autosize_spec, {"mark": "rect"}))
def test_spec_but_no_data(self):
"""Test that it can be called with only data set to None."""
st._legacy_vega_lite_chart(None, {"mark": "rect"})
c = self.get_delta_from_queue().new_element.vega_lite_chart
self.assertEqual(c.HasField("data"), False)
self.assertDictEqual(json.loads(c.spec),
merge_dicts(autosize_spec, {"mark": "rect"}))
def test_width_inside_spec(self):
"""Test the width up to Vega-Lite."""
st._legacy_vega_lite_chart(df1, {"mark": "rect", "width": 200})
c = self.get_delta_from_queue().new_element.vega_lite_chart
self.assertDictEqual(
json.loads(c.spec),
merge_dicts(autosize_spec, {"mark": "rect", "width": 200}),
)
def test_use_container_width(self):
"""Test that use_container_width=True autosets to full width."""
st._legacy_vega_lite_chart(df1, {"mark": "rect"}, use_container_width=True)
c = self.get_delta_from_queue().new_element.vega_lite_chart
self.assertDictEqual(
json.loads(c.spec), merge_dicts(autosize_spec, {"mark": "rect"})
)
self.assertEqual(c.use_container_width, True)
def _get_unnamed_data_methods(self):
"""DeltaGenerator methods that do not produce named datasets."""
return [
lambda df: st._legacy_dataframe(df),
lambda df: st._legacy_table(df),
lambda df: st._legacy_vega_lite_chart(
df, {"mark": "line", "encoding": {"x": "a", "y": "b"}}
),
# TODO: _legacy_line_chart, _legacy_bar_chart, etc.
]
def test_no_args_add_rows(self):
"""Test that you can call _legacy_add_rows on a _legacy_vega_lite_chart(None)."""
x = st._legacy_vega_lite_chart({"mark": "rect"})
c = self.get_delta_from_queue().new_element.vega_lite_chart
self.assertEqual(c.HasField("data"), False)
x._legacy_add_rows(df1)
c = self.get_delta_from_queue().new_element.vega_lite_chart
self.assertEqual(len(c.data.data.cols[0].strings.data), 4)
def _get_named_data_methods(self):
"""DeltaGenerator methods that produce named datasets."""
# These should always name the desired data "mydata1"
return [
lambda df: st._legacy_vega_lite_chart(
{
"mark": "line",
"datasets": {"mydata1": df},
"data": {"name": "mydata1"},
"encoding": {"x": "a", "y": "b"},
}
),
# TODO: deck_gl_chart
]
def test_legacy_add_rows(self):
"""Test that you can call _legacy_add_rows on a _legacy_vega_lite_chart(data)."""
x = st._legacy_vega_lite_chart(df1, {"mark": "rect"})
c = self.get_delta_from_queue().new_element.vega_lite_chart
self.assertEqual(len(c.data.data.cols[0].strings.data), 4)
x._legacy_add_rows(df2)
c = self.get_delta_from_queue().new_element.vega_lite_chart
self.assertEqual(len(c.data.data.cols[0].strings.data), 8)
self.assertDictEqual(json.loads(c.spec),
merge_dicts(autosize_spec, {"mark": "rect"}))
c = self.get_delta_from_queue().new_element.vega_lite_chart
self.assertEqual(c.HasField("data"), True)
"color": {"field": "c", "type": "quantitative"},
},
}
spec_with_width = {
"mark": "circle",
"encoding": {
"x": {"field": "a", "type": "quantitative"},
"y": {"field": "b", "type": "quantitative"},
"size": {"field": "c", "type": "quantitative"},
"color": {"field": "c", "type": "quantitative"},
},
"width": "500",
}
st._legacy_vega_lite_chart(df, spec, use_container_width=True)
st._legacy_vega_lite_chart(df, spec, use_container_width=True)
st._legacy_vega_lite_chart(df, spec)
st._legacy_vega_lite_chart(df, spec_with_width)
# Screenshot comparison
st.header("Different ways to get the exact same plot")
df = pd.DataFrame([["A", "B", "C", "D"], [28, 55, 43, 91]], index=["a", "b"]).T
st.write("Using a top-level `df` and a `spec` dict:")
st._legacy_vega_lite_chart(
df,
{
def test_pyarrow_table_data(self):
"""Test that an error is raised when called with `pyarrow.Table` data."""
with self.assertRaises(StreamlitAPIException):
st._legacy_vega_lite_chart(pa.Table.from_pandas(df1), {"mark": "rect"})
def test_none_args(self):
"""Test that an error is raised when called with args set to None."""
with self.assertRaises(ValueError):
st._legacy_vega_lite_chart(None, None)
def test_no_args(self):
"""Test that an error is raised when called with no args."""
with self.assertRaises(ValueError):
st._legacy_vega_lite_chart()
import matplotlib.pyplot as plt
import streamlit as st
import pandas as pd
data = pd.DataFrame({"a": [1, 2, 3, 4], "b": [1, 3, 2, 4]})
spec = {
"mark": "line",
"encoding": {
"x": {"field": "a", "type": "quantitative"},
"y": {"field": "b", "type": "quantitative"},
},
}
# 5 empty charts
st._legacy_vega_lite_chart(spec, use_container_width=True)
fig, ax = plt.subplots()
st.pyplot(fig, use_container_width=True)
st._legacy_line_chart()
st._legacy_bar_chart()
st._legacy_area_chart()
# 1 empty map
# 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._legacy_vega_lite_chart({}, use_container_width=True)
table_el = st._legacy_table(df1)
dataframe_el = st._legacy_dataframe(df1)
chart_el1 = st._legacy_line_chart()
chart_el2 = st._legacy_line_chart(df1)
# 4 identical charts, built in different ways.
vega_el1 = st._legacy_vega_lite_chart(
df1,
{
"mark": {
"type": "line",
"point": True
},
"encoding": {
"x": {
"field": "a",
"type": "quantitative"
},
"y": {
"field": "b",
"type": "quantitative"
},
},
},
use_container_width=True,
)
vega_el2 = st._legacy_vega_lite_chart(
{
"datasets": {
"foo": df1
},
"data": {
