def _maybe_compose_deltas(old_delta: Delta,
new_delta: Delta) -> Optional[Delta]:
"""Combines new_delta onto old_delta if possible.
If the combination takes place, the function returns a new Delta that
should replace old_delta in the queue.
If the new_delta is incompatible with old_delta, the function returns None.
In this case, the new_delta should just be appended to the queue as normal.
"""
old_delta_type = old_delta.WhichOneof("type")
if old_delta_type == "add_block":
# We never replace add_block deltas, because blocks can have
# other dependent deltas later in the queue. For example:
#
# placeholder = st.empty()
# placeholder.columns(1)
# placeholder.empty()
#
# The call to "placeholder.columns(1)" creates two blocks, a parent
# container with delta_path (0, 0), and a column child with
# delta_path (0, 0, 0). If the final "placeholder.empty()" Delta
# is composed with the parent container Delta, the frontend will
# throw an error when it tries to add that column child to what is
# now just an element, and not a block.
return None
new_delta_type = new_delta.WhichOneof("type")
if new_delta_type == "new_element":
return new_delta
if new_delta_type == "add_block":
return new_delta
return None
def _maybe_compose_deltas(old_delta: Delta,
new_delta: Delta) -> Optional[Delta]:
"""Combines new_delta onto old_delta if possible.
If the combination takes place, the function returns a new Delta that
should replace old_delta in the queue.
If the new_delta is incompatible with old_delta, the function returns None.
In this case, the new_delta should just be appended to the queue as normal.
"""
old_delta_type = old_delta.WhichOneof("type")
if old_delta_type == "add_block":
# We never replace add_block deltas, because blocks can have
# other dependent deltas later in the queue. For example:
#
# placeholder = st.empty()
# placeholder.columns(1)
# placeholder.empty()
#
# The call to "placeholder.columns(1)" creates two blocks, a parent
# container with delta_path (0, 0), and a column child with
# delta_path (0, 0, 0). If the final "placeholder.empty()" Delta
# is composed with the parent container Delta, the frontend will
# throw an error when it tries to add that column child to what is
# now just an element, and not a block.
return None
new_delta_type = new_delta.WhichOneof("type")
if new_delta_type == "new_element":
return new_delta
if new_delta_type == "add_block":
return new_delta
if new_delta_type == "add_rows":
import streamlit.elements.legacy_data_frame as data_frame
# We should make data_frame.add_rows *not* mutate any of the
# inputs. In the meantime, we have to deepcopy the input that will be
# mutated.
composed_delta = copy.deepcopy(old_delta)
data_frame.add_rows(composed_delta,
new_delta,
name=new_delta.add_rows.name)
return composed_delta
# We deliberately don't handle the "arrow_add_rows" delta type. With Arrow,
# `add_rows` is a frontend-only operation.
return None
def _enqueue_new_element_delta(self, marshall_element):
"""Fake enqueue new element delta.
The real DeltaGenerator method actually enqueues the deltas but
to test _with_element we just need this method to exist. The
real enqueue_new_element_delta will be tested later on.
"""
delta = Delta()
marshall_element(delta.new_element)
return delta
def _get_data_frame(delta: Delta, name: Optional[str] = None) -> DataFrame:
"""Extract the dataframe protobuf from a delta protobuf."""
delta_type = delta.WhichOneof("type")
if delta_type == "new_element":
element_type = delta.new_element.WhichOneof("type")
# Some element types don't support named datasets.
if name and element_type in ("data_frame", "table", "chart"):
raise ValueError("Dataset names not supported for st.%s" %
element_type)
if element_type in "data_frame":
return delta.new_element.data_frame
elif element_type in "table":
return delta.new_element.table
elif element_type == "chart":
return delta.new_element.chart.data
elif element_type == "vega_lite_chart":
chart_proto = delta.new_element.vega_lite_chart
if name:
return _get_or_create_dataset(chart_proto.datasets, name)
elif len(chart_proto.datasets) == 1:
# Support the case where the dataset name was randomly given by
# the charting library (e.g. Altair) and the user has no
# knowledge of it.
return chart_proto.datasets[0].data
else:
return chart_proto.data
# TODO: Support DeckGL. Need to figure out how to handle layer indices
# first.
elif delta_type == "add_rows":
if delta.add_rows.has_name and name != delta.add_rows.name:
raise ValueError('No dataset found with name "%s".' % name)
return delta.add_rows.data
else:
raise ValueError("Cannot extract DataFrame from %s." % delta_type)
def _enqueue(self, delta_type, element_proto):
delta = Delta()
el_proto = getattr(delta.new_element, delta_type)
el_proto.CopyFrom(element_proto)
return delta
def test_get_data_frame(self):
"""Test streamlit.data_frame_proto._get_data_frame."""
# Test delta not new_element or add_rows
with pytest.raises(ValueError) as e:
delta = Delta()
data_frame_proto._get_data_frame(delta)
err_msg = "Cannot extract DataFrame from None."
self.assertEqual(err_msg, str(e.value))
# Generic Data
aa = AnyArray()
aa.int64s.data.extend([1, 2, 3])
# Delta DataFrame
delta_df = Delta()
delta_df.new_element.data_frame.data.cols.extend([aa])
df = data_frame_proto._get_data_frame(delta_df)
self.assertEqual(df, delta_df.new_element.data_frame)
# Delta Table
delta_table = Delta()
delta_table.new_element.table.data.cols.extend([aa])
df = data_frame_proto._get_data_frame(delta_table)
self.assertEqual(df, delta_table.new_element.table)
# Vega-Lite Chart
delta_vega = Delta()
delta_vega.new_element.vega_lite_chart.data.data.cols.extend([aa])
df = data_frame_proto._get_data_frame(delta_vega)
self.assertEqual(df, delta_vega.new_element.vega_lite_chart.data)
# Vega-Lite Chart w/ named dataset
delta_vega_dataset = Delta()
ds1 = NamedDataSet()
ds1.name = "dataset 1"
ds1.has_name = True
ds1.data.data.cols.extend([aa])
delta_vega_dataset.new_element.vega_lite_chart.datasets.extend([ds1])
df = data_frame_proto._get_data_frame(delta_vega_dataset, "dataset 1")
self.assertEqual(
df, delta_vega_dataset.new_element.vega_lite_chart.datasets[0].data
)
# Vega-Lite Chart w/ unnamed dataset
delta_vega_unnamed_dataset = Delta()
ds2 = NamedDataSet()
ds2.has_name = False
ds2.data.data.cols.extend([aa])
delta_vega_unnamed_dataset.new_element.vega_lite_chart.datasets.extend([ds2])
df = data_frame_proto._get_data_frame(delta_vega_unnamed_dataset)
self.assertEqual(
df, delta_vega_unnamed_dataset.new_element.vega_lite_chart.datasets[0].data
)
# add_rows w/ name
delta_add_rows = Delta()
delta_add_rows.add_rows.name = "named dataset"
delta_add_rows.add_rows.has_name = True
delta_add_rows.add_rows.data.data.cols.extend([aa])
df = data_frame_proto._get_data_frame(delta_add_rows, "named dataset")
self.assertEqual(df, delta_add_rows.add_rows.data)
# add_rows w/out name
with pytest.raises(ValueError) as e:
delta_add_rows_noname = Delta()
delta_add_rows_noname.add_rows.name = "named dataset"
delta_add_rows_noname.add_rows.has_name = True
delta_add_rows_noname.add_rows.data.data.cols.extend([aa])
df = data_frame_proto._get_data_frame(delta_add_rows_noname)
err_msg = 'No dataset found with name "None".'
self.assertEqual(err_msg, str(e.value))
def test_add_rows(self):
"""Test streamlit.data_frame_proto._add_rows."""
# Generic Data
aa = AnyArray()
aa.int64s.data.extend([1, 2])
cell_style = CellStyle()
cell_style.css.extend([_css_style("color", "black")])
style = CellStyleArray()
style.styles.extend([cell_style])
# Delta DataFrame
dt1 = Delta()
dt1.new_element.data_frame.data.cols.extend([aa])
dt1.new_element.data_frame.index.plain_index.data.int64s.data.extend([3, 4])
dt1.new_element.data_frame.columns.plain_index.data.int64s.data.extend([5, 6])
dt1.new_element.data_frame.style.cols.extend([style])
dt2 = Delta()
dt2.new_element.data_frame.data.cols.extend([aa])
dt2.new_element.data_frame.index.plain_index.data.int64s.data.extend([3, 4])
dt2.new_element.data_frame.columns.plain_index.data.int64s.data.extend([5, 6])
dt2.new_element.data_frame.style.cols.extend([style])
combined = Delta()
aa_combined = AnyArray()
aa_combined.int64s.data.extend([1, 2, 1, 2])
style_combined = CellStyleArray()
style_combined.styles.extend([cell_style, cell_style])
combined.new_element.data_frame.data.cols.extend([aa_combined])
row_index = combined.new_element.data_frame.index.plain_index
row_index.data.int64s.data.extend([3, 4, 3, 4])
col_index = combined.new_element.data_frame.columns.plain_index
col_index.data.int64s.data.extend([5, 6])
combined.new_element.data_frame.style.cols.extend([style_combined])
# Test both not empty
data_frame_proto.add_rows(dt1, dt2)
self.assertEqual(dt1, combined)
# Test one empty
dt0 = Delta()
dt0.new_element.data_frame.data.cols.extend([])
data_frame_proto.add_rows(dt0, dt1)
self.assertEqual(str(dt0), str(dt1))
# Test both empty
empty0 = Delta()
empty0.new_element.data_frame.data.cols.extend([])
empty1 = Delta()
empty1.new_element.data_frame.data.cols.extend([])
data_frame_proto.add_rows(empty0, empty1)
self.assertEqual(str(empty0), str(empty1))
# Test different data shapes
diff0 = Delta()
diff0.new_element.data_frame.data.cols.extend([aa, aa])
diff1 = Delta()
diff1.new_element.data_frame.data.cols.extend([aa])
with pytest.raises(ValueError) as e:
data_frame_proto.add_rows(diff0, diff1)
err_msg = "Dataframes have incompatible shapes"
self.assertEqual(err_msg, str(e.value))
def test_get_data_frame(self):
"""Test streamlit.data_frame_proto._get_data_frame."""
# Test delta not new_element or add_rows
with pytest.raises(ValueError) as e:
delta = Delta()
data_frame_proto._get_data_frame(delta)
err_msg = 'Cannot extract DataFrame from None.'
self.assertEqual(err_msg, str(e.value))
# Test delta = new_element, a name is used and type is chart, df, table
with pytest.raises(ValueError) as e:
delta = Delta()
# TODO(armando): test df and table
delta.new_element.chart.type = 'some chart'
data_frame_proto._get_data_frame(delta, name='some name')
err_msg = 'Dataset names not supported for st.chart'
self.assertEqual(err_msg, str(e.value))
# Generic Data
aa = AnyArray()
aa.int64s.data.extend([1, 2, 3])
# Delta DataFrame
delta_df = Delta()
delta_df.new_element.data_frame.data.cols.extend([aa])
df = data_frame_proto._get_data_frame(delta_df)
self.assertEqual(df, delta_df.new_element.data_frame)
# Delta Table
delta_table = Delta()
delta_table.new_element.table.data.cols.extend([aa])
df = data_frame_proto._get_data_frame(delta_table)
self.assertEqual(df, delta_table.new_element.table)
# Delta Chart
delta_chart = Delta()
delta_chart.new_element.chart.data.data.cols.extend([aa])
df = data_frame_proto._get_data_frame(delta_chart)
self.assertEqual(df, delta_chart.new_element.chart.data)
# Vega-Lite Chart
delta_vega = Delta()
delta_vega.new_element.vega_lite_chart.data.data.cols.extend([aa])
df = data_frame_proto._get_data_frame(delta_vega)
self.assertEqual(df, delta_vega.new_element.vega_lite_chart.data)
# Vega-Lite Chart w/ named dataset
delta_vega_dataset = Delta()
ds1 = NamedDataSet()
ds1.name = 'dataset 1'
ds1.has_name = True
ds1.data.data.cols.extend([aa])
delta_vega_dataset.new_element.vega_lite_chart.datasets.extend([ds1])
df = data_frame_proto._get_data_frame(delta_vega_dataset, 'dataset 1')
self.assertEqual(
df,
delta_vega_dataset.new_element.vega_lite_chart.datasets[0].data)
# Vega-Lite Chart w/ unnamed dataset
delta_vega_unnamed_dataset = Delta()
ds2 = NamedDataSet()
ds2.has_name = False
ds2.data.data.cols.extend([aa])
delta_vega_unnamed_dataset.new_element.vega_lite_chart.datasets.extend(
[ds2])
df = data_frame_proto._get_data_frame(delta_vega_unnamed_dataset)
self.assertEqual(
df, delta_vega_unnamed_dataset.new_element.vega_lite_chart.
datasets[0].data)
# add_rows w/ name
delta_add_rows = Delta()
delta_add_rows.add_rows.name = 'named dataset'
delta_add_rows.add_rows.has_name = True
delta_add_rows.add_rows.data.data.cols.extend([aa])
df = data_frame_proto._get_data_frame(delta_add_rows, 'named dataset')
self.assertEqual(df, delta_add_rows.add_rows.data)
# add_rows w/out name
with pytest.raises(ValueError) as e:
delta_add_rows_noname = Delta()
delta_add_rows_noname.add_rows.name = 'named dataset'
delta_add_rows_noname.add_rows.has_name = True
delta_add_rows_noname.add_rows.data.data.cols.extend([aa])
df = data_frame_proto._get_data_frame(delta_add_rows_noname)
err_msg = 'No dataset found with name "None".'
self.assertEqual(err_msg, str(e.value))
