def test_simple_add_rows_with_clear_queue(self):
"""Test plain old add_rows after clearing the queue."""
all_methods = self._get_unnamed_data_methods() + self._get_named_data_methods()
for method in all_methods:
# Create a new data-carrying element (e.g. st.dataframe)
el = method(DATAFRAME)
# Make sure it has 2 rows in it.
df_proto = data_frame._get_data_frame(self.get_delta_from_queue())
num_rows = len(df_proto.data.cols[0].int64s.data)
self.assertEqual(num_rows, 2)
# This is what we're testing:
self.report_queue.clear()
el.add_rows(NEW_ROWS)
# Make sure there are 3 rows in the delta that got appended.
ar = self.get_delta_from_queue().add_rows
num_rows = len(ar.data.data.cols[0].int64s.data)
self.assertEqual(num_rows, 3)
# Clear the queue so the next loop is like a brand new test.
get_report_ctx().reset()
self.report_queue.clear()
def test_no_index_no_data_add_rows(self):
"""Test plain old add_rows."""
all_methods = self._get_unnamed_data_methods()
for method in all_methods:
# Create a new data-carrying element (e.g. st.dataframe)
el = method(None)
data_frame._get_data_frame(self.get_delta_from_queue())
# This is what we're testing:
el.add_rows(DATAFRAME)
# Make sure there are 2 rows in it now.
df_proto = data_frame._get_data_frame(self.get_delta_from_queue())
num_rows = len(df_proto.data.cols[0].int64s.data)
self.assertEqual(num_rows, 2)
# Clear the queue so the next loop is like a brand new test.
get_report_ctx().reset()
self.report_queue.clear()
def test_named_add_rows(self):
"""Test add_rows with a named dataset."""
for method in self._get_named_data_methods():
# Create a new data-carrying element (e.g. st.dataframe)
el = method(DATAFRAME)
# Make sure it has 2 rows in it.
df_proto = data_frame._get_data_frame(self.get_delta_from_queue())
num_rows = len(df_proto.data.cols[0].int64s.data)
self.assertEqual(num_rows, 2)
# This is what we're testing:
el.add_rows(mydata1=NEW_ROWS)
# Make sure there are 5 rows in it now.
df_proto = data_frame._get_data_frame(self.get_delta_from_queue())
num_rows = len(df_proto.data.cols[0].int64s.data)
self.assertEqual(num_rows, 5)
# Clear the queue so the next loop is like a brand new test.
get_report_ctx().reset()
self.report_queue.clear()
def test_deltas_that_melt_dataframes(self):
deltas = self._get_deltas_that_melt_dataframes()
for delta in deltas:
el = delta(DATAFRAME)
el.add_rows(NEW_ROWS)
# It is important that we test after this second call to add_rows
# to cover the logic to compute the index.
# See:
# https://github.com/streamlit/streamlit/issues/748
el.add_rows(NEW_ROWS)
df_proto = data_frame._get_data_frame(self.get_delta_from_queue())
num_rows = len(df_proto.data.cols[0].int64s.data)
self.assertEqual(num_rows, 16)
self.assertEqual(
[0, 1, 0, 1, 2, 3, 4, 2, 3, 4, 5, 6, 7, 5, 6, 7],
df_proto.data.cols[0].int64s.data,
)
def test_get_data_frame(self):
"""Test streamlit.data_frame._get_data_frame."""
# Test delta not new_element or add_rows
with pytest.raises(ValueError) as e:
delta = Delta()
data_frame._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._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._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._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._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._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._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._get_data_frame(delta_add_rows_noname)
err_msg = 'No dataset found with name "None".'
self.assertEqual(err_msg, str(e.value))