def test_tabulator_stream_series_paginated_follow(document, comm):
df = makeMixedDataFrame()
table = Tabulator(df, pagination='remote', page_size=2)
model = table.get_root(document, comm)
stream_value = pd.Series({
'A': 5,
'B': 1,
'C': 'foo6',
'D': dt.datetime(2009, 1, 8)
})
table.stream(stream_value, follow=True)
assert table.page == 3
assert len(table.value) == 6
expected = {
'index':
np.array([4, 5]),
'A':
np.array([4, 5]),
'B':
np.array([0, 1]),
'C':
np.array(['foo5', 'foo6']),
'D':
np.array(
['2009-01-07T00:00:00.000000000', '2009-01-08T00:00:00.000000000'],
dtype='datetime64[ns]').astype(np.int64) / 10e5
}
for col, values in model.source.data.items():
np.testing.assert_array_equal(values, expected[col])
def test_tabulator_empty_table(document, comm):
value_df = makeMixedDataFrame()
empty_df = pd.DataFrame([], columns=value_df.columns)
table = Tabulator(empty_df)
table.get_root(document, comm)
assert table.value.shape == empty_df.shape
table.stream(value_df, follow=True)
assert table.value.shape == value_df.shape
def test_tabulator_stream_dataframe_selectable_rows(document, comm):
df = makeMixedDataFrame()
table = Tabulator(df,
selectable_rows=lambda df: list(range(0, len(df), 2)))
model = table.get_root(document, comm)
assert model.selectable_rows == [0, 2, 4]
stream_value = pd.DataFrame({
'A': [5, 6],
'B': [1, 0],
'C': ['foo6', 'foo7'],
'D': [dt.datetime(2009, 1, 8),
dt.datetime(2009, 1, 9)]
})
table.stream(stream_value)
print(len(table._processed))
assert model.selectable_rows == [0, 2, 4, 6]
def test_tabulator_stream_dataframe(document, comm):
df = makeMixedDataFrame()
table = Tabulator(df)
model = table.get_root(document, comm)
stream_value = pd.DataFrame({
'A': [5, 6],
'B': [1, 0],
'C': ['foo6', 'foo7'],
'D': [dt.datetime(2009, 1, 8),
dt.datetime(2009, 1, 9)]
})
table.stream(stream_value)
assert len(table.value) == 7
expected = {
'index':
np.array([0, 1, 2, 3, 4, 5, 6]),
'A':
np.array([0, 1, 2, 3, 4, 5, 6]),
'B':
np.array([0, 1, 0, 1, 0, 1, 0]),
'C':
np.array(['foo1', 'foo2', 'foo3', 'foo4', 'foo5', 'foo6', 'foo7']),
'D':
np.array([
'2009-01-01T00:00:00.000000000', '2009-01-02T00:00:00.000000000',
'2009-01-05T00:00:00.000000000', '2009-01-06T00:00:00.000000000',
'2009-01-07T00:00:00.000000000', '2009-01-08T00:00:00.000000000',
'2009-01-09T00:00:00.000000000'
],
dtype='datetime64[ns]').astype(np.int64) / 10e5
}
for col, values in model.source.data.items():
np.testing.assert_array_equal(values, expected[col])
def test_tabulator_stream_df_rollover(document, comm):
df = makeMixedDataFrame()
table = Tabulator(df)
model = table.get_root(document, comm)
stream_value = pd.Series({
'A': 5,
'B': 1,
'C': 'foo6',
'D': dt.datetime(2009, 1, 8)
}).to_frame().T
table.stream(stream_value, rollover=5)
assert len(table.value) == 5
expected = {
'index':
np.array([1, 2, 3, 4, 5]),
'A':
np.array([1, 2, 3, 4, 5]),
'B':
np.array([1, 0, 1, 0, 1]),
'C':
np.array(['foo2', 'foo3', 'foo4', 'foo5', 'foo6']),
'D':
np.array([
'2009-01-02T00:00:00.000000000', '2009-01-05T00:00:00.000000000',
'2009-01-06T00:00:00.000000000', '2009-01-07T00:00:00.000000000',
'2009-01-08T00:00:00.000000000'
],
dtype='datetime64[ns]').astype(np.int64) / 10e5
}
for col, values in model.source.data.items():
np.testing.assert_array_equal(values, expected[col])