def test_set_nonsettable_objects(nonsettable_objects_data):
"""
Test that errors trying to set attributes in ColEdit are handled properly.
Unit regression test for issues #6727 and #6728 .
"""
for test_obj, expected_obj, keys in nonsettable_objects_data:
col_model = CollectionsModel(None, test_obj)
indicies = [col_model.get_index_from_key(key) for key in keys]
for idx in indicies:
assert not col_model.set_value(idx, "2")
# Due to numpy's deliberate breakage of __eq__ comparison
assert all([key == "_typ" or
(getattr(col_model.get_data().__obj__, key)
== getattr(expected_obj, key)) for key in keys])
def test_notimplementederror_multiindex():
"""
Test that the NotImplementedError when scrolling a MultiIndex is handled.
Regression test for spyder-ide/spyder#6284.
"""
time_deltas = [pandas.Timedelta(minutes=minute)
for minute in range(5, 35, 5)]
time_delta_multiindex = pandas.MultiIndex.from_product([[0, 1, 2, 3, 4],
time_deltas])
col_model = CollectionsModel(None, time_delta_multiindex)
assert col_model.rowCount() == col_model.rows_loaded == ROWS_TO_LOAD
assert col_model.columnCount() == 5
col_model.fetchMore()
assert col_model.rowCount() == 2 * ROWS_TO_LOAD
for _ in range(3):
col_model.fetchMore()
assert col_model.rowCount() == 5 * ROWS_TO_LOAD
def test_collectionsmodel_with_two_ints():
coll = {'x': 1, 'y': 2}
cm = CollectionsModel(None, coll)
assert cm.rowCount() == 2
assert cm.columnCount() == 4
# dict is unordered, so first row might be x or y
assert data(cm, 0, 0) in {'x', 'y'}
if data(cm, 0, 0) == 'x':
row_with_x = 0
row_with_y = 1
else:
row_with_x = 1
row_with_y = 0
assert data(cm, row_with_x, 1) == 'int'
assert data(cm, row_with_x, 2) == '1'
assert data(cm, row_with_x, 3) == '1'
assert data(cm, row_with_y, 0) == 'y'
assert data(cm, row_with_y, 1) == 'int'
assert data(cm, row_with_y, 2) == '1'
assert data(cm, row_with_y, 3) == '2'
def test_collectionsmodel_with_two_ints():
coll = {'x': 1, 'y': 2}
cm = CollectionsModel(None, coll)
assert cm.rowCount() == 2
assert cm.columnCount() == 4
# dict is unordered, so first row might be x or y
assert data(cm, 0, 0) in {'x', 'y'}
if data(cm, 0, 0) == 'x':
row_with_x = 0
row_with_y = 1
else:
row_with_x = 1
row_with_y = 0
assert data(cm, row_with_x, 1) == 'int'
assert data(cm, row_with_x, 2) == '1'
assert data(cm, row_with_x, 3) == '1'
assert data(cm, row_with_y, 0) == 'y'
assert data(cm, row_with_y, 1) == 'int'
assert data(cm, row_with_y, 2) == '1'
assert data(cm, row_with_y, 3) == '2'
def test_collectionsmodel_with_index():
# Regression test for issue #3380, modified for #3758
for rng_name, rng in generate_pandas_indexes().items():
coll = {'rng': rng}
cm = CollectionsModel(None, coll)
assert data(cm, 0, 0) == 'rng'
assert data(cm, 0, 1) == rng_name
assert data(cm, 0, 2) == '(20,)' or data(cm, 0, 2) == '(20L,)'
try:
assert data(cm, 0, 3) == rng._summary()
except AttributeError:
assert data(cm, 0, 3) == rng.summary()
def test_notimplementederror_multiindex():
"""
Test that the NotImplementedError when scrolling a MultiIndex is handled.
Regression test for issue #6284 .
"""
time_deltas = [pandas.Timedelta(minutes=minute)
for minute in range(5, 35, 5)]
time_delta_multiindex = pandas.MultiIndex.from_product([[0, 1, 2, 3, 4],
time_deltas])
col_model = CollectionsModel(None, time_delta_multiindex)
assert col_model.rowCount() == col_model.rows_loaded == ROWS_TO_LOAD
assert col_model.columnCount() == 4
col_model.fetchMore()
assert col_model.rowCount() == 2 * ROWS_TO_LOAD
for _ in range(3):
col_model.fetchMore()
assert col_model.rowCount() == 5 * ROWS_TO_LOAD
def test_sort_collectionsmodel_with_many_rows():
coll = list(range(2*LARGE_NROWS))
cm = CollectionsModel(None, coll)
assert cm.rowCount() == cm.rows_loaded == ROWS_TO_LOAD
assert cm.columnCount() == 5
cm.sort(1) # This was causing an issue (#5232)
cm.fetchMore()
assert cm.rowCount() == 2 * ROWS_TO_LOAD
for _ in range(3):
cm.fetchMore()
assert cm.rowCount() == len(coll)
def test_sort_collectionsmodel():
var_list1 = [0, 1, 2]
var_list2 = [3, 4, 5, 6]
var_dataframe1 = pandas.DataFrame([[1, 2, 3], [20, 30, 40], [2, 2, 2]])
var_dataframe2 = pandas.DataFrame([[1, 2, 3], [20, 30, 40]])
var_series1 = pandas.Series(var_list1)
var_series2 = pandas.Series(var_list2)
coll = [1, 3, 2]
cm = CollectionsModel(None, coll)
assert cm.rowCount() == 3
assert cm.columnCount() == 5
cm.sort(0) # sort by index
assert data_table(cm, 3, 4) == [[0, 1, 2],
['int', 'int', 'int'],
[1, 1, 1],
['1', '3', '2']]
cm.sort(3) # sort by value
assert data_table(cm, 3, 4) == [[0, 2, 1],
['int', 'int', 'int'],
[1, 1, 1],
['1', '2', '3']]
coll = [1, var_list1, var_list2, var_dataframe1, var_dataframe2,
var_series1, var_series2]
cm = CollectionsModel(None, coll)
assert cm.rowCount() == 7
assert cm.columnCount() == 5
cm.sort(1) # sort by type
assert data_table(cm, 7, 4) == [
[3, 4, 5, 6, 0, 1, 2],
['DataFrame', 'DataFrame', 'Series', 'Series', 'int', 'list', 'list'],
['(3, 3)', '(2, 3)', '(3,)', '(4,)', 1, 3, 4],
['Column names: 0, 1, 2',
'Column names: 0, 1, 2',
'Series object of pandas.core.series module',
'Series object of pandas.core.series module',
'1',
'[0, 1, 2]',
'[3, 4, 5, 6]']]
cm.sort(2) # sort by size
assert data_table(cm, 7, 4) == [
[3, 4, 5, 6, 0, 1, 2],
['DataFrame', 'DataFrame', 'Series', 'Series', 'int', 'list', 'list'],
['(2, 3)', '(3,)', '(3, 3)', '(4,)', 1, 3, 4],
['Column names: 0, 1, 2',
'Column names: 0, 1, 2',
'Series object of pandas.core.series module',
'Series object of pandas.core.series module',
'1',
'[0, 1, 2]',
'[3, 4, 5, 6]']] or data_table(cm, 7, 4) == [
[0, 1, 2, 4, 5, 3, 6],
[u'int', u'list', u'list', u'DataFrame', u'Series', u'DataFrame',
u'Series'],
[1, 3, 4, u'(2, 3)', u'(3,)', u'(3, 3)', u'(4,)'],
['1',
'[0, 1, 2]',
'[3, 4, 5, 6]',
'Column names: 0, 1, 2',
'Series object of pandas.core.series module',
'Column names: 0, 1, 2',
'Series object of pandas.core.series module',
]]
def test_sort_collectionsmodel():
coll = [1, 3, 2]
cm = CollectionsModel(None, coll)
assert cm.rowCount() == 3
assert cm.columnCount() == 4
cm.sort(0) # sort by index
assert data_table(cm, 3, 4) == [['0', '1', '2'], ['int', 'int', 'int'],
['1', '1', '1'], ['1', '3', '2']]
cm.sort(3) # sort by value
assert data_table(cm, 3, 4) == [['0', '2', '1'], ['int', 'int', 'int'],
['1', '1', '1'], ['1', '2', '3']]
coll = [[1, 2], 3]
cm = CollectionsModel(None, coll)
assert cm.rowCount() == 2
assert cm.columnCount() == 4
cm.sort(1) # sort by type
assert data_table(cm, 2, 4) == [['1', '0'], ['int', 'list'], ['1', '2'],
['3', '[1, 2]']]
cm.sort(2) # sort by size
assert data_table(cm, 2, 4) == [['1', '0'], ['int', 'list'], ['1', '2'],
['3', '[1, 2]']]
def test_sort_collectionsmodel_with_many_rows():
coll = list(range(2*LARGE_NROWS))
cm = CollectionsModel(None, coll)
assert cm.rowCount() == cm.rows_loaded == ROWS_TO_LOAD
assert cm.columnCount() == 4
cm.sort(1) # This was causing an issue (#5232)
cm.fetchMore()
assert cm.rowCount() == 2 * ROWS_TO_LOAD
for _ in range(3):
cm.fetchMore()
assert cm.rowCount() == len(coll)
def test_sort_collectionsmodel():
coll = [1, 3, 2]
cm = CollectionsModel(None, coll)
assert cm.rowCount() == 3
assert cm.columnCount() == 4
cm.sort(0) # sort by index
assert data_table(cm, 3, 4) == [['0', '1', '2'],
['int', 'int', 'int'],
['1', '1', '1'],
['1', '3', '2']]
cm.sort(3) # sort by value
assert data_table(cm, 3, 4) == [['0', '2', '1'],
['int', 'int', 'int'],
['1', '1', '1'],
['1', '2', '3']]
coll = [[1, 2], 3]
cm = CollectionsModel(None, coll)
assert cm.rowCount() == 2
assert cm.columnCount() == 4
cm.sort(1) # sort by type
assert data_table(cm, 2, 4) == [['1', '0'],
['int', 'list'],
['1', '2'],
['3', '[1, 2]']]
cm.sort(2) # sort by size
assert data_table(cm, 2, 4) == [['1', '0'],
['int', 'list'],
['1', '2'],
['3', '[1, 2]']]