def test_clean_column_valid(self):
context = RenderContext(
None, TableShape(3, [
Column('A', ColumnType.NUMBER()),
]), None, None)
result = clean_value(ParamDType.Column(), 'A', context)
self.assertEqual(result, 'A')
def test_clean_column_missing_becomes_empty_string(self):
context = RenderContext(
None, TableShape(3, [
Column('A', ColumnType.NUMBER()),
]), None, None)
result = clean_value(ParamDType.Column(), 'B', context)
self.assertEqual(result, '')
def test_clean_multichartseries_non_number_is_prompting_error(self):
context = RenderContext(
None,
TableShape(3, [
Column('A', ColumnType.TEXT()),
Column('B', ColumnType.DATETIME()),
]), None, None)
value = [
{
'column': 'A',
'color': '#aaaaaa'
},
{
'column': 'B',
'color': '#cccccc'
},
]
with self.assertRaises(PromptingError) as cm:
clean_value(ParamDType.Multichartseries(), value, context)
self.assertEqual(cm.exception.errors, [
PromptingError.WrongColumnType(['A'], 'text', frozenset({'number'
})),
PromptingError.WrongColumnType(['B'], 'datetime',
frozenset({'number'})),
])
def test_clean_multicolumn_sort_in_table_order(self):
context = RenderContext(
None,
TableShape(3, [
Column('B', ColumnType.NUMBER()),
Column('A', ColumnType.NUMBER()),
]), None, None)
result = clean_value(ParamDType.Multicolumn(), ['A', 'B'], context)
self.assertEqual(result, ['B', 'A'])
def test_clean_multicolumn_missing_is_removed(self):
context = RenderContext(
None,
TableShape(3, [
Column('A', ColumnType.NUMBER()),
Column('B', ColumnType.NUMBER()),
]), None, None)
result = clean_value(ParamDType.Multicolumn(), ['A', 'X', 'B'],
context)
self.assertEqual(result, ['A', 'B'])
def test_clean_column_missing_becomes_empty_string(self):
context = RenderContext(
None, TableShape(3, [
Column('A', ColumnType.NUMBER),
]), None, None)
schema = ParamDType.Dict({
'column': ParamDType.Column(),
})
value = {'column': 'B'}
result = clean_value(schema, value, context)
self.assertEqual(result, {'column': ''})
def test_clean_multicolumn_missing_is_removed(self):
context = RenderContext(
None,
TableShape(3, [
Column('A', ColumnType.NUMBER),
Column('B', ColumnType.NUMBER),
]), None, None)
schema = ParamDType.Dict({
'columns': ParamDType.Multicolumn(),
})
value = {'columns': 'A,X,B'}
result = clean_value(schema, value, context)
self.assertEqual(result, {'columns': 'A,B'})
def test_clean_column_prompting_error_convert_to_text(self):
# TODO make this _automatic_ instead of quick-fix?
# Consider Regex. We probably want to pass the module a text Series
# _separately_ from the input DataFrame. That way Regex can output
# a new Text column but preserve its input column's data type.
#
# ... but for now: prompt for a Quick Fix.
context = RenderContext(None, None, TableShape(3, [
Column('A', ColumnType.NUMBER()),
]), None, None)
with self.assertRaises(PromptingError) as cm:
clean_value(ParamDType.Column(column_types=frozenset({'text'})),
'A', context)
self.assertEqual(cm.exception.errors, [
PromptingError.WrongColumnType(['A'], 'number',
frozenset({'text'})),
])
def test_clean_tabs_happy_path(self):
tab1_output = ProcessResult(pd.DataFrame({'A': [1, 2]}))
workflow = Workflow.create_and_init()
tab1 = workflow.tabs.first()
wfm = tab1.wf_modules.create(
order=0, last_relevant_delta_id=workflow.last_delta_id)
wfm.cache_render_result(workflow.last_delta_id, tab1_output)
context = RenderContext(
workflow.id, None, {
tab1.slug: StepResultShape('ok', tab1_output.table_shape),
}, None)
result = clean_value(ParamDType.Multitab(), [tab1.slug], context)
self.assertEqual(result[0].slug, tab1.slug)
self.assertEqual(result[0].name, tab1.name)
self.assertEqual(result[0].columns, {
'A': RenderColumn('A', 'number', '{:,}'),
})
assert_frame_equal(result[0].dataframe, pd.DataFrame({'A': [1, 2]}))
def test_clean_tabs_tab_error_raises_cycle(self):
context = RenderContext(None, None, {'tab-1': None}, None)
schema = ParamDType.Dict({'tabs': ParamDType.Multitab()})
with self.assertRaises(TabCycleError):
clean_value(schema, {'tabs': ['tab-1']}, context)