def test_clean_column_prompting_error_convert_to_number(self):
input_shape = TableShape(3, [Column('A', ColumnType.TEXT())])
with self.assertRaises(PromptingError) as cm:
clean_value(ParamDType.Column(column_types=frozenset({'number'})),
'A', input_shape)
self.assertEqual(cm.exception.errors, [
PromptingError.WrongColumnType(['A'], 'text', frozenset({'number'
})),
])
def test_clean_column_prompting_error_convert_to_number(self):
input_shape = TableMetadata(3, [Column("A", ColumnType.Text())])
with self.assertRaises(PromptingError) as cm:
clean_value(ParamDType.Column(column_types=frozenset({"number"})),
"A", input_shape)
self.assertEqual(
cm.exception.errors,
[
PromptingError.WrongColumnType(["A"], "text",
frozenset({"number"}))
],
)
def test_clean_multicolumn_valid(self):
input_shape = TableShape(3, [
Column("A", ColumnType.NUMBER()),
Column("B", ColumnType.NUMBER())
])
result = clean_value(ParamDType.Multicolumn(), ["A", "B"], input_shape)
self.assertEqual(result, ["A", "B"])
def test_clean_multicolumn_sort_in_table_order(self):
input_shape = TableMetadata(3, [
Column("B", ColumnType.Number()),
Column("A", ColumnType.Number())
])
result = clean_value(ParamDType.Multicolumn(), ["A", "B"], input_shape)
self.assertEqual(result, ["B", "A"])
def test_clean_float_with_int_value(self):
# ParamDType.Float can have `int` values (because values come from
# json.parse(), which only gives Numbers so can give "3" instead of
# "3.0". We want to pass that as `float` in the `params` dict.
result = clean_value(ParamDType.Float(), 3, None)
self.assertEqual(result, 3.0)
self.assertIsInstance(result, float)
def test_clean_multicolumn_sort_in_table_order(self):
input_shape = TableShape(3, [
Column('B', ColumnType.NUMBER()),
Column('A', ColumnType.NUMBER()),
])
result = clean_value(ParamDType.Multicolumn(), ['A', 'B'], input_shape)
self.assertEqual(result, ['B', 'A'])
def test_clean_column_happy_path(self):
input_shape = TableMetadata(3, [Column("A", ColumnType.Number())])
self.assertEqual(
clean_value(ParamDType.Column(column_types=frozenset({"number"})),
"A", input_shape),
"A",
)
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.
input_shape = TableMetadata(3, [Column("A", ColumnType.Number())])
with self.assertRaises(PromptingError) as cm:
clean_value(ParamDType.Column(column_types=frozenset({"text"})),
"A", input_shape)
self.assertEqual(
cm.exception.errors,
[PromptingError.WrongColumnType(["A"], None, frozenset({"text"}))],
)
def test_clean_multicolumn_missing_is_removed(self):
input_shape = TableShape(3, [
Column('A', ColumnType.NUMBER()),
Column('B', ColumnType.NUMBER()),
])
result = clean_value(ParamDType.Multicolumn(), ['A', 'X', 'B'],
input_shape)
self.assertEqual(result, ['A', 'B'])
def test_clean_multicolumn_valid(self):
input_shape = TableMetadata(3, [
Column("A", ColumnType.Number()),
Column("B", ColumnType.Number())
])
result = clean_value(ParamSchema.Multicolumn(), ["A", "B"],
input_shape)
self.assertEqual(result, ["A", "B"])
def test_clean_multicolumn_missing_is_removed(self):
input_shape = TableMetadata(3, [
Column("A", ColumnType.Number()),
Column("B", ColumnType.Number())
])
result = clean_value(ParamDType.Multicolumn(), ["A", "X", "B"],
input_shape)
self.assertEqual(result, ["A", "B"])
def test_clean_multicolumn_prompting_error_convert_to_text(self):
# TODO make this _automatic_ instead of quick-fix?
# ... but for now: prompt for a Quick Fix.
input_shape = TableShape(3, [
Column('A', ColumnType.NUMBER()),
Column('B', ColumnType.DATETIME()),
Column('C', ColumnType.TEXT()),
])
with self.assertRaises(PromptingError) as cm:
schema = ParamDType.Multicolumn(column_types=frozenset({'text'}))
clean_value(schema, 'A,B', input_shape)
self.assertEqual(cm.exception.errors, [
PromptingError.WrongColumnType(['A'], 'number', frozenset({'text'
})),
PromptingError.WrongColumnType(['B'], 'datetime',
frozenset({'text'})),
])
def test_clean_normal_dict(self):
input_shape = TableShape(3, [Column("A", ColumnType.NUMBER())])
schema = ParamDType.Dict(
{"str": ParamDType.String(), "int": ParamDType.Integer()}
)
value = {"str": "foo", "int": 3}
expected = dict(value) # no-op
result = clean_value(schema, value, input_shape)
self.assertEqual(result, expected)
def test_clean_multicolumn_prompting_error_convert_to_text(self):
# TODO make this _automatic_ instead of quick-fix?
# ... but for now: prompt for a Quick Fix.
input_shape = TableShape(
3,
[
Column("A", ColumnType.NUMBER()),
Column("B", ColumnType.DATETIME()),
Column("C", ColumnType.TEXT()),
],
)
with self.assertRaises(PromptingError) as cm:
schema = ParamDType.Multicolumn(column_types=frozenset({"text"}))
clean_value(schema, "A,B", input_shape)
self.assertEqual(
cm.exception.errors,
[PromptingError.WrongColumnType(["A", "B"], None, frozenset({"text"}))],
)
def test_clean_normal_dict(self):
input_shape = TableShape(3, [Column('A', ColumnType.NUMBER())])
schema = ParamDType.Dict({
'str': ParamDType.String(),
'int': ParamDType.Integer(),
})
value = {'str': 'foo', 'int': 3}
expected = dict(value) # no-op
result = clean_value(schema, value, input_shape)
self.assertEqual(result, expected)
def test_dict_prompting_error(self):
input_shape = TableShape(
3, [Column("A", ColumnType.TEXT()), Column("B", ColumnType.TEXT())]
)
schema = ParamDType.Dict(
{
"col1": ParamDType.Column(column_types=frozenset({"number"})),
"col2": ParamDType.Column(column_types=frozenset({"datetime"})),
}
)
with self.assertRaises(PromptingError) as cm:
clean_value(schema, {"col1": "A", "col2": "B"}, input_shape)
self.assertEqual(
cm.exception.errors,
[
PromptingError.WrongColumnType(["A"], "text", frozenset({"number"})),
PromptingError.WrongColumnType(["B"], "text", frozenset({"datetime"})),
],
)
def test_dict_prompting_error(self):
input_shape = TableShape(3, [
Column('A', ColumnType.TEXT()),
Column('B', ColumnType.TEXT()),
])
schema = ParamDType.Dict({
'col1':
ParamDType.Column(column_types=frozenset({'number'})),
'col2':
ParamDType.Column(column_types=frozenset({'datetime'})),
})
with self.assertRaises(PromptingError) as cm:
clean_value(schema, {'col1': 'A', 'col2': 'B'}, input_shape)
self.assertEqual(cm.exception.errors, [
PromptingError.WrongColumnType(['A'], 'text', frozenset({'number'
})),
PromptingError.WrongColumnType(['B'], 'text',
frozenset({'datetime'})),
])
def test_clean_column_missing(self):
input_shape = TableShape(3, [Column('A', ColumnType.NUMBER())])
self.assertEqual(clean_value(ParamDType.Column(), 'B', input_shape),
'')
def test_clean_column_missing(self):
input_shape = TableMetadata(3, [Column("A", ColumnType.Number())])
self.assertEqual(clean_value(ParamDType.Column(), "B", input_shape),
"")
def test_clean_column_tab_parameter_is_error(self):
input_shape = TableMetadata(3, [Column("A", ColumnType.Number())])
with self.assertRaisesRegex(
RuntimeError, "Unsupported: fetch column with tab_parameter"):
clean_value(ParamDType.Column(tab_parameter="tab-2"), "A",
input_shape)
def test_clean_column_no_input_is_empty(self):
self.assertEqual(
clean_value(ParamDType.Column(), "A", TableMetadata()), "")
def test_clean_file_error(self):
with self.assertRaisesRegex(RuntimeError, "Unsupported: fetch file"):
clean_value(ParamDType.File(), None, None)
def test_clean_multitab_unsupported(self):
with self.assertRaisesRegex(RuntimeError,
"Unsupported: fetch multitab"):
clean_value(ParamDType.Multitab(), "", None)
def test_clean_multichartseries_is_error(self):
with self.assertRaisesRegex(RuntimeError,
"Unsupported: fetch multichartseries"):
clean_value(ParamDType.Multichartseries(), [], None)
def test_clean_column_happy_path(self):
input_shape = TableShape(3, [Column('A', ColumnType.NUMBER())])
self.assertEqual(
clean_value(ParamDType.Column(column_types=frozenset({'number'})),
'A', input_shape), 'A')
def test_clean_tab_unsupported(self):
with self.assertRaisesRegex(RuntimeError, "Unsupported: fetch tab"):
clean_value(ParamSchema.Tab(), "", None)
def test_clean_column_no_input_is_empty(self):
self.assertEqual(clean_value(ParamDType.Column(), "A", None), "")
def test_clean_column_tab_parameter_is_error(self):
input_shape = TableShape(3, [Column('A', ColumnType.NUMBER())])
with self.assertRaisesRegex(
RuntimeError, 'Unsupported: fetch column with tab_parameter'):
clean_value(ParamDType.Column(tab_parameter='tab-2'), 'A',
input_shape)
def test_clean_float(self):
result = clean_value(ParamDType.Float(), 3.0, None)
self.assertEqual(result, 3.0)
self.assertIsInstance(result, float)
def test_clean_multicolumn_no_input_is_empty(self):
self.assertEqual(
clean_value(ParamSchema.Multicolumn(), "A", TableMetadata()), [])
