def test_clean_tab_wf_module_changed_raises_unneededexecution(self):
"""
If a user changes tabs' output during render, raise UnneededExecution.
It doesn't really matter _what_ the return value is, since the render()
result will never be saved if this WfModule's delta has changed.
UnneededExecution seems like the simplest contract to enforce.
"""
# tab_output is what 'render' _thinks_ the output should be
tab_output = ProcessResult(pd.DataFrame({'A': [1, 2]}))
workflow = Workflow.create_and_init()
tab = workflow.tabs.first()
wfm = tab.wf_modules.create(
order=0, last_relevant_delta_id=workflow.last_delta_id)
wfm.cache_render_result(workflow.last_delta_id, tab_output)
# Simulate reality: wfm.last_relevant_delta_id will change
wfm.last_relevant_delta_id += 1
wfm.save(update_fields=['last_relevant_delta_id'])
context = RenderContext(
workflow.id, None, None, {
tab.slug: StepResultShape('ok', tab_output.table_shape),
}, None)
with self.assertRaises(UnneededExecution):
clean_value(ParamDType.Tab(), tab.slug, context)
def test_clean_column_missing_becomes_empty_string(self):
context = RenderContext(
None, None, TableShape(3, [
Column('A', ColumnType.NUMBER()),
]), None, None)
result = clean_value(ParamDType.Column(), 'B', context)
self.assertEqual(result, '')
def test_clean_column_valid(self):
context = RenderContext(
None, None, TableShape(3, [
Column('A', ColumnType.NUMBER()),
]), None, None)
result = clean_value(ParamDType.Column(), 'A', context)
self.assertEqual(result, 'A')
def test_clean_file_no_uploaded_file(self):
workflow = Workflow.create_and_init()
tab = workflow.tabs.first()
wfm = tab.wf_modules.create(module_id_name='uploadfile', order=0)
context = RenderContext(workflow.id, wfm.id, None, None, None)
result = clean_value(ParamDType.File(), str(uuid.uuid4()), context)
self.assertIsNone(result)
def test_clean_multichartseries_non_number_is_prompting_error(self):
context = RenderContext(
None,
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_from_other_tab(self):
tab_output = ProcessResult(pd.DataFrame({"A-from-tab-2": [1, 2]}))
workflow = Workflow.create_and_init()
tab = workflow.tabs.first()
wfm = tab.wf_modules.create(
order=0,
slug="step-1",
last_relevant_delta_id=workflow.last_delta_id)
wfm.cache_render_result(workflow.last_delta_id, tab_output)
schema = ParamDType.Dict({
"tab":
ParamDType.Tab(),
"columns":
ParamDType.Multicolumn(tab_parameter="tab"),
})
params = {"tab": tab.slug, "columns": ["A-from-tab-1", "A-from-tab-2"]}
context = RenderContext(
workflow.id,
None,
TableShape(3, [Column("A-from-tab-1", ColumnType.NUMBER())]),
{tab.slug: StepResultShape("ok", tab_output.table_shape)},
params,
)
result = clean_value(schema, params, context)
# result['tab'] is not what we're testing here
self.assertEqual(result["columns"], ["A-from-tab-2"])
def test_clean_tab_tab_delete_race_raises_unneededexecution(self):
"""
If a user deletes the tab during render, raise UnneededExecution.
It doesn't really matter _what_ the return value is, since the render()
result will never be saved if this WfModule's delta has changed.
UnneededExecution just seems like the quickest way out of this mess:
it's an error the caller is meant to raise anyway, unlike
`Tab.DoesNotExist`.
"""
# tab_output is what 'render' _thinks_ the output should be
tab_output = ProcessResult(pd.DataFrame({'A': [1, 2]}))
workflow = Workflow.create_and_init()
tab = workflow.tabs.first()
wfm = tab.wf_modules.create(
order=0, last_relevant_delta_id=workflow.last_delta_id)
wfm.cache_render_result(workflow.last_delta_id, tab_output)
tab.is_deleted = True
tab.save(update_fields=['is_deleted'])
# Simulate reality: wfm.last_relevant_delta_id will change
wfm.last_relevant_delta_id += 1
wfm.save(update_fields=['last_relevant_delta_id'])
context = RenderContext(
workflow.id, None, None, {
tab.slug: StepResultShape('ok', tab_output.table_shape),
}, None)
with self.assertRaises(UnneededExecution):
clean_value(ParamDType.Tab(), tab.slug, context)
def test_clean_file_happy_path(self):
workflow = Workflow.create_and_init()
tab = workflow.tabs.first()
wfm = tab.wf_modules.create(module_id_name="uploadfile",
order=0,
slug="step-1")
id = str(uuid.uuid4())
key = f"wf-${workflow.id}/wfm-${wfm.id}/${id}"
minio.put_bytes(minio.UserFilesBucket, key, b"1234")
UploadedFile.objects.create(
wf_module=wfm,
name="x.csv.gz",
size=4,
uuid=id,
bucket=minio.UserFilesBucket,
key=key,
)
context = RenderContext(workflow.id, wfm.id, None, None, None)
result = clean_value(ParamDType.File(), id, context)
self.assertIsInstance(result, pathlib.Path)
self.assertEqual(result.read_bytes(), b"1234")
self.assertEqual(result.suffixes, [".csv", ".gz"])
# Assert that once `path` goes out of scope, it's deleted
str_path = str(result) # get the filesystem path
del result # should finalize, deleting the file on the filesystem
with self.assertRaises(FileNotFoundError):
os.open(str_path, 0)
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.
context = RenderContext(
None,
None,
TableShape(
3,
[
Column("A", ColumnType.NUMBER()),
Column("B", ColumnType.DATETIME()),
Column("C", ColumnType.TEXT()),
],
),
None,
None,
)
with self.assertRaises(PromptingError) as cm:
schema = ParamDType.Multicolumn(column_types=frozenset({"text"}))
clean_value(schema, "A,B", context)
self.assertEqual(
cm.exception.errors,
[
PromptingError.WrongColumnType(["A", "B"], None,
frozenset({"text"}))
],
)
def test_clean_multichartseries_non_number_is_prompting_error(self):
context = RenderContext(
None, 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_dict_prompting_error_concatenate_different_types(self):
context = RenderContext(
None,
None,
TableShape(3, [
Column("A", ColumnType.TEXT()),
Column("B", ColumnType.DATETIME())
]),
None,
None,
)
schema = ParamDType.Dict({
"x":
ParamDType.Column(column_types=frozenset({"number"})),
"y":
ParamDType.Column(column_types=frozenset({"number"})),
})
with self.assertRaises(PromptingError) as cm:
clean_value(schema, {"x": "A", "y": "B"}, context)
self.assertEqual(
cm.exception.errors,
[
PromptingError.WrongColumnType(["A"], "text",
frozenset({"number"})),
PromptingError.WrongColumnType(["B"], "datetime",
frozenset({"number"})),
],
)
def test_list_prompting_error_concatenate_different_type_to_text(self):
context = RenderContext(
None,
None,
TableShape(
3,
[
Column("A", ColumnType.NUMBER()),
Column("B", ColumnType.DATETIME())
],
),
None,
None,
)
schema = ParamDType.List(inner_dtype=ParamDType.Column(
column_types=frozenset({"text"})))
with self.assertRaises(PromptingError) as cm:
clean_value(schema, ["A", "B"], context)
self.assertEqual(
cm.exception.errors,
[
PromptingError.WrongColumnType(["A", "B"], None,
frozenset({"text"}))
],
)
def test_clean_multicolumn_from_other_tab(self):
tab_output = ProcessResult(pd.DataFrame({'A-from-tab-2': [1, 2]}))
workflow = Workflow.create_and_init()
tab = workflow.tabs.first()
wfm = tab.wf_modules.create(
order=0, last_relevant_delta_id=workflow.last_delta_id)
wfm.cache_render_result(workflow.last_delta_id, tab_output)
schema = ParamDType.Dict({
'tab':
ParamDType.Tab(),
'columns':
ParamDType.Multicolumn(tab_parameter='tab'),
})
params = {'tab': tab.slug, 'columns': ['A-from-tab-1', 'A-from-tab-2']}
context = RenderContext(
workflow.id, None,
TableShape(3, [
Column('A-from-tab-1', ColumnType.NUMBER()),
]), {
tab.slug: StepResultShape('ok', tab_output.table_shape),
}, params)
result = clean_value(schema, params, context)
# result['tab'] is not what we're testing here
self.assertEqual(result['columns'], ['A-from-tab-2'])
def test_clean_multicolumn_sort_in_table_order(self):
context = RenderContext(
None, 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_tab_missing_tab_selected_gives_none(self):
"""
If the user has selected a nonexistent tab, pretend tab is blank.
The JS side of things will see the nonexistent tab, but not render().
"""
context = RenderContext(None, None, None, {}, None)
result = clean_value(ParamDType.Tab(), 'tab-XXX', context)
self.assertEqual(result, None)
def test_clean_normal_dict(self):
context = RenderContext(None, None, None, None, None)
schema = ParamDType.Dict({
'str': ParamDType.String(),
'int': ParamDType.Integer(),
})
value = {'str': 'foo', 'int': 3}
expected = dict(value) # no-op
result = clean_value(schema, value, context)
self.assertEqual(result, expected)
def test_clean_multicolumn_missing_is_removed(self):
context = RenderContext(
None, 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_prompting_error_convert_to_number(self):
context = RenderContext(
None, None, TableShape(3, [
Column('A', ColumnType.TEXT()),
]), None, None)
with self.assertRaises(PromptingError) as cm:
clean_value(ParamDType.Column(column_types=frozenset({'number'})),
'A', context)
self.assertEqual(cm.exception.errors, [
PromptingError.WrongColumnType(['A'], 'text', frozenset({'number'
})),
])
def test_clean_multicolumn_sort_in_table_order(self):
context = RenderContext(
None,
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,
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_list_prompting_error_concatenate_same_type(self):
context = RenderContext(
None, None,
TableShape(3, [
Column('A', ColumnType.TEXT()),
Column('B', ColumnType.TEXT()),
]), None, None)
schema = ParamDType.List(inner_dtype=ParamDType.Column(
column_types=frozenset({'number'})))
with self.assertRaises(PromptingError) as cm:
clean_value(schema, ['A', 'B'], context)
self.assertEqual(cm.exception.errors, [
PromptingError.WrongColumnType(['A', 'B'], 'text',
frozenset({'number'})),
])
def test_clean_file_wrong_wf_module(self):
workflow = Workflow.create_and_init()
tab = workflow.tabs.first()
wfm = tab.wf_modules.create(module_id_name='uploadfile', order=0)
wfm2 = tab.wf_modules.create(module_id_name='uploadfile', order=1)
id = str(uuid.uuid4())
key = f'wf-${workflow.id}/wfm-${wfm.id}/${id}'
minio.put_bytes(minio.UserFilesBucket, key, b'1234')
UploadedFile.objects.create(wf_module=wfm2,
name='x.csv.gz',
size=4,
uuid=id,
bucket=minio.UserFilesBucket,
key=key)
context = RenderContext(workflow.id, wfm.id, None, None, None)
result = clean_value(ParamDType.File(), id, context)
self.assertIsNone(result)
def test_clean_tabs_preserve_ordering(self):
tab2_output = ProcessResult(pd.DataFrame({"A": [1, 2]}))
tab3_output = ProcessResult(pd.DataFrame({"B": [2, 3]}))
workflow = Workflow.create_and_init()
tab1 = workflow.tabs.first()
tab2 = workflow.tabs.create(position=1, slug="tab-2", name="Tab 2")
tab3 = workflow.tabs.create(position=1, slug="tab-3", name="Tab 3")
wfm2 = tab2.wf_modules.create(
order=0,
slug="step-1",
last_relevant_delta_id=workflow.last_delta_id)
wfm2.cache_render_result(workflow.last_delta_id, tab2_output)
wfm3 = tab3.wf_modules.create(
order=0,
slug="step-2",
last_relevant_delta_id=workflow.last_delta_id)
wfm3.cache_render_result(workflow.last_delta_id, tab3_output)
# RenderContext's dict ordering determines desired tab order. (Python
# 3.7 spec: dict is ordered in insertion order. CPython 3.6 and PyPy 7
# do this, too.)
context = RenderContext(
workflow.id,
None,
None,
{
tab1.slug: None,
tab2.slug: StepResultShape("ok", tab2_output.table_shape),
tab3.slug: StepResultShape("ok", tab3_output.table_shape),
},
None,
)
# Supply wrongly-ordered tabs. Cleaned, they should be in order.
result = clean_value(ParamDType.Multitab(), [tab3.slug, tab2.slug],
context)
self.assertEqual(result[0].slug, tab2.slug)
self.assertEqual(result[0].name, tab2.name)
self.assertEqual(result[0].columns,
{"A": RenderColumn("A", "number", "{:,}")})
assert_frame_equal(result[0].dataframe, pd.DataFrame({"A": [1, 2]}))
self.assertEqual(result[1].slug, tab3.slug)
self.assertEqual(result[1].name, tab3.name)
self.assertEqual(result[1].columns,
{"B": RenderColumn("B", "number", "{:,}")})
assert_frame_equal(result[1].dataframe, pd.DataFrame({"B": [2, 3]}))
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"], None, frozenset({"text"}))],
)
def _render_context(
self,
*,
wf_module_id=None,
input_table=None,
tab_results={},
params={},
exit_stack=None,
) -> RenderContext:
if exit_stack is None:
exit_stack = self.exit_stack
return RenderContext(
wf_module_id=wf_module_id,
input_table=input_table,
tab_results=tab_results,
basedir=self.basedir,
exit_stack=exit_stack,
params=params,
)
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, 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_multichartseries_missing_is_removed(self):
context = RenderContext(
None, None,
TableShape(3, [
Column('A', ColumnType.NUMBER()),
Column('B', ColumnType.NUMBER()),
]), None, None)
value = [
{
'column': 'A',
'color': '#aaaaaa'
},
{
'column': 'C',
'color': '#cccccc'
},
]
result = clean_value(ParamDType.Multichartseries(), value, context)
self.assertEqual(result, [{'column': 'A', 'color': '#aaaaaa'}])
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.
context = RenderContext(
None, None,
TableShape(3, [
Column('A', ColumnType.NUMBER()),
Column('B', ColumnType.DATETIME()),
Column('C', ColumnType.TEXT()),
]), None, None)
with self.assertRaises(PromptingError) as cm:
schema = ParamDType.Multicolumn(column_types=frozenset({'text'}))
clean_value(schema, 'A,B', context)
self.assertEqual(cm.exception.errors, [
PromptingError.WrongColumnType(['A'], 'number', frozenset({'text'
})),
PromptingError.WrongColumnType(['B'], 'datetime',
frozenset({'text'})),
])
def test_clean_multicolumn_from_other_tab_that_does_not_exist(self):
# The other tab would not exist if the user selected and then deleted
# it.
workflow = Workflow.create_and_init()
workflow.tabs.first()
schema = ParamDType.Dict({
'tab':
ParamDType.Tab(),
'columns':
ParamDType.Multicolumn(tab_parameter='tab'),
})
params = {'tab': 'tab-missing', 'columns': ['A-from-tab']}
context = RenderContext(
workflow.id, None,
TableShape(3, [
Column('A-from-tab-1', ColumnType.NUMBER()),
]), {}, params)
result = clean_value(schema, params, context)
# result['tab'] is not what we're testing here
self.assertEqual(result['columns'], [])
def test_dict_prompting_error_concatenate_different_types(self):
context = RenderContext(
None, None,
TableShape(3, [
Column('A', ColumnType.TEXT()),
Column('B', ColumnType.DATETIME()),
]), None, None)
schema = ParamDType.Dict({
'x':
ParamDType.Column(column_types=frozenset({'number'})),
'y':
ParamDType.Column(column_types=frozenset({'number'})),
})
with self.assertRaises(PromptingError) as cm:
clean_value(schema, {'x': 'A', 'y': 'B'}, context)
self.assertEqual(cm.exception.errors, [
PromptingError.WrongColumnType(['A'], 'text', frozenset({'number'
})),
PromptingError.WrongColumnType(['B'], 'datetime',
frozenset({'number'})),
])