def test_aggregate(self):
md = {}
with self.assertRaises(ModelError):
measure = MeasureAggregate.from_metadata(md)
measure = MeasureAggregate.from_metadata("amount_sum")
self.assertIsInstance(measure, MeasureAggregate)
self.assertEqual("amount_sum", measure.name)
def test_aggregate(self):
md = {}
with self.assertRaises(ModelError):
measure = MeasureAggregate.from_metadata(md)
measure = MeasureAggregate.from_metadata("amount_sum")
self.assertIsInstance(measure, MeasureAggregate)
self.assertEqual("amount_sum", measure.name)
def test_fact_count(self):
md = {"name": "count", "function": "count"}
agg = MeasureAggregate.from_metadata(md)
self.assertEqual("count", agg.name)
self.assertIsNone(agg.measure)
self.assertEqual("count", agg.function)
self.assertIsNone(agg.formula)
def test_fact_count(self):
md = {"name": "count", "function": "count"}
agg = MeasureAggregate.from_metadata(md)
self.assertEqual("count", agg.name)
self.assertIsNone(agg.measure)
self.assertEqual("count", agg.function)
self.assertIsNone(agg.formula)
def cube(self, name, locale=None, namespace=None, metaonly=None):
if name == "geometry":
return getGeomCube(self, metaonly)
dataset = get_dataset(name)
if name is None:
raise NoSuchCubeError("Unknown dataset %s" % name, name)
mappings = {}
joins = []
fact_table = dataset.source.model.table.name
aggregates = [
MeasureAggregate('num_entries',
label='Number of entries',
function='count')
]
measures = []
# "wma": partial(_window_function_factory, window_function=weighted_moving_average, label='Weighted Moving Avg. of {measure}'),
# "sma": partial(_window_function_factory, window_function=simple_moving_average, label='Simple Moving Avg. of {measure}'),
# "sms": partial(_window_function_factory, window_function=simple_moving_sum, label='Simple Moving Sum of {measure}'),
aggregation_funcs = ["sum", "min", "max", "avg"]
for measure in dataset.source.model.measures:
cubes_measure = Measure(measure.name, label=measure.label)
measures.append(cubes_measure)
for agg_func in aggregation_funcs:
aggregate = MeasureAggregate(measure.name + "_" + agg_func,
label=measure.label + agg_func,
measure=measure.name,
function=agg_func)
aggregates.append(aggregate)
dimensions = []
for dim in dataset.source.model.dimensions:
meta = dim.to_cubes(mappings, joins)
meta.update({'name': dim.name, 'label': dim.label})
dimensions.append(Dimension.from_metadata(meta))
cube_meta = {
"name": dataset.name,
"fact": fact_table,
"aggregates": aggregates,
"measures": measures,
#change these when they get addeed to the model
"label": dataset.label,
"description": "non null description",
"dimensions": dimensions,
"store": self.store,
"mappings": mappings,
"joins": joins
}
if metaonly:
return cube_meta
else:
return Cube(name=cube_meta['name'],
fact=cube_meta['fact'],
aggregates=cube_meta['aggregates'],
measures=cube_meta['measures'],
label=cube_meta['label'],
description=cube_meta['description'],
dimensions=cube_meta['dimensions'],
store=cube_meta['store'],
mappings=cube_meta['mappings'],
joins=cube_meta['joins'])
def cube(self, name, locale=None, namespace=None):
dataset = Dataset.by_name(name)
if name is None:
raise NoSuchCubeError("Unknown dataset %s" % name, name)
measures, dimensions, mappings = [], [], {}
aggregates = [
MeasureAggregate('fact_count',
label='Number of entries',
function='count')
]
for measure in dataset.model.measures:
cubes_measure = Measure(measure.name, label=measure.label)
measures.append(cubes_measure)
aggregate = MeasureAggregate(measure.name + '_sum',
label=measure.label,
measure=measure.name,
function='sum')
aggregates.append(aggregate)
mappings[measure.name] = measure.column
for dimension in dataset.model.dimensions:
attributes, last_col = [], None
for attr in dimension.attributes:
attributes.append({'name': attr.name, 'label': attr.label})
mappings[attr.path] = last_col = attr.column
# Workaround because the cubes mapper shortens references
# for single-attribute dimensions to just the dimension name.
if len(attributes) == 1:
mappings[dimension.name] = last_col
# Translate into cubes' categories
cardinality = 'high'
if dimension.cardinality:
if dimension.cardinality < 6:
cardinality = 'tiny'
elif dimension.cardinality < 51:
cardinality = 'low'
elif dimension.cardinality < 1001:
cardinality = 'medium'
meta = {
'label':
dimension.label,
'name':
dimension.name,
'cardinality':
cardinality,
'levels': [{
'name': dimension.name,
'label': dimension.label,
'cardinality': cardinality,
'attributes': attributes
}]
}
if dimension.key_attribute:
meta['levels'][0]['key'] = dimension.key_attribute.name
if dimension.label_attribute:
meta['levels'][0]['label_attribute'] = \
dimension.label_attribute.name
meta['levels'][0]['order_attribute'] = \
dimension.label_attribute.name
dimensions.append(Dimension.from_metadata(meta))
cube = Cube(name=dataset.name,
fact=dataset.fact_table.table.name,
aggregates=aggregates,
measures=measures,
label=dataset.label,
description=dataset.description,
dimensions=dimensions,
store=self.store,
mappings=mappings)
link_cube(cube, locale, provider=self, namespace=namespace)
return cube