def date_schema(name, state):
schema = property_schema(name, state)
schema.add(key('column', validator=chained(
nonempty_string,
)))
schema.add(key('datatype', validator=chained(
nonempty_string,
specific_datatype('date')
)))
return schema
def attribute_dimension_schema(name, state):
schema = property_schema(name, state)
schema.add(key('column', validator=chained(
nonempty_string,
)))
schema.add(key('datatype', validator=chained(
nonempty_string,
valid_datatype,
)))
return schema
def property_schema(name, state):
""" This is validation which is common to all properties,
i.e. both dimensions and measures. """
schema = mapping(name, validator=chained(
name_wrap(reserved_name, name),
name_wrap(database_name, name),
no_dimension_id_overlap(name, state)
))
schema.add(key('label', validator=chained(
nonempty_string,
)))
schema.add(key('description', validator=chained(
nonempty_string,
), missing=None))
return schema
def compound_dimension_schema(name, state):
schema = property_schema(name, state)
schema.add(sequence('fields', dimension_attribute_schema(state),
validator=chained(
compound_attributes_include_name,
compound_attributes_include_label
)))
return schema
def dimension_attribute_schema(state):
schema = mapping('field', validator=chained(
compound_attribute_name_is_id_type,
compound_attribute_label_is_string_type
))
schema.add(key('name', validator=chained(
nonempty_string,
reserved_name,
database_name
)))
schema.add(key('column', validator=chained(
nonempty_string,
)))
schema.add(key('datatype', validator=chained(
nonempty_string,
valid_datatype
)))
return schema
def dataset_schema(state):
schema = mapping('dataset')
schema.add(key('name', validator=chained(
nonempty_string,
reserved_name,
database_name,
no_double_underscore
)))
schema.add(key('currency', validator=chained(
valid_currency
)))
schema.add(key('label', validator=chained(
nonempty_string,
)))
schema.add(key('description', validator=chained(
nonempty_string,
)))
schema.add(sequence('unique_keys',
key('key', validator=chained(
unique_keys_are_attributes(state),
)), missing=[]))
return schema
def mapping_schema(state):
schema = mapping('mapping', validator=chained(
require_time_dimension,
require_amount_dimension
))
for name, meta in state.mapping_items:
type_schema = {
'measure': measure_schema,
'value': attribute_dimension_schema,
'attribute': attribute_dimension_schema,
'date': date_schema,
}.get(meta.get('type'),
compound_dimension_schema)
schema.add(type_schema(name, state))
return schema
def view_schema(state):
schema = mapping('view')
schema.add(key('name', validator=chained(
nonempty_string,
database_name
)))
schema.add(key('label', validator=nonempty_string))
schema.add(key('dimension',
validator=dimension_or_dataset(state)))
schema.add(key('drilldown',
validator=dimension_or_not(state),
missing=None))
schema.add(mapping('cuts',
validator=key_is_attribute(state),
missing={}))
return schema
