def __init__(self, name='DynFilterSrv', condition_srv_name='ConditionSrv'):
'''
@param name: The unique name of the service
'''
self._dfilters = Case().tag(name).tag(DynFilter.__name__)
self._conditions = Showcase.instance().get_case(condition_srv_name)
INamed.__init__(self, name)
def clear_dselects(self):
#dselect = Showcase.instance().get('morpho_dselect')
#dselect.clear()
#dselect = Showcase.instance().get('clinic_dselect')
#dselect.clear()
dselect = Showcase.instance().get('joined_dselect')
dselect.clear()
def describe_stats(dselect_name, dataset_name, attr_name):
dselect = Showcase.instance().get(dselect_name)
dataset = Showcase.instance().get(dataset_name)
description = None
project = {attr_name: True}
query = dselect.query if dselect.get_conditions() else {}
data = dataset.find(query, project).get_data('c_list')
attr_scheme = dataset.schema.attributes[attr_name]
if data and attr_scheme.attribute_type == "QUANTITATIVE":
desc = [d if pd.np.isreal(d) else None for d in data[attr_name]]
description = pd.Series(desc).describe().to_dict()
return description
def export_dselect(dselect_name, dataset_name, name):
dselect = Showcase.instance().get(dselect_name)
dataset = Showcase.instance().get(dataset_name)
download_name = name.replace(" ", "_") + '.xlsx'
project = dselect.projection
# Multidimensial attributes are not exported in tables
for name, attr in dataset.schema.attributes.items():
if attr.is_multidimensional():
project[name] = False
data = dataset.find(dselect.query, project).get_data('rows')
df = pd.DataFrame(data)
df.to_excel(os.path.join(ASSETSPATH, 'exports', download_name))
return os.path.join('assets', 'exports', download_name)
def build(self, grammar, objects=None):
showcase = Showcase.instance()
if objects:
objects = {o:showcase.get(o) for o in objects}
instances = Root.build(grammar, objects)
print '////', instances
for name, instance in instances.items():
case = showcase.get_case(instance.__class__.__name__)
case[name] = instance
return instances.values()
def new_condition(self, kind, data, *args, **kwargs):
dataset = Showcase.instance().get(data)
if kind == 'categorical':
new_condition = CategoricalCondition(dataset, *args, **kwargs)
if kind == 'attribute':
new_condition = AttributeCondition(dataset, *args, **kwargs)
if kind == 'range':
new_condition = RangeCondition(dataset, *args, **kwargs)
if kind == 'query':
new_condition = QueryCondition(dataset, *args, **kwargs)
self._conditions[new_condition.oid] = new_condition
return new_condition
def new_dfilter(self, name, data, setop='AND', prefix=''):
dataset = Showcase.instance().get(data)
new_dfilter = DynFilter(name, dataset, setop, prefix=prefix)
self._dfilters[new_dfilter.oid] = new_dfilter
return new_dfilter
def new_dselect(self, name, data, setop='OR', prefix=''):
dataset = Showcase.instance().get(data)
new_dselect = DynSelect(name, dataset, setop, prefix=prefix)
self._dselects[new_dselect.oid] = new_dselect
return new_dselect
def _proxy_instanciator(self, method, root_oid, object_or_objects):
showcase = Showcase.instance()
names = object_or_objects if isinstance(object_or_objects, list) else [object_or_objects]
objects = [showcase.get(n) for n in names]
return self._proxy(method, root_oid, objects)
def write_csv(self, table_name, filepath, schema=None, *args, **kwargs):
case = Showcase.instance().get_case(self._table_srv_name)
table = case[table_name]
schema = schema if schema is not None else table.schema
return write_csv(table, filepath, schema, *args, **kwargs)
def read_csv(self, table_name, filepath, schema=None, *args, **kwargs):
table = read_csv(table_name, filepath, schema, *args, **kwargs)
case = Showcase.instance().get_case(self._table_srv_name)
case[table.oid] = table
return table