def decorate_model_class(self, entity_cls, model_cls):
schema_name = derive_schema_name(model_cls)
# Return the model class if it was already seen/decorated
if schema_name in self._model_classes:
return self._model_classes[schema_name]
# If `model_cls` is already subclassed from MemoryModel,
# this method call is a no-op
if issubclass(model_cls, MemoryModel):
return model_cls
else:
custom_attrs = {
key: value
for (key, value) in vars(model_cls).items()
if key not in ["Meta", "__module__", "__doc__", "__weakref__"]
}
# Protean
from protean.core.model import ModelMeta
meta_ = ModelMeta()
meta_.entity_cls = entity_cls
custom_attrs.update({"meta_": meta_})
# FIXME Ensure the custom model attributes are constructed properly
decorated_model_cls = type(model_cls.__name__,
(MemoryModel, model_cls), custom_attrs)
# Memoize the constructed model class
self._model_classes[schema_name] = decorated_model_cls
return decorated_model_cls
def construct_model_class(self, entity_cls):
"""Return associated, fully-baked Model class"""
model_cls = None
# Return the model class if it was already seen/decorated
if entity_cls.meta_.schema_name in self._model_classes:
model_cls = self._model_classes[entity_cls.meta_.schema_name]
else:
# Protean
from protean.core.model import ModelMeta
meta_ = ModelMeta()
meta_.entity_cls = entity_cls
attrs = {
"meta_": meta_,
}
# FIXME Ensure the custom model attributes are constructed properly
model_cls = type(entity_cls.__name__ + "Model", (MemoryModel, ),
attrs)
# Memoize the constructed model class
self._model_classes[entity_cls.meta_.schema_name] = model_cls
# Set Entity Class as a class level attribute for the Model, to be able to reference later.
return model_cls
def construct_model_class(self, entity_cls):
"""Return a fully-baked Model class for a given Entity class"""
model_cls = None
# Return the model class if it was already seen/decorated
if entity_cls.meta_.schema_name in self._model_classes:
model_cls = self._model_classes[entity_cls.meta_.schema_name]
else:
from protean.core.model import ModelMeta
meta_ = ModelMeta()
meta_.entity_cls = entity_cls
# Construct Inner Index class with options
options = {}
options["name"] = self.derive_schema_name(entity_cls)
if "SETTINGS" in self.conn_info and self.conn_info["SETTINGS"]:
options["settings"] = self.conn_info["SETTINGS"]
index_cls = type("Index", (object, ), options)
attrs = {"meta_": meta_, "Index": index_cls}
# FIXME Ensure the custom model attributes are constructed properly
model_cls = type(entity_cls.__name__ + "Model",
(ElasticsearchModel, ), attrs)
# Create Dynamic Mapping and associate with index
# FIXME Expand to all types of fields
id_field_name = id_field(entity_cls).field_name
m = Mapping()
m.field(id_field_name, Keyword())
model_cls._index.mapping(m)
# Memoize the constructed model class
self._model_classes[entity_cls.meta_.schema_name] = model_cls
# Set Entity Class as a class level attribute for the Model, to be able to reference later.
return model_cls