def motor_cursor(self):
if self.fetch_links:
aggregation_pipeline: List[
Dict[str, Any]
] = construct_lookup_queries(self.document_model)
sort_pipeline = {
"$sort": {i[0]: i[1] for i in self.sort_expressions}
}
if sort_pipeline["$sort"]:
aggregation_pipeline.append(sort_pipeline)
if self.skip_number != 0:
aggregation_pipeline.append({"$skip": self.skip_number})
if self.limit_number != 0:
aggregation_pipeline.append({"$limit": self.limit_number})
aggregation_pipeline.append({"$match": self.get_filter_query()})
aggregation_pipeline.append(
{"$project": get_projection(self.projection_model)}
)
return self.document_model.get_motor_collection().aggregate(
aggregation_pipeline, session=self.session
)
return self.document_model.get_motor_collection().find(
filter=self.get_filter_query(),
sort=self.sort_expressions,
projection=get_projection(self.projection_model),
skip=self.skip_number,
limit=self.limit_number,
session=self.session,
)
async def _find_one(self):
if self.document_model.get_link_fields() is not None:
for i, query in enumerate(self.find_expressions):
self.find_expressions[i] = convert_ids(
query,
doc=self.document_model,
fetch_links=self.fetch_links,
)
if self.fetch_links:
result = await self.document_model.find(
*self.find_expressions,
session=self.session,
fetch_links=self.fetch_links,
**self.pymongo_kwargs,
).to_list(length=1)
if result:
return result[0]
else:
return None
return await self.document_model.get_motor_collection().find_one(
filter=self.get_filter_query(),
projection=get_projection(self.projection_model),
session=self.session,
**self.pymongo_kwargs,
)
def motor_cursor(self):
if self.document_model.get_link_fields() is not None:
for i, query in enumerate(self.find_expressions):
self.find_expressions[i] = convert_ids(
query,
doc=self.document_model,
fetch_links=self.fetch_links,
)
if self.fetch_links:
aggregation_pipeline: List[Dict[str,
Any]] = construct_lookup_queries(
self.document_model)
aggregation_pipeline.append({"$match": self.get_filter_query()})
sort_pipeline = {
"$sort": {i[0]: i[1]
for i in self.sort_expressions}
}
if sort_pipeline["$sort"]:
aggregation_pipeline.append(sort_pipeline)
if self.skip_number != 0:
aggregation_pipeline.append({"$skip": self.skip_number})
if self.limit_number != 0:
aggregation_pipeline.append({"$limit": self.limit_number})
projection = get_projection(self.projection_model)
if projection is not None:
aggregation_pipeline.append({"$project": projection})
return self.document_model.get_motor_collection().aggregate(
aggregation_pipeline,
session=self.session,
**self.pymongo_kwargs,
)
return self.document_model.get_motor_collection().find(
filter=self.get_filter_query(),
sort=self.sort_expressions,
projection=get_projection(self.projection_model),
skip=self.skip_number,
limit=self.limit_number,
session=self.session,
**self.pymongo_kwargs,
)
async def test_projection():
projection = get_projection(DocumentTestModel)
assert projection == {
"_id": 1,
"test_int": 1,
"test_list": 1,
"test_str": 1,
}
def get_aggregation_pipeline(self, ) -> List[Mapping[str, Any]]:
match_pipeline: List[Mapping[str, Any]] = ([{
"$match": self.find_query
}] if self.find_query else [])
projection_pipeline: List[Mapping[str, Any]] = ([{
"$project":
get_projection(self.projection_model)
}] if self.projection_model else [])
return match_pipeline + self.aggregation_pipeline + projection_pipeline
def motor_cursor(self):
return self.document_model.get_motor_collection().find(
filter=self.get_filter_query(),
sort=self.sort_expressions,
projection=get_projection(self.projection_model),
skip=self.skip_number,
limit=self.limit_number,
session=self.session,
)
def get_aggregation_pipeline(self, ) -> List[Mapping[str, Any]]:
match_pipeline: List[Mapping[str, Any]] = ([{
"$match": self.find_query
}] if self.find_query else [])
projection_pipeline: List[Mapping[str, Any]] = []
if self.projection_model:
projection = get_projection(self.projection_model)
if projection is not None:
projection_pipeline = [{"$project": projection}]
return match_pipeline + self.aggregation_pipeline + projection_pipeline
def _cache_key(self) -> str:
return LRUCache.create_key(
{
"type": "FindMany",
"filter": self.get_filter_query(),
"sort": self.sort_expressions,
"projection": get_projection(self.projection_model),
"skip": self.skip_number,
"limit": self.limit_number,
}
)
def _cache_key(self) -> str:
return LRUCache.create_key({
"type":
"Aggregation",
"filter":
self.find_query,
"pipeline":
self.aggregation_pipeline,
"projection":
get_projection(self.projection_model)
if self.projection_model else None,
})
def __await__(self):
"""
Run the query
:return: BaseModel
"""
projection = get_projection(self.projection_model)
document: Dict[str, Any] = (
yield from self.document_model.get_motor_collection().find_one(
filter=self.get_filter_query(),
projection=projection,
session=self.session,
))
if document is None:
return None
return self.projection_model.parse_obj(document)
def __await__(
self, ) -> Generator[Coroutine, Any, Optional[FindQueryResultType]]:
"""
Run the query
:return: BaseModel
"""
projection = get_projection(self.projection_model)
document: Dict[str, Any] = (
yield from self.document_model.get_motor_collection().find_one(
filter=self.get_filter_query(),
projection=projection,
session=self.session,
))
if document is None:
return None
return cast(FindQueryResultType,
parse_obj(self.projection_model, document))
async def _find_one(self):
if self.fetch_links:
lookup_queries = construct_lookup_queries(self.document_model)
result = (
await self.document_model.find(*self.find_expressions)
.aggregate(
aggregation_pipeline=lookup_queries,
projection_model=self.projection_model,
session=self.session,
)
.to_list(length=1)
)
if result:
return result[0]
else:
return None
return await self.document_model.get_motor_collection().find_one(
filter=self.get_filter_query(),
projection=get_projection(self.projection_model),
session=self.session,
)
