71 lines
2.3 KiB
Python
71 lines
2.3 KiB
Python
from abc import abstractmethod
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from typing import Any, Dict, Optional, Type, TypeVar, Union, overload
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from pydantic import BaseModel
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from pymongo.asynchronous.client_session import AsyncClientSession
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from beanie.odm.queries.aggregation import AggregationQuery
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from beanie.odm.queries.find import FindMany
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DocType = TypeVar("DocType", bound="AggregateInterface")
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DocumentProjectionType = TypeVar("DocumentProjectionType", bound=BaseModel)
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class AggregateInterface:
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@classmethod
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@abstractmethod
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def find_all(cls) -> FindMany:
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pass
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@overload
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@classmethod
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def aggregate(
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cls: Type[DocType],
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aggregation_pipeline: list,
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projection_model: None = None,
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session: Optional[AsyncClientSession] = None,
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ignore_cache: bool = False,
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**pymongo_kwargs: Any,
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) -> AggregationQuery[Dict[str, Any]]: ...
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@overload
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@classmethod
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def aggregate(
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cls: Type[DocType],
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aggregation_pipeline: list,
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projection_model: Type[DocumentProjectionType],
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session: Optional[AsyncClientSession] = None,
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ignore_cache: bool = False,
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**pymongo_kwargs: Any,
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) -> AggregationQuery[DocumentProjectionType]: ...
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@classmethod
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def aggregate(
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cls: Type[DocType],
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aggregation_pipeline: list,
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projection_model: Optional[Type[DocumentProjectionType]] = None,
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session: Optional[AsyncClientSession] = None,
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ignore_cache: bool = False,
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**pymongo_kwargs: Any,
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) -> Union[
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AggregationQuery[Dict[str, Any]],
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AggregationQuery[DocumentProjectionType],
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]:
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"""
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Aggregate over collection.
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Returns [AggregationQuery](query.md#aggregationquery) query object
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:param aggregation_pipeline: list - aggregation pipeline
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:param projection_model: Type[BaseModel]
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:param session: Optional[AsyncClientSession] - pymongo session.
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:param ignore_cache: bool
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:param **pymongo_kwargs: pymongo native parameters for aggregate operation
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:return: [AggregationQuery](query.md#aggregationquery)
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"""
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return cls.find_all().aggregate(
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aggregation_pipeline=aggregation_pipeline,
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projection_model=projection_model,
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session=session,
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ignore_cache=ignore_cache,
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**pymongo_kwargs,
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)
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