import json import logging from typing import List, Union, Optional, Type, TypeVar, cast from opensearchpy import OpenSearch from opensearchorm.model import BaseModel from opensearchorm.query import ModelQuery, Expr from opensearchorm.aggs import Aggregation, Sum, Cardinality from opensearchorm.utils import parse_aggregations Host = Union[str, dict] Model = TypeVar('Model', bound=BaseModel) class SearchSession: def __init__(self, hosts: Union[Host, List[Host]], user: str, password: str, **kwargs) -> None: """ :arg hosts: list of nodes, or a single node, we should connect to. Node should be a dictionary ({"host": "localhost", "port": 9200}), the entire dictionary will be passed to the :class:`~opensearchpy.Connection` class as kwargs, or a string in the format of ``host[:port]`` which will be translated to a dictionary automatically. :arg user: http auth username :arg password: http auth password :arg kwargs: any additional arguments will be passed on to the opensearch-py call """ self.client = OpenSearch( hosts=hosts, http_auth=(user, password), http_compress=True, **kwargs, ) def __enter__(self): return self def __exit__(self, type, value, traceback): self.client.close() def select(self, model: Type[Model]): return QueryExecutor(model, self) def search(self, **kwargs): return self.client.search(**kwargs) def count(self, **kwargs): return self.client.count(**kwargs) class QueryExecutor: def __init__(self, model_cls: Type[Model], session: SearchSession): self.__query = ModelQuery(model_cls) self.__model_cls = model_cls self.__include_fields = [] self.__limit: Optional[int] = None self.__offset: Optional[int] = None self.__session = session def filter(self, *args: Expr, **kwargs): self.__query.filter(*args, **kwargs) return self def union(self, *args: Expr, **kwargs): self.__query.union(*args, **kwargs) return self def exclude(self, *args: Expr, **kwargs): self.__query.exclude(*args, **kwargs) return self def limit(self, limit: int): self.__limit = limit return self def offset(self, offset: int): self.__offset = offset return self def values(self, fields: List[str]): self.__include_fields = fields return self def fetch(self, **kwargs): """ :arg kwargs: any additional arguments will be passed on to the opensearch-py call """ body = { 'query': self.__query.compile(), } logging.debug('query:\n%s', json.dumps(body)) model = self.__model_cls assert model and model.__index__, 'model has no index' resp = self.__session.search( body=body, index=model.__index__, size=self.__limit, from_=self.__offset, _source_includes=self.__include_fields or model.default_fields(), **kwargs, ) hits = resp['hits']['hits'] logging.debug('raw result: %s', hits) if self.__include_fields: return [hit['_source'] for hit in hits] else: return [model.parse_obj(hit['_source']) for hit in hits] def scroll(self, **kwargs): ... def aggregate(self, aggs: Aggregation, **kwargs): """ :arg kwargs: any additional arguments will be passed on to the opensearch-py call """ body = { 'query': self.__query.compile(), 'aggs': aggs.compile(depth=1), } logging.debug('query:\n%s', json.dumps(body)) model = self.__model_cls assert model and model.__index__, 'model has no index' resp = self.__session.search( body=body, index=model.__index__, size=0, **kwargs, ) data = resp['aggregations'] return parse_aggregations(data, depth=1) def unique_count(self, field: str, **kwargs) -> int: resp = self.aggregate(Cardinality(field), **kwargs) return cast(int, resp) def sum(self, field: str, **kwargs) -> float: resp = self.aggregate(Sum(field), **kwargs) return cast(int, resp) def count(self, **kwargs) -> int: body = { 'query': self.__query.compile(), } logging.debug('query:\n%s', json.dumps(body)) model = self.__model_cls assert model and model.__index__, 'model has no index' resp = self.__session.count( body=body, index=model.__index__, **kwargs, ) return resp['count']