Source code for airflow.providers.elasticsearch.log.es_response

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from __future__ import annotations

from typing import Iterator


def _wrap(val):
    if isinstance(val, dict):
        return AttributeDict(val)
    return val


[docs]class AttributeList: """Helper class to provide attribute like access to List objects.""" def __init__(self, _list): if not isinstance(_list, list): _list = list(_list) self._l_ = _list
[docs] def __getitem__(self, k): """Retrieve an item or a slice from the list. If the item is a dictionary, it is wrapped in an AttributeDict.""" val = self._l_[k] if isinstance(val, slice): return AttributeList(val) return _wrap(val)
[docs] def __iter__(self): """Provide an iterator for the list or the dictionary.""" return (_wrap(i) for i in self._l_)
[docs] def __bool__(self): """Check if the list is non-empty.""" return bool(self._l_)
[docs]class AttributeDict: """Helper class to provide attribute like access to Dictionary objects.""" def __init__(self, d): super().__setattr__("_d_", d)
[docs] def __getattr__(self, attr_name): """Retrieve an item as an attribute from the dictionary.""" try: return self.__getitem__(attr_name) except KeyError: raise AttributeError(f"{self.__class__.__name__!r} object has no attribute {attr_name!r}")
[docs] def __getitem__(self, key): """Retrieve an item using a key from the dictionary.""" return _wrap(self._d_[key])
[docs] def to_dict(self): return self._d_
[docs]class Hit(AttributeDict): """ The Hit class is used to manage and access elements in a document. It inherits from the AttributeDict class and provides attribute-like access to its elements, similar to a dictionary. """ def __init__(self, document): data = {} if "_source" in document: data = document["_source"] if "fields" in document: data.update(document["fields"]) super().__init__(data) super().__setattr__("meta", HitMeta(document))
[docs]class HitMeta(AttributeDict): """ The HitMeta class is used to manage and access metadata of a document. This class inherits from the AttributeDict class and provides attribute-like access to its elements. """ def __init__(self, document, exclude=("_source", "_fields")): d = {k[1:] if k.startswith("_") else k: v for (k, v) in document.items() if k not in exclude} if "type" in d: # make sure we are consistent everywhere in python d["doc_type"] = d.pop("type") super().__init__(d)
[docs]class ElasticSearchResponse(AttributeDict): """ The ElasticSearchResponse class is used to manage and access the response from an Elasticsearch search. This class can be iterated over directly to access hits in the response. Indexing the class instance with an integer or slice will also access the hits. The class also evaluates to True if there are any hits in the response. The hits property returns an AttributeList of hits in the response, with each hit transformed into an instance of the doc_class if provided. The response parameter stores the dictionary returned by the Elasticsearch client search method. """ def __init__(self, search, response, doc_class=None): super().__setattr__("_search", search) super().__setattr__("_doc_class", doc_class) super().__init__(response)
[docs] def __iter__(self) -> Iterator[Hit]: """Provide an iterator over the hits in the Elasticsearch response.""" return iter(self.hits)
[docs] def __getitem__(self, key): """Retrieve a specific hit or a slice of hits from the Elasticsearch response.""" if isinstance(key, (slice, int)): return self.hits[key] return super().__getitem__(key)
[docs] def __bool__(self): """Evaluate the presence of hits in the Elasticsearch response.""" return bool(self.hits)
@property
[docs] def hits(self) -> list[Hit]: """ This property provides access to the hits (i.e., the results) of the Elasticsearch response. The hits are represented as an `AttributeList` of `Hit` instances, which allow for easy, attribute-like access to the hit data. The hits are lazily loaded, meaning they're not processed until this property is accessed. Upon first access, the hits data from the response is processed using the `_get_result` method of the associated `Search` instance (i.e. an instance from ElasticsearchTaskHandler class), and the results are stored for future accesses. Each hit also includes all the additional data present in the "hits" field of the response, accessible as attributes of the hit. """ if not hasattr(self, "_hits"): h = self._d_["hits"] try: hits = AttributeList(map(self._search._get_result, h["hits"])) except AttributeError as e: raise TypeError("Could not parse hits.", e) super().__setattr__("_hits", hits) for k in h: setattr(self._hits, k, _wrap(h[k])) return self._hits

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