# SPDX-License-Identifier: Apache-2.0
#
# The OpenSearch Contributors require contributions made to
# this file be licensed under the Apache-2.0 license or a
# compatible open source license.
#
# Modifications Copyright OpenSearch Contributors. See
# GitHub history for details.
#
# Licensed to Elasticsearch B.V. under one or more contributor
# license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright
# ownership. Elasticsearch B.V. licenses this file to you under
# the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
import collections.abc as collections_abc
import copy
from typing import Any
from six import iteritems, string_types
from opensearchpy.connection.connections import get_connection
from opensearchpy.exceptions import TransportError
from opensearchpy.helpers import scan
from ..exceptions import IllegalOperation
from ..helpers.query import Bool, Q
from .aggs import A, AggBase
from .response import Hit, Response
from .utils import AttrDict, DslBase, recursive_to_dict
class QueryProxy(object):
"""
Simple proxy around DSL objects (queries) that can be called
(to add query/post_filter) and also allows attribute access which is proxied to
the wrapped query.
"""
def __init__(self, search: Any, attr_name: Any) -> None:
self._search = search
self._proxied: Any = None
self._attr_name = attr_name
def __nonzero__(self) -> bool:
return self._proxied is not None
__bool__ = __nonzero__
def __call__(self, *args: Any, **kwargs: Any) -> Any:
s = self._search._clone()
# we cannot use self._proxied since we just cloned self._search and
# need to access the new self on the clone
proxied = getattr(s, self._attr_name)
if proxied._proxied is None:
proxied._proxied = Q(*args, **kwargs)
else:
proxied._proxied &= Q(*args, **kwargs)
# always return search to be chainable
return s
def __getattr__(self, attr_name: Any) -> Any:
return getattr(self._proxied, attr_name)
def __setattr__(self, attr_name: Any, value: Any) -> None:
if not attr_name.startswith("_"):
self._proxied = Q(self._proxied.to_dict())
setattr(self._proxied, attr_name, value)
super(QueryProxy, self).__setattr__(attr_name, value)
def __getstate__(self) -> Any:
return self._search, self._proxied, self._attr_name
def __setstate__(self, state: Any) -> None:
self._search, self._proxied, self._attr_name = state
class ProxyDescriptor(object):
"""
Simple descriptor to enable setting of queries and filters as:
s = Search()
s.query = Q(...)
"""
def __init__(self, name: str) -> None:
self._attr_name = "_%s_proxy" % name
def __get__(self, instance: Any, owner: Any) -> Any:
return getattr(instance, self._attr_name)
def __set__(self, instance: Any, value: Any) -> None:
proxy = getattr(instance, self._attr_name)
proxy._proxied = Q(value)
class AggsProxy(AggBase, DslBase):
name = "aggs"
def __init__(self, search: Any) -> None:
self._base = self
self._search = search
self._params = {"aggs": {}}
def to_dict(self) -> Any:
return super(AggsProxy, self).to_dict().get("aggs", {})
class Request(object):
_doc_type: Any
_doc_type_map: Any
def __init__(
self,
using: str = "default",
index: Any = None,
doc_type: Any = None,
extra: Any = None,
) -> None:
self._using = using
self._index = None
if isinstance(index, (tuple, list)):
self._index = list(index)
elif index:
self._index = [index]
self._doc_type = []
self._doc_type_map = {}
if isinstance(doc_type, (tuple, list)):
self._doc_type.extend(doc_type)
elif isinstance(doc_type, collections_abc.Mapping):
self._doc_type.extend(doc_type.keys())
self._doc_type_map.update(doc_type)
elif doc_type:
self._doc_type.append(doc_type)
self._params: Any = {}
self._extra: Any = extra or {}
def __eq__(self: Any, other: Any) -> bool:
return (
isinstance(other, Request)
and other._params == self._params
and other._index == self._index
and other._doc_type == self._doc_type
and other.to_dict() == self.to_dict() # type: ignore
)
def __copy__(self) -> Any:
return self._clone()
def params(self, **kwargs: Any) -> Any:
"""
Specify query params to be used when executing the search. All the
keyword arguments will override the current values.
Example::
s = Search()
s = s.params(routing='user-1', preference='local')
"""
s = self._clone()
s._params.update(kwargs)
return s
def index(self, *index: Any) -> Any:
"""
Set the index for the search. If called empty it will remove all information.
Example:
s = Search()
s = s.index('twitter-2015.01.01', 'twitter-2015.01.02')
s = s.index(['twitter-2015.01.01', 'twitter-2015.01.02'])
"""
# .index() resets
s = self._clone()
if not index:
s._index = None
else:
indexes = []
for i in index:
if isinstance(i, string_types):
indexes.append(i)
elif isinstance(i, list):
indexes += i
elif isinstance(i, tuple):
indexes += list(i)
s._index = (self._index or []) + indexes
return s
def _resolve_field(self, path: Any) -> Any:
for dt in self._doc_type:
if not hasattr(dt, "_index"):
continue
field = dt._index.resolve_field(path)
if field is not None:
return field
def _resolve_nested(self, hit: Any, parent_class: Any = None) -> Any:
doc_class = Hit
nested_path: Any = []
nesting = hit["_nested"]
while nesting and "field" in nesting:
nested_path.append(nesting["field"])
nesting = nesting.get("_nested")
nested_path = ".".join(nested_path)
if hasattr(parent_class, "_index"):
nested_field = parent_class._index.resolve_field(nested_path)
else:
nested_field = self._resolve_field(nested_path)
if nested_field is not None:
return nested_field._doc_class
return doc_class
def _get_result(self, hit: Any, parent_class: Any = None) -> Any:
doc_class = Hit
dt = hit.get("_type")
if "_nested" in hit:
doc_class = self._resolve_nested(hit, parent_class)
elif dt in self._doc_type_map:
doc_class = self._doc_type_map[dt]
else:
for doc_type in self._doc_type:
if hasattr(doc_type, "_matches") and doc_type._matches(hit):
doc_class = doc_type
break
for t in hit.get("inner_hits", ()):
hit["inner_hits"][t] = Response(
self, hit["inner_hits"][t], doc_class=doc_class
)
callback = getattr(doc_class, "from_opensearch", doc_class)
return callback(hit)
def doc_type(self, *doc_type: Any, **kwargs: Any) -> Any:
"""
Set the type to search through. You can supply a single value or
multiple. Values can be strings or subclasses of ``Document``.
You can also pass in any keyword arguments, mapping a doc_type to a
callback that should be used instead of the Hit class.
If no doc_type is supplied any information stored on the instance will
be erased.
Example:
s = Search().doc_type('product', 'store', User, custom=my_callback)
"""
# .doc_type() resets
s = self._clone()
if not doc_type and not kwargs:
s._doc_type = []
s._doc_type_map = {}
else:
s._doc_type.extend(doc_type)
s._doc_type.extend(kwargs.keys())
s._doc_type_map.update(kwargs)
return s
def using(self, client: Any) -> Any:
"""
Associate the search request with an opensearch client. A fresh copy
will be returned with current instance remaining unchanged.
:arg client: an instance of ``opensearchpy.OpenSearch`` to use or
an alias to look up in ``opensearchpy.connections``
"""
s = self._clone()
s._using = client
return s
def extra(self, **kwargs: Any) -> Any:
"""
Add extra keys to the request body. Mostly here for backwards
compatibility.
"""
s = self._clone()
if "from_" in kwargs:
kwargs["from"] = kwargs.pop("from_")
s._extra.update(kwargs)
return s
def _clone(self) -> Any:
s = self.__class__(
using=self._using, index=self._index, doc_type=self._doc_type
)
s._doc_type_map = self._doc_type_map.copy()
s._extra = self._extra.copy()
s._params = self._params.copy()
return s
[docs]class Search(Request):
query = ProxyDescriptor("query")
post_filter = ProxyDescriptor("post_filter")
def __init__(self, **kwargs: Any) -> None:
"""
Search request to opensearch.
:arg using: `OpenSearch` instance to use
:arg index: limit the search to index
:arg doc_type: only query this type.
All the parameters supplied (or omitted) at creation type can be later
overridden by methods (`using`, `index` and `doc_type` respectively).
"""
super(Search, self).__init__(**kwargs)
self.aggs = AggsProxy(self)
self._sort: Any = []
self._collapse: Any = {}
self._source: Any = None
self._highlight: Any = {}
self._highlight_opts: Any = {}
self._suggest: Any = {}
self._script_fields: Any = {}
self._response_class = Response
self._query_proxy = QueryProxy(self, "query")
self._post_filter_proxy = QueryProxy(self, "post_filter")
def filter(self, *args: Any, **kwargs: Any) -> Any:
return self.query(Bool(filter=[Q(*args, **kwargs)]))
def exclude(self, *args: Any, **kwargs: Any) -> Any:
return self.query(Bool(filter=[~Q(*args, **kwargs)]))
[docs] def __iter__(self) -> Any:
"""
Iterate over the hits.
"""
return iter(self.execute())
[docs] def __getitem__(self, n: Any) -> Any:
"""
Support slicing the `Search` instance for pagination.
Slicing equates to the from/size parameters. E.g.::
s = Search().query(...)[0:25]
is equivalent to::
s = Search().query(...).extra(from_=0, size=25)
"""
s = self._clone()
if isinstance(n, slice):
# If negative slicing, abort.
if n.start and n.start < 0 or n.stop and n.stop < 0:
raise ValueError("Search does not support negative slicing.")
# OpenSearch won't get all results so we default to size: 10 if
# stop not given.
s._extra["from"] = n.start or 0
s._extra["size"] = max(
0, n.stop - (n.start or 0) if n.stop is not None else 10
)
return s
else: # This is an index lookup, equivalent to slicing by [n:n+1].
# If negative index, abort.
if n < 0:
raise ValueError("Search does not support negative indexing.")
s._extra["from"] = n
s._extra["size"] = 1
return s
[docs] @classmethod
def from_dict(cls, d: Any) -> Any:
"""
Construct a new `Search` instance from a raw dict containing the search
body. Useful when migrating from raw dictionaries.
Example::
s = Search.from_dict({
"query": {
"bool": {
"must": [...]
}
},
"aggs": {...}
})
s = s.filter('term', published=True)
"""
s = cls()
s.update_from_dict(d)
return s
[docs] def _clone(self) -> Any:
"""
Return a clone of the current search request. Performs a shallow copy
of all the underlying objects. Used internally by most state modifying
APIs.
"""
s = super(Search, self)._clone()
s._response_class = self._response_class
s._sort = self._sort[:]
s._source = copy.copy(self._source) if self._source is not None else None
s._highlight = self._highlight.copy()
s._highlight_opts = self._highlight_opts.copy()
s._suggest = self._suggest.copy()
s._script_fields = self._script_fields.copy()
for x in ("query", "post_filter"):
getattr(s, x)._proxied = getattr(self, x)._proxied
# copy top-level bucket definitions
if self.aggs._params.get("aggs"):
s.aggs._params = {"aggs": self.aggs._params["aggs"].copy()}
return s
[docs] def response_class(self, cls: Any) -> Any:
"""
Override the default wrapper used for the response.
"""
s = self._clone()
s._response_class = cls
return s
[docs] def update_from_dict(self, d: Any) -> "Search":
"""
Apply options from a serialized body to the current instance. Modifies
the object in-place. Used mostly by ``from_dict``.
"""
d = d.copy()
if "query" in d:
self.query._proxied = Q(d.pop("query"))
if "post_filter" in d:
self.post_filter._proxied = Q(d.pop("post_filter"))
aggs = d.pop("aggs", d.pop("aggregations", {}))
if aggs:
self.aggs._params = {
"aggs": {name: A(value) for (name, value) in iteritems(aggs)}
}
if "sort" in d:
self._sort = d.pop("sort")
if "_source" in d:
self._source = d.pop("_source")
if "highlight" in d:
high = d.pop("highlight").copy()
self._highlight = high.pop("fields")
self._highlight_opts = high
if "suggest" in d:
self._suggest = d.pop("suggest")
if "text" in self._suggest:
text = self._suggest.pop("text")
for s in self._suggest.values():
s.setdefault("text", text)
if "script_fields" in d:
self._script_fields = d.pop("script_fields")
self._extra.update(d)
return self
[docs] def script_fields(self, **kwargs: Any) -> Any:
"""
Define script fields to be calculated on hits.
Example::
s = Search()
s = s.script_fields(times_two="doc['field'].value * 2")
s = s.script_fields(
times_three={
'script': {
'lang': 'painless',
'source': "doc['field'].value * params.n",
'params': {'n': 3}
}
}
)
"""
s = self._clone()
for name in kwargs:
if isinstance(kwargs[name], string_types):
kwargs[name] = {"script": kwargs[name]}
s._script_fields.update(kwargs)
return s
[docs] def source(self, fields: Any = None, **kwargs: Any) -> Any:
"""
Selectively control how the _source field is returned.
:arg fields: wildcard string, array of wildcards, or dictionary of includes and excludes
If ``fields`` is None, the entire document will be returned for
each hit. If fields is a dictionary with keys of 'includes' and/or
'excludes' the fields will be either included or excluded appropriately.
Calling this multiple times with the same named parameter will override the
previous values with the new ones.
Example::
s = Search()
s = s.source(includes=['obj1.*'], excludes=["*.description"])
s = Search()
s = s.source(includes=['obj1.*']).source(excludes=["*.description"])
"""
s = self._clone()
if fields and kwargs:
raise ValueError("You cannot specify fields and kwargs at the same time.")
if fields is not None:
s._source = fields
return s
if kwargs and not isinstance(s._source, dict):
s._source = {}
for key, value in kwargs.items():
if value is None:
try:
del s._source[key]
except KeyError:
pass
else:
s._source[key] = value
return s
[docs] def sort(self, *keys: Any) -> Any:
"""
Add sorting information to the search request. If called without
arguments it will remove all sort requirements. Otherwise it will
replace them. Acceptable arguments are::
'some.field'
'-some.other.field'
{'different.field': {'any': 'dict'}}
so for example::
s = Search().sort(
'category',
'-title',
{"price" : {"order" : "asc", "mode" : "avg"}}
)
will sort by ``category``, ``title`` (in descending order) and
``price`` in ascending order using the ``avg`` mode.
The API returns a copy of the Search object and can thus be chained.
"""
s = self._clone()
s._sort = []
for k in keys:
if isinstance(k, string_types) and k.startswith("-"):
if k[1:] == "_score":
raise IllegalOperation("Sorting by `-_score` is not allowed.")
k = {k[1:]: {"order": "desc"}}
s._sort.append(k)
return s
[docs] def collapse(
self,
field: Any = None,
inner_hits: Any = None,
max_concurrent_group_searches: Any = None,
) -> Any:
"""
Add collapsing information to the search request.
If called without providing ``field``, it will remove all collapse
requirements, otherwise it will replace them with the provided
arguments.
The API returns a copy of the Search object and can thus be chained.
"""
s = self._clone()
s._collapse = {}
if field is None:
return s
s._collapse["field"] = field
if inner_hits:
s._collapse["inner_hits"] = inner_hits
if max_concurrent_group_searches:
s._collapse["max_concurrent_group_searches"] = max_concurrent_group_searches
return s
[docs] def highlight_options(self, **kwargs: Any) -> Any:
"""
Update the global highlighting options used for this request. For
example::
s = Search()
s = s.highlight_options(order='score')
"""
s = self._clone()
s._highlight_opts.update(kwargs)
return s
[docs] def highlight(self, *fields: Any, **kwargs: Any) -> Any:
"""
Request highlighting of some fields. All keyword arguments passed in will be
used as parameters for all the fields in the ``fields`` parameter. Example::
Search().highlight('title', 'body', fragment_size=50)
will produce the equivalent of::
{
"highlight": {
"fields": {
"body": {"fragment_size": 50},
"title": {"fragment_size": 50}
}
}
}
If you want to have different options for different fields
you can call ``highlight`` twice::
Search().highlight('title', fragment_size=50).highlight('body', fragment_size=100)
which will produce::
{
"highlight": {
"fields": {
"body": {"fragment_size": 100},
"title": {"fragment_size": 50}
}
}
}
"""
s = self._clone()
for f in fields:
s._highlight[f] = kwargs
return s
[docs] def suggest(self, name: Any, text: Any, **kwargs: Any) -> Any:
"""
Add a suggestions request to the search.
:arg name: name of the suggestion
:arg text: text to suggest on
All keyword arguments will be added to the suggestions body. For example::
s = Search()
s = s.suggest('suggestion-1', 'OpenSearch', term={'field': 'body'})
"""
s = self._clone()
s._suggest[name] = {"text": text}
s._suggest[name].update(kwargs)
return s
[docs] def to_dict(self, count: bool = False, **kwargs: Any) -> Any:
"""
Serialize the search into the dictionary that will be sent over as the
request's body.
:arg count: a flag to specify if we are interested in a body for count -
no aggregations, no pagination bounds etc.
All additional keyword arguments will be included into the dictionary.
"""
d = {}
if self.query:
d["query"] = self.query.to_dict()
# count request doesn't care for sorting and other things
if not count:
if self.post_filter:
d["post_filter"] = self.post_filter.to_dict()
if self.aggs.aggs:
d.update(self.aggs.to_dict())
if self._sort:
d["sort"] = self._sort
if self._collapse:
d["collapse"] = self._collapse
d.update(recursive_to_dict(self._extra))
if self._source not in (None, {}):
d["_source"] = self._source
if self._highlight:
d["highlight"] = {"fields": self._highlight}
d["highlight"].update(self._highlight_opts)
if self._suggest:
d["suggest"] = self._suggest
if self._script_fields:
d["script_fields"] = self._script_fields
d.update(recursive_to_dict(kwargs))
return d
[docs] def count(self) -> Any:
"""
Return the number of hits matching the query and filters. Note that
only the actual number is returned.
"""
if hasattr(self, "_response") and self._response.hits.total.relation == "eq":
return self._response.hits.total.value
opensearch = get_connection(self._using)
d = self.to_dict(count=True)
# TODO: failed shards detection
return opensearch.count(index=self._index, body=d, **self._params)["count"]
[docs] def execute(self, ignore_cache: bool = False) -> Any:
"""
Execute the search and return an instance of ``Response`` wrapping all
the data.
:arg ignore_cache: if set to ``True``, consecutive calls will hit
OpenSearch, while cached result will be ignored. Defaults to `False`
"""
if ignore_cache or not hasattr(self, "_response"):
opensearch = get_connection(self._using)
self._response = self._response_class(
self,
opensearch.search(
index=self._index, body=self.to_dict(), **self._params
),
)
return self._response
[docs] def scan(self) -> Any:
"""
Turn the search into a scan search and return a generator that will
iterate over all the documents matching the query.
Use ``params`` method to specify any additional arguments you with to
pass to the underlying ``scan`` helper from ``opensearchpy``
"""
opensearch = get_connection(self._using)
for hit in scan(
opensearch, query=self.to_dict(), index=self._index, **self._params
):
yield self._get_result(hit)
[docs] def delete(self) -> Any:
"""
delete() executes the query by delegating to delete_by_query()
"""
opensearch = get_connection(self._using)
return AttrDict(
opensearch.delete_by_query(
index=self._index, body=self.to_dict(), **self._params
)
)
class MultiSearch(Request):
"""
Combine multiple :class:`~opensearchpy.Search` objects into a single
request.
"""
def __init__(self, **kwargs: Any) -> None:
super(MultiSearch, self).__init__(**kwargs)
self._searches: Any = []
def __getitem__(self, key: Any) -> Any:
return self._searches[key]
def __iter__(self) -> Any:
return iter(self._searches)
def _clone(self) -> Any:
ms = super(MultiSearch, self)._clone()
ms._searches = self._searches[:]
return ms
def add(self, search: Any) -> Any:
"""
Adds a new :class:`~opensearchpy.Search` object to the request::
ms = MultiSearch(index='my-index')
ms = ms.add(Search(doc_type=Category).filter('term', category='python'))
ms = ms.add(Search(doc_type=Blog))
"""
ms = self._clone()
ms._searches.append(search)
return ms
def to_dict(self) -> Any:
out = []
for s in self._searches:
meta = {}
if s._index:
meta["index"] = s._index
meta.update(s._params)
out.append(meta)
out.append(s.to_dict())
return out
def execute(self, ignore_cache: Any = False, raise_on_error: Any = True) -> Any:
"""
Execute the multi search request and return a list of search results.
"""
if ignore_cache or not hasattr(self, "_response"):
opensearch = get_connection(self._using)
responses = opensearch.msearch(
index=self._index, body=self.to_dict(), **self._params
)
out = []
for s, r in zip(self._searches, responses["responses"]):
if r.get("error", False):
if raise_on_error:
raise TransportError("N/A", r["error"]["type"], r["error"])
r = None
else:
r = Response(s, r)
out.append(r)
self._response = out
return self._response
__all__ = ["Q"]