# 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.
import copy
from typing import Any, Dict, Sequence, cast
from opensearchpy._async.helpers.actions import aiter, async_scan
from opensearchpy.connection.async_connections import get_connection
from opensearchpy.exceptions import IllegalOperation, TransportError
from opensearchpy.helpers.aggs import A
from opensearchpy.helpers.query import Bool, Q
from opensearchpy.helpers.response import Response
from opensearchpy.helpers.search import AggsProxy, ProxyDescriptor, QueryProxy, Request
from opensearchpy.helpers.utils import AttrDict, recursive_to_dict
class AsyncSearch(Request):
query = ProxyDescriptor("query")
post_filter = ProxyDescriptor("post_filter")
def __init__(self, **kwargs: Any) -> None:
"""
Search request to opensearch.
:arg using: `AsyncOpenSearch` 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().__init__(**kwargs)
self.aggs = AggsProxy(self)
self._sort: Sequence[Any] = []
self._collapse: Dict[str, Any] = {}
self._source: Any = None
self._highlight: Any = {}
self._highlight_opts: Any = {}
self._suggest: Any = {}
self._script_fields: Any = {}
self._response_class: Any = 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)]))
def __getitem__(self, n: Any) -> Any:
"""
Support slicing the `AsyncSearch` instance for pagination.
Slicing equates to the from/size parameters. E.g.::
s = AsyncSearch().query(...)[0:25]
is equivalent to::
s = AsyncSearch().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("AsyncSearch 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("AsyncSearch does not support negative indexing.")
s._extra["from"] = n
s._extra["size"] = 1
return s
@classmethod
def from_dict(cls, d: Any) -> Any:
"""
Construct a new `AsyncSearch` instance from a raw dict containing the search
body. Useful when migrating from raw dictionaries.
Example::
s = AsyncSearch.from_dict({
"query": {
"bool": {
"must": [...]
}
},
"aggs": {...}
})
s = s.filter('term', published=True)
"""
s = cls()
s.update_from_dict(d)
return s
def _clone(self) -> "AsyncSearch":
"""
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 = cast(AsyncSearch, super()._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()
s._collapse = self._collapse.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
def response_class(self, cls: Any) -> Any:
"""
Override the default wrapper used for the response.
"""
s = self._clone()
s._response_class = cls
return s
def update_from_dict(self, d: Any) -> "AsyncSearch":
"""
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 aggs.items()}
}
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
def script_fields(self, **kwargs: Any) -> Any:
"""
Define script fields to be calculated on hits.
Example::
s = AsyncSearch()
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], str):
kwargs[name] = {"script": kwargs[name]}
s._script_fields.update(kwargs)
return s
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 = AsyncSearch()
s = s.source(includes=['obj1.*'], excludes=["*.description"])
s = AsyncSearch()
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
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 = AsyncSearch().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 AsyncSearch object and can thus be chained.
"""
s = self._clone()
s._sort = []
for k in keys:
if isinstance(k, str) 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
def collapse(
self,
field: Any = None,
inner_hits: Any = None,
max_concurrent_group_searches: Any = None,
) -> "AsyncSearch":
"""
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 AsyncSearch 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
def highlight_options(self, **kwargs: Any) -> Any:
"""
Update the global highlighting options used for this request. For
example::
s = AsyncSearch()
s = s.highlight_options(order='score')
"""
s = self._clone()
s._highlight_opts.update(kwargs)
return s
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::
AsyncSearch().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::
AsyncSearch().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
def suggest(self, name: str, text: str, **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 = AsyncSearch()
s = s.suggest('suggestion-1', 'AsyncOpenSearch', term={'field': 'body'})
"""
s = self._clone()
s._suggest[name] = {"text": text}
s._suggest[name].update(kwargs)
return s
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
async 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 = await get_connection(self._using)
d = self.to_dict(count=True)
# TODO: failed shards detection
return (await opensearch.count(index=self._index, body=d, **self._params))[
"count"
]
async 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
AsyncOpenSearch, while cached result will be ignored. Defaults to `False`
"""
if ignore_cache or not hasattr(self, "_response"):
opensearch = await get_connection(self._using)
self._response = self._response_class(
self,
await opensearch.search(
index=self._index, body=self.to_dict(), **self._params
),
)
return self._response
async 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 ``async_scan`` helper from ``opensearchpy``
"""
opensearch = await get_connection(self._using)
async for hit in aiter(
async_scan(
opensearch, query=self.to_dict(), index=self._index, **self._params
)
):
yield self._get_result(hit)
async def delete(self) -> Any:
"""
delete() executes the query by delegating to delete_by_query()
"""
opensearch = await get_connection(self._using)
return AttrDict(
await opensearch.delete_by_query(
index=self._index, body=self.to_dict(), **self._params
)
)
class AsyncMultiSearch(Request):
"""
Combine multiple :class:`~opensearchpy.AsyncSearch` objects into a single
request.
"""
def __init__(self, **kwargs: Any) -> None:
super().__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()._clone()
ms._searches = self._searches[:]
return ms
def add(self, search: Any) -> Any:
"""
Adds a new :class:`~opensearchpy.AsyncSearch` object to the request::
ms = AsyncMultiSearch(index='my-index')
ms = ms.add(AsyncSearch(doc_type=Category).filter('term', category='python'))
ms = ms.add(AsyncSearch(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
async def execute(
self, ignore_cache: bool = False, raise_on_error: bool = True
) -> Any:
"""
Execute the multi search request and return a list of search results.
"""
if ignore_cache or not hasattr(self, "_response"):
opensearch = await get_connection(self._using)
responses = await 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