diff --git a/document_stores/elasticsearch/src/elasticsearch_haystack/document_store.py b/document_stores/elasticsearch/src/elasticsearch_haystack/document_store.py
index 0cf01d311..4f5b23cea 100644
--- a/document_stores/elasticsearch/src/elasticsearch_haystack/document_store.py
+++ b/document_stores/elasticsearch/src/elasticsearch_haystack/document_store.py
@@ -107,7 +107,7 @@ def _search_documents(self, **kwargs) -> List[Document]:
         """
 
         top_k = kwargs.get("size")
-        if top_k is None and 'knn' in kwargs and 'k' in kwargs["knn"]:
+        if top_k is None and "knn" in kwargs and "k" in kwargs["knn"]:
             top_k = kwargs["knn"]["k"]
 
         documents: List[Document] = []
diff --git a/document_stores/elasticsearch/tests/test_document_store.py b/document_stores/elasticsearch/tests/test_document_store.py
index 9376a991d..b35ba6644 100644
--- a/document_stores/elasticsearch/tests/test_document_store.py
+++ b/document_stores/elasticsearch/tests/test_document_store.py
@@ -1,9 +1,9 @@
 # SPDX-FileCopyrightText: 2023-present Silvano Cerza <silvanocerza@gmail.com>
 #
 # SPDX-License-Identifier: Apache-2.0
+import random
 from typing import List
 from unittest.mock import patch
-import random
 
 import pandas as pd
 import pytest
@@ -316,7 +316,7 @@ def test_embedding_retrieval_pagination(self, docstore: ElasticsearchDocumentSto
         Test that handling of pagination works as expected, when the matching documents are > 10.
         """
 
-        docs = [Document(content=f"Document {i}", embedding=[random.random() for _ in range(4)]) for i in range(20)]
+        docs = [Document(content=f"Document {i}", embedding=[random.random() for _ in range(4)]) for i in range(20)] # noqa: S311
 
         docstore.write_documents(docs)
         results = docstore._embedding_retrieval(query_embedding=[0.1, 0.1, 0.1, 0.1], top_k=11, filters={})