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test(qdrant): replace in-place Document mutations with dataclasses.replace() #3180

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test(qdrant): replace in-place Document mutations with dataclasses.replace() #3180

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6 changes: 6 additions & 0 deletions integrations/qdrant/CHANGELOG.md
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@bogdankostic bogdankostic Apr 20, 2026

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Please revert the changes made here, the Changelog is generated automatically whenever we release a new version.

Original file line number Diff line number Diff line change
@@ -1,5 +1,11 @@
# Changelog

## [Unreleased]

### 🧪 Testing

- Replace in-place `Document` dataclass mutations with `dataclasses.replace()` in sparse embedding retriever tests (#3180)

## [integrations/qdrant-v10.3.0] - 2026-03-23

### 📚 Documentation
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28 changes: 16 additions & 12 deletions integrations/qdrant/tests/test_sparse_embedding_retriever.py
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Original file line number Diff line number Diff line change
@@ -1,3 +1,5 @@
import dataclasses

import pytest
from haystack.dataclasses import Document, SparseEmbedding
from haystack.document_stores.types import FilterPolicy
Expand Down Expand Up @@ -153,9 +155,9 @@ def test_run(self, filterable_docs: list[Document], generate_sparse_embedding):
document_store = QdrantDocumentStore(location=":memory:", index="Boi", use_sparse_embeddings=True)

# Add fake sparse embedding to documents
for doc in filterable_docs:
doc.sparse_embedding = generate_sparse_embedding()

filterable_docs = [
dataclasses.replace(doc, sparse_embedding=generate_sparse_embedding()) for doc in filterable_docs
]
document_store.write_documents(filterable_docs)
retriever = QdrantSparseEmbeddingRetriever(document_store=document_store)
sparse_embedding = SparseEmbedding(indices=[0, 1, 2, 3], values=[0.1, 0.8, 0.05, 0.33])
Expand All @@ -173,9 +175,10 @@ def test_run_with_group_by(self, filterable_docs: list[Document], generate_spars
document_store = QdrantDocumentStore(location=":memory:", index="Boi", use_sparse_embeddings=True)

# Add fake sparse embedding to documents
for index, doc in enumerate(filterable_docs):
doc.sparse_embedding = generate_sparse_embedding()
doc.meta = {"group_field": index // 2} # So at least two docs have same group each time
filterable_docs = [
dataclasses.replace(doc, sparse_embedding=generate_sparse_embedding(), meta={"group_field": index // 2})
for index, doc in enumerate(filterable_docs)
] # So at least two docs have same group each time
document_store.write_documents(filterable_docs)
retriever = QdrantSparseEmbeddingRetriever(document_store=document_store)
sparse_embedding = SparseEmbedding(indices=[0, 1, 2, 3], values=[0.1, 0.8, 0.05, 0.33])
Expand All @@ -197,9 +200,9 @@ async def test_run_async(self, filterable_docs: list[Document], generate_sparse_
document_store = QdrantDocumentStore(location=":memory:", index="Boi", use_sparse_embeddings=True)

# Add fake sparse embedding to documents
for doc in filterable_docs:
doc.sparse_embedding = generate_sparse_embedding()

filterable_docs = [
dataclasses.replace(doc, sparse_embedding=generate_sparse_embedding()) for doc in filterable_docs
]
await document_store.write_documents_async(filterable_docs)
retriever = QdrantSparseEmbeddingRetriever(document_store=document_store)
sparse_embedding = SparseEmbedding(indices=[0, 1, 2, 3], values=[0.1, 0.8, 0.05, 0.33])
Expand All @@ -218,9 +221,10 @@ async def test_run_with_group_by_async(self, filterable_docs: list[Document], ge
document_store = QdrantDocumentStore(location=":memory:", index="Boi", use_sparse_embeddings=True)

# Add fake sparse embedding to documents
for index, doc in enumerate(filterable_docs):
doc.sparse_embedding = generate_sparse_embedding()
doc.meta = {"group_field": index // 2} # So at least two docs have same group each time
filterable_docs = [
dataclasses.replace(doc, sparse_embedding=generate_sparse_embedding(), meta={"group_field": index // 2})
for index, doc in enumerate(filterable_docs)
] # So at least two docs have same group each time
await document_store.write_documents_async(filterable_docs)
retriever = QdrantSparseEmbeddingRetriever(document_store=document_store)
sparse_embedding = SparseEmbedding(indices=[0, 1, 2, 3], values=[0.1, 0.8, 0.05, 0.33])
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