fix: handle single-row batch search in ShardedIndex merge path (#22)

Treat batch_size=1 queries as single queries so usearch's 1D Matches
return type is handled correctly by all merge/filter/truncate paths.

Author: titusz

CHANGELOG.md

@@ -7,6 +7,13 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+## [0.6.1] - 2026-03-10
+
+### Fixed
+
+- `ShardedIndex.search()` raises `AxisError` when merging results from view and active shards
+    with a single-row 2D query of shape `(1, ndim)` ([#22](https://github.com/iscc/iscc-usearch/issues/22))
+
 ## [0.6.0] - 2026-02-22
 
 ### Added

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "iscc-usearch"
-version = "0.5.0"
+version = "0.6.1"
 description = "Scalable approximate nearest neighbor search for variable-length binary bit-vectors using NPHD metric."
 readme = "README.md"
 license = "Apache-2.0"

src/iscc_usearch/sharded.py

@@ -731,7 +731,10 @@ def search(
             raise ValueError("`count` must be >= 1")
 
         vectors = np.asarray(vectors)
-        is_single = vectors.ndim == 1
+        # Treat batch_size=1 as single query — usearch returns 1D Matches
+        # for single-row batches, so all downstream merge/filter/truncate
+        # logic must use the single-query path (see issue #22).
+        is_single = vectors.ndim == 1 or (vectors.ndim == 2 and vectors.shape[0] == 1)
 
         view_results: Matches | BatchMatches | None = None
         active_results: Matches | BatchMatches | None = None

tests/test_sharded_single_row_batch.py

@@ -0,0 +1,35 @@
+"""Test ShardedIndex search with single-row 2D batch input.
+
+Regression test for GitHub issue #22: AxisError when merging results from
+both view shards and active shard with a (1, ndim) shaped query vector.
+"""
+
+import numpy as np
+
+from iscc_usearch.sharded import ShardedIndex
+
+
+def test_search_single_row_batch_with_merge(tmp_path):
+    """Search with shape (1, ndim) when both view and active shards have data."""
+    ndim = 64
+    index = ShardedIndex(ndim=ndim, path=tmp_path, shard_size=4096)
+
+    # Add vectors and save to create view shards
+    vectors = np.random.rand(50, ndim).astype(np.float32)
+    index.add(list(range(50)), vectors)
+    index.save()
+
+    # Add more to active shard so merge path is triggered
+    extra = np.random.rand(10, ndim).astype(np.float32)
+    index.add(list(range(50, 60)), extra)
+
+    # Verify both view and active shards have data
+    assert index._view_shards is not None and len(index._view_shards) > 0
+    assert index._active_shard is not None and len(index._active_shard) > 0
+
+    # Single-row 2D input — this triggers the bug
+    query = np.random.rand(1, ndim).astype(np.float32)
+    result = index.search(query, count=5)
+
+    assert len(result.keys) <= 5
+    assert len(result.distances) <= 5