Add optional orjson support

docs/guide/configuration.asciidoc

@@ -264,6 +264,24 @@ es = Elasticsearch(
 )
 ------------------------------------
 
+If the `orjson` package is installed, you can use the faster ``OrjsonSerializer`` for the default mimetype (``application/json``):
+
+[source,python]
+------------------------------------
+from elasticsearch import Elasticsearch, OrjsonSerializer
+
+es = Elasticsearch(
+    ...,
+    serializer=OrjsonSerializer()
+)
+------------------------------------
+
+orjson is particularly fast when serializing vectors as it has native numpy support. This will be the default in a future release. Note that you can install orjson with the `orjson` extra:
+
+[source,sh]
+--------------------------------------------
+$ python -m pip install elasticsearch[orjson]
+--------------------------------------------
 
 [discrete]
 [[nodes]]

elasticsearch_serverless/__init__.py

@@ -63,6 +63,11 @@
 )
 from .serializer import JSONSerializer, JsonSerializer
 
+try:
+    from .serializer import OrjsonSerializer
+except ImportError:
+    OrjsonSerializer = None  # type: ignore[assignment,misc]
+
 # Only raise one warning per deprecation message so as not
 # to spam up the user if the same action is done multiple times.
 warnings.simplefilter("default", category=ElasticsearchWarning, append=True)
@@ -86,6 +91,8 @@
     "UnsupportedProductError",
     "ElasticsearchWarning",
 ]
+if OrjsonSerializer is not None:
+    __all__.append("OrjsonSerializer")
 
 fixup_module_metadata(__name__, globals())
 del fixup_module_metadata

elasticsearch_serverless/serializer.py

@@ -41,6 +41,13 @@
     "MapboxVectorTileSerializer",
 ]
 
+try:
+    from elastic_transport import OrjsonSerializer as _OrjsonSerializer
+
+    __all__.append("OrjsonSerializer")
+except ImportError:
+    _OrjsonSerializer = None  # type: ignore[assignment,misc]
+
 
 class JsonSerializer(_JsonSerializer):
     mimetype: ClassVar[str] = "application/json"
@@ -73,6 +80,13 @@ def default(self, data: Any) -> Any:
         raise TypeError(f"Unable to serialize {data!r} (type: {type(data)})")
 
 
+if _OrjsonSerializer is not None:
+
+    class OrjsonSerializer(JsonSerializer, _OrjsonSerializer):
+        def default(self, data: Any) -> Any:
+            return JsonSerializer.default(self, data)
+
+
 class NdjsonSerializer(JsonSerializer, _NdjsonSerializer):
     mimetype: ClassVar[str] = "application/x-ndjson"
 

noxfile.py

@@ -86,7 +86,7 @@ def lint(session):
     session.run("python", "utils/license-headers.py", "check", *SOURCE_FILES)
 
     # Workaround to make '-r' to still work despite uninstalling aiohttp below.
-    session.install(".[async,requests]", env=INSTALL_ENV)
+    session.install(".[async,requests,orjson]", env=INSTALL_ENV)
 
     # Run mypy on the package and then the type examples separately for
     # the two different mypy use-cases, ourselves and our users.
@@ -118,5 +118,5 @@ def lint(session):
 
 @nox.session()
 def docs(session):
-    session.install(".[docs]")
+    session.install(".[docs,orjson]")
     session.run("sphinx-build", "docs/sphinx/", "docs/sphinx/_build", "-b", "html")

pyproject.toml

@@ -44,12 +44,9 @@ dependencies = [
 ]
 
 [project.optional-dependencies]
-async = [
-    "aiohttp>=3,<4",
-]
-requests = [
-    "requests>=2.4.0, <3.0.0",
-]
+async = ["aiohttp>=3,<4"]
+requests = ["requests>=2.4.0, <3.0.0" ]
+orjson = ["orjson>=3"]
 dev = [
     "requests>=2, <3",
     "aiohttp",
@@ -66,6 +63,7 @@ dev = [
     "twine",
     "build",
     "nox",
+    "orjson",
     "numpy",
     "pandas",
     "mapbox-vector-tile",

test_elasticsearch_serverless/test_serializer.py

@@ -16,7 +16,6 @@
 #  specific language governing permissions and limitations
 #  under the License.
 
-import sys
 import uuid
 from datetime import datetime
 from decimal import Decimal
@@ -33,131 +32,138 @@
 
 from elasticsearch_serverless import Elasticsearch
 from elasticsearch_serverless.exceptions import SerializationError
-from elasticsearch_serverless.serializer import JSONSerializer, TextSerializer
+from elasticsearch_serverless.serializer import (
+    JSONSerializer,
+    OrjsonSerializer,
+    TextSerializer,
+)
 
 requires_numpy_and_pandas = pytest.mark.skipif(
-    np is None or pd is None, reason="Test requires numpy or pandas to be available"
+    np is None or pd is None, reason="Test requires numpy and pandas to be available"
 )
 
 
-def test_datetime_serialization():
-    assert b'{"d":"2010-10-01T02:30:00"}' == JSONSerializer().dumps(
+@pytest.fixture(params=[JSONSerializer, OrjsonSerializer])
+def json_serializer(request: pytest.FixtureRequest):
+    yield request.param()
+
+
+def test_datetime_serialization(json_serializer):
+    assert b'{"d":"2010-10-01T02:30:00"}' == json_serializer.dumps(
         {"d": datetime(2010, 10, 1, 2, 30)}
     )
 
 
-def test_decimal_serialization():
-    requires_numpy_and_pandas()
+def test_decimal_serialization(json_serializer):
+    assert b'{"d":3.8}' == json_serializer.dumps({"d": Decimal("3.8")})
 
-    if sys.version_info[:2] == (2, 6):
-        pytest.skip("Float rounding is broken in 2.6.")
-    assert b'{"d":3.8}' == JSONSerializer().dumps({"d": Decimal("3.8")})
 
-
-def test_uuid_serialization():
-    assert b'{"d":"00000000-0000-0000-0000-000000000003"}' == JSONSerializer().dumps(
+def test_uuid_serialization(json_serializer):
+    assert b'{"d":"00000000-0000-0000-0000-000000000003"}' == json_serializer.dumps(
         {"d": uuid.UUID("00000000-0000-0000-0000-000000000003")}
     )
 
 
 @requires_numpy_and_pandas
-def test_serializes_numpy_bool():
-    assert b'{"d":true}' == JSONSerializer().dumps({"d": np.bool_(True)})
+def test_serializes_numpy_bool(json_serializer):
+    assert b'{"d":true}' == json_serializer.dumps({"d": np.bool_(True)})
 
 
 @requires_numpy_and_pandas
-def test_serializes_numpy_integers():
-    ser = JSONSerializer()
+def test_serializes_numpy_integers(json_serializer):
     for np_type in (
         np.int_,
         np.int8,
         np.int16,
         np.int32,
         np.int64,
     ):
-        assert ser.dumps({"d": np_type(-1)}) == b'{"d":-1}'
+        assert json_serializer.dumps({"d": np_type(-1)}) == b'{"d":-1}'
 
     for np_type in (
         np.uint8,
         np.uint16,
         np.uint32,
         np.uint64,
     ):
-        assert ser.dumps({"d": np_type(1)}) == b'{"d":1}'
+        assert json_serializer.dumps({"d": np_type(1)}) == b'{"d":1}'
 
 
 @requires_numpy_and_pandas
-def test_serializes_numpy_floats():
-    ser = JSONSerializer()
+def test_serializes_numpy_floats(json_serializer):
     for np_type in (
         np.float32,
         np.float64,
     ):
-        assert re.search(rb'^{"d":1\.2[\d]*}$', ser.dumps({"d": np_type(1.2)}))
+        assert re.search(
+            rb'^{"d":1\.2[\d]*}$', json_serializer.dumps({"d": np_type(1.2)})
+        )
 
 
 @requires_numpy_and_pandas
-def test_serializes_numpy_datetime():
-    assert b'{"d":"2010-10-01T02:30:00"}' == JSONSerializer().dumps(
+def test_serializes_numpy_datetime(json_serializer):
+    assert b'{"d":"2010-10-01T02:30:00"}' == json_serializer.dumps(
         {"d": np.datetime64("2010-10-01T02:30:00")}
     )
 
 
 @requires_numpy_and_pandas
-def test_serializes_numpy_ndarray():
-    assert b'{"d":[0,0,0,0,0]}' == JSONSerializer().dumps(
+def test_serializes_numpy_ndarray(json_serializer):
+    assert b'{"d":[0,0,0,0,0]}' == json_serializer.dumps(
         {"d": np.zeros((5,), dtype=np.uint8)}
     )
     # This isn't useful for Elasticsearch, just want to make sure it works.
-    assert b'{"d":[[0,0],[0,0]]}' == JSONSerializer().dumps(
+    assert b'{"d":[[0,0],[0,0]]}' == json_serializer.dumps(
         {"d": np.zeros((2, 2), dtype=np.uint8)}
     )
 
 
 @requires_numpy_and_pandas
 def test_serializes_numpy_nan_to_nan():
-    assert b'{"d":NaN}' == JSONSerializer().dumps({"d": np.nan})
+    assert b'{"d":NaN}' == JSONSerializer().dumps({"d": float("NaN")})
+    # NaN is invalid JSON, and orjson silently converts it to null
+    assert b'{"d":null}' == OrjsonSerializer().dumps({"d": float("NaN")})
 
 
 @requires_numpy_and_pandas
-def test_serializes_pandas_timestamp():
-    assert b'{"d":"2010-10-01T02:30:00"}' == JSONSerializer().dumps(
+def test_serializes_pandas_timestamp(json_serializer):
+    assert b'{"d":"2010-10-01T02:30:00"}' == json_serializer.dumps(
         {"d": pd.Timestamp("2010-10-01T02:30:00")}
     )
 
 
 @requires_numpy_and_pandas
-def test_serializes_pandas_series():
-    assert b'{"d":["a","b","c","d"]}' == JSONSerializer().dumps(
+def test_serializes_pandas_series(json_serializer):
+    assert b'{"d":["a","b","c","d"]}' == json_serializer.dumps(
         {"d": pd.Series(["a", "b", "c", "d"])}
     )
 
 
 @requires_numpy_and_pandas
 @pytest.mark.skipif(not hasattr(pd, "NA"), reason="pandas.NA is required")
-def test_serializes_pandas_na():
-    assert b'{"d":null}' == JSONSerializer().dumps({"d": pd.NA})
+def test_serializes_pandas_na(json_serializer):
+    assert b'{"d":null}' == json_serializer.dumps({"d": pd.NA})
 
 
 @requires_numpy_and_pandas
 @pytest.mark.skipif(not hasattr(pd, "NaT"), reason="pandas.NaT required")
-def test_raises_serialization_error_pandas_nat():
+def test_raises_serialization_error_pandas_nat(json_serializer):
     with pytest.raises(SerializationError):
-        JSONSerializer().dumps({"d": pd.NaT})
+        json_serializer.dumps({"d": pd.NaT})
 
 
 @requires_numpy_and_pandas
-def test_serializes_pandas_category():
+def test_serializes_pandas_category(json_serializer):
     cat = pd.Categorical(["a", "c", "b", "a"], categories=["a", "b", "c"])
-    assert b'{"d":["a","c","b","a"]}' == JSONSerializer().dumps({"d": cat})
+    assert b'{"d":["a","c","b","a"]}' == json_serializer.dumps({"d": cat})
 
     cat = pd.Categorical([1, 2, 3], categories=[1, 2, 3])
-    assert b'{"d":[1,2,3]}' == JSONSerializer().dumps({"d": cat})
+    assert b'{"d":[1,2,3]}' == json_serializer.dumps({"d": cat})
 
 
-def test_json_raises_serialization_error_on_dump_error():
+def test_json_raises_serialization_error_on_dump_error(json_serializer):
     with pytest.raises(SerializationError):
-        JSONSerializer().dumps(object())
+        json_serializer.dumps(object())
 
 
 def test_raises_serialization_error_on_load_error():