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# Licensed to Elasticsearch B.V. under one or more contributor
# license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright
# ownership. Elasticsearch B.V. licenses this file to you under
# the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
import uuid
from datetime import datetime
from decimal import Decimal
import pytest
try:
import pyarrow as pa
from elasticsearch.serializer import PyArrowSerializer
except ImportError:
pa = None
try:
import numpy as np
import pandas as pd
except ImportError:
np = pd = None
import re
from elasticsearch import Elasticsearch
from elasticsearch.exceptions import SerializationError
from elasticsearch.serializer import JSONSerializer, OrjsonSerializer, TextSerializer
requires_numpy_and_pandas = pytest.mark.skipif(
np is None or pd is None, reason="Test requires numpy and pandas to be available"
)
@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)}
)
@requires_numpy_and_pandas
def test_decimal_serialization(json_serializer):
assert b'{"d":3.8}' == json_serializer.dumps({"d": Decimal("3.8")})
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(json_serializer):
assert b'{"d":true}' == json_serializer.dumps({"d": np.bool_(True)})
@requires_numpy_and_pandas
def test_serializes_numpy_integers(json_serializer):
for np_type in (
np.int_,
np.int8,
np.int16,
np.int32,
np.int64,
):
assert json_serializer.dumps({"d": np_type(-1)}) == b'{"d":-1}'
for np_type in (
np.uint8,
np.uint16,
np.uint32,
np.uint64,
):
assert json_serializer.dumps({"d": np_type(1)}) == b'{"d":1}'
@requires_numpy_and_pandas
def test_serializes_numpy_floats(json_serializer):
for np_type in (
np.float32,
np.float64,
):
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(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(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]]}' == 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": 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(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(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(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(json_serializer):
with pytest.raises(SerializationError):
json_serializer.dumps({"d": pd.NaT})
@requires_numpy_and_pandas
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"]}' == json_serializer.dumps({"d": cat})
cat = pd.Categorical([1, 2, 3], categories=[1, 2, 3])
assert b'{"d":[1,2,3]}' == json_serializer.dumps({"d": cat})
@pytest.mark.skipif(pa is None, reason="Test requires pyarrow to be available")
def test_pyarrow_loads():
data = [
pa.array([1, 2, 3, 4]),
pa.array(["foo", "bar", "baz", None]),
pa.array([True, None, False, True]),
]
batch = pa.record_batch(data, names=["f0", "f1", "f2"])
sink = pa.BufferOutputStream()
with pa.ipc.new_stream(sink, batch.schema) as writer:
writer.write_batch(batch)
serializer = PyArrowSerializer()
assert serializer.loads(sink.getvalue()).to_pydict() == {
"f0": [1, 2, 3, 4],
"f1": ["foo", "bar", "baz", None],
"f2": [True, None, False, True],
}
def test_json_raises_serialization_error_on_dump_error(json_serializer):
with pytest.raises(SerializationError):
json_serializer.dumps(object())
def test_raises_serialization_error_on_load_error(json_serializer):
with pytest.raises(SerializationError):
json_serializer.loads(object())
with pytest.raises(SerializationError):
json_serializer.loads("")
with pytest.raises(SerializationError):
json_serializer.loads("{{")
def test_strings_are_left_untouched():
assert b"\xe4\xbd\xa0\xe5\xa5\xbd" == TextSerializer().dumps("你好")
def test_text_raises_serialization_error_on_dump_error():
with pytest.raises(SerializationError):
TextSerializer().dumps({})
class TestDeserializer:
def setup_method(self, _):
self.serializers = Elasticsearch("http://localhost:9200").transport.serializers
def test_deserializes_json_by_default(self):
assert {"some": "data"} == self.serializers.loads('{"some":"data"}')
@pytest.mark.parametrize("data", ['{"some":"data"}', b'{"some":"data"}'])
def test_deserializes_text_with_correct_ct(self, data):
assert '{"some":"data"}' == self.serializers.loads(data, "text/plain")
assert '{"some":"data"}' == self.serializers.loads(
data, "text/plain; charset=whatever"
)
def test_deserialize_compatibility_header(self):
for content_type in (
"application/vnd.elasticsearch+json;compatible-with=8",
"application/vnd.elasticsearch+json; compatible-with=8",
"application/vnd.elasticsearch+json;compatible-with=9",
"application/vnd.elasticsearch+json; compatible-with=9",
):
assert {"some": "data"} == self.serializers.loads(
'{"some":"data"}', content_type
)
assert b'{"some":"data"}' == self.serializers.dumps(
'{"some":"data"}', content_type
)
for content_type in (
"application/vnd.elasticsearch+x-ndjson;compatible-with=8",
"application/vnd.elasticsearch+x-ndjson; compatible-with=8",
"application/vnd.elasticsearch+x-ndjson;compatible-with=9",
"application/vnd.elasticsearch+x-ndjson; compatible-with=9",
):
assert b'{"some":"data"}\n{"some":"data"}\n' == self.serializers.dumps(
['{"some":"data"}', {"some": "data"}], content_type
)
assert [{"some": "data"}, {"some": "data"}] == self.serializers.loads(
b'{"some":"data"}\n{"some":"data"}\n', content_type
)
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