167 lines
4.6 KiB
Python
Executable File
167 lines
4.6 KiB
Python
Executable File
# Licensed to Elasticsearch B.V. under one or more contributor
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# license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright
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# ownership. Elasticsearch B.V. licenses this file to you under
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# the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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try:
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import simplejson as json
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except ImportError:
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import json
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import uuid
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from datetime import date, datetime
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from decimal import Decimal
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from .compat import string_types
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from .exceptions import ImproperlyConfigured, SerializationError
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INTEGER_TYPES = ()
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FLOAT_TYPES = (Decimal,)
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TIME_TYPES = (date, datetime)
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try:
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import numpy as np
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INTEGER_TYPES += (
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np.int_,
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np.intc,
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np.int8,
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np.int16,
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np.int32,
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np.int64,
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np.uint8,
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np.uint16,
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np.uint32,
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np.uint64,
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)
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FLOAT_TYPES += (
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np.float_,
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np.float16,
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np.float32,
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np.float64,
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)
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except ImportError:
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np = None
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try:
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import pandas as pd
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TIME_TYPES += (pd.Timestamp,)
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except ImportError:
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pd = None
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class Serializer(object):
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mimetype = ""
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def loads(self, s):
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raise NotImplementedError()
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def dumps(self, data):
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raise NotImplementedError()
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class TextSerializer(Serializer):
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mimetype = "text/plain"
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def loads(self, s):
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return s
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def dumps(self, data):
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if isinstance(data, string_types):
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return data
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raise SerializationError("Cannot serialize %r into text." % data)
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class JSONSerializer(Serializer):
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mimetype = "application/json"
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def default(self, data):
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if isinstance(data, TIME_TYPES) and getattr(pd, "NaT", None) is not data:
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return data.isoformat()
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elif isinstance(data, uuid.UUID):
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return str(data)
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elif isinstance(data, FLOAT_TYPES):
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return float(data)
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elif INTEGER_TYPES and isinstance(data, INTEGER_TYPES):
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return int(data)
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# Special cases for numpy and pandas types
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elif np:
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if isinstance(data, np.bool_):
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return bool(data)
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elif isinstance(data, np.datetime64):
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return data.item().isoformat()
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elif isinstance(data, np.ndarray):
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return data.tolist()
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if pd:
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if isinstance(data, (pd.Series, pd.Categorical)):
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return data.tolist()
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elif data is getattr(pd, "NA", None):
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return None
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raise TypeError("Unable to serialize %r (type: %s)" % (data, type(data)))
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def loads(self, s):
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try:
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return json.loads(s)
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except (ValueError, TypeError) as e:
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raise SerializationError(s, e)
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def dumps(self, data):
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# don't serialize strings
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if isinstance(data, string_types):
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return data
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try:
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return json.dumps(
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data, default=self.default, ensure_ascii=False, separators=(",", ":")
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)
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except (ValueError, TypeError) as e:
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raise SerializationError(data, e)
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DEFAULT_SERIALIZERS = {
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JSONSerializer.mimetype: JSONSerializer(),
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TextSerializer.mimetype: TextSerializer(),
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}
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class Deserializer(object):
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def __init__(self, serializers, default_mimetype="application/json"):
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try:
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self.default = serializers[default_mimetype]
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except KeyError:
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raise ImproperlyConfigured(
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"Cannot find default serializer (%s)" % default_mimetype
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)
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self.serializers = serializers
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def loads(self, s, mimetype=None):
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if not mimetype:
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deserializer = self.default
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else:
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# split out charset
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mimetype, _, _ = mimetype.partition(";")
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try:
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deserializer = self.serializers[mimetype]
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except KeyError:
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raise SerializationError(
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"Unknown mimetype, unable to deserialize: %s" % mimetype
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)
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return deserializer.loads(s)
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