Seth Michael Larson
144 lines
3.7 KiB
Python
144 lines
3.7 KiB
Python
# Licensed to Elasticsearch B.V under one or more agreements.
|
|
# Elasticsearch B.V licenses this file to you under the Apache 2.0 License.
|
|
# See the LICENSE file in the project root for more information
|
|
|
|
try:
|
|
import simplejson as json
|
|
except ImportError:
|
|
import json
|
|
|
|
import uuid
|
|
from datetime import date, datetime
|
|
from decimal import Decimal
|
|
|
|
from .exceptions import SerializationError, ImproperlyConfigured
|
|
from .compat import string_types
|
|
|
|
INTEGER_TYPES = ()
|
|
FLOAT_TYPES = (Decimal,)
|
|
TIME_TYPES = (date, datetime)
|
|
|
|
try:
|
|
import numpy as np
|
|
|
|
INTEGER_TYPES += (
|
|
np.int_,
|
|
np.intc,
|
|
np.int8,
|
|
np.int16,
|
|
np.int32,
|
|
np.int64,
|
|
np.uint8,
|
|
np.uint16,
|
|
np.uint32,
|
|
np.uint64,
|
|
)
|
|
FLOAT_TYPES += (
|
|
np.float_,
|
|
np.float16,
|
|
np.float32,
|
|
np.float64,
|
|
)
|
|
except ImportError:
|
|
np = None
|
|
|
|
try:
|
|
import pandas as pd
|
|
|
|
TIME_TYPES += (pd.Timestamp,)
|
|
except ImportError:
|
|
pd = None
|
|
|
|
|
|
class TextSerializer(object):
|
|
mimetype = "text/plain"
|
|
|
|
def loads(self, s):
|
|
return s
|
|
|
|
def dumps(self, data):
|
|
if isinstance(data, string_types):
|
|
return data
|
|
|
|
raise SerializationError("Cannot serialize %r into text." % data)
|
|
|
|
|
|
class JSONSerializer(object):
|
|
mimetype = "application/json"
|
|
|
|
def default(self, data):
|
|
if isinstance(data, TIME_TYPES):
|
|
return data.isoformat()
|
|
elif isinstance(data, uuid.UUID):
|
|
return str(data)
|
|
elif isinstance(data, FLOAT_TYPES):
|
|
return float(data)
|
|
elif INTEGER_TYPES and isinstance(data, INTEGER_TYPES):
|
|
return int(data)
|
|
|
|
# Special cases for numpy and pandas types
|
|
elif np:
|
|
if isinstance(data, np.bool_):
|
|
return bool(data)
|
|
elif isinstance(data, np.datetime64):
|
|
return data.item().isoformat()
|
|
elif isinstance(data, np.ndarray):
|
|
return data.tolist()
|
|
if pd:
|
|
if isinstance(data, (pd.Series, pd.Categorical)):
|
|
return data.tolist()
|
|
elif hasattr(pd, "NA") and pd.isna(data):
|
|
return None
|
|
|
|
raise TypeError("Unable to serialize %r (type: %s)" % (data, type(data)))
|
|
|
|
def loads(self, s):
|
|
try:
|
|
return json.loads(s)
|
|
except (ValueError, TypeError) as e:
|
|
raise SerializationError(s, e)
|
|
|
|
def dumps(self, data):
|
|
# don't serialize strings
|
|
if isinstance(data, string_types):
|
|
return data
|
|
|
|
try:
|
|
return json.dumps(
|
|
data, default=self.default, ensure_ascii=False, separators=(",", ":")
|
|
)
|
|
except (ValueError, TypeError) as e:
|
|
raise SerializationError(data, e)
|
|
|
|
|
|
DEFAULT_SERIALIZERS = {
|
|
JSONSerializer.mimetype: JSONSerializer(),
|
|
TextSerializer.mimetype: TextSerializer(),
|
|
}
|
|
|
|
|
|
class Deserializer(object):
|
|
def __init__(self, serializers, default_mimetype="application/json"):
|
|
try:
|
|
self.default = serializers[default_mimetype]
|
|
except KeyError:
|
|
raise ImproperlyConfigured(
|
|
"Cannot find default serializer (%s)" % default_mimetype
|
|
)
|
|
self.serializers = serializers
|
|
|
|
def loads(self, s, mimetype=None):
|
|
if not mimetype:
|
|
deserializer = self.default
|
|
else:
|
|
# split out charset
|
|
mimetype, _, _ = mimetype.partition(";")
|
|
try:
|
|
deserializer = self.serializers[mimetype]
|
|
except KeyError:
|
|
raise SerializationError(
|
|
"Unknown mimetype, unable to deserialize: %s" % mimetype
|
|
)
|
|
|
|
return deserializer.loads(s)
|