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#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF 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 decimal
from types import FunctionType
from aenum import Enum
class long(int):
pass
class bigint(int):
pass
class short(int):
pass
FloatType = float
ShortType = short
IntType = int
LongType = long
BigIntType = bigint
TypeType = type
ListType = list
DictType = dict
SetType = set
ByteBufferType = bytes
class timestamp(float):
"""
In Python a timestamp is simply a float. This dummy class (similar to long), allows users to wrap a float
in a GLV script to make sure the value is serialized as a Gremlin timestamp.
"""
pass
class SingleByte(int):
"""
Provides a way to pass a single byte via Gremlin.
"""
def __new__(cls, b):
if -128 <= b < 128:
return int.__new__(cls, b)
else:
raise ValueError("value must be between -128 and 127 inclusive")
class SingleChar(str):
"""
Provides a way to pass a single character via Gremlin.
"""
def __new__(cls, c):
if len(c) == 1:
return str.__new__(cls, c)
else:
raise ValueError("string must contain a single character")
class GremlinType(object):
"""
Provides a way to represent a "Java class" for Gremlin.
"""
def __init__(self, gremlin_type):
self.gremlin_type = gremlin_type
class BigDecimal(object):
"""
Provides a way to represent a BigDecimal for Gremlin.
"""
def __init__(self, scale, unscaled_value):
self.scale = scale
self.unscaled_value = unscaled_value
@property
def value(self):
self._as_decimal = decimal.Decimal(self.unscaled_value)
precision = len(self._as_decimal.as_tuple().digits)
with decimal.localcontext(decimal.Context(prec=precision)):
return self._as_decimal.scaleb(-self.scale)
def __eq__(self, other):
if not isinstance(other, BigDecimal):
return False
return self.scale == other.scale and self.unscaled_value == other.unscaled_value
def __hash__(self):
return hash((self.scale, self.unscaled_value))
def __repr__(self):
return f"BigDecimal(scale={self.scale}, unscaled_value={self.unscaled_value})"
def __str__(self):
return str(self.value)
"""
Create a BigDecimal from a number that can be converted to a Decimal. Note precision may be lost during the conversion.
"""
def bigdecimal(value):
try:
decimal_value = value if isinstance(value, decimal.Decimal) else decimal.Decimal(str(value))
scale = -decimal_value.as_tuple().exponent
unscaled_value = int("".join(map(str, decimal_value.as_tuple().digits)))
except TypeError:
raise ValueError("BigDecimal does not support NaN, Infinity or -Infinity")
except Exception as err:
raise ValueError(f'Encountered error: {err}. Value must be able to convert to a Decimal.')
return BigDecimal(scale, unscaled_value if decimal_value >= 0 else -unscaled_value)
staticMethods = {}
staticEnums = {}
default_lambda_language = "gremlin-groovy"
def add_static(key, value):
if isinstance(value, Enum):
staticEnums[key] = value
else:
staticMethods[key] = value
def load_statics(global_dict):
for key in staticMethods:
global_dict[key] = staticMethods[key]
for key in staticEnums:
global_dict[key] = staticEnums[key]
def unload_statics(global_dict):
for key in staticMethods:
if key in global_dict:
del global_dict[key]
for key in staticEnums:
if key in global_dict:
del global_dict[key]