300 lines
12 KiB
Python
300 lines
12 KiB
Python
# Copyright 2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"). You
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# may not use this file except in compliance with the License. A copy of
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# the License is located at
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#
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# http://aws.amazon.com/apache2.0/
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#
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# or in the "license" file accompanying this file. This file is
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# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
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# ANY KIND, either express or implied. See the License for the specific
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# language governing permissions and limitations under the License.
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import copy
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from collections import Mapping, MutableSequence
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from boto3.dynamodb.types import TypeSerializer, TypeDeserializer
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from boto3.dynamodb.conditions import ConditionBase
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from boto3.dynamodb.conditions import ConditionExpressionBuilder
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from boto3.docs.utils import DocumentModifiedShape
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def register_high_level_interface(base_classes, **kwargs):
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base_classes.insert(0, DynamoDBHighLevelResource)
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def copy_dynamodb_params(params, **kwargs):
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return copy.deepcopy(params)
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class DynamoDBHighLevelResource(object):
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def __init__(self, *args, **kwargs):
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super(DynamoDBHighLevelResource, self).__init__(*args, **kwargs)
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# Apply handler that creates a copy of the user provided dynamodb
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# item such that it can be modified.
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self.meta.client.meta.events.register(
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'provide-client-params.dynamodb',
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copy_dynamodb_params,
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unique_id='dynamodb-create-params-copy'
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)
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self._injector = TransformationInjector()
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# Apply the handler that generates condition expressions including
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# placeholders.
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self.meta.client.meta.events.register(
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'before-parameter-build.dynamodb',
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self._injector.inject_condition_expressions,
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unique_id='dynamodb-condition-expression')
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# Apply the handler that serializes the request from python
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# types to dynamodb types.
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self.meta.client.meta.events.register(
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'before-parameter-build.dynamodb',
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self._injector.inject_attribute_value_input,
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unique_id='dynamodb-attr-value-input')
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# Apply the handler that deserializes the response from dynamodb
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# types to python types.
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self.meta.client.meta.events.register(
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'after-call.dynamodb',
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self._injector.inject_attribute_value_output,
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unique_id='dynamodb-attr-value-output')
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# Apply the documentation customizations to account for
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# the transformations.
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attr_value_shape_docs = DocumentModifiedShape(
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'AttributeValue',
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new_type='valid DynamoDB type',
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new_description=(
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'- The value of the attribute. The valid value types are '
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'listed in the '
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':ref:`DynamoDB Reference Guide<ref_valid_dynamodb_types>`.'
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),
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new_example_value=(
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'\'string\'|123|Binary(b\'bytes\')|True|None|set([\'string\'])'
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'|set([123])|set([Binary(b\'bytes\')])|[]|{}')
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)
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key_expression_shape_docs = DocumentModifiedShape(
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'KeyExpression',
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new_type=(
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'condition from :py:class:`boto3.dynamodb.conditions.Key` '
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'method'
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),
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new_description=(
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'The condition(s) a key(s) must meet. Valid conditions are '
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'listed in the '
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':ref:`DynamoDB Reference Guide<ref_dynamodb_conditions>`.'
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),
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new_example_value='Key(\'mykey\').eq(\'myvalue\')'
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)
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con_expression_shape_docs = DocumentModifiedShape(
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'ConditionExpression',
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new_type=(
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'condition from :py:class:`boto3.dynamodb.conditions.Attr` '
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'method'
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),
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new_description=(
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'The condition(s) an attribute(s) must meet. Valid conditions '
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'are listed in the '
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':ref:`DynamoDB Reference Guide<ref_dynamodb_conditions>`.'
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),
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new_example_value='Attr(\'myattribute\').eq(\'myvalue\')'
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)
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self.meta.client.meta.events.register(
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'docs.*.dynamodb.*.complete-section',
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attr_value_shape_docs.replace_documentation_for_matching_shape,
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unique_id='dynamodb-attr-value-docs')
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self.meta.client.meta.events.register(
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'docs.*.dynamodb.*.complete-section',
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key_expression_shape_docs.replace_documentation_for_matching_shape,
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unique_id='dynamodb-key-expression-docs')
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self.meta.client.meta.events.register(
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'docs.*.dynamodb.*.complete-section',
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con_expression_shape_docs.replace_documentation_for_matching_shape,
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unique_id='dynamodb-cond-expression-docs')
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class TransformationInjector(object):
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"""Injects the transformations into the user provided parameters."""
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def __init__(self, transformer=None, condition_builder=None,
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serializer=None, deserializer=None):
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self._transformer = transformer
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if transformer is None:
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self._transformer = ParameterTransformer()
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self._condition_builder = condition_builder
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if condition_builder is None:
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self._condition_builder = ConditionExpressionBuilder()
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self._serializer = serializer
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if serializer is None:
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self._serializer = TypeSerializer()
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self._deserializer = deserializer
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if deserializer is None:
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self._deserializer = TypeDeserializer()
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def inject_condition_expressions(self, params, model, **kwargs):
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"""Injects the condition expression transformation into the parameters
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This injection includes transformations for ConditionExpression shapes
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and KeyExpression shapes. It also handles any placeholder names and
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values that are generated when transforming the condition expressions.
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"""
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self._condition_builder.reset()
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generated_names = {}
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generated_values = {}
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# Create and apply the Condition Expression transformation.
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transformation = ConditionExpressionTransformation(
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self._condition_builder,
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placeholder_names=generated_names,
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placeholder_values=generated_values,
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is_key_condition=False
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)
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self._transformer.transform(
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params, model.input_shape, transformation,
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'ConditionExpression')
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# Create and apply the Key Condition Expression transformation.
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transformation = ConditionExpressionTransformation(
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self._condition_builder,
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placeholder_names=generated_names,
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placeholder_values=generated_values,
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is_key_condition=True
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)
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self._transformer.transform(
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params, model.input_shape, transformation,
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'KeyExpression')
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expr_attr_names_input = 'ExpressionAttributeNames'
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expr_attr_values_input = 'ExpressionAttributeValues'
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# Now that all of the condition expression transformation are done,
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# update the placeholder dictionaries in the request.
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if expr_attr_names_input in params:
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params[expr_attr_names_input].update(generated_names)
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else:
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if generated_names:
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params[expr_attr_names_input] = generated_names
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if expr_attr_values_input in params:
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params[expr_attr_values_input].update(generated_values)
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else:
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if generated_values:
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params[expr_attr_values_input] = generated_values
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def inject_attribute_value_input(self, params, model, **kwargs):
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"""Injects DynamoDB serialization into parameter input"""
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self._transformer.transform(
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params, model.input_shape, self._serializer.serialize,
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'AttributeValue')
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def inject_attribute_value_output(self, parsed, model, **kwargs):
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"""Injects DynamoDB deserialization into responses"""
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if model.output_shape is not None:
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self._transformer.transform(
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parsed, model.output_shape, self._deserializer.deserialize,
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'AttributeValue'
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)
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class ConditionExpressionTransformation(object):
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"""Provides a transformation for condition expressions
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The ``ParameterTransformer`` class can call this class directly
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to transform the condition expressions in the parameters provided.
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"""
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def __init__(self, condition_builder, placeholder_names,
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placeholder_values, is_key_condition=False):
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self._condition_builder = condition_builder
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self._placeholder_names = placeholder_names
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self._placeholder_values = placeholder_values
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self._is_key_condition = is_key_condition
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def __call__(self, value):
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if isinstance(value, ConditionBase):
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# Create a conditional expression string with placeholders
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# for the provided condition.
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built_expression = self._condition_builder.build_expression(
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value, is_key_condition=self._is_key_condition)
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self._placeholder_names.update(
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built_expression.attribute_name_placeholders)
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self._placeholder_values.update(
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built_expression.attribute_value_placeholders)
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return built_expression.condition_expression
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# Use the user provided value if it is not a ConditonBase object.
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return value
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class ParameterTransformer(object):
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"""Transforms the input to and output from botocore based on shape"""
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def transform(self, params, model, transformation, target_shape):
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"""Transforms the dynamodb input to or output from botocore
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It applies a specified transformation whenever a specific shape name
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is encountered while traversing the parameters in the dictionary.
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:param params: The parameters structure to transform.
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:param model: The operation model.
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:param transformation: The function to apply the parameter
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:param target_shape: The name of the shape to apply the
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transformation to
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"""
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self._transform_parameters(
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model, params, transformation, target_shape)
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def _transform_parameters(self, model, params, transformation,
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target_shape):
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type_name = model.type_name
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if type_name in ['structure', 'map', 'list']:
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getattr(self, '_transform_%s' % type_name)(
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model, params, transformation, target_shape)
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def _transform_structure(self, model, params, transformation,
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target_shape):
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if not isinstance(params, Mapping):
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return
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for param in params:
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if param in model.members:
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member_model = model.members[param]
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member_shape = member_model.name
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if member_shape == target_shape:
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params[param] = transformation(params[param])
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else:
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self._transform_parameters(
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member_model, params[param], transformation,
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target_shape)
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def _transform_map(self, model, params, transformation, target_shape):
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if not isinstance(params, Mapping):
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return
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value_model = model.value
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value_shape = value_model.name
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for key, value in params.items():
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if value_shape == target_shape:
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params[key] = transformation(value)
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else:
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self._transform_parameters(
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value_model, params[key], transformation, target_shape)
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def _transform_list(self, model, params, transformation, target_shape):
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if not isinstance(params, MutableSequence):
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return
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member_model = model.member
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member_shape = member_model.name
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for i, item in enumerate(params):
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if member_shape == target_shape:
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params[i] = transformation(item)
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else:
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self._transform_parameters(
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member_model, params[i], transformation, target_shape)
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