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Please provide a description of the function:def _construct_body_s3_dict(self):
if isinstance(self.definition_uri, dict):
if not self.definition_uri.get("Bucket", None) or not self.definition_uri.get("Key", None):
# DefinitionUri is a dictionary but does not contain Bucket or Key property
raise InvalidResourceException(self.logical_id,
"'DefinitionUri' requires Bucket and Key properties to be specified")
s3_pointer = self.definition_uri
else:
# DefinitionUri is a string
s3_pointer = parse_s3_uri(self.definition_uri)
if s3_pointer is None:
raise InvalidResourceException(self.logical_id,
'\'DefinitionUri\' is not a valid S3 Uri of the form '
'"s3://bucket/key" with optional versionId query parameter.')
body_s3 = {
'Bucket': s3_pointer['Bucket'],
'Key': s3_pointer['Key']
}
if 'Version' in s3_pointer:
body_s3['Version'] = s3_pointer['Version']
return body_s3 | [
"Constructs the RestApi's `BodyS3Location property`_, from the SAM Api's DefinitionUri property.\n\n :returns: a BodyS3Location dict, containing the S3 Bucket, Key, and Version of the Swagger definition\n :rtype: dict\n "
] |
Please provide a description of the function:def _construct_deployment(self, rest_api):
deployment = ApiGatewayDeployment(self.logical_id + 'Deployment',
attributes=self.passthrough_resource_attributes)
deployment.RestApiId = rest_api.get_runtime_attr('rest_api_id')
deployment.StageName = 'Stage'
return deployment | [
"Constructs and returns the ApiGateway Deployment.\n\n :param model.apigateway.ApiGatewayRestApi rest_api: the RestApi for this Deployment\n :returns: the Deployment to which this SAM Api corresponds\n :rtype: model.apigateway.ApiGatewayDeployment\n "
] |
Please provide a description of the function:def _construct_stage(self, deployment, swagger):
# If StageName is some intrinsic function, then don't prefix the Stage's logical ID
# This will NOT create duplicates because we allow only ONE stage per API resource
stage_name_prefix = self.stage_name if isinstance(self.stage_name, string_types) else ""
stage = ApiGatewayStage(self.logical_id + stage_name_prefix + 'Stage',
attributes=self.passthrough_resource_attributes)
stage.RestApiId = ref(self.logical_id)
stage.update_deployment_ref(deployment.logical_id)
stage.StageName = self.stage_name
stage.CacheClusterEnabled = self.cache_cluster_enabled
stage.CacheClusterSize = self.cache_cluster_size
stage.Variables = self.variables
stage.MethodSettings = self.method_settings
stage.AccessLogSetting = self.access_log_setting
stage.CanarySetting = self.canary_setting
stage.TracingEnabled = self.tracing_enabled
if swagger is not None:
deployment.make_auto_deployable(stage, swagger)
return stage | [
"Constructs and returns the ApiGateway Stage.\n\n :param model.apigateway.ApiGatewayDeployment deployment: the Deployment for this Stage\n :returns: the Stage to which this SAM Api corresponds\n :rtype: model.apigateway.ApiGatewayStage\n "
] |
Please provide a description of the function:def to_cloudformation(self):
rest_api = self._construct_rest_api()
deployment = self._construct_deployment(rest_api)
swagger = None
if rest_api.Body is not None:
swagger = rest_api.Body
elif rest_api.BodyS3Location is not None:
swagger = rest_api.BodyS3Location
stage = self._construct_stage(deployment, swagger)
permissions = self._construct_authorizer_lambda_permission()
return rest_api, deployment, stage, permissions | [
"Generates CloudFormation resources from a SAM API resource\n\n :returns: a tuple containing the RestApi, Deployment, and Stage for an empty Api.\n :rtype: tuple\n "
] |
Please provide a description of the function:def _add_cors(self):
INVALID_ERROR = "Invalid value for 'Cors' property"
if not self.cors:
return
if self.cors and not self.definition_body:
raise InvalidResourceException(self.logical_id,
"Cors works only with inline Swagger specified in "
"'DefinitionBody' property")
if isinstance(self.cors, string_types) or is_instrinsic(self.cors):
# Just set Origin property. Others will be defaults
properties = CorsProperties(AllowOrigin=self.cors)
elif isinstance(self.cors, dict):
# Make sure keys in the dict are recognized
if not all(key in CorsProperties._fields for key in self.cors.keys()):
raise InvalidResourceException(self.logical_id, INVALID_ERROR)
properties = CorsProperties(**self.cors)
else:
raise InvalidResourceException(self.logical_id, INVALID_ERROR)
if not SwaggerEditor.is_valid(self.definition_body):
raise InvalidResourceException(self.logical_id, "Unable to add Cors configuration because "
"'DefinitionBody' does not contain a valid Swagger")
if properties.AllowCredentials is True and properties.AllowOrigin == _CORS_WILDCARD:
raise InvalidResourceException(self.logical_id, "Unable to add Cors configuration because "
"'AllowCredentials' can not be true when "
"'AllowOrigin' is \"'*'\" or not set")
editor = SwaggerEditor(self.definition_body)
for path in editor.iter_on_path():
editor.add_cors(path, properties.AllowOrigin, properties.AllowHeaders, properties.AllowMethods,
max_age=properties.MaxAge, allow_credentials=properties.AllowCredentials)
# Assign the Swagger back to template
self.definition_body = editor.swagger | [
"\n Add CORS configuration to the Swagger file, if necessary\n "
] |
Please provide a description of the function:def _add_auth(self):
if not self.auth:
return
if self.auth and not self.definition_body:
raise InvalidResourceException(self.logical_id,
"Auth works only with inline Swagger specified in "
"'DefinitionBody' property")
# Make sure keys in the dict are recognized
if not all(key in AuthProperties._fields for key in self.auth.keys()):
raise InvalidResourceException(
self.logical_id, "Invalid value for 'Auth' property")
if not SwaggerEditor.is_valid(self.definition_body):
raise InvalidResourceException(self.logical_id, "Unable to add Auth configuration because "
"'DefinitionBody' does not contain a valid Swagger")
swagger_editor = SwaggerEditor(self.definition_body)
auth_properties = AuthProperties(**self.auth)
authorizers = self._get_authorizers(auth_properties.Authorizers, auth_properties.DefaultAuthorizer)
if authorizers:
swagger_editor.add_authorizers(authorizers)
self._set_default_authorizer(swagger_editor, authorizers, auth_properties.DefaultAuthorizer)
# Assign the Swagger back to template
self.definition_body = swagger_editor.swagger | [
"\n Add Auth configuration to the Swagger file, if necessary\n "
] |
Please provide a description of the function:def _add_gateway_responses(self):
if not self.gateway_responses:
return
if self.gateway_responses and not self.definition_body:
raise InvalidResourceException(
self.logical_id, "GatewayResponses works only with inline Swagger specified in "
"'DefinitionBody' property")
# Make sure keys in the dict are recognized
for responses_key, responses_value in self.gateway_responses.items():
for response_key in responses_value.keys():
if response_key not in GatewayResponseProperties:
raise InvalidResourceException(
self.logical_id,
"Invalid property '{}' in 'GatewayResponses' property '{}'".format(response_key, responses_key))
if not SwaggerEditor.is_valid(self.definition_body):
raise InvalidResourceException(
self.logical_id, "Unable to add Auth configuration because "
"'DefinitionBody' does not contain a valid Swagger")
swagger_editor = SwaggerEditor(self.definition_body)
gateway_responses = {}
for response_type, response in self.gateway_responses.items():
gateway_responses[response_type] = ApiGatewayResponse(
api_logical_id=self.logical_id,
response_parameters=response.get('ResponseParameters', {}),
response_templates=response.get('ResponseTemplates', {}),
status_code=response.get('StatusCode', None)
)
if gateway_responses:
swagger_editor.add_gateway_responses(gateway_responses)
# Assign the Swagger back to template
self.definition_body = swagger_editor.swagger | [
"\n Add Gateway Response configuration to the Swagger file, if necessary\n "
] |
Please provide a description of the function:def _get_permission(self, authorizer_name, authorizer_lambda_function_arn):
rest_api = ApiGatewayRestApi(self.logical_id, depends_on=self.depends_on, attributes=self.resource_attributes)
api_id = rest_api.get_runtime_attr('rest_api_id')
partition = ArnGenerator.get_partition_name()
resource = '${__ApiId__}/authorizers/*'
source_arn = fnSub(ArnGenerator.generate_arn(partition=partition, service='execute-api', resource=resource),
{"__ApiId__": api_id})
lambda_permission = LambdaPermission(self.logical_id + authorizer_name + 'AuthorizerPermission',
attributes=self.passthrough_resource_attributes)
lambda_permission.Action = 'lambda:invokeFunction'
lambda_permission.FunctionName = authorizer_lambda_function_arn
lambda_permission.Principal = 'apigateway.amazonaws.com'
lambda_permission.SourceArn = source_arn
return lambda_permission | [
"Constructs and returns the Lambda Permission resource allowing the Authorizer to invoke the function.\n\n :returns: the permission resource\n :rtype: model.lambda_.LambdaPermission\n "
] |
Please provide a description of the function:def _set_endpoint_configuration(self, rest_api, value):
rest_api.EndpointConfiguration = {"Types": [value]}
rest_api.Parameters = {"endpointConfigurationTypes": value} | [
"\n Sets endpoint configuration property of AWS::ApiGateway::RestApi resource\n :param rest_api: RestApi resource\n :param string/dict value: Value to be set\n "
] |
Please provide a description of the function:def retry(time_unit, multiplier, backoff_coefficient, max_delay, max_attempts, expiration_duration, enable_jitter):
def deco_retry(task_to_try):
@wraps(task_to_try)
def retry_impl(*args, **kwargs):
total_wait_time = 0
have_tried = 0
retry_errors = []
while have_tried < max_attempts:
try:
task_to_try(*args, **kwargs)
return
except Exception as e:
retry_errors.append(e)
going_to_sleep_for = min(max_delay, multiplier * (backoff_coefficient ** have_tried))
if enable_jitter:
going_to_sleep_for = random.random() * going_to_sleep_for
duration = going_to_sleep_for * time_unit
if total_wait_time + duration > expiration_duration:
raise RetryTimeoutException(task_to_try.__name__, have_tried, max_attempts, total_wait_time,
multiplier, backoff_coefficient, enable_jitter, retry_errors)
runtime_logger.warn('Retrying [{0}], going to sleep for {1} seconds, exception stacktrace:\n{2}'
.format(task_to_try.__name__, duration, traceback.format_exc()))
time.sleep(duration)
total_wait_time += duration
have_tried += 1
raise RetryTimeoutException(task_to_try.__name__, have_tried, max_attempts, total_wait_time, multiplier,
backoff_coefficient, enable_jitter, retry_errors)
return retry_impl
return deco_retry | [
"\n The retry function will keep retrying `task_to_try` until either:\n (1) it returns None, then retry() finishes\n (2) `max_attempts` is reached, then retry() raises an exception.\n (3) if retrying one more time will cause total wait time to go above: `expiration_duration`, then\n retry() raises an exception\n\n Beware that any exception raised by task_to_try won't get surfaced until (2) or (3) is satisfied.\n\n At step n, it sleeps for [0, delay), where delay is defined as the following:\n `delay = min(max_delay, multiplier * (backoff_coefficient ** (n - 1))) * time_unit` seconds\n\n Additionally, if you enable jitter, for each retry, the function will instead sleep for:\n random.random() * sleep, that is [0, sleep) seconds.\n\n :param time_unit: This field represents a fraction of a second, which is used as a\n multiplier to compute the amount of time to sleep.\n :type time_unit: float\n\n :param multiplier: The initial wait duration for the first retry.\n :type multiplier: float\n\n :param backoff_coefficient: the base value for exponential retry.\n :type backoff_coefficient: float\n\n :param max_delay: The maximum amount of time to wait per try.\n :type max_delay: float\n\n :param max_attempts: This method will retry up to this value.\n :type max_attempts: int\n\n :param expiration_duration: the maximum amount of time retry can wait.\n :type expiration_duration: float\n\n :param enable_jitter: Setting this to true will add jitter.\n :type enable_jitter: bool\n "
] |
Please provide a description of the function:def to_cloudformation(self, **kwargs):
resources = []
intrinsics_resolver = kwargs["intrinsics_resolver"]
if self.DeadLetterQueue:
self._validate_dlq()
lambda_function = self._construct_lambda_function()
resources.append(lambda_function)
lambda_alias = None
if self.AutoPublishAlias:
alias_name = self._get_resolved_alias_name("AutoPublishAlias", self.AutoPublishAlias, intrinsics_resolver)
lambda_version = self._construct_version(lambda_function, intrinsics_resolver=intrinsics_resolver)
lambda_alias = self._construct_alias(alias_name, lambda_function, lambda_version)
resources.append(lambda_version)
resources.append(lambda_alias)
if self.DeploymentPreference:
self._validate_deployment_preference_and_add_update_policy(kwargs.get('deployment_preference_collection',
None),
lambda_alias, intrinsics_resolver)
managed_policy_map = kwargs.get('managed_policy_map', {})
if not managed_policy_map:
raise Exception('Managed policy map is empty, but should not be.')
execution_role = None
if lambda_function.Role is None:
execution_role = self._construct_role(managed_policy_map)
lambda_function.Role = execution_role.get_runtime_attr('arn')
resources.append(execution_role)
try:
resources += self._generate_event_resources(lambda_function, execution_role, kwargs['event_resources'],
lambda_alias=lambda_alias)
except InvalidEventException as e:
raise InvalidResourceException(self.logical_id, e.message)
return resources | [
"Returns the Lambda function, role, and event resources to which this SAM Function corresponds.\n\n :param dict kwargs: already-converted resources that may need to be modified when converting this \\\n macro to pure CloudFormation\n :returns: a list of vanilla CloudFormation Resources, to which this Function expands\n :rtype: list\n "
] |
Please provide a description of the function:def _get_resolved_alias_name(self, property_name, original_alias_value, intrinsics_resolver):
# Try to resolve.
resolved_alias_name = intrinsics_resolver.resolve_parameter_refs(original_alias_value)
if not isinstance(resolved_alias_name, string_types):
# This is still a dictionary which means we are not able to completely resolve intrinsics
raise InvalidResourceException(self.logical_id,
"'{}' must be a string or a Ref to a template parameter"
.format(property_name))
return resolved_alias_name | [
"\n Alias names can be supplied as an intrinsic function. This method tries to extract alias name from a reference\n to a parameter. If it cannot completely resolve (ie. if a complex intrinsic function was used), then this\n method raises an exception. If alias name is just a plain string, it will return as is\n\n :param dict or string original_alias_value: Value of Alias property as provided by the customer\n :param samtranslator.intrinsics.resolver.IntrinsicsResolver intrinsics_resolver: Instance of the resolver that\n knows how to resolve parameter references\n :return string: Alias name\n :raises InvalidResourceException: If the value is a complex intrinsic function that cannot be resolved\n "
] |
Please provide a description of the function:def _construct_lambda_function(self):
lambda_function = LambdaFunction(self.logical_id, depends_on=self.depends_on,
attributes=self.resource_attributes)
if self.FunctionName:
lambda_function.FunctionName = self.FunctionName
lambda_function.Handler = self.Handler
lambda_function.Runtime = self.Runtime
lambda_function.Description = self.Description
lambda_function.MemorySize = self.MemorySize
lambda_function.Timeout = self.Timeout
lambda_function.VpcConfig = self.VpcConfig
lambda_function.Role = self.Role
lambda_function.Environment = self.Environment
lambda_function.Code = self._construct_code_dict()
lambda_function.KmsKeyArn = self.KmsKeyArn
lambda_function.ReservedConcurrentExecutions = self.ReservedConcurrentExecutions
lambda_function.Tags = self._construct_tag_list(self.Tags)
lambda_function.Layers = self.Layers
if self.Tracing:
lambda_function.TracingConfig = {"Mode": self.Tracing}
if self.DeadLetterQueue:
lambda_function.DeadLetterConfig = {"TargetArn": self.DeadLetterQueue['TargetArn']}
return lambda_function | [
"Constructs and returns the Lambda function.\n\n :returns: a list containing the Lambda function and execution role resources\n :rtype: list\n "
] |
Please provide a description of the function:def _construct_role(self, managed_policy_map):
execution_role = IAMRole(self.logical_id + 'Role', attributes=self.get_passthrough_resource_attributes())
execution_role.AssumeRolePolicyDocument = IAMRolePolicies.lambda_assume_role_policy()
managed_policy_arns = [ArnGenerator.generate_aws_managed_policy_arn('service-role/AWSLambdaBasicExecutionRole')]
if self.Tracing:
managed_policy_arns.append(ArnGenerator.generate_aws_managed_policy_arn('AWSXrayWriteOnlyAccess'))
function_policies = FunctionPolicies({"Policies": self.Policies},
# No support for policy templates in the "core"
policy_template_processor=None)
policy_documents = []
if self.DeadLetterQueue:
policy_documents.append(IAMRolePolicies.dead_letter_queue_policy(
self.dead_letter_queue_policy_actions[self.DeadLetterQueue['Type']],
self.DeadLetterQueue['TargetArn']))
for index, policy_entry in enumerate(function_policies.get()):
if policy_entry.type is PolicyTypes.POLICY_STATEMENT:
policy_documents.append({
'PolicyName': execution_role.logical_id + 'Policy' + str(index),
'PolicyDocument': policy_entry.data
})
elif policy_entry.type is PolicyTypes.MANAGED_POLICY:
# There are three options:
# Managed Policy Name (string): Try to convert to Managed Policy ARN
# Managed Policy Arn (string): Insert it directly into the list
# Intrinsic Function (dict): Insert it directly into the list
#
# When you insert into managed_policy_arns list, de-dupe to prevent same ARN from showing up twice
#
policy_arn = policy_entry.data
if isinstance(policy_entry.data, string_types) and policy_entry.data in managed_policy_map:
policy_arn = managed_policy_map[policy_entry.data]
# De-Duplicate managed policy arns before inserting. Mainly useful
# when customer specifies a managed policy which is already inserted
# by SAM, such as AWSLambdaBasicExecutionRole
if policy_arn not in managed_policy_arns:
managed_policy_arns.append(policy_arn)
else:
# Policy Templates are not supported here in the "core"
raise InvalidResourceException(
self.logical_id,
"Policy at index {} in the 'Policies' property is not valid".format(index))
execution_role.ManagedPolicyArns = list(managed_policy_arns)
execution_role.Policies = policy_documents or None
execution_role.PermissionsBoundary = self.PermissionsBoundary
return execution_role | [
"Constructs a Lambda execution role based on this SAM function's Policies property.\n\n :returns: the generated IAM Role\n :rtype: model.iam.IAMRole\n "
] |
Please provide a description of the function:def _validate_dlq(self):
# Validate required logical ids
valid_dlq_types = str(list(self.dead_letter_queue_policy_actions.keys()))
if not self.DeadLetterQueue.get('Type') or not self.DeadLetterQueue.get('TargetArn'):
raise InvalidResourceException(self.logical_id,
"'DeadLetterQueue' requires Type and TargetArn properties to be specified"
.format(valid_dlq_types))
# Validate required Types
if not self.DeadLetterQueue['Type'] in self.dead_letter_queue_policy_actions:
raise InvalidResourceException(self.logical_id,
"'DeadLetterQueue' requires Type of {}".format(valid_dlq_types)) | [
"Validates whether the DeadLetterQueue LogicalId is validation\n :raise: InvalidResourceException\n "
] |
Please provide a description of the function:def _generate_event_resources(self, lambda_function, execution_role, event_resources, lambda_alias=None):
resources = []
if self.Events:
for logical_id, event_dict in self.Events.items():
try:
eventsource = self.event_resolver.resolve_resource_type(event_dict).from_dict(
lambda_function.logical_id + logical_id, event_dict, logical_id)
except TypeError as e:
raise InvalidEventException(logical_id, "{}".format(e))
kwargs = {
# When Alias is provided, connect all event sources to the alias and *not* the function
'function': lambda_alias or lambda_function,
'role': execution_role,
}
for name, resource in event_resources[logical_id].items():
kwargs[name] = resource
resources += eventsource.to_cloudformation(**kwargs)
return resources | [
"Generates and returns the resources associated with this function's events.\n\n :param model.lambda_.LambdaFunction lambda_function: generated Lambda function\n :param iam.IAMRole execution_role: generated Lambda execution role\n :param implicit_api: Global Implicit API resource where the implicit APIs get attached to, if necessary\n :param implicit_api_stage: Global implicit API stage resource where implicit APIs get attached to, if necessary\n :param event_resources: All the event sources associated with this Lambda function\n :param model.lambda_.LambdaAlias lambda_alias: Optional Lambda Alias resource if we want to connect the\n event sources to this alias\n\n :returns: a list containing the function's event resources\n :rtype: list\n "
] |
Please provide a description of the function:def _construct_version(self, function, intrinsics_resolver):
code_dict = function.Code
if not code_dict:
raise ValueError("Lambda function code must be a valid non-empty dictionary")
if not intrinsics_resolver:
raise ValueError("intrinsics_resolver is required for versions creation")
# Resolve references to template parameters before creating hash. This will *not* resolve all intrinsics
# because we cannot resolve runtime values like Arn of a resource. For purposes of detecting changes, this
# is good enough. Here is why:
#
# When using intrinsic functions there are two cases when has must change:
# - Value of the template parameter changes
# - (or) LogicalId of a referenced resource changes ie. !GetAtt NewResource.Arn
#
# Later case will already change the hash because some value in the Code dictionary changes. We handle the
# first case by resolving references to template parameters. It is okay even if these references are
# present inside another intrinsic such as !Join. The resolver will replace the reference with the parameter's
# value and keep all other parts of !Join identical. This will still trigger a change in the hash.
code_dict = intrinsics_resolver.resolve_parameter_refs(code_dict)
# Construct the LogicalID of Lambda version by appending 10 characters of SHA of CodeUri. This is necessary
# to trigger creation of a new version every time code location changes. Since logicalId changes, CloudFormation
# will drop the old version and create a new one for us. We set a DeletionPolicy on the version resource to
# prevent CloudFormation from actually deleting the underlying version resource
#
# SHA Collisions: For purposes of triggering a new update, we are concerned about just the difference previous
# and next hashes. The chances that two subsequent hashes collide is fairly low.
prefix = "{id}Version".format(id=self.logical_id)
logical_id = logical_id_generator.LogicalIdGenerator(prefix, code_dict).gen()
attributes = self.get_passthrough_resource_attributes()
if attributes is None:
attributes = {}
attributes["DeletionPolicy"] = "Retain"
lambda_version = LambdaVersion(logical_id=logical_id, attributes=attributes)
lambda_version.FunctionName = function.get_runtime_attr('name')
lambda_version.Description = self.VersionDescription
return lambda_version | [
"Constructs a Lambda Version resource that will be auto-published when CodeUri of the function changes.\n Old versions will not be deleted without a direct reference from the CloudFormation template.\n\n :param model.lambda_.LambdaFunction function: Lambda function object that is being connected to a version\n :param model.intrinsics.resolver.IntrinsicsResolver intrinsics_resolver: Class that can help resolve\n references to parameters present in CodeUri. It is a common usecase to set S3Key of Code to be a\n template parameter. Need to resolve the values otherwise we will never detect a change in Code dict\n :return: Lambda function Version resource\n "
] |
Please provide a description of the function:def _construct_alias(self, name, function, version):
if not name:
raise InvalidResourceException(self.logical_id, "Alias name is required to create an alias")
logical_id = "{id}Alias{suffix}".format(id=function.logical_id, suffix=name)
alias = LambdaAlias(logical_id=logical_id, attributes=self.get_passthrough_resource_attributes())
alias.Name = name
alias.FunctionName = function.get_runtime_attr('name')
alias.FunctionVersion = version.get_runtime_attr("version")
return alias | [
"Constructs a Lambda Alias for the given function and pointing to the given version\n\n :param string name: Name of the alias\n :param model.lambda_.LambdaFunction function: Lambda function object to associate the alias with\n :param model.lambda_.LambdaVersion version: Lambda version object to associate the alias with\n :return: Lambda alias object\n :rtype model.lambda_.LambdaAlias\n "
] |
Please provide a description of the function:def to_cloudformation(self, **kwargs):
resources = []
api_generator = ApiGenerator(self.logical_id,
self.CacheClusterEnabled,
self.CacheClusterSize,
self.Variables,
self.depends_on,
self.DefinitionBody,
self.DefinitionUri,
self.Name,
self.StageName,
endpoint_configuration=self.EndpointConfiguration,
method_settings=self.MethodSettings,
binary_media=self.BinaryMediaTypes,
minimum_compression_size=self.MinimumCompressionSize,
cors=self.Cors,
auth=self.Auth,
gateway_responses=self.GatewayResponses,
access_log_setting=self.AccessLogSetting,
canary_setting=self.CanarySetting,
tracing_enabled=self.TracingEnabled,
resource_attributes=self.resource_attributes,
passthrough_resource_attributes=self.get_passthrough_resource_attributes())
rest_api, deployment, stage, permissions = api_generator.to_cloudformation()
resources.extend([rest_api, deployment, stage])
resources.extend(permissions)
return resources | [
"Returns the API Gateway RestApi, Deployment, and Stage to which this SAM Api corresponds.\n\n :param dict kwargs: already-converted resources that may need to be modified when converting this \\\n macro to pure CloudFormation\n :returns: a list of vanilla CloudFormation Resources, to which this Function expands\n :rtype: list\n "
] |
Please provide a description of the function:def _construct_nested_stack(self):
nested_stack = NestedStack(self.logical_id, depends_on=self.depends_on,
attributes=self.get_passthrough_resource_attributes())
nested_stack.Parameters = self.Parameters
nested_stack.NotificationArns = self.NotificationArns
application_tags = self._get_application_tags()
nested_stack.Tags = self._construct_tag_list(self.Tags, application_tags)
nested_stack.TimeoutInMinutes = self.TimeoutInMinutes
nested_stack.TemplateURL = self.TemplateUrl if self.TemplateUrl else ""
return nested_stack | [
"Constructs a AWS::CloudFormation::Stack resource\n "
] |
Please provide a description of the function:def _get_application_tags(self):
application_tags = {}
if isinstance(self.Location, dict):
if (self.APPLICATION_ID_KEY in self.Location.keys() and
self.Location[self.APPLICATION_ID_KEY] is not None):
application_tags[self._SAR_APP_KEY] = self.Location[self.APPLICATION_ID_KEY]
if (self.SEMANTIC_VERSION_KEY in self.Location.keys() and
self.Location[self.SEMANTIC_VERSION_KEY] is not None):
application_tags[self._SAR_SEMVER_KEY] = self.Location[self.SEMANTIC_VERSION_KEY]
return application_tags | [
"Adds tags to the stack if this resource is using the serverless app repo\n "
] |
Please provide a description of the function:def to_cloudformation(self, **kwargs):
resources = []
# Append any CFN resources:
intrinsics_resolver = kwargs["intrinsics_resolver"]
resources.append(self._construct_lambda_layer(intrinsics_resolver))
return resources | [
"Returns the Lambda layer to which this SAM Layer corresponds.\n\n :param dict kwargs: already-converted resources that may need to be modified when converting this \\\n macro to pure CloudFormation\n :returns: a list of vanilla CloudFormation Resources, to which this Function expands\n :rtype: list\n "
] |
Please provide a description of the function:def _construct_lambda_layer(self, intrinsics_resolver):
# Resolve intrinsics if applicable:
self.LayerName = self._resolve_string_parameter(intrinsics_resolver, self.LayerName, 'LayerName')
self.LicenseInfo = self._resolve_string_parameter(intrinsics_resolver, self.LicenseInfo, 'LicenseInfo')
self.Description = self._resolve_string_parameter(intrinsics_resolver, self.Description, 'Description')
self.RetentionPolicy = self._resolve_string_parameter(intrinsics_resolver, self.RetentionPolicy,
'RetentionPolicy')
retention_policy_value = self._get_retention_policy_value()
attributes = self.get_passthrough_resource_attributes()
if attributes is None:
attributes = {}
attributes['DeletionPolicy'] = retention_policy_value
old_logical_id = self.logical_id
new_logical_id = logical_id_generator.LogicalIdGenerator(old_logical_id, self.to_dict()).gen()
self.logical_id = new_logical_id
lambda_layer = LambdaLayerVersion(self.logical_id, depends_on=self.depends_on, attributes=attributes)
# Changing the LayerName property: when a layer is published, it is given an Arn
# example: arn:aws:lambda:us-west-2:123456789012:layer:MyLayer:1
# where MyLayer is the LayerName property if it exists; otherwise, it is the
# LogicalId of this resource. Since a LayerVersion is an immutable resource, when
# CloudFormation updates this resource, it will ALWAYS create a new version then
# delete the old version if the logical ids match. What this does is change the
# logical id of every layer (so a `DeletionPolicy: Retain` can work) and set the
# LayerName property of the layer so that the Arn will still always be the same
# with the exception of an incrementing version number.
if not self.LayerName:
self.LayerName = old_logical_id
lambda_layer.LayerName = self.LayerName
lambda_layer.Description = self.Description
lambda_layer.Content = construct_s3_location_object(self.ContentUri, self.logical_id, 'ContentUri')
lambda_layer.CompatibleRuntimes = self.CompatibleRuntimes
lambda_layer.LicenseInfo = self.LicenseInfo
return lambda_layer | [
"Constructs and returns the Lambda function.\n\n :returns: a list containing the Lambda function and execution role resources\n :rtype: list\n "
] |
Please provide a description of the function:def _get_retention_policy_value(self):
if self.RetentionPolicy is None or self.RetentionPolicy.lower() == self.RETAIN.lower():
return self.RETAIN
elif self.RetentionPolicy.lower() == self.DELETE.lower():
return self.DELETE
elif self.RetentionPolicy.lower() not in self.retention_policy_options:
raise InvalidResourceException(self.logical_id,
"'{}' must be one of the following options: {}."
.format('RetentionPolicy', [self.RETAIN, self.DELETE])) | [
"\n Sets the deletion policy on this resource. The default is 'Retain'.\n\n :return: value for the DeletionPolicy attribute.\n "
] |
Please provide a description of the function:def order_flowers(intent_request):
flower_type = get_slots(intent_request)["FlowerType"]
date = get_slots(intent_request)["PickupDate"]
time = get_slots(intent_request)["PickupTime"]
source = intent_request['invocationSource']
if source == 'DialogCodeHook':
# Perform basic validation on the supplied input slots.
# Use the elicitSlot dialog action to re-prompt for the first violation detected.
slots = get_slots(intent_request)
validation_result = validate_order_flowers(flower_type, date, time)
if not validation_result['isValid']:
slots[validation_result['violatedSlot']] = None
return elicit_slot(intent_request['sessionAttributes'],
intent_request['currentIntent']['name'],
slots,
validation_result['violatedSlot'],
validation_result['message'])
# Pass the price of the flowers back through session attributes to be used in various prompts defined
# on the bot model.
output_session_attributes = intent_request['sessionAttributes']
if flower_type is not None:
output_session_attributes['Price'] = len(flower_type) * 5 # Elegant pricing model
return delegate(output_session_attributes, get_slots(intent_request))
# Order the flowers, and rely on the goodbye message of the bot to define the message to the end user.
# In a real bot, this would likely involve a call to a backend service.
return close(intent_request['sessionAttributes'],
'Fulfilled',
{'contentType': 'PlainText',
'content': 'Thanks, your order for {} has been placed and will be ready for pickup by {} on {}'.format(flower_type, time, date)}) | [
"\n Performs dialog management and fulfillment for ordering flowers.\n Beyond fulfillment, the implementation of this intent demonstrates the use of the elicitSlot dialog action\n in slot validation and re-prompting.\n "
] |
Please provide a description of the function:def dispatch(intent_request):
logger.debug('dispatch userId={}, intentName={}'.format(intent_request['userId'], intent_request['currentIntent']['name']))
intent_name = intent_request['currentIntent']['name']
# Dispatch to your bot's intent handlers
if intent_name == 'OrderFlowers':
return order_flowers(intent_request)
raise Exception('Intent with name ' + intent_name + ' not supported') | [
"\n Called when the user specifies an intent for this bot.\n "
] |
Please provide a description of the function:def _construct_permission(self, function, source_arn=None, source_account=None, suffix="", event_source_token=None):
lambda_permission = LambdaPermission(self.logical_id + 'Permission' + suffix,
attributes=function.get_passthrough_resource_attributes())
try:
# Name will not be available for Alias resources
function_name_or_arn = function.get_runtime_attr("name")
except NotImplementedError:
function_name_or_arn = function.get_runtime_attr("arn")
lambda_permission.Action = 'lambda:invokeFunction'
lambda_permission.FunctionName = function_name_or_arn
lambda_permission.Principal = self.principal
lambda_permission.SourceArn = source_arn
lambda_permission.SourceAccount = source_account
lambda_permission.EventSourceToken = event_source_token
return lambda_permission | [
"Constructs the Lambda Permission resource allowing the source service to invoke the function this event\n source triggers.\n\n :returns: the permission resource\n :rtype: model.lambda_.LambdaPermission\n "
] |
Please provide a description of the function:def to_cloudformation(self, **kwargs):
function = kwargs.get('function')
if not function:
raise TypeError("Missing required keyword argument: function")
resources = []
events_rule = EventsRule(self.logical_id)
resources.append(events_rule)
events_rule.ScheduleExpression = self.Schedule
events_rule.Targets = [self._construct_target(function)]
source_arn = events_rule.get_runtime_attr("arn")
if CONDITION in function.resource_attributes:
events_rule.set_resource_attribute(CONDITION, function.resource_attributes[CONDITION])
resources.append(self._construct_permission(function, source_arn=source_arn))
return resources | [
"Returns the CloudWatch Events Rule and Lambda Permission to which this Schedule event source corresponds.\n\n :param dict kwargs: no existing resources need to be modified\n :returns: a list of vanilla CloudFormation Resources, to which this pull event expands\n :rtype: list\n "
] |
Please provide a description of the function:def _construct_target(self, function):
target = {
'Arn': function.get_runtime_attr("arn"),
'Id': self.logical_id + 'LambdaTarget'
}
if self.Input is not None:
target['Input'] = self.Input
if self.InputPath is not None:
target['InputPath'] = self.InputPath
return target | [
"Constructs the Target property for the CloudWatch Events Rule.\n\n :returns: the Target property\n :rtype: dict\n "
] |
Please provide a description of the function:def to_cloudformation(self, **kwargs):
function = kwargs.get('function')
if not function:
raise TypeError("Missing required keyword argument: function")
if 'bucket' not in kwargs or kwargs['bucket'] is None:
raise TypeError("Missing required keyword argument: bucket")
if 'bucket_id' not in kwargs or kwargs['bucket_id'] is None:
raise TypeError("Missing required keyword argument: bucket_id")
bucket = kwargs['bucket']
bucket_id = kwargs['bucket_id']
resources = []
source_account = ref('AWS::AccountId')
permission = self._construct_permission(function, source_account=source_account)
if CONDITION in permission.resource_attributes:
self._depend_on_lambda_permissions_using_tag(bucket, permission)
else:
self._depend_on_lambda_permissions(bucket, permission)
resources.append(permission)
# NOTE: `bucket` here is a dictionary representing the S3 Bucket resource in your SAM template. If there are
# multiple S3 Events attached to the same bucket, we will update the Bucket resource with notification
# configuration for each event. This is the reason why we continue to use existing bucket dict and append onto
# it.
#
# NOTE: There is some fragile logic here where we will append multiple resources to output
# SAM template but de-dupe them when merging into output CFN template. This is scary because the order of
# merging is literally "last one wins", which works fine because we linearly loop through the template once.
# The de-dupe happens inside `samtranslator.translator.Translator.translate` method when merging results of
# to_cloudformation() to output template.
self._inject_notification_configuration(function, bucket)
resources.append(S3Bucket.from_dict(bucket_id, bucket))
return resources | [
"Returns the Lambda Permission resource allowing S3 to invoke the function this event source triggers.\n\n :param dict kwargs: S3 bucket resource\n :returns: a list of vanilla CloudFormation Resources, to which this S3 event expands\n :rtype: list\n "
] |
Please provide a description of the function:def _depend_on_lambda_permissions(self, bucket, permission):
depends_on = bucket.get("DependsOn", [])
# DependsOn can be either a list of strings or a scalar string
if isinstance(depends_on, string_types):
depends_on = [depends_on]
depends_on_set = set(depends_on)
depends_on_set.add(permission.logical_id)
bucket["DependsOn"] = list(depends_on_set)
return bucket | [
"\n Make the S3 bucket depends on Lambda Permissions resource because when S3 adds a Notification Configuration,\n it will check whether it has permissions to access Lambda. This will fail if the Lambda::Permissions is not\n already applied for this bucket to invoke the Lambda.\n\n :param dict bucket: Dictionary representing the bucket in SAM template. This is a raw dictionary and not a\n \"resource\" object\n :param model.lambda_.lambda_permission permission: Lambda Permission resource that needs to be created before\n the bucket.\n :return: Modified Bucket dictionary\n "
] |
Please provide a description of the function:def _depend_on_lambda_permissions_using_tag(self, bucket, permission):
properties = bucket.get('Properties', None)
if properties is None:
properties = {}
bucket['Properties'] = properties
tags = properties.get('Tags', None)
if tags is None:
tags = []
properties['Tags'] = tags
dep_tag = {
'sam:ConditionalDependsOn:' + permission.logical_id: {
'Fn::If': [
permission.resource_attributes[CONDITION],
ref(permission.logical_id),
'no dependency'
]
}
}
properties['Tags'] = tags + get_tag_list(dep_tag)
return bucket | [
"\n Since conditional DependsOn is not supported this undocumented way of\n implicitely making dependency through tags is used.\n\n See https://stackoverflow.com/questions/34607476/cloudformation-apply-condition-on-dependson\n\n It is done by using Ref wrapped in a conditional Fn::If. Using Ref implies a\n dependency, so CloudFormation will automatically wait once it reaches that function, the same\n as if you were using a DependsOn.\n "
] |
Please provide a description of the function:def to_cloudformation(self, **kwargs):
function = kwargs.get('function')
if not function:
raise TypeError("Missing required keyword argument: function")
return [self._construct_permission(function, source_arn=self.Topic),
self._inject_subscription(function, self.Topic, self.FilterPolicy)] | [
"Returns the Lambda Permission resource allowing SNS to invoke the function this event source triggers.\n\n :param dict kwargs: no existing resources need to be modified\n :returns: a list of vanilla CloudFormation Resources, to which this SNS event expands\n :rtype: list\n "
] |
Please provide a description of the function:def resources_to_link(self, resources):
rest_api_id = self.RestApiId
if isinstance(rest_api_id, dict) and "Ref" in rest_api_id:
rest_api_id = rest_api_id["Ref"]
# If RestApiId is a resource in the same template, then we try find the StageName by following the reference
# Otherwise we default to a wildcard. This stage name is solely used to construct the permission to
# allow this stage to invoke the Lambda function. If we are unable to resolve the stage name, we will
# simply permit all stages to invoke this Lambda function
# This hack is necessary because customers could use !ImportValue, !Ref or other intrinsic functions which
# can be sometimes impossible to resolve (ie. when it has cross-stack references)
permitted_stage = "*"
stage_suffix = "AllStages"
explicit_api = None
if isinstance(rest_api_id, string_types):
if rest_api_id in resources \
and "Properties" in resources[rest_api_id] \
and "StageName" in resources[rest_api_id]["Properties"]:
explicit_api = resources[rest_api_id]["Properties"]
permitted_stage = explicit_api["StageName"]
# Stage could be a intrinsic, in which case leave the suffix to default value
if isinstance(permitted_stage, string_types):
if not permitted_stage:
raise InvalidResourceException(rest_api_id, 'StageName cannot be empty.')
stage_suffix = permitted_stage
else:
stage_suffix = "Stage"
else:
# RestApiId is a string, not an intrinsic, but we did not find a valid API resource for this ID
raise InvalidEventException(self.relative_id, "RestApiId property of Api event must reference a valid "
"resource in the same template.")
return {
'explicit_api': explicit_api,
'explicit_api_stage': {
'permitted_stage': permitted_stage,
'suffix': stage_suffix
}
} | [
"\n If this API Event Source refers to an explicit API resource, resolve the reference and grab\n necessary data from the explicit API\n "
] |
Please provide a description of the function:def to_cloudformation(self, **kwargs):
resources = []
function = kwargs.get('function')
if not function:
raise TypeError("Missing required keyword argument: function")
if self.Method is not None:
# Convert to lower case so that user can specify either GET or get
self.Method = self.Method.lower()
resources.extend(self._get_permissions(kwargs))
explicit_api = kwargs['explicit_api']
if explicit_api.get("__MANAGE_SWAGGER"):
self._add_swagger_integration(explicit_api, function)
return resources | [
"If the Api event source has a RestApi property, then simply return the Lambda Permission resource allowing\n API Gateway to call the function. If no RestApi is provided, then additionally inject the path, method, and the\n x-amazon-apigateway-integration into the Swagger body for a provided implicit API.\n\n :param dict kwargs: a dict containing the implicit RestApi to be modified, should no explicit RestApi \\\n be provided.\n :returns: a list of vanilla CloudFormation Resources, to which this Api event expands\n :rtype: list\n "
] |
Please provide a description of the function:def _add_swagger_integration(self, api, function):
swagger_body = api.get("DefinitionBody")
if swagger_body is None:
return
function_arn = function.get_runtime_attr('arn')
partition = ArnGenerator.get_partition_name()
uri = fnSub('arn:' + partition + ':apigateway:${AWS::Region}:lambda:path/2015-03-31/functions/' +
make_shorthand(function_arn) + '/invocations')
editor = SwaggerEditor(swagger_body)
if editor.has_integration(self.Path, self.Method):
# Cannot add the Lambda Integration, if it is already present
raise InvalidEventException(
self.relative_id,
'API method "{method}" defined multiple times for path "{path}".'.format(
method=self.Method, path=self.Path))
condition = None
if CONDITION in function.resource_attributes:
condition = function.resource_attributes[CONDITION]
editor.add_lambda_integration(self.Path, self.Method, uri, self.Auth, api.get('Auth'), condition=condition)
if self.Auth:
method_authorizer = self.Auth.get('Authorizer')
if method_authorizer:
api_auth = api.get('Auth')
api_authorizers = api_auth and api_auth.get('Authorizers')
if method_authorizer != 'AWS_IAM':
if not api_authorizers:
raise InvalidEventException(
self.relative_id,
'Unable to set Authorizer [{authorizer}] on API method [{method}] for path [{path}] '
'because the related API does not define any Authorizers.'.format(
authorizer=method_authorizer, method=self.Method, path=self.Path))
if method_authorizer != 'NONE' and not api_authorizers.get(method_authorizer):
raise InvalidEventException(
self.relative_id,
'Unable to set Authorizer [{authorizer}] on API method [{method}] for path [{path}] '
'because it wasn\'t defined in the API\'s Authorizers.'.format(
authorizer=method_authorizer, method=self.Method, path=self.Path))
if method_authorizer == 'NONE' and not api_auth.get('DefaultAuthorizer'):
raise InvalidEventException(
self.relative_id,
'Unable to set Authorizer on API method [{method}] for path [{path}] because \'NONE\' '
'is only a valid value when a DefaultAuthorizer on the API is specified.'.format(
method=self.Method, path=self.Path))
editor.add_auth_to_method(api=api, path=self.Path, method_name=self.Method, auth=self.Auth)
api["DefinitionBody"] = editor.swagger | [
"Adds the path and method for this Api event source to the Swagger body for the provided RestApi.\n\n :param model.apigateway.ApiGatewayRestApi rest_api: the RestApi to which the path and method should be added.\n "
] |
Please provide a description of the function:def resolve_parameter_refs(self, input):
return self._traverse(input, self.parameters, self._try_resolve_parameter_refs) | [
"\n Resolves references to parameters within the given dictionary recursively. Other intrinsic functions such as\n !GetAtt, !Sub or !Ref to non-parameters will be left untouched.\n\n Result is a dictionary where parameter values are inlined. Don't pass this dictionary directly into\n transform's output because it changes the template structure by inlining parameter values.\n\n :param input: Any primitive type (dict, array, string etc) whose values might contain intrinsic functions\n :return: A copy of a dictionary with parameter references replaced by actual value.\n "
] |
Please provide a description of the function:def resolve_sam_resource_refs(self, input, supported_resource_refs):
return self._traverse(input, supported_resource_refs, self._try_resolve_sam_resource_refs) | [
"\n Customers can provide a reference to a \"derived\" SAM resource such as Alias of a Function or Stage of an API\n resource. This method recursively walks the tree, converting all derived references to the real resource name,\n if it is present.\n\n Example:\n {\"Ref\": \"MyFunction.Alias\"} -> {\"Ref\": \"MyFunctionAliasLive\"}\n\n This method does not attempt to validate a reference. If it is invalid or non-resolvable, it skips the\n occurrence and continues with the rest. It is recommended that you have an external process that detects and\n surfaces invalid references.\n\n For first call, it is recommended that `template` is the entire CFN template in order to handle\n references in Mapping or Output sections.\n\n :param dict input: CFN template that needs resolution. This method will modify the input\n directly resolving references. In subsequent recursions, this will be a fragment of the CFN template.\n :param SupportedResourceReferences supported_resource_refs: Object that contains information about the resource\n references supported in this SAM template, along with the value they should resolve to.\n :return list errors: List of dictionary containing information about invalid reference. Empty list otherwise\n "
] |
Please provide a description of the function:def resolve_sam_resource_id_refs(self, input, supported_resource_id_refs):
return self._traverse(input, supported_resource_id_refs, self._try_resolve_sam_resource_id_refs) | [
"\n Some SAM resources have their logical ids mutated from the original id that the customer writes in the\n template. This method recursively walks the tree and updates these logical ids from the old value\n to the new value that is generated by SAM.\n\n Example:\n {\"Ref\": \"MyLayer\"} -> {\"Ref\": \"MyLayerABC123\"}\n\n This method does not attempt to validate a reference. If it is invalid or non-resolvable, it skips the\n occurrence and continues with the rest. It is recommended that you have an external process that detects and\n surfaces invalid references.\n\n For first call, it is recommended that `template` is the entire CFN template in order to handle\n references in Mapping or Output sections.\n\n :param dict input: CFN template that needs resolution. This method will modify the input\n directly resolving references. In subsequent recursions, this will be a fragment of the CFN template.\n :param dict supported_resource_id_refs: Dictionary that maps old logical ids to new ones.\n :return list errors: List of dictionary containing information about invalid reference. Empty list otherwise\n "
] |
Please provide a description of the function:def _traverse(self, input, resolution_data, resolver_method):
# There is data to help with resolution. Skip the traversal altogether
if len(resolution_data) == 0:
return input
#
# Traversal Algorithm:
#
# Imagine the input dictionary/list as a tree. We are doing a Pre-Order tree traversal here where we first
# process the root node before going to its children. Dict and Lists are the only two iterable nodes.
# Everything else is a leaf node.
#
# We do a Pre-Order traversal to handle the case where `input` contains intrinsic function as its only child
# ie. input = {"Ref": "foo}.
#
# We will try to resolve the intrinsics if we can, otherwise return the original input. In some cases, resolving
# an intrinsic will result in a terminal state ie. {"Ref": "foo"} could resolve to a string "bar". In other
# cases, resolving intrinsics is only partial and we might need to continue traversing the tree (ex: Fn::Sub)
# to handle nested intrinsics. All of these cases lend well towards a Pre-Order traversal where we try and
# process the intrinsic, which results in a modified sub-tree to traverse.
#
input = resolver_method(input, resolution_data)
if isinstance(input, dict):
return self._traverse_dict(input, resolution_data, resolver_method)
elif isinstance(input, list):
return self._traverse_list(input, resolution_data, resolver_method)
else:
# We can iterate only over dict or list types. Primitive types are terminals
return input | [
"\n Driver method that performs the actual traversal of input and calls the appropriate `resolver_method` when\n to perform the resolution.\n\n :param input: Any primitive type (dict, array, string etc) whose value might contain an intrinsic function\n :param resolution_data: Data that will help with resolution. For example, when resolving parameter references,\n this object will contain a dictionary of parameter names and their values.\n :param resolver_method: Method that will be called to actually resolve an intrinsic function. This method\n is called with the parameters `(input, resolution_data)`.\n :return: Modified `input` with intrinsics resolved\n "
] |
Please provide a description of the function:def _traverse_dict(self, input_dict, resolution_data, resolver_method):
for key, value in input_dict.items():
input_dict[key] = self._traverse(value, resolution_data, resolver_method)
return input_dict | [
"\n Traverse a dictionary to resolve intrinsic functions on every value\n\n :param input_dict: Input dictionary to traverse\n :param resolution_data: Data that the `resolver_method` needs to operate\n :param resolver_method: Method that can actually resolve an intrinsic function, if it detects one\n :return: Modified dictionary with values resolved\n "
] |
Please provide a description of the function:def _traverse_list(self, input_list, resolution_data, resolver_method):
for index, value in enumerate(input_list):
input_list[index] = self._traverse(value, resolution_data, resolver_method)
return input_list | [
"\n Traverse a list to resolve intrinsic functions on every element\n\n :param input_list: List of input\n :param resolution_data: Data that the `resolver_method` needs to operate\n :param resolver_method: Method that can actually resolve an intrinsic function, if it detects one\n :return: Modified list with intrinsic functions resolved\n "
] |
Please provide a description of the function:def _try_resolve_parameter_refs(self, input, parameters):
if not self._is_intrinsic_dict(input):
return input
function_type = list(input.keys())[0]
return self.supported_intrinsics[function_type].resolve_parameter_refs(input, parameters) | [
"\n Try to resolve parameter references on the given input object. The object could be of any type.\n If the input is not in the format used by intrinsics (ie. dictionary with one key), input is returned\n unmodified. If the single key in dictionary is one of the supported intrinsic function types,\n go ahead and try to resolve it.\n\n :param input: Input object to resolve\n :param parameters: Parameter values used to for ref substitution\n :return:\n "
] |
Please provide a description of the function:def _try_resolve_sam_resource_refs(self, input, supported_resource_refs):
if not self._is_intrinsic_dict(input):
return input
function_type = list(input.keys())[0]
return self.supported_intrinsics[function_type].resolve_resource_refs(input, supported_resource_refs) | [
"\n Try to resolve SAM resource references on the given template. If the given object looks like one of the\n supported intrinsics, it calls the appropriate resolution on it. If not, this method returns the original input\n unmodified.\n\n :param dict input: Dictionary that may represent an intrinsic function\n :param SupportedResourceReferences supported_resource_refs: Object containing information about available\n resource references and the values they resolve to.\n :return: Modified input dictionary with references resolved\n "
] |
Please provide a description of the function:def _try_resolve_sam_resource_id_refs(self, input, supported_resource_id_refs):
if not self._is_intrinsic_dict(input):
return input
function_type = list(input.keys())[0]
return self.supported_intrinsics[function_type].resolve_resource_id_refs(input, supported_resource_id_refs) | [
"\n Try to resolve SAM resource id references on the given template. If the given object looks like one of the\n supported intrinsics, it calls the appropriate resolution on it. If not, this method returns the original input\n unmodified.\n\n :param dict input: Dictionary that may represent an intrinsic function\n :param dict supported_resource_id_refs: Dictionary that maps old logical ids to new ones.\n :return: Modified input dictionary with id references resolved\n "
] |
Please provide a description of the function:def _is_intrinsic_dict(self, input):
# All intrinsic functions are dictionaries with just one key
return isinstance(input, dict) \
and len(input) == 1 \
and list(input.keys())[0] in self.supported_intrinsics | [
"\n Can the input represent an intrinsic function in it?\n\n :param input: Object to be checked\n :return: True, if the input contains a supported intrinsic function. False otherwise\n "
] |
Please provide a description of the function:def to_cloudformation(self, **kwargs):
function = kwargs.get('function')
if not function:
raise TypeError("Missing required keyword argument: function")
source_arn = self.get_source_arn()
permission = self._construct_permission(function, source_arn=source_arn)
subscription_filter = self.get_subscription_filter(function, permission)
resources = [permission, subscription_filter]
return resources | [
"Returns the CloudWatch Logs Subscription Filter and Lambda Permission to which this CloudWatch Logs event source\n corresponds.\n\n :param dict kwargs: no existing resources need to be modified\n :returns: a list of vanilla CloudFormation Resources, to which this push event expands\n :rtype: list\n "
] |
Please provide a description of the function:def convert(self, template_name, parameter_values):
if not self.has(template_name):
raise TemplateNotFoundException(template_name)
template = self.get(template_name)
return template.to_statement(parameter_values) | [
"\n Converts the given template to IAM-ready policy statement by substituting template parameters with the given\n values.\n\n :param template_name: Name of the template\n :param parameter_values: Values for all parameters of the template\n :return dict: Dictionary containing policy statement\n :raises ValueError: If the given inputs don't represent valid template\n :raises InsufficientParameterValues: If the parameter values don't have values for all required parameters\n "
] |
Please provide a description of the function:def _is_valid_templates_dict(policy_templates_dict, schema=None):
if not schema:
schema = PolicyTemplatesProcessor._read_schema()
try:
jsonschema.validate(policy_templates_dict, schema)
except ValidationError as ex:
# Stringifying the exception will give us useful error message
raise ValueError(str(ex))
return True | [
"\n Is this a valid policy template dictionary\n\n :param dict policy_templates_dict: Data to be validated\n :param dict schema: Optional, dictionary containing JSON Schema representing policy template\n :return: True, if it is valid.\n :raises ValueError: If the template dictionary doesn't match up with the schema\n "
] |
Please provide a description of the function:def render_chart_to_file(self, template_name: str, chart: Any, path: str):
tpl = self.env.get_template(template_name)
html = tpl.render(chart=self.generate_js_link(chart))
write_utf8_html_file(path, self._reg_replace(html)) | [
"\n Render a chart or page to local html files.\n\n :param chart: A Chart or Page object\n :param path: The destination file which the html code write to\n :param template_name: The name of template file.\n "
] |
Please provide a description of the function:def decode_base64(data: str) -> bytes:
missing_padding = len(data) % 4
if missing_padding != 0:
data += "=" * (4 - missing_padding)
return base64.decodebytes(data.encode("utf-8")) | [
"Decode base64, padding being optional.\n\n :param data: Base64 data as an ASCII byte string\n :returns: The decoded byte string.\n "
] |
Please provide a description of the function:def _set_collapse_interval(data, interval):
if interval <= 0:
return data
if data and isinstance(data, list):
for d in data:
children = d.get("children", None)
if children and interval > 0:
for index, value in enumerate(children):
if index % interval == 0:
value.update(collapsed="false")
return data | [
"\r\n 间隔折叠节点，当节点过多时可以解决节点显示过杂间隔。\r\n\r\n :param data: 节点数据\r\n :param interval: 指定间隔\r\n "
] |
Please provide a description of the function:def parse_pin(name_str):
if len(name_str) < 1:
raise ValueError("Expecting pin name to be at least 4 charcters.")
if name_str[0] != 'P':
raise ValueError("Expecting pin name to start with P")
pin_str = name_str[1:].split('/')[0]
if not pin_str.isdigit():
raise ValueError("Expecting numeric pin number.")
return int(pin_str) | [
"Parses a string and returns a pin-num."
] |
Please provide a description of the function:def ptr(self):
if self.fn_num is None:
return self.func
return '{:s}{:d}'.format(self.func, self.fn_num) | [
"Returns the numbered function (i.e. USART6) for this AF."
] |
Please provide a description of the function:def print(self):
if self.supported:
print(' AF', end='')
else:
print(' //', end='')
fn_num = self.fn_num
if fn_num is None:
fn_num = 0
print('({:2d}, {:8s}, {:2d}, {:10s}, {:8s}), // {:s}'.format(self.idx,
self.func, fn_num, self.pin_type, self.ptr(), self.af_str)) | [
"Prints the C representation of this AF."
] |
Please provide a description of the function:def run_loop(leds=all_leds):
print('Loop started.\nPress Ctrl+C to break out of the loop.')
while 1:
try:
if switch():
[led.on() for led in leds]
else:
[led.off() for led in leds]
except OSError: # VCPInterrupt # Ctrl+C in interpreter mode.
break | [
"\n Start the loop.\n\n :param `leds`: Which LEDs to light up upon switch press.\n :type `leds`: sequence of LED objects\n "
] |
Please provide a description of the function:def find_c_file(obj_file, vpath):
c_file = None
relative_c_file = os.path.splitext(obj_file)[0] + ".c"
relative_c_file = relative_c_file.lstrip('/\\')
for p in vpath:
possible_c_file = os.path.join(p, relative_c_file)
if os.path.exists(possible_c_file):
c_file = possible_c_file
break
return c_file | [
" Search vpaths for the c file that matches the provided object_file.\n\n :param str obj_file: object file to find the matching c file for\n :param List[str] vpath: List of base paths, similar to gcc vpath\n :return: str path to c file or None\n "
] |
Please provide a description of the function:def find_module_registrations(c_file):
global pattern
if c_file is None:
# No c file to match the object file, skip
return set()
with io.open(c_file, encoding='utf-8') as c_file_obj:
return set(re.findall(pattern, c_file_obj.read())) | [
" Find any MP_REGISTER_MODULE definitions in the provided c file.\n\n :param str c_file: path to c file to check\n :return: List[(module_name, obj_module, enabled_define)]\n "
] |
Please provide a description of the function:def generate_module_table_header(modules):
# Print header file for all external modules.
mod_defs = []
print("// Automatically generated by makemoduledefs.py.\n")
for module_name, obj_module, enabled_define in modules:
mod_def = "MODULE_DEF_{}".format(module_name.upper())
mod_defs.append(mod_def)
print((
"#if ({enabled_define})\n"
" extern const struct _mp_obj_module_t {obj_module};\n"
" #define {mod_def} {{ MP_ROM_QSTR({module_name}), MP_ROM_PTR(&{obj_module}) }},\n"
"#else\n"
" #define {mod_def}\n"
"#endif\n"
).format(module_name=module_name, obj_module=obj_module,
enabled_define=enabled_define, mod_def=mod_def)
)
print("\n#define MICROPY_REGISTERED_MODULES \\")
for mod_def in mod_defs:
print(" {mod_def} \\".format(mod_def=mod_def))
print("// MICROPY_REGISTERED_MODULES") | [
" Generate header with module table entries for builtin modules.\n\n :param List[(module_name, obj_module, enabled_define)] modules: module defs\n :return: None\n "
] |
Please provide a description of the function:def readfiles():
tests = list(filter(lambda x: x.endswith('.py'), os.listdir(TESTPATH)))
tests.sort()
files = []
for test in tests:
text = open(TESTPATH + test, 'r').read()
try:
class_, desc, cause, workaround, code = [x.rstrip() for x in \
list(filter(None, re.split(SPLIT, text)))]
output = Output(test, class_, desc, cause, workaround, code, '', '', '')
files.append(output)
except IndexError:
print('Incorrect format in file ' + TESTPATH + test)
return files | [
" Reads test files "
] |
Please provide a description of the function:def uimports(code):
for uimport in UIMPORTLIST:
uimport = bytes(uimport, 'utf8')
code = code.replace(uimport, b'u' + uimport)
return code | [
" converts CPython module names into MicroPython equivalents "
] |
Please provide a description of the function:def indent(block, spaces):
new_block = ''
for line in block.split('\n'):
new_block += spaces + line + '\n'
return new_block | [
" indents paragraphs of text for rst formatting "
] |
Please provide a description of the function:def gen_table(contents):
xlengths = []
ylengths = []
for column in contents:
col_len = 0
for entry in column:
lines = entry.split('\n')
for line in lines:
col_len = max(len(line) + 2, col_len)
xlengths.append(col_len)
for i in range(len(contents[0])):
ymax = 0
for j in range(len(contents)):
ymax = max(ymax, len(contents[j][i].split('\n')))
ylengths.append(ymax)
table_divider = '+' + ''.join(['-' * i + '+' for i in xlengths]) + '\n'
table = table_divider
for i in range(len(ylengths)):
row = [column[i] for column in contents]
row = [entry + '\n' * (ylengths[i]-len(entry.split('\n'))) for entry in row]
row = [entry.split('\n') for entry in row]
for j in range(ylengths[i]):
k = 0
for entry in row:
width = xlengths[k]
table += ''.join(['| {:{}}'.format(entry[j], width - 1)])
k += 1
table += '|\n'
table += table_divider
return table + '\n' | [
" creates a table given any set of columns "
] |
Please provide a description of the function:def gen_rst(results):
# make sure the destination directory exists
try:
os.mkdir(DOCPATH)
except OSError as e:
if e.args[0] != errno.EEXIST and e.args[0] != errno.EISDIR:
raise
toctree = []
class_ = []
for output in results:
section = output.class_.split(',')
for i in range(len(section)):
section[i] = section[i].rstrip()
if section[i] in CLASSMAP:
section[i] = CLASSMAP[section[i]]
if i >= len(class_) or section[i] != class_[i]:
if i == 0:
filename = section[i].replace(' ', '_').lower()
rst = open(DOCPATH + filename + '.rst', 'w')
rst.write(HEADER)
rst.write(section[i] + '\n')
rst.write(RSTCHARS[0] * len(section[i]))
rst.write(time.strftime("\nGenerated %a %d %b %Y %X UTC\n\n", time.gmtime()))
toctree.append(filename)
else:
rst.write(section[i] + '\n')
rst.write(RSTCHARS[min(i, len(RSTCHARS)-1)] * len(section[i]))
rst.write('\n\n')
class_ = section
rst.write('.. _cpydiff_%s:\n\n' % output.name.rsplit('.', 1)[0])
rst.write(output.desc + '\n')
rst.write('~' * len(output.desc) + '\n\n')
if output.cause != 'Unknown':
rst.write('**Cause:** ' + output.cause + '\n\n')
if output.workaround != 'Unknown':
rst.write('**Workaround:** ' + output.workaround + '\n\n')
rst.write('Sample code::\n\n' + indent(output.code, TAB) + '\n')
output_cpy = indent(''.join(output.output_cpy[0:2]), TAB).rstrip()
output_cpy = ('::\n\n' if output_cpy != '' else '') + output_cpy
output_upy = indent(''.join(output.output_upy[0:2]), TAB).rstrip()
output_upy = ('::\n\n' if output_upy != '' else '') + output_upy
table = gen_table([['CPy output:', output_cpy], ['uPy output:', output_upy]])
rst.write(table)
template = open(INDEXTEMPLATE, 'r')
index = open(DOCPATH + INDEX, 'w')
index.write(HEADER)
index.write(template.read())
for section in INDEXPRIORITY:
if section in toctree:
index.write(indent(section + '.rst', TAB))
toctree.remove(section)
for section in toctree:
index.write(indent(section + '.rst', TAB)) | [
" creates restructured text documents to display tests "
] |
Please provide a description of the function:def main():
# set search path so that test scripts find the test modules (and no other ones)
os.environ['PYTHONPATH'] = TESTPATH
os.environ['MICROPYPATH'] = TESTPATH
files = readfiles()
results = run_tests(files)
gen_rst(results) | [
" Main function "
] |
Please provide a description of the function:def init():
global __dev, __cfg_descr
devices = get_dfu_devices(idVendor=__VID, idProduct=__PID)
if not devices:
raise ValueError('No DFU device found')
if len(devices) > 1:
raise ValueError("Multiple DFU devices found")
__dev = devices[0]
__dev.set_configuration()
# Claim DFU interface
usb.util.claim_interface(__dev, __DFU_INTERFACE)
# Find the DFU configuration descriptor, either in the device or interfaces
__cfg_descr = None
for cfg in __dev.configurations():
__cfg_descr = find_dfu_cfg_descr(cfg.extra_descriptors)
if __cfg_descr:
break
for itf in cfg.interfaces():
__cfg_descr = find_dfu_cfg_descr(itf.extra_descriptors)
if __cfg_descr:
break
# Get device into idle state
for attempt in range(4):
status = get_status()
if status == __DFU_STATE_DFU_IDLE:
break
elif (status == __DFU_STATE_DFU_DOWNLOAD_IDLE
or status == __DFU_STATE_DFU_UPLOAD_IDLE):
abort_request()
else:
clr_status() | [
"Initializes the found DFU device so that we can program it."
] |
Please provide a description of the function:def page_erase(addr):
if __verbose:
print("Erasing page: 0x%x..." % (addr))
# Send DNLOAD with first byte=0x41 and page address
buf = struct.pack("<BI", 0x41, addr)
__dev.ctrl_transfer(0x21, __DFU_DNLOAD, 0, __DFU_INTERFACE, buf, __TIMEOUT)
# Execute last command
if get_status() != __DFU_STATE_DFU_DOWNLOAD_BUSY:
raise Exception("DFU: erase failed")
# Check command state
if get_status() != __DFU_STATE_DFU_DOWNLOAD_IDLE:
raise Exception("DFU: erase failed") | [
"Erases a single page."
] |
Please provide a description of the function:def set_address(addr):
# Send DNLOAD with first byte=0x21 and page address
buf = struct.pack("<BI", 0x21, addr)
__dev.ctrl_transfer(0x21, __DFU_DNLOAD, 0, __DFU_INTERFACE, buf, __TIMEOUT)
# Execute last command
if get_status() != __DFU_STATE_DFU_DOWNLOAD_BUSY:
raise Exception("DFU: set address failed")
# Check command state
if get_status() != __DFU_STATE_DFU_DOWNLOAD_IDLE:
raise Exception("DFU: set address failed") | [
"Sets the address for the next operation."
] |
Please provide a description of the function:def write_memory(addr, buf, progress=None, progress_addr=0, progress_size=0):
xfer_count = 0
xfer_bytes = 0
xfer_total = len(buf)
xfer_base = addr
while xfer_bytes < xfer_total:
if __verbose and xfer_count % 512 == 0:
print ("Addr 0x%x %dKBs/%dKBs..." % (xfer_base + xfer_bytes,
xfer_bytes // 1024,
xfer_total // 1024))
if progress and xfer_count % 2 == 0:
progress(progress_addr, xfer_base + xfer_bytes - progress_addr,
progress_size)
# Set mem write address
set_address(xfer_base+xfer_bytes)
# Send DNLOAD with fw data
chunk = min(__cfg_descr.wTransferSize, xfer_total-xfer_bytes)
__dev.ctrl_transfer(0x21, __DFU_DNLOAD, 2, __DFU_INTERFACE,
buf[xfer_bytes:xfer_bytes + chunk], __TIMEOUT)
# Execute last command
if get_status() != __DFU_STATE_DFU_DOWNLOAD_BUSY:
raise Exception("DFU: write memory failed")
# Check command state
if get_status() != __DFU_STATE_DFU_DOWNLOAD_IDLE:
raise Exception("DFU: write memory failed")
xfer_count += 1
xfer_bytes += chunk | [
"Writes a buffer into memory. This routine assumes that memory has\n already been erased.\n "
] |
Please provide a description of the function:def write_page(buf, xfer_offset):
xfer_base = 0x08000000
# Set mem write address
set_address(xfer_base+xfer_offset)
# Send DNLOAD with fw data
__dev.ctrl_transfer(0x21, __DFU_DNLOAD, 2, __DFU_INTERFACE, buf, __TIMEOUT)
# Execute last command
if get_status() != __DFU_STATE_DFU_DOWNLOAD_BUSY:
raise Exception("DFU: write memory failed")
# Check command state
if get_status() != __DFU_STATE_DFU_DOWNLOAD_IDLE:
raise Exception("DFU: write memory failed")
if __verbose:
print ("Write: 0x%x " % (xfer_base + xfer_offset)) | [
"Writes a single page. This routine assumes that memory has already\n been erased.\n "
] |
Please provide a description of the function:def exit_dfu():
# set jump address
set_address(0x08000000)
# Send DNLOAD with 0 length to exit DFU
__dev.ctrl_transfer(0x21, __DFU_DNLOAD, 0, __DFU_INTERFACE,
None, __TIMEOUT)
try:
# Execute last command
if get_status() != __DFU_STATE_DFU_MANIFEST:
print("Failed to reset device")
# Release device
usb.util.dispose_resources(__dev)
except:
pass | [
"Exit DFU mode, and start running the program."
] |
Please provide a description of the function:def consume(fmt, data, names):
size = struct.calcsize(fmt)
return named(struct.unpack(fmt, data[:size]), names), data[size:] | [
"Parses the struct defined by `fmt` from `data`, stores the parsed fields\n into a named tuple using `names`. Returns the named tuple, and the data\n with the struct stripped off."
] |
Please provide a description of the function:def read_dfu_file(filename):
print("File: {}".format(filename))
with open(filename, 'rb') as fin:
data = fin.read()
crc = compute_crc(data[:-4])
elements = []
# Decode the DFU Prefix
#
# <5sBIB
# < little endian
# 5s char[5] signature "DfuSe"
# B uint8_t version 1
# I uint32_t size Size of the DFU file (not including suffix)
# B uint8_t targets Number of targets
dfu_prefix, data = consume('<5sBIB', data,
'signature version size targets')
print (" %(signature)s v%(version)d, image size: %(size)d, "
"targets: %(targets)d" % dfu_prefix)
for target_idx in range(dfu_prefix['targets']):
# Decode the Image Prefix
#
# <6sBI255s2I
# < little endian
# 6s char[6] signature "Target"
# B uint8_t altsetting
# I uint32_t named bool indicating if a name was used
# 255s char[255] name name of the target
# I uint32_t size size of image (not incl prefix)
# I uint32_t elements Number of elements in the image
img_prefix, data = consume('<6sBI255s2I', data,
'signature altsetting named name '
'size elements')
img_prefix['num'] = target_idx
if img_prefix['named']:
img_prefix['name'] = cstring(img_prefix['name'])
else:
img_prefix['name'] = ''
print(' %(signature)s %(num)d, alt setting: %(altsetting)s, '
'name: "%(name)s", size: %(size)d, elements: %(elements)d'
% img_prefix)
target_size = img_prefix['size']
target_data, data = data[:target_size], data[target_size:]
for elem_idx in range(img_prefix['elements']):
# Decode target prefix
# < little endian
# I uint32_t element address
# I uint32_t element size
elem_prefix, target_data = consume('<2I', target_data, 'addr size')
elem_prefix['num'] = elem_idx
print(' %(num)d, address: 0x%(addr)08x, size: %(size)d'
% elem_prefix)
elem_size = elem_prefix['size']
elem_data = target_data[:elem_size]
target_data = target_data[elem_size:]
elem_prefix['data'] = elem_data
elements.append(elem_prefix)
if len(target_data):
print("target %d PARSE ERROR" % target_idx)
# Decode DFU Suffix
# < little endian
# H uint16_t device Firmware version
# H uint16_t product
# H uint16_t vendor
# H uint16_t dfu 0x11a (DFU file format version)
# 3s char[3] ufd 'UFD'
# B uint8_t len 16
# I uint32_t crc32
dfu_suffix = named(struct.unpack('<4H3sBI', data[:16]),
'device product vendor dfu ufd len crc')
print (' usb: %(vendor)04x:%(product)04x, device: 0x%(device)04x, '
'dfu: 0x%(dfu)04x, %(ufd)s, %(len)d, 0x%(crc)08x' % dfu_suffix)
if crc != dfu_suffix['crc']:
print("CRC ERROR: computed crc32 is 0x%08x" % crc)
return
data = data[16:]
if data:
print("PARSE ERROR")
return
return elements | [
"Reads a DFU file, and parses the individual elements from the file.\n Returns an array of elements. Each element is a dictionary with the\n following keys:\n num - The element index\n address - The address that the element data should be written to.\n size - The size of the element ddata.\n data - The element data.\n If an error occurs while parsing the file, then None is returned.\n "
] |
Please provide a description of the function:def get_dfu_devices(*args, **kwargs):
# convert to list for compatibility with newer pyusb
return list(usb.core.find(*args, find_all=True,
custom_match=FilterDFU(), **kwargs)) | [
"Returns a list of USB device which are currently in DFU mode.\n Additional filters (like idProduct and idVendor) can be passed in to\n refine the search.\n "
] |
Please provide a description of the function:def get_memory_layout(device):
cfg = device[0]
intf = cfg[(0, 0)]
mem_layout_str = get_string(device, intf.iInterface)
mem_layout = mem_layout_str.split('/')
result = []
for mem_layout_index in range(1, len(mem_layout), 2):
addr = int(mem_layout[mem_layout_index], 0)
segments = mem_layout[mem_layout_index + 1].split(',')
seg_re = re.compile(r'(\d+)\*(\d+)(.)(.)')
for segment in segments:
seg_match = seg_re.match(segment)
num_pages = int(seg_match.groups()[0], 10)
page_size = int(seg_match.groups()[1], 10)
multiplier = seg_match.groups()[2]
if multiplier == 'K':
page_size *= 1024
if multiplier == 'M':
page_size *= 1024 * 1024
size = num_pages * page_size
last_addr = addr + size - 1
result.append(named((addr, last_addr, size, num_pages, page_size),
"addr last_addr size num_pages page_size"))
addr += size
return result | [
"Returns an array which identifies the memory layout. Each entry\n of the array will contain a dictionary with the following keys:\n addr - Address of this memory segment\n last_addr - Last address contained within the memory segment.\n size - size of the segment, in bytes\n num_pages - number of pages in the segment\n page_size - size of each page, in bytes\n "
] |
Please provide a description of the function:def list_dfu_devices(*args, **kwargs):
devices = get_dfu_devices(*args, **kwargs)
if not devices:
print("No DFU capable devices found")
return
for device in devices:
print("Bus {} Device {:03d}: ID {:04x}:{:04x}"
.format(device.bus, device.address,
device.idVendor, device.idProduct))
layout = get_memory_layout(device)
print("Memory Layout")
for entry in layout:
print(" 0x{:x} {:2d} pages of {:3d}K bytes"
.format(entry['addr'], entry['num_pages'],
entry['page_size'] // 1024)) | [
"Prints a lits of devices detected in DFU mode."
] |
Please provide a description of the function:def write_elements(elements, mass_erase_used, progress=None):
mem_layout = get_memory_layout(__dev)
for elem in elements:
addr = elem['addr']
size = elem['size']
data = elem['data']
elem_size = size
elem_addr = addr
if progress:
progress(elem_addr, 0, elem_size)
while size > 0:
write_size = size
if not mass_erase_used:
for segment in mem_layout:
if addr >= segment['addr'] and \
addr <= segment['last_addr']:
# We found the page containing the address we want to
# write, erase it
page_size = segment['page_size']
page_addr = addr & ~(page_size - 1)
if addr + write_size > page_addr + page_size:
write_size = page_addr + page_size - addr
page_erase(page_addr)
break
write_memory(addr, data[:write_size], progress,
elem_addr, elem_size)
data = data[write_size:]
addr += write_size
size -= write_size
if progress:
progress(elem_addr, addr - elem_addr, elem_size) | [
"Writes the indicated elements into the target memory,\n erasing as needed.\n "
] |
Please provide a description of the function:def cli_progress(addr, offset, size):
width = 25
done = offset * width // size
print("\r0x{:08x} {:7d} [{}{}] {:3d}% "
.format(addr, size, '=' * done, ' ' * (width - done),
offset * 100 // size), end="")
try:
sys.stdout.flush()
except OSError:
pass # Ignore Windows CLI "WinError 87" on Python 3.6
if offset == size:
print("") | [
"Prints a progress report suitable for use on the command line."
] |
Please provide a description of the function:def main():
global __verbose
# Parse CMD args
parser = argparse.ArgumentParser(description='DFU Python Util')
#parser.add_argument("path", help="file path")
parser.add_argument(
"-l", "--list",
help="list available DFU devices",
action="store_true",
default=False
)
parser.add_argument(
"-m", "--mass-erase",
help="mass erase device",
action="store_true",
default=False
)
parser.add_argument(
"-u", "--upload",
help="read file from DFU device",
dest="path",
default=False
)
parser.add_argument(
"-v", "--verbose",
help="increase output verbosity",
action="store_true",
default=False
)
args = parser.parse_args()
__verbose = args.verbose
if args.list:
list_dfu_devices(idVendor=__VID, idProduct=__PID)
return
init()
if args.mass_erase:
print ("Mass erase...")
mass_erase()
if args.path:
elements = read_dfu_file(args.path)
if not elements:
return
print("Writing memory...")
write_elements(elements, args.mass_erase, progress=cli_progress)
print("Exiting DFU...")
exit_dfu()
return
print("No command specified") | [
"Test program for verifying this files functionality."
] |
Please provide a description of the function:def parse_port_pin(name_str):
if len(name_str) < 3:
raise ValueError("Expecting pin name to be at least 3 charcters.")
if name_str[0] != 'P':
raise ValueError("Expecting pin name to start with P")
if name_str[1] < 'A' or name_str[1] > 'K':
raise ValueError("Expecting pin port to be between A and K")
port = ord(name_str[1]) - ord('A')
pin_str = name_str[2:]
if not pin_str.isdigit():
raise ValueError("Expecting numeric pin number.")
return (port, int(pin_str)) | [
"Parses a string and returns a (port-num, pin-num) tuple."
] |
Please provide a description of the function:def print(self):
cond_var = None
if self.supported:
cond_var = conditional_var('{}{}'.format(self.func, self.fn_num))
print_conditional_if(cond_var)
print(' AF', end='')
else:
print(' //', end='')
fn_num = self.fn_num
if fn_num is None:
fn_num = 0
print('({:2d}, {:8s}, {:2d}, {:10s}, {:8s}), // {:s}'.format(self.idx,
self.func, fn_num, self.pin_type, self.ptr(), self.af_str))
print_conditional_endif(cond_var) | [
"Prints the C representation of this AF."
] |
Please provide a description of the function:def parse_port_pin(name_str):
if len(name_str) < 3:
raise ValueError("Expecting pin name to be at least 3 characters")
if name_str[:2] != 'GP':
raise ValueError("Expecting pin name to start with GP")
if not name_str[2:].isdigit():
raise ValueError("Expecting numeric GPIO number")
port = int(int(name_str[2:]) / 8)
gpio_bit = 1 << int(int(name_str[2:]) % 8)
return (port, gpio_bit) | [
"Parses a string and returns a (port, gpio_bit) tuple."
] |
Please provide a description of the function:def run_node(cls,
node, # type: NodeProto
inputs, # type: Any
device='CPU', # type: Text
outputs_info=None, # type: Optional[Sequence[Tuple[numpy.dtype, Tuple[int, ...]]]]
**kwargs # type: Dict[Text, Any]
): # type: (...) -> Optional[Tuple[Any, ...]]
'''Simple run one operator and return the results.
Args:
outputs_info: a list of tuples, which contains the element type and
shape of each output. First element of the tuple is the dtype, and
the second element is the shape. More use case can be found in
https://github.com/onnx/onnx/blob/master/onnx/backend/test/runner/__init__.py
'''
# TODO Remove Optional from return type
if 'opset_version' in kwargs:
special_context = c_checker.CheckerContext()
special_context.ir_version = IR_VERSION
special_context.opset_imports = {'': kwargs['opset_version']} # type: ignore
onnx.checker.check_node(node, special_context)
else:
onnx.checker.check_node(node)
return None | [] |
Please provide a description of the function:def load_external_data_for_tensor(tensor, base_dir): # type: (TensorProto, Text) -> None
if tensor.HasField("raw_data"): # already loaded
return
info = ExternalDataInfo(tensor)
file_location = _sanitize_path(info.location)
external_data_file_path = os.path.join(base_dir, file_location)
with open(external_data_file_path, 'rb') as data_file:
if info.offset:
data_file.seek(info.offset)
if info.length:
tensor.raw_data = data_file.read(info.length)
else:
tensor.raw_data = data_file.read() | [
"\n Load data from an external file for tensor.\n\n @params\n tensor: a TensorProto object.\n base_dir: directory that contains the external data.\n "
] |
Please provide a description of the function:def load_external_data_for_model(model, base_dir): # type: (ModelProto, Text) -> None
for tensor in _get_all_tensors(model):
if uses_external_data(tensor):
load_external_data_for_tensor(tensor, base_dir) | [
"\n Loads external tensors into model\n\n @params\n model: ModelProto to load external data to\n base_dir: directory that contains external data\n "
] |
Please provide a description of the function:def convert_model_to_external_data(model, all_tensors_to_one_file=True, location=None):
# type: (ModelProto, bool, Optional[Text]) -> None
if all_tensors_to_one_file:
file_name = Text(uuid.uuid1())
if location:
file_name = location
for tensor in _get_all_tensors(model):
set_external_data(tensor, file_name)
else:
for tensor in _get_all_tensors(model):
set_external_data(tensor, tensor.name) | [
"\n call to set all tensors as external data. save_model saves all the tensors data as external data after calling this function.\n @params\n model: ModelProto to be converted.\n all_tensors_to_one_file: If true, save all tensors to one external file specified by location.\n If false, save each tensor to a file named with the tensor name.\n location: specify the external file that all tensors to save to.\n If not specified, will use the model name.\n "
] |
Please provide a description of the function:def convert_model_from_external_data(model): # type: (ModelProto) -> None
for tensor in _get_all_tensors(model):
if uses_external_data(tensor):
if not tensor.HasField("raw_data"):
raise ValueError("raw_data field doesn't exist.")
del tensor.external_data[:]
tensor.data_location = TensorProto.DEFAULT | [
"\n call to set all tensors data as embedded data. save_model saves all the tensors data as embedded data after calling this function.\n @params\n model: ModelProto to be converted.\n "
] |
Please provide a description of the function:def save_external_data(tensor, base_path): # type: (TensorProto, Text) -> None
info = ExternalDataInfo(tensor)
external_data_file_path = os.path.join(base_path, info.location)
# Retrieve the tensor's data from raw_data or load external file
if not tensor.HasField("raw_data"):
raise ValueError("raw_data field doesn't exist.")
# Create file if it doesn't exist
if not os.path.isfile(external_data_file_path):
open(external_data_file_path, 'ab').close()
# Open file for reading and writing at random locations ('r+b')
with open(external_data_file_path, 'r+b') as data_file:
data_file.seek(0, 2)
if info.offset is not None:
# Pad file to required offset if needed
file_size = data_file.tell()
if info.offset > file_size:
data_file.write(b"\0" * (info.offset - file_size))
data_file.seek(info.offset)
offset = data_file.tell()
data_file.write(tensor.raw_data)
set_external_data(tensor, info.location, offset, data_file.tell() - offset) | [
"\n Write tensor data to an external file according to information in the `external_data` field.\n\n @params\n tensor: Tensor object to be serialized\n base_path: System path of a folder where tensor data is to be stored\n "
] |
Please provide a description of the function:def _get_attribute_tensors(onnx_model_proto): # type: (ModelProto) -> Iterable[TensorProto]
for node in onnx_model_proto.graph.node:
for attribute in node.attribute:
if attribute.HasField("t"):
yield attribute.t
for tensor in attribute.tensors:
yield tensor | [
"Create an iterator of tensors from node attributes of an ONNX model."
] |
Please provide a description of the function:def remove_external_data_field(tensor, field_key): # type: (TensorProto, Text) -> None
for (i, field) in enumerate(tensor.external_data):
if field.key == field_key:
del tensor.external_data[i] | [
"\n Remove a field from a Tensor's external_data key-value store.\n\n Modifies tensor object in place.\n\n @params\n tensor: Tensor object from which value will be removed\n field_key: The key of the field to be removed\n "
] |
Please provide a description of the function:def write_external_data_tensors(model, filepath): # type: (ModelProto, Text) -> ModelProto
for tensor in _get_all_tensors(model):
if uses_external_data(tensor):
save_external_data(tensor, filepath)
tensor.ClearField(str('raw_data'))
return model | [
"\n Write external data of all tensors to files on disk.\n\n Note: This function also strips basepath information from all tensors' external_data fields.\n\n @params\n model: Model object which is the source of tensors to serialize.\n filepath: System path to the directory which should be treated as base path for external data.\n\n @return\n The modified model object.\n "
] |
Please provide a description of the function:def _import(self, path, name):
# type: (Text, Text) -> Text
imp = path.replace('/', '.')
self.imports[imp].add(name)
return name | [
"Imports a stdlib path and returns a handle to it\n eg. self._import(\"typing\", \"Optional\") -> \"Optional\"\n "
] |
Please provide a description of the function:def _import_message(self, type_name):
# type: (d.FieldDescriptorProto) -> Text
name = cast(Text, type_name)
if name[0] == '.' and name[1].isupper() and name[2].islower():
# Message defined in this file
return name[1:]
message_fd = self.descriptors.message_to_fd[name]
if message_fd.name == self.fd.name:
# message defined in this package
split = name.split('.')
for i, segment in enumerate(split):
if segment and segment[0].isupper() and segment[1].islower():
return ".".join(split[i:])
# Not in package. Must import
split = name.split(".")
for i, segment in enumerate(split):
if segment and segment[0].isupper() and segment[1].islower():
assert message_fd.name.endswith('.proto')
import_name = self._import(message_fd.name[:-6].replace('-', '_') + "_pb2", segment)
remains = ".".join(split[i + 1:])
if not remains:
return import_name
raise AssertionError("Don't support nested imports yet")
# return new_nested_import(import_name, remains)
raise AssertionError("Could not parse local name " + name) | [
"Import a referenced message and return a handle"
] |
Please provide a description of the function:def run(self):
onnx_script = os.path.realpath(os.path.join(os.path.dirname(os.path.abspath(__file__)), "tools/mypy-onnx.py"))
returncode = subprocess.call([sys.executable, onnx_script])
sys.exit(returncode) | [
"Run command."
] |
Please provide a description of the function:def make_node(
op_type, # type: Text
inputs, # type: Sequence[Text]
outputs, # type: Sequence[Text]
name=None, # type: Optional[Text]
doc_string=None, # type: Optional[Text]
domain=None, # type: Optional[Text]
**kwargs # type: Any
): # type: (...) -> NodeProto
node = NodeProto()
node.op_type = op_type
node.input.extend(inputs)
node.output.extend(outputs)
if name:
node.name = name
if doc_string:
node.doc_string = doc_string
if domain is not None:
node.domain = domain
if kwargs:
node.attribute.extend(
make_attribute(key, value)
for key, value in sorted(kwargs.items()))
return node | [
"Construct a NodeProto.\n\n Arguments:\n op_type (string): The name of the operator to construct\n inputs (list of string): list of input names\n outputs (list of string): list of output names\n name (string, default None): optional unique identifier for NodeProto\n doc_string (string, default None): optional documentation string for NodeProto\n domain (string, default None): optional domain for NodeProto.\n If it's None, we will just use default domain (which is empty)\n **kwargs (dict): the attributes of the node. The acceptable values\n are documented in :func:`make_attribute`.\n "
] |
Please provide a description of the function:def make_operatorsetid(
domain, # type: Text
version, # type: int
): # type: (...) -> OperatorSetIdProto
operatorsetid = OperatorSetIdProto()
operatorsetid.domain = domain
operatorsetid.version = version
return operatorsetid | [
"Construct an OperatorSetIdProto.\n\n Arguments:\n domain (string): The domain of the operator set id\n version (integer): Version of operator set id\n "
] |
Please provide a description of the function:def _to_bytes_or_false(val): # type: (Union[Text, bytes]) -> Union[bytes, bool]
if isinstance(val, bytes):
return val
else:
try:
return val.encode('utf-8')
except AttributeError:
return False | [
"An internal graph to convert the input to a bytes or to False.\n\n The criteria for conversion is as follows and should be python 2 and 3\n compatible:\n - If val is py2 str or py3 bytes: return bytes\n - If val is py2 unicode or py3 str: return val.decode('utf-8')\n - Otherwise, return False\n "
] |
Please provide a description of the function:def make_attribute(
key, # type: Text
value, # type: Any
doc_string=None # type: Optional[Text]
): # type: (...) -> AttributeProto
attr = AttributeProto()
attr.name = key
if doc_string:
attr.doc_string = doc_string
is_iterable = isinstance(value, collections.Iterable)
bytes_or_false = _to_bytes_or_false(value)
# First, singular cases
# float
if isinstance(value, float):
attr.f = value
attr.type = AttributeProto.FLOAT
# integer
elif isinstance(value, numbers.Integral):
attr.i = cast(int, value)
attr.type = AttributeProto.INT
# string
elif bytes_or_false:
assert isinstance(bytes_or_false, bytes)
attr.s = bytes_or_false
attr.type = AttributeProto.STRING
elif isinstance(value, TensorProto):
attr.t.CopyFrom(value)
attr.type = AttributeProto.TENSOR
elif isinstance(value, GraphProto):
attr.g.CopyFrom(value)
attr.type = AttributeProto.GRAPH
# third, iterable cases
elif is_iterable:
byte_array = [_to_bytes_or_false(v) for v in value]
if all(isinstance(v, float) for v in value):
attr.floats.extend(value)
attr.type = AttributeProto.FLOATS
elif all(isinstance(v, numbers.Integral) for v in value):
# Turn np.int32/64 into Python built-in int.
attr.ints.extend(int(v) for v in value)
attr.type = AttributeProto.INTS
elif all(byte_array):
attr.strings.extend(cast(List[bytes], byte_array))
attr.type = AttributeProto.STRINGS
elif all(isinstance(v, TensorProto) for v in value):
attr.tensors.extend(value)
attr.type = AttributeProto.TENSORS
elif all(isinstance(v, GraphProto) for v in value):
attr.graphs.extend(value)
attr.type = AttributeProto.GRAPHS
else:
raise ValueError(
"You passed in an iterable attribute but I cannot figure out "
"its applicable type.")
else:
raise ValueError(
'Value "{}" is not valid attribute data type.'.format(value))
return attr | [
"Makes an AttributeProto based on the value type."
] |
Please provide a description of the function:def make_tensor_value_info(
name, # type: Text
elem_type, # type: int
shape, # type: Optional[Sequence[Union[Text, int]]]
doc_string="", # type: Text
shape_denotation=None, # type: Optional[List[Text]]
): # type: (...) -> ValueInfoProto
value_info_proto = ValueInfoProto()
value_info_proto.name = name
if doc_string:
value_info_proto.doc_string = doc_string
tensor_type_proto = value_info_proto.type.tensor_type
tensor_type_proto.elem_type = elem_type
tensor_shape_proto = tensor_type_proto.shape
if shape is not None:
# You might think this is a no-op (extending a normal Python
# list by [] certainly is), but protobuf lists work a little
# differently; if a field is never set, it is omitted from the
# resulting protobuf; a list that is explicitly set to be
# empty will get an (empty) entry in the protobuf. This
# difference is visible to our consumers, so make sure we emit
# an empty shape!
tensor_shape_proto.dim.extend([])
if shape_denotation:
if len(shape_denotation) != len(shape):
raise ValueError(
'Invalid shape_denotation. '
'Must be of the same length as shape.')
for i, d in enumerate(shape):
dim = tensor_shape_proto.dim.add()
if d is None:
pass
elif isinstance(d, integer_types):
dim.dim_value = d
elif isinstance(d, text_type):
dim.dim_param = d
else:
raise ValueError(
'Invalid item in shape: {}. '
'Needs to of integer_types or text_type.'.format(d))
if shape_denotation:
dim.denotation = shape_denotation[i]
return value_info_proto | [
"Makes a ValueInfoProto based on the data type and shape."
] |
Please provide a description of the function:def strip_doc_string(proto): # type: (google.protobuf.message.Message) -> None
assert isinstance(proto, google.protobuf.message.Message)
for descriptor in proto.DESCRIPTOR.fields:
if descriptor.name == 'doc_string':
proto.ClearField(descriptor.name)
elif descriptor.type == descriptor.TYPE_MESSAGE:
if descriptor.label == descriptor.LABEL_REPEATED:
for x in getattr(proto, descriptor.name):
strip_doc_string(x)
elif proto.HasField(descriptor.name):
strip_doc_string(getattr(proto, descriptor.name)) | [
"\n Empties `doc_string` field on any nested protobuf messages\n "
] |
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