def parse_policy_types(toscayaml, model_name):
"""
Create types internal representation
"""
pol_types = {}
pol_def = toscayaml.get('policy_types')
if type(pol_def) is dict:
for type_name, type_def in pol_def.items():
val = {}
if type_name in pol_types:
val = pol_types[type_name]
val['name'] = type_name
# get the list of parents
val['types'] = get_types(pol_def, type_name)
if len(val['types']) > 0:
val['derived_from'] = val['types'][0]
else:
print "ERROR : types list is empty for policy type '{}'".format(
type_name)
# get the version of the node type
val['version'] = str(Version(type_def.get('version')))
# get metadata
val['metadata'] = {}
metadata = type_def.get('metadata')
if isinstance(metadata, dict) and all(
map(lambda x: isinstance(x, basestring),
metadata.values())):
val['metadata'] = metadata
# get descrption
val['description'] = ""
descr = type_def.get('description')
if descr is not None:
val['description'] = descr
# get properties and attributes
val['properties'] = get_property_definitions(
type_def.get('properties'))
# get targets
## TODO: verify each member is a node type or a group type
val['targets'] = []
targets = type_def.get('targets')
if isinstance(targets, list) and all(
map(lambda x: isinstance(x, basestring), targets)):
val['targets'] = targets
# get triggers
val['triggers'] = get_trigger_definitions(type_def.get('triggers'))
pol_types[type_name] = val
# store in the ditrit space
for type_name, type_val in pol_types.items():
linda_out('types/{}/policies/{}'.format(model_name, type_name),
type_val)
def parse_group_types(toscayaml, model_name):
"""
Create types internal representation
"""
grp_types = {}
grp_def = toscayaml.get('group_types')
if type(grp_def) is dict:
for type_name, type_def in grp_def.items():
val = {}
if type_name in grp_types:
val = grp_types[type_name]
val['name'] = type_name
# get the list of parents
val['types'] = get_types(grp_def, type_name)
if len(val['types']) > 0:
val['derived_from'] = val['types'][0]
else:
print "ERROR : types list is empty for group type '{}'".format(type_name)
# get the version of the node type
val['version'] = str(Version(type_def.get('version')))
# get metadata
val['metadata'] = {}
metadata = type_def.get('metadata')
if isinstance(metadata, dict) and all(map(lambda x: isinstance(x, basestring), metadata.values())):
val['metadata'] = metadata
# get descrption
val['description'] = ""
descr = type_def.get('description')
if descr is not None:
val['description'] = descr
# get properties and attributes
val['properties'] = get_property_definitions(type_def.get('properties'))
# get requirements and capabilities
val['requirements'] = get_requirement_definitions(type_def.get('requirements'))
val['capabilities'] = get_capability_definitions(type_def.get('capabilities'))
# get members
## TODO: verify each member is a nodei type, a capability type or a group type
val['members'] = []
members = type_def.get('members')
if isinstance(members, list) and all(map(lambda x: isinstance(x, basestring), members)):
val['members'] = members
# get interfaces
val['interfaces'] = get_interface_definitions(type_def.get('interfaces'))
grp_types[type_name] = val
# store in the ditrit space
for type_name, type_val in grp_types.items():
linda_out('types/{}/groups/{}'.format(model_name, type_name), type_val)
def parse_data_types(toscayaml, model_name):
"""
Create types internal representation
"""
data_types = {}
data_def = copy.deepcopy(basetypes)
if 'data_types' in toscayaml.keys():
data_def.update(toscayaml['data_types'])
if type(data_def) is dict:
for type_name, type_def in data_def.items():
val = {}
if type_name in data_types:
val = data_types[type_name]
val['name'] = type_name
# get the list of parents
val['types'] = get_types(data_def, type_name)
if len(val['types']) > 0:
val['derived_from'] = val['types'][0]
else:
print "ERROR : types list is empty for data type '{}'".format(
type_name)
# get the version of the node type
val['version'] = str(Version(type_def.get('version')))
# get metadata
val['metadata'] = {}
metadata = type_def.get('metadata')
if isinstance(metadata, dict) and all(
map(lambda x: isinstance(x, basestring),
metadata.values())):
val['metadata'] = metadata
# get descrption
val['description'] = ""
descr = type_def.get('description')
if descr is not None:
val['description'] = descr
# get constraints
## TODO: verify constraint is ok with parse_constraint (should retuirn None if not ok)
val['constraints'] = type_def.get('constraints')
# get properties
val['properties'] = get_property_definitions(
type_def.get('properties'))
data_types[type_name] = val
# store in the ditrit space
for type_name, type_val in data_types.items():
linda_out('types/{}/datatypes/{}'.format(model_name, type_name),
type_val)
def parse_interface_types(toscayaml, model_name):
"""
Create types internal representation
"""
if_types = {}
if_def = toscayaml.get('interface_types')
if type(if_def) is dict:
for type_name, type_def in if_def.items():
val = {}
if type_name in if_types:
val = if_types[type_name]
val['name'] = type_name
# get the list of parents
val['types'] = get_types(if_def, type_name)
if len(val['types']) > 0:
val['derived_from'] = val['types'][0]
else:
print "ERROR : types list is empty for interface type '{}'".format(
type_name)
# get the version of the node type
val['version'] = str(Version(type_def.get('version')))
# get metadata
val['metadata'] = {}
metadata = type_def.get('metadata')
if isinstance(metadata, dict) and all(
map(lambda x: isinstance(x, basestring),
metadata.values())):
val['metadata'] = metadata
# get descrption
val['description'] = ""
descr = type_def.get('description')
if descr is not None:
val['description'] = descr
# get properties and attributes
val['inputs'] = get_property_definitions(type_def.get('inputs'))
# get requirements and capabilities
val['operations'] = get_operation_definitions(type_def)
if_types[type_name] = val
# store in the ditrit space
for type_name, type_val in if_types.items():
linda_out('types/{}/interfaces/{}'.format(model_name, type_name),
type_val)
def parse_capability_types(toscayaml, model_name):
"""
Create types internal representation
"""
capa_types = {}
# Part of the workflows defined in nodes have to be parsed before the part defined in relations.
capa_def = toscayaml.get('capability_types')
if type(capa_def) is dict:
for type_name, type_def in capa_def.items():
val = {}
if type_name in capa_types:
val = capa_types[type_name]
val['name'] = type_name
# get the list of parents
val['types'] = get_types(capa_def, type_name)
if len(val['types']) > 0:
val['derived_from'] = val['types'][0]
else:
print "ERROR : types list is empty for node type '{}'".format(
type_name)
# get the version of the node type
val['version'] = str(Version(type_def.get('version')))
# get descrption
val['description'] = ""
descr = type_def.get('description')
if descr is not None:
val['description'] = descr
# get properties and attributes
val['attributes'] = get_attribute_definitions(
type_def.get('attributes'))
val['properties'] = get_property_definitions(
type_def.get('properties'))
# get valid_source_types
val['valid_source_types'] = []
sources = type_def.get('valid_source_types')
if isinstance(sources, list) and all(
map(lambda x: isinstance(x, basestring), sources)):
val['valid_source_types'] = sources
capa_types[type_name] = val
# store in the ditrit space
for type_name, type_val in capa_types.items():
linda_out('types/{}/capabilities/{}'.format(model_name, type_name),
type_val)
def parse_artifact_types(toscayaml, model_name):
"""
Create types internal representation
"""
artifact_types = {}
artifact_def = toscayaml.get('artifact_types')
if type(artifact_def) is dict:
for type_name, type_def in artifact_def.items():
val = {}
if type_name in artifact_types:
val = artifact_types[type_name]
val['name'] = type_name
# get the list of parents
val['types'] = get_types(artifact_def, type_name)
if len(val['types']) > 0:
val['derived_from'] = val['types'][0]
else:
print "ERROR : types list is empty for data type '{}'".format(
type_name)
# get the version of the node type
val['version'] = str(Version(type_def.get('version')))
# get metadata
val['metadata'] = {}
metadata = type_def.get('metadata')
if isinstance(metadata, dict) and all(
map(lambda x: isinstance(x, basestring),
metadata.values())):
val['metadata'] = metadata
# get descrption
val['description'] = ""
descr = type_def.get('description')
if descr is not None:
val['description'] = descr
# get mime_type
val['mime_type'] = type_def.get('mime_type')
if not isinstance(val['mime_type'], basestring):
val['mime_type'] = None
# get file_exts
exts = type_def.get('file_ext')
if exts is None:
exts = []
if isinstance(exts, list) and all(
map(lambda x: isinstance(x, basestring), exts)):
val['file_ext'] = exts
else:
print "Syntax Error : syntax error for file extensions '{}' for artifact type '{}'".format(
exts, type_name)
val['file_ext'] = None
# get properties
val['properties'] = get_property_definitions(
type_def.get('properties'))
artifact_types[type_name] = val
# store in the ditrit space
for type_name, type_val in artifact_types.items():
linda_out('types/{}/artifacts/{}'.format(model_name, type_name),
type_val)
def parse_node_types(toscayaml, model_name):
"""
Create types internal representation
"""
node_types = {}
# Part of the workflows defined in nodes have to be parsed before the part defined in relations.
nt_def = toscayaml.get('node_types')
if type(nt_def) is dict:
for type_name, type_def in nt_def.items():
val = {}
if type_name in node_types:
val = node_types[type_name]
val['name'] = type_name
# get the list of parents
val['types'] = get_types(nt_def, type_name)
if len(val['types']) > 0:
val['derived_from'] = val['types'][0]
else:
print "ERROR : types list is empty for node type '{}'".format(
type_name)
# for each declarative workflow defined in parents, get the nearest parent declaring the workflow
types_for_workflows = {}
for parent_type in val['types']:
parent_def = nt_def.get(parent_type)
if parent_def is None:
print "ERROR: node type '{}' is referenced but not defined".format(
parent_def)
else:
workflows = parent_def.get('workflows')
if isinstance(workflows, dict):
for workflow_name in workflows.keys():
workflow_type = types_for_workflows.get(
workflow_name)
if workflow_type is None:
types_for_workflows[
workflow_name] = parent_type
val['types_for_workflows'] = types_for_workflows
# is the node type derived from Compute ?
val['isCompute'] = 'tosca.nodes.Compute' in val['types']
# get the version of the node type
val['version'] = str(Version(type_def.get('version')))
# get metadata
val['metadata'] = {}
metadata = type_def.get('metadata')
if isinstance(metadata, dict) and all(
map(lambda x: isinstance(x, basestring),
metadata.values())):
val['metadata'] = metadata
# get descrption
val['description'] = ""
descr = type_def.get('description')
if descr is not None:
val['description'] = descr
# get properties and attributes
val['attributes'] = get_attribute_definitions(
type_def.get('attributes'))
val['properties'] = get_property_definitions(
type_def.get('properties'))
# get requirements and capabilities
val['requirements'] = get_requirement_definitions(
type_def.get('requirements'))
val['capabilities'] = get_capability_definitions(
type_def.get('capabilities'))
# get interfaces
val['interfaces'] = get_interface_definitions(
type_def.get('interfaces'))
# get workflows
val['workflows'] = type_def.get('workflows')
node_types[type_name] = val
# store in the ditrit space
for type_name, type_val in node_types.items():
linda_out('types/{}/nodes/{}'.format(model_name, type_name), type_val)