Current File : //proc/thread-self/root/opt/cloudlinux/venv/lib/python3.11/site-packages/yaml/representer.py
__all__ = ['BaseRepresenter', 'SafeRepresenter', 'Representer',
'RepresenterError']
from .error import *
from .nodes import *
import datetime, copyreg, types, base64, collections
class RepresenterError(YAMLError):
pass
class BaseRepresenter:
yaml_representers = {}
yaml_multi_representers = {}
def __init__(self, default_style=None, default_flow_style=False, sort_keys=True):
self.default_style = default_style
self.sort_keys = sort_keys
self.default_flow_style = default_flow_style
self.represented_objects = {}
self.object_keeper = []
self.alias_key = None
def represent(self, data):
node = self.represent_data(data)
self.serialize(node)
self.represented_objects = {}
self.object_keeper = []
self.alias_key = None
def represent_data(self, data):
if self.ignore_aliases(data):
self.alias_key = None
else:
self.alias_key = id(data)
if self.alias_key is not None:
if self.alias_key in self.represented_objects:
node = self.represented_objects[self.alias_key]
#if node is None:
# raise RepresenterError("recursive objects are not allowed: %r" % data)
return node
#self.represented_objects[alias_key] = None
self.object_keeper.append(data)
data_types = type(data).__mro__
if data_types[0] in self.yaml_representers:
node = self.yaml_representers[data_types[0]](self, data)
else:
for data_type in data_types:
if data_type in self.yaml_multi_representers:
node = self.yaml_multi_representers[data_type](self, data)
break
else:
if None in self.yaml_multi_representers:
node = self.yaml_multi_representers[None](self, data)
elif None in self.yaml_representers:
node = self.yaml_representers[None](self, data)
else:
node = ScalarNode(None, str(data))
#if alias_key is not None:
# self.represented_objects[alias_key] = node
return node
@classmethod
def add_representer(cls, data_type, representer):
if not 'yaml_representers' in cls.__dict__:
cls.yaml_representers = cls.yaml_representers.copy()
cls.yaml_representers[data_type] = representer
@classmethod
def add_multi_representer(cls, data_type, representer):
if not 'yaml_multi_representers' in cls.__dict__:
cls.yaml_multi_representers = cls.yaml_multi_representers.copy()
cls.yaml_multi_representers[data_type] = representer
def represent_scalar(self, tag, value, style=None):
if style is None:
style = self.default_style
node = ScalarNode(tag, value, style=style)
if self.alias_key is not None:
self.represented_objects[self.alias_key] = node
return node
def represent_sequence(self, tag, sequence, flow_style=None):
value = []
node = SequenceNode(tag, value, flow_style=flow_style)
if self.alias_key is not None:
self.represented_objects[self.alias_key] = node
best_style = True
for item in sequence:
node_item = self.represent_data(item)
if not (isinstance(node_item, ScalarNode) and not node_item.style):
best_style = False
value.append(node_item)
if flow_style is None:
if self.default_flow_style is not None:
node.flow_style = self.default_flow_style
else:
node.flow_style = best_style
return node
def represent_mapping(self, tag, mapping, flow_style=None):
value = []
node = MappingNode(tag, value, flow_style=flow_style)
if self.alias_key is not None:
self.represented_objects[self.alias_key] = node
best_style = True
if hasattr(mapping, 'items'):
mapping = list(mapping.items())
if self.sort_keys:
try:
mapping = sorted(mapping)
except TypeError:
pass
for item_key, item_value in mapping:
node_key = self.represent_data(item_key)
node_value = self.represent_data(item_value)
if not (isinstance(node_key, ScalarNode) and not node_key.style):
best_style = False
if not (isinstance(node_value, ScalarNode) and not node_value.style):
best_style = False
value.append((node_key, node_value))
if flow_style is None:
if self.default_flow_style is not None:
node.flow_style = self.default_flow_style
else:
node.flow_style = best_style
return node
def ignore_aliases(self, data):
return False
class SafeRepresenter(BaseRepresenter):
def ignore_aliases(self, data):
if data is None:
return True
if isinstance(data, tuple) and data == ():
return True
if isinstance(data, (str, bytes, bool, int, float)):
return True
def represent_none(self, data):
return self.represent_scalar('tag:yaml.org,2002:null', 'null')
def represent_str(self, data):
return self.represent_scalar('tag:yaml.org,2002:str', data)
def represent_binary(self, data):
if hasattr(base64, 'encodebytes'):
data = base64.encodebytes(data).decode('ascii')
else:
data = base64.encodestring(data).decode('ascii')
return self.represent_scalar('tag:yaml.org,2002:binary', data, style='|')
def represent_bool(self, data):
if data:
value = 'true'
else:
value = 'false'
return self.represent_scalar('tag:yaml.org,2002:bool', value)
def represent_int(self, data):
return self.represent_scalar('tag:yaml.org,2002:int', str(data))
inf_value = 1e300
while repr(inf_value) != repr(inf_value*inf_value):
inf_value *= inf_value
def represent_float(self, data):
if data != data or (data == 0.0 and data == 1.0):
value = '.nan'
elif data == self.inf_value:
value = '.inf'
elif data == -self.inf_value:
value = '-.inf'
else:
value = repr(data).lower()
# Note that in some cases `repr(data)` represents a float number
# without the decimal parts. For instance:
# >>> repr(1e17)
# '1e17'
# Unfortunately, this is not a valid float representation according
# to the definition of the `!!float` tag. We fix this by adding
# '.0' before the 'e' symbol.
if '.' not in value and 'e' in value:
value = value.replace('e', '.0e', 1)
return self.represent_scalar('tag:yaml.org,2002:float', value)
def represent_list(self, data):
#pairs = (len(data) > 0 and isinstance(data, list))
#if pairs:
# for item in data:
# if not isinstance(item, tuple) or len(item) != 2:
# pairs = False
# break
#if not pairs:
return self.represent_sequence('tag:yaml.org,2002:seq', data)
#value = []
#for item_key, item_value in data:
# value.append(self.represent_mapping(u'tag:yaml.org,2002:map',
# [(item_key, item_value)]))
#return SequenceNode(u'tag:yaml.org,2002:pairs', value)
def represent_dict(self, data):
return self.represent_mapping('tag:yaml.org,2002:map', data)
def represent_set(self, data):
value = {}
for key in data:
value[key] = None
return self.represent_mapping('tag:yaml.org,2002:set', value)
def represent_date(self, data):
value = data.isoformat()
return self.represent_scalar('tag:yaml.org,2002:timestamp', value)
def represent_datetime(self, data):
value = data.isoformat(' ')
return self.represent_scalar('tag:yaml.org,2002:timestamp', value)
def represent_yaml_object(self, tag, data, cls, flow_style=None):
if hasattr(data, '__getstate__'):
state = data.__getstate__()
else:
state = data.__dict__.copy()
return self.represent_mapping(tag, state, flow_style=flow_style)
def represent_undefined(self, data):
raise RepresenterError("cannot represent an object", data)
SafeRepresenter.add_representer(type(None),
SafeRepresenter.represent_none)
SafeRepresenter.add_representer(str,
SafeRepresenter.represent_str)
SafeRepresenter.add_representer(bytes,
SafeRepresenter.represent_binary)
SafeRepresenter.add_representer(bool,
SafeRepresenter.represent_bool)
SafeRepresenter.add_representer(int,
SafeRepresenter.represent_int)
SafeRepresenter.add_representer(float,
SafeRepresenter.represent_float)
SafeRepresenter.add_representer(list,
SafeRepresenter.represent_list)
SafeRepresenter.add_representer(tuple,
SafeRepresenter.represent_list)
SafeRepresenter.add_representer(dict,
SafeRepresenter.represent_dict)
SafeRepresenter.add_representer(set,
SafeRepresenter.represent_set)
SafeRepresenter.add_representer(datetime.date,
SafeRepresenter.represent_date)
SafeRepresenter.add_representer(datetime.datetime,
SafeRepresenter.represent_datetime)
SafeRepresenter.add_representer(None,
SafeRepresenter.represent_undefined)
class Representer(SafeRepresenter):
def represent_complex(self, data):
if data.imag == 0.0:
data = '%r' % data.real
elif data.real == 0.0:
data = '%rj' % data.imag
elif data.imag > 0:
data = '%r+%rj' % (data.real, data.imag)
else:
data = '%r%rj' % (data.real, data.imag)
return self.represent_scalar('tag:yaml.org,2002:python/complex', data)
def represent_tuple(self, data):
return self.represent_sequence('tag:yaml.org,2002:python/tuple', data)
def represent_name(self, data):
name = '%s.%s' % (data.__module__, data.__name__)
return self.represent_scalar('tag:yaml.org,2002:python/name:'+name, '')
def represent_module(self, data):
return self.represent_scalar(
'tag:yaml.org,2002:python/module:'+data.__name__, '')
def represent_object(self, data):
# We use __reduce__ API to save the data. data.__reduce__ returns
# a tuple of length 2-5:
# (function, args, state, listitems, dictitems)
# For reconstructing, we calls function(*args), then set its state,
# listitems, and dictitems if they are not None.
# A special case is when function.__name__ == '__newobj__'. In this
# case we create the object with args[0].__new__(*args).
# Another special case is when __reduce__ returns a string - we don't
# support it.
# We produce a !!python/object, !!python/object/new or
# !!python/object/apply node.
cls = type(data)
if cls in copyreg.dispatch_table:
reduce = copyreg.dispatch_table[cls](data)
elif hasattr(data, '__reduce_ex__'):
reduce = data.__reduce_ex__(2)
elif hasattr(data, '__reduce__'):
reduce = data.__reduce__()
else:
raise RepresenterError("cannot represent an object", data)
reduce = (list(reduce)+[None]*5)[:5]
function, args, state, listitems, dictitems = reduce
args = list(args)
if state is None:
state = {}
if listitems is not None:
listitems = list(listitems)
if dictitems is not None:
dictitems = dict(dictitems)
if function.__name__ == '__newobj__':
function = args[0]
args = args[1:]
tag = 'tag:yaml.org,2002:python/object/new:'
newobj = True
else:
tag = 'tag:yaml.org,2002:python/object/apply:'
newobj = False
function_name = '%s.%s' % (function.__module__, function.__name__)
if not args and not listitems and not dictitems \
and isinstance(state, dict) and newobj:
return self.represent_mapping(
'tag:yaml.org,2002:python/object:'+function_name, state)
if not listitems and not dictitems \
and isinstance(state, dict) and not state:
return self.represent_sequence(tag+function_name, args)
value = {}
if args:
value['args'] = args
if state or not isinstance(state, dict):
value['state'] = state
if listitems:
value['listitems'] = listitems
if dictitems:
value['dictitems'] = dictitems
return self.represent_mapping(tag+function_name, value)
def represent_ordered_dict(self, data):
# Provide uniform representation across different Python versions.
data_type = type(data)
tag = 'tag:yaml.org,2002:python/object/apply:%s.%s' \
% (data_type.__module__, data_type.__name__)
items = [[key, value] for key, value in data.items()]
return self.represent_sequence(tag, [items])
Representer.add_representer(complex,
Representer.represent_complex)
Representer.add_representer(tuple,
Representer.represent_tuple)
Representer.add_multi_representer(type,
Representer.represent_name)
Representer.add_representer(collections.OrderedDict,
Representer.represent_ordered_dict)
Representer.add_representer(types.FunctionType,
Representer.represent_name)
Representer.add_representer(types.BuiltinFunctionType,
Representer.represent_name)
Representer.add_representer(types.ModuleType,
Representer.represent_module)
Representer.add_multi_representer(object,
Representer.represent_object)
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