Filename: //lib/python3/////dist-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_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)

./Ninja\.