mirror of
https://github.com/PiBrewing/craftbeerpi4.git
synced 2024-12-29 17:01:44 +01:00
389 lines
14 KiB
Python
389 lines
14 KiB
Python
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__all__ = ['BaseRepresenter', 'SafeRepresenter', 'Representer',
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'RepresenterError']
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from .error import *
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from .nodes import *
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import datetime, copyreg, types, base64, collections
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class RepresenterError(YAMLError):
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pass
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class BaseRepresenter:
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yaml_representers = {}
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yaml_multi_representers = {}
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def __init__(self, default_style=None, default_flow_style=False, sort_keys=True):
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self.default_style = default_style
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self.sort_keys = sort_keys
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self.default_flow_style = default_flow_style
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self.represented_objects = {}
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self.object_keeper = []
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self.alias_key = None
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def represent(self, data):
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node = self.represent_data(data)
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self.serialize(node)
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self.represented_objects = {}
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self.object_keeper = []
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self.alias_key = None
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def represent_data(self, data):
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if self.ignore_aliases(data):
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self.alias_key = None
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else:
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self.alias_key = id(data)
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if self.alias_key is not None:
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if self.alias_key in self.represented_objects:
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node = self.represented_objects[self.alias_key]
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#if node is None:
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# raise RepresenterError("recursive objects are not allowed: %r" % data)
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return node
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#self.represented_objects[alias_key] = None
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self.object_keeper.append(data)
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data_types = type(data).__mro__
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if data_types[0] in self.yaml_representers:
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node = self.yaml_representers[data_types[0]](self, data)
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else:
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for data_type in data_types:
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if data_type in self.yaml_multi_representers:
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node = self.yaml_multi_representers[data_type](self, data)
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break
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else:
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if None in self.yaml_multi_representers:
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node = self.yaml_multi_representers[None](self, data)
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elif None in self.yaml_representers:
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node = self.yaml_representers[None](self, data)
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else:
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node = ScalarNode(None, str(data))
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#if alias_key is not None:
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# self.represented_objects[alias_key] = node
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return node
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@classmethod
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def add_representer(cls, data_type, representer):
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if not 'yaml_representers' in cls.__dict__:
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cls.yaml_representers = cls.yaml_representers.copy()
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cls.yaml_representers[data_type] = representer
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@classmethod
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def add_multi_representer(cls, data_type, representer):
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if not 'yaml_multi_representers' in cls.__dict__:
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cls.yaml_multi_representers = cls.yaml_multi_representers.copy()
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cls.yaml_multi_representers[data_type] = representer
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def represent_scalar(self, tag, value, style=None):
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if style is None:
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style = self.default_style
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node = ScalarNode(tag, value, style=style)
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if self.alias_key is not None:
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self.represented_objects[self.alias_key] = node
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return node
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def represent_sequence(self, tag, sequence, flow_style=None):
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value = []
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node = SequenceNode(tag, value, flow_style=flow_style)
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if self.alias_key is not None:
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self.represented_objects[self.alias_key] = node
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best_style = True
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for item in sequence:
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node_item = self.represent_data(item)
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if not (isinstance(node_item, ScalarNode) and not node_item.style):
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best_style = False
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value.append(node_item)
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if flow_style is None:
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if self.default_flow_style is not None:
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node.flow_style = self.default_flow_style
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else:
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node.flow_style = best_style
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return node
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def represent_mapping(self, tag, mapping, flow_style=None):
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value = []
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node = MappingNode(tag, value, flow_style=flow_style)
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if self.alias_key is not None:
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self.represented_objects[self.alias_key] = node
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best_style = True
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if hasattr(mapping, 'items'):
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mapping = list(mapping.items())
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if self.sort_keys:
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try:
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mapping = sorted(mapping)
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except TypeError:
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pass
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for item_key, item_value in mapping:
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node_key = self.represent_data(item_key)
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node_value = self.represent_data(item_value)
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if not (isinstance(node_key, ScalarNode) and not node_key.style):
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best_style = False
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if not (isinstance(node_value, ScalarNode) and not node_value.style):
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best_style = False
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value.append((node_key, node_value))
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if flow_style is None:
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if self.default_flow_style is not None:
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node.flow_style = self.default_flow_style
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else:
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node.flow_style = best_style
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return node
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def ignore_aliases(self, data):
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return False
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class SafeRepresenter(BaseRepresenter):
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def ignore_aliases(self, data):
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if data is None:
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return True
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if isinstance(data, tuple) and data == ():
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return True
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if isinstance(data, (str, bytes, bool, int, float)):
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return True
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def represent_none(self, data):
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return self.represent_scalar('tag:yaml.org,2002:null', 'null')
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def represent_str(self, data):
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return self.represent_scalar('tag:yaml.org,2002:str', data)
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def represent_binary(self, data):
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if hasattr(base64, 'encodebytes'):
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data = base64.encodebytes(data).decode('ascii')
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else:
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data = base64.encodestring(data).decode('ascii')
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return self.represent_scalar('tag:yaml.org,2002:binary', data, style='|')
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def represent_bool(self, data):
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if data:
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value = 'true'
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else:
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value = 'false'
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return self.represent_scalar('tag:yaml.org,2002:bool', value)
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def represent_int(self, data):
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return self.represent_scalar('tag:yaml.org,2002:int', str(data))
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inf_value = 1e300
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while repr(inf_value) != repr(inf_value*inf_value):
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inf_value *= inf_value
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def represent_float(self, data):
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if data != data or (data == 0.0 and data == 1.0):
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value = '.nan'
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elif data == self.inf_value:
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value = '.inf'
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elif data == -self.inf_value:
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value = '-.inf'
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else:
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value = repr(data).lower()
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# Note that in some cases `repr(data)` represents a float number
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# without the decimal parts. For instance:
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# >>> repr(1e17)
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# '1e17'
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# Unfortunately, this is not a valid float representation according
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# to the definition of the `!!float` tag. We fix this by adding
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# '.0' before the 'e' symbol.
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if '.' not in value and 'e' in value:
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value = value.replace('e', '.0e', 1)
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return self.represent_scalar('tag:yaml.org,2002:float', value)
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def represent_list(self, data):
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#pairs = (len(data) > 0 and isinstance(data, list))
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#if pairs:
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# for item in data:
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# if not isinstance(item, tuple) or len(item) != 2:
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# pairs = False
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# break
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#if not pairs:
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return self.represent_sequence('tag:yaml.org,2002:seq', data)
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#value = []
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#for item_key, item_value in data:
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# value.append(self.represent_mapping(u'tag:yaml.org,2002:map',
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# [(item_key, item_value)]))
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#return SequenceNode(u'tag:yaml.org,2002:pairs', value)
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def represent_dict(self, data):
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return self.represent_mapping('tag:yaml.org,2002:map', data)
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def represent_set(self, data):
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value = {}
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for key in data:
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value[key] = None
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return self.represent_mapping('tag:yaml.org,2002:set', value)
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def represent_date(self, data):
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value = data.isoformat()
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return self.represent_scalar('tag:yaml.org,2002:timestamp', value)
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def represent_datetime(self, data):
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value = data.isoformat(' ')
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return self.represent_scalar('tag:yaml.org,2002:timestamp', value)
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def represent_yaml_object(self, tag, data, cls, flow_style=None):
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if hasattr(data, '__getstate__'):
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state = data.__getstate__()
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else:
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state = data.__dict__.copy()
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return self.represent_mapping(tag, state, flow_style=flow_style)
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def represent_undefined(self, data):
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raise RepresenterError("cannot represent an object", data)
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SafeRepresenter.add_representer(type(None),
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SafeRepresenter.represent_none)
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SafeRepresenter.add_representer(str,
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SafeRepresenter.represent_str)
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SafeRepresenter.add_representer(bytes,
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SafeRepresenter.represent_binary)
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SafeRepresenter.add_representer(bool,
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SafeRepresenter.represent_bool)
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SafeRepresenter.add_representer(int,
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SafeRepresenter.represent_int)
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SafeRepresenter.add_representer(float,
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SafeRepresenter.represent_float)
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SafeRepresenter.add_representer(list,
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SafeRepresenter.represent_list)
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SafeRepresenter.add_representer(tuple,
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SafeRepresenter.represent_list)
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SafeRepresenter.add_representer(dict,
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SafeRepresenter.represent_dict)
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SafeRepresenter.add_representer(set,
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SafeRepresenter.represent_set)
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SafeRepresenter.add_representer(datetime.date,
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SafeRepresenter.represent_date)
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SafeRepresenter.add_representer(datetime.datetime,
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SafeRepresenter.represent_datetime)
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SafeRepresenter.add_representer(None,
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SafeRepresenter.represent_undefined)
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class Representer(SafeRepresenter):
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def represent_complex(self, data):
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if data.imag == 0.0:
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data = '%r' % data.real
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elif data.real == 0.0:
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data = '%rj' % data.imag
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elif data.imag > 0:
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data = '%r+%rj' % (data.real, data.imag)
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else:
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data = '%r%rj' % (data.real, data.imag)
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return self.represent_scalar('tag:yaml.org,2002:python/complex', data)
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def represent_tuple(self, data):
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return self.represent_sequence('tag:yaml.org,2002:python/tuple', data)
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def represent_name(self, data):
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name = '%s.%s' % (data.__module__, data.__name__)
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return self.represent_scalar('tag:yaml.org,2002:python/name:'+name, '')
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def represent_module(self, data):
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return self.represent_scalar(
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'tag:yaml.org,2002:python/module:'+data.__name__, '')
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def represent_object(self, data):
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# We use __reduce__ API to save the data. data.__reduce__ returns
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# a tuple of length 2-5:
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# (function, args, state, listitems, dictitems)
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# For reconstructing, we calls function(*args), then set its state,
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# listitems, and dictitems if they are not None.
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# A special case is when function.__name__ == '__newobj__'. In this
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# case we create the object with args[0].__new__(*args).
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# Another special case is when __reduce__ returns a string - we don't
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# support it.
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# We produce a !!python/object, !!python/object/new or
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# !!python/object/apply node.
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cls = type(data)
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if cls in copyreg.dispatch_table:
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reduce = copyreg.dispatch_table[cls](data)
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elif hasattr(data, '__reduce_ex__'):
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reduce = data.__reduce_ex__(2)
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elif hasattr(data, '__reduce__'):
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reduce = data.__reduce__()
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else:
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raise RepresenterError("cannot represent an object", data)
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reduce = (list(reduce)+[None]*5)[:5]
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function, args, state, listitems, dictitems = reduce
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args = list(args)
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if state is None:
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state = {}
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if listitems is not None:
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listitems = list(listitems)
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if dictitems is not None:
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dictitems = dict(dictitems)
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if function.__name__ == '__newobj__':
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function = args[0]
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args = args[1:]
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tag = 'tag:yaml.org,2002:python/object/new:'
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newobj = True
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else:
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tag = 'tag:yaml.org,2002:python/object/apply:'
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newobj = False
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function_name = '%s.%s' % (function.__module__, function.__name__)
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if not args and not listitems and not dictitems \
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and isinstance(state, dict) and newobj:
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return self.represent_mapping(
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'tag:yaml.org,2002:python/object:'+function_name, state)
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if not listitems and not dictitems \
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and isinstance(state, dict) and not state:
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return self.represent_sequence(tag+function_name, args)
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value = {}
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if args:
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value['args'] = args
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if state or not isinstance(state, dict):
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value['state'] = state
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if listitems:
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value['listitems'] = listitems
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if dictitems:
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value['dictitems'] = dictitems
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return self.represent_mapping(tag+function_name, value)
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def represent_ordered_dict(self, data):
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# Provide uniform representation across different Python versions.
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data_type = type(data)
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tag = 'tag:yaml.org,2002:python/object/apply:%s.%s' \
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% (data_type.__module__, data_type.__name__)
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items = [[key, value] for key, value in data.items()]
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return self.represent_sequence(tag, [items])
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Representer.add_representer(complex,
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Representer.represent_complex)
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Representer.add_representer(tuple,
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Representer.represent_tuple)
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Representer.add_representer(type,
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Representer.represent_name)
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Representer.add_representer(collections.OrderedDict,
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Representer.represent_ordered_dict)
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Representer.add_representer(types.FunctionType,
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Representer.represent_name)
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Representer.add_representer(types.BuiltinFunctionType,
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Representer.represent_name)
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Representer.add_representer(types.ModuleType,
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Representer.represent_module)
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Representer.add_multi_representer(object,
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Representer.represent_object)
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