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def dict_tree(dictionary, indent=0):
"""
Create a visual tree representation of a dictionary.
Args:
dictionary (dict): The dictionary to represent as a tree.
indent (int): The current indentation level.
Returns:
str: A string representing the dictionary as a tree.
"""
tree_str = ''
for key, value in dictionary.items():
if indent > 0:
tree_str += ' |-----' * indent + f"{key}\n"
else:
tree_str += f"--{key}\n"
if isinstance(value, dict):
tree_str += dict_tree(value, indent + 1)
return tree_str
class Node:
def __init__(self):
pass
def __repr__(self):
return dict_tree(self.dictionary)
def __attr__(self):
"""
Recursively gather attributes of the node.
Returns:
list: A list of attribute names.
"""
attributes = []
lst = self.__dir__()
for item in lst:
if not item.startswith('__'):
if isinstance(getattr(self, item), Node):
attributes.extend([f'{item}.{i}' for i in getattr(self, item).__attr__()])
else:
attributes.append(item)
return list(filter(lambda x: 'dictionary' not in x, attributes))
def register_node(node, dictionary):
"""
Register a dictionary into a Node object.
Args:
node (Node): The node to register the dictionary to.
dictionary (dict): The dictionary to register.
"""
setattr(node, 'dictionary', dictionary)
for key, value in dictionary.items():
if isinstance(value, dict):
setattr(node, key, Node())
register_node(getattr(node, key), value)
else:
setattr(node, key, value)
def df_row_to_dict(row, column_names=None):
"""
Convert a row of a DataFrame to a dictionary.
Args:
row (pandas.Series): A row of a DataFrame.
column_names (list, optional): The list of column names. Defaults to None.
Returns:
dict: A dictionary that contains the same information as the row.
"""
if column_names is None:
column_names = row.index
return {name: row[name] for name in column_names}
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