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# -------------------------------------------------------------------------
# Copyright (c) 2015-2017 AT&T Intellectual Property
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# -------------------------------------------------------------------------
#
import collections
import itertools
class DotDict(dict):
"""A dot-dict mixin to be able to access a dictionary via dot notation
source: https://stackoverflow.com/questions/2352181/how-to-use-a-dot-to-access-members-of-dictionary
"""
__getattr__ = dict.get
__setattr__ = dict.__setitem__
__delattr__ = dict.__delitem__
class MetaSingleton(type):
"""Singleton class (2nd Chapter) from Learning Python Design Patterns - 2nd ed.
Chetan Giridhar, Packt Publ. 2016"""
_instances = {}
def __call__(cls, *args, **kwargs):
if cls not in cls._instances:
cls._instances[cls] = super(MetaSingleton, cls).__call__(*args, **kwargs)
return cls._instances[cls]
def namedtuple_with_defaults(typename, field_names, default_values=()):
"""A namedtuple with default values -- Stack overflow recipe from Mark Lodato
http://stackoverflow.com/questions/11351032/named-tuple-and-optional-keyword-arguments
:param typename: Name for the class (same as for namedtuple)
:param field_names: Field names (same as for namedtuple)
:param default_values: Can be specified as a dictionary or as a list
:return: New namedtuple object
"""
T = collections.namedtuple(typename, field_names)
T.__new__.__defaults__ = (None,) * len(T._fields)
if isinstance(default_values, collections.Mapping):
prototype = T(**default_values)
else:
prototype = T(*default_values)
T.__new__.__defaults__ = tuple(prototype)
return T
def dot_notation(dict_like, dot_spec):
"""Return the value corresponding to the dot_spec from a dict_like object
:param dict_like: dictionary, JSON, etc.
:param dot_spec: a dot notation (e.g. a1.b1.c1.d1 => a1["b1"]["c1"]["d1"])
:return: the value referenced by the dot_spec
"""
attrs = dot_spec.split(".") # we split the path
parent = dict_like.get(attrs[0])
children = ".".join(attrs[1:])
if not (parent and children): # if no children or no parent, bail out
return parent
if isinstance(parent, list): # here, we apply remaining path spec to all children
return [dot_notation(j, children) for j in parent]
elif isinstance(parent, dict):
return dot_notation(parent, children)
else:
return None
def list_flatten(l):
"""
Flatten a complex nested list of nested lists into a flat list (DFS).
For example, [ [1, 2], [[[2,3,4], [2,3,4]], [3,4,5, 'hello']]]
will produce [1, 2, 2, 3, 4, 2, 3, 4, 3, 4, 5, 'hello']
"""
return list(itertools.chain(*[list_flatten(j) if isinstance(j, list) else [j] for j in l]))
def inverted_dict(keys: list, key_val_dict: dict) -> dict:
"""
Get val -> [keys] mapping for the given keys using key_val_dict
:param keys: the keys we are interested in (a list)
:param key_val_dict: the key -> val mapping
:return: inverted dictionary of val -> [keys] (for the subset dict of given keys)
"""
res = {}
all_tuples = ((k, key_val_dict[k] if k in key_val_dict else 'no-parent-' + k) for k in keys)
for k, v in all_tuples:
if v in res:
res[v].append(k)
else:
res[v] = [k]
# making sure to remove duplicate keys
res = dict((v, list(set(k_list))) for v, k_list in res.items())
return res
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