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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