munch

mbda x: x*x}) In [4]: d.square(4) Out[4]: 16 In [5]: d Out[5]: {'a': 'b', 'c': [1, 2, 3], 'square': <function <lambda> at 0x7f9ef5d5b0d0>} In [6]: import datetime In [7]: d.created_at = datetime.datetime.now() In [8]: d Out[8]: {'a': 'b', 'c': [1, 2, 3], 'square': <function <lambda> at 0x7f9ef5d5b0d0>, 'created_at': datetime.datetime(2021, 7, 19, 19, 42, 32, 341393)} In practice, this can lead to headaches. Take, for example, what happens if we try to serialize `d` (which has a non-serializable lambda function in its keys) using the built-in pickle module: In [9]: import pickle In [10]: pickle.dumps(d) Traceback (most recent call last): File "<stdin>", line 1, in <module> _pickle.PicklingError: Can't pickle <class 'DotDict'>: attribute lookup DotDict on builtins failed Thankfully there's a third-party library called cloudpickle which can serialize just about any python object to bytes -- even including the user-defined DotDict class (!): In [12]: deserialized_d = cloudpickle.loads(cloudpickle.dumps(d)) In [13]: deserialized_d Out[13]: {'a': 'b', 'c': [1, 2, 3], 'square': <function <lambda> at 0x7f9ef650fee0>, 'created_at': datetime.datetime(2021, 7, 19, 19, 42, 32, 341393)} Since the entire class definition is serialized along with the instance, the deserialized copy preserves the object's attribute-style interface as before: In [14]: deserialized_d.created_at.strftime("%c") Out[14]: 'Mon Jul 19 19:42:32 2021' But I recommend Munch over rolling your own because subclassing `dict` is fraught with a surprising number of edge cases.