The problem with this chunk of code:

class myDict(dict):
    def __init__(self):
        self._dict = {}

    def add(id, val):
        self._dict[id] = val


md = myDict()
md.add('id', 123)

…is that your ‘add’ method (…and any method you want to be a member of a class) needs to have an explicit ‘self’ declared as its first argument, like:

def add(self, 'id', 23):

To implement the operator overloading to access items by key, look in the docs for the magic methods __getitem__ and __setitem__.

Note that because Python uses Duck Typing, there may actually be no reason to derive your custom dict class from the language’s dict class — without knowing more about what you’re trying to do (e.g, if you need to pass an instance of this class into some code someplace that will break unless isinstance(MyDict(), dict) == True), you may be better off just implementing the API that makes your class sufficiently dict-like and stopping there.

Like this

class CustomDictOne(dict):
   def __init__(self,*arg,**kw):
      super(CustomDictOne, self).__init__(*arg, **kw)

Now you can use the built-in functions, like dict.get() as self.get().

You do not need to wrap a hidden self._dict. Your class already is a dict.

class Mapping(dict):

    def __setitem__(self, key, item):
        self.__dict__[key] = item

    def __getitem__(self, key):
        return self.__dict__[key]

    def __repr__(self):
        return repr(self.__dict__)

    def __len__(self):
        return len(self.__dict__)

    def __delitem__(self, key):
        del self.__dict__[key]

    def clear(self):
        return self.__dict__.clear()

    def copy(self):
        return self.__dict__.copy()

    def has_key(self, k):
        return k in self.__dict__

    def update(self, *args, **kwargs):
        return self.__dict__.update(*args, **kwargs)

    def keys(self):
        return self.__dict__.keys()

    def values(self):
        return self.__dict__.values()

    def items(self):
        return self.__dict__.items()

    def pop(self, *args):
        return self.__dict__.pop(*args)

    def __cmp__(self, dict_):
        return self.__cmp__(self.__dict__, dict_)

    def __contains__(self, item):
        return item in self.__dict__

    def __iter__(self):
        return iter(self.__dict__)

    def __unicode__(self):
        return unicode(repr(self.__dict__))


o = Mapping()
o.foo = "bar"
o['lumberjack'] = 'foo'
o.update({'a': 'b'}, c=44)
print 'lumberjack' in o
print o

In [187]: run mapping.py
True
{'a': 'b', 'lumberjack': 'foo', 'foo': 'bar', 'c': 44}

Don’t inherit from Python built-in dict, ever! for example update method woldn’t use __setitem__, they do a lot for optimization. Use UserDict.

from collections import UserDict

class MyDict(UserDict):
    def __delitem__(self, key):
        pass
    def __setitem__(self, key, value):
        pass

Here is an alternative solution:

class AttrDict(dict):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self.__dict__ = self

a = AttrDict()
a.a = 1
a.b = 2

I really don’t see the right answer to this anywhere

class MyClass(dict):
    
    def __init__(self, a_property):
        self[a_property] = a_property

All you are really having to do is define your own __init__ – that really is all that there is too it.

Another example (little more complex):

class MyClass(dict):

    def __init__(self, planet):
        self[planet] = planet
        info = self.do_something_that_returns_a_dict()
        if info:
            for k, v in info.items():
                self[k] = v

    def do_something_that_returns_a_dict(self):
        return {"mercury": "venus", "mars": "jupiter"}

This last example is handy when you want to embed some kind of logic.

Anyway… in short class GiveYourClassAName(dict) is enough to make your class act like a dict. Any dict operation you do on self will be just like a regular dict.

This is my best solution. I used this many times.

class DictLikeClass:
    ...
    def __getitem__(self, key):
        return getattr(self, key)

    def __setitem__(self, key, value):
        setattr(self, key, value)
    ...

You can use like:

>>> d = DictLikeClass()
>>> d["key"] = "value"
>>> print(d["key"])

A python class that acts like dict

What’s wrong with this?

Can anyone point out why most of the inheritance snippets look like the one below?

class CustomDictOne(dict):
   def __init__(self):
      self._mydict = {} 

Presumably there’s a good reason to inherit from dict (maybe you’re already passing one around and you want a more specific kind of dict) and you have a good reason to instantiate another dict to delegate to (because this will instantiate two dicts per instance of this class.) But doesn’t that sound incorrect?

I never run into this use-case myself. I do like the idea of typing dicts where you are using dicts that are type-able. But in that case I like the idea of typed class attributes even moreso – and the whole point of a dict is you can give it keys of any hashable type, and values of any type.

So why do we see snippets like this? I personally think it’s an easily made mistake that went uncorrected and thus perpetuated over time.

I would rather see, in these snippets, this, to demonstrate code reuse through inheritance:

class AlternativeOne(dict):
    __slots__ = ()
    def __init__(self):
        super().__init__()
        # other init code here
    # new methods implemented here

or, to demonstrate re-implementing the behavior of dicts, this:

from collections.abc import MutableMapping 

class AlternativeTwo(MutableMapping):
    __slots__ = '_mydict'
    def __init__(self):
        self._mydict = {}
        # other init code here
    # dict methods reimplemented and new methods implemented here

By request – adding slots to a dict subclass.

Why add slots? A builtin dict instance doesn’t have arbitrary attributes:

>>> d = dict()
>>> d.foo = 'bar'
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: 'dict' object has no attribute 'foo'

If we create a subclass the way most are doing it here on this answer, we see we don’t get the same behavior, because we’ll have a __dict__ attribute, causing our dicts to take up to potentially twice the space:

my_dict(dict):
    """my subclass of dict""" 

md = my_dict()
md.foo = 'bar'

Since there’s no error created by the above, the above class doesn’t actually act, "like dict."

We can make it act like dict by giving it empty slots:

class my_dict(dict):
    __slots__ = ()

md = my_dict()

So now attempting to use arbitrary attributes will fail:

>>> md.foo = 'bar'
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: 'my_dict' object has no attribute 'foo'

And this Python class acts more like a dict.

For more on how and why to use slots, see this Q&A: Usage of __slots__?

UserDict from the Python standard library is designed for this purpose.