Accessing dict keys like an attribute?

Question

I find it more convenient to access dict keys as obj.foo instead of obj[\'foo\'], so I wrote this snippet:

class AttributeDict(dict         


        

Answer 1

No need to write your own as setattr() and getattr() already exist.

The advantage of class objects probably comes into play in class definition and inheritance.

Answer 2

This isn't a 'good' answer, but I thought this was nifty (it doesn't handle nested dicts in current form). Simply wrap your dict in a function:

def make_funcdict(d=None, **kwargs)
    def funcdict(d=None, **kwargs):
        if d is not None:
            funcdict.__dict__.update(d)
        funcdict.__dict__.update(kwargs)
        return funcdict.__dict__
    funcdict(d, **kwargs)
    return funcdict

Now you have slightly different syntax. To acces the dict items as attributes do f.key. To access the dict items (and other dict methods) in the usual manner do f()['key'] and we can conveniently update the dict by calling f with keyword arguments and/or a dictionary

Example

d = {'name':'Henry', 'age':31}
d = make_funcdict(d)
>>> for key in d():
...     print key
... 
age
name
>>> print d.name
... Henry
>>> print d.age
... 31
>>> d({'Height':'5-11'}, Job='Carpenter')
... {'age': 31, 'name': 'Henry', 'Job': 'Carpenter', 'Height': '5-11'}

And there it is. I'll be happy if anyone suggests benefits and drawbacks of this method.

Answer 3

From This other SO question there's a great implementation example that simplifies your existing code. How about:

class AttributeDict(dict):
    __slots__ = () 
    __getattr__ = dict.__getitem__
    __setattr__ = dict.__setitem__

Much more concise and doesn't leave any room for extra cruft getting into your __getattr__ and __setattr__ functions in the future.

Answer 4

Let me post another implementation, which builds upon the answer of Kinvais, but integrates ideas from the AttributeDict proposed in http://databio.org/posts/python_AttributeDict.html.

The advantage of this version is that it also works for nested dictionaries:

class AttrDict(dict):
    """
    A class to convert a nested Dictionary into an object with key-values
    that are accessible using attribute notation (AttrDict.attribute) instead of
    key notation (Dict["key"]). This class recursively sets Dicts to objects,
    allowing you to recurse down nested dicts (like: AttrDict.attr.attr)
    """

    # Inspired by:
    # http://stackoverflow.com/a/14620633/1551810
    # http://databio.org/posts/python_AttributeDict.html

    def __init__(self, iterable, **kwargs):
        super(AttrDict, self).__init__(iterable, **kwargs)
        for key, value in iterable.items():
            if isinstance(value, dict):
                self.__dict__[key] = AttrDict(value)
            else:
                self.__dict__[key] = value

Answer 5

The best way to do this is:

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

Some pros:

• It actually works!
• No dictionary class methods are shadowed (e.g. .keys() work just fine. Unless - of course - you assign some value to them, see below)
• Attributes and items are always in sync
• Trying to access non-existent key as an attribute correctly raises AttributeError instead of KeyError
• Supports [Tab] autocompletion (e.g. in jupyter & ipython)

Cons:

• Methods like .keys() will not work just fine if they get overwritten by incoming data
• Each AttrDict instance actually stores 2 dictionaries, one inherited and another one in __dict__
• Causes a memory leak in Python < 2.7.4 / Python3 < 3.2.3
• Pylint goes bananas with E1123(unexpected-keyword-arg) and E1103(maybe-no-member)
• For the uninitiated it seems like pure magic.

A short explanation on how this works

• All python objects internally store their attributes in a dictionary that is named __dict__.
• There is no requirement that the internal dictionary __dict__ would need to be "just a plain dict", so we can assign any subclass of dict() to the internal dictionary.
• In our case we simply assign the AttrDict() instance we are instantiating (as we are in __init__).
• By calling super()'s __init__() method we made sure that it (already) behaves exactly like a dictionary, since that function calls all the dictionary instantiation code.

One reason why Python doesn't provide this functionality out of the box

As noted in the "cons" list, this combines the namespace of stored keys (which may come from arbitrary and/or untrusted data!) with the namespace of builtin dict method attributes. For example:

d = AttrDict()
d.update({'items':["jacket", "necktie", "trousers"]})
for k, v in d.items():    # TypeError: 'list' object is not callable
    print "Never reached!"

Update - 2020

Since this question was asked almost ten years ago, quite a bit has changed in Python itself since then.

While this approach is still valid for some cases, e.g. legacy projects stuck to older versions of Python and cases where you really need to handle dictionaries with very dynamic string keys - I think that in general the dataclasses introduced in Python 3.7 are the obvious/correct solution to vast majority of the use cases of AttrDict.

Answer 6

What if you wanted a key which was a method, such as __eq__ or __getattr__?

And you wouldn't be able to have an entry that didn't start with a letter, so using 0343853 as a key is out.

And what if you didn't want to use a string?