Class that acts as mapping for **unpacking


Without subclassing dict, what would a class need to be considered a mapping so that it can be passed to a method with **.

from abc import ABCMeta

class uobj:
    __metaclass__ = ABCMeta


def f(**k): return k

o = uobj()

# outputs: f() argument after ** must be a mapping, not uobj

At least to the point where it throws errors of missing functionality of mapping, so I can begin implementing.

I reviewed emulating container types but simply defining magic methods has no effect, and using ABCMeta to override and register it as a dict validates assertions as subclass, but fails isinstance(o, dict). Ideally, I dont even want to use ABCMeta.

Asked By: dskinner



The __getitem__() and keys() methods will suffice:

>>> class D:
        def keys(self):
            return ['a', 'b']
        def __getitem__(self, key):
            return key.upper()

>>> def f(**kwds):
        print kwds

>>> f(**D())
{'a': 'A', 'b': 'B'}
Answered By: Raymond Hettinger

If you’re trying to create a Mapping — not just satisfy the requirements for passing to a function — then you really should inherit from As described in the documentation, you need to implement just:


The Mixin will implement everything else for you: __contains__, keys, items, values, get, __eq__, and __ne__.

Answered By: Neil G

The answer can be found by digging through the source.

When attempting to use a non-mapping object with **, the following error is given:

TypeError: 'Foo' object is not a mapping

If we search CPython’s source for that error, we can find the code that causes that error to be raised:

    PyObject *update = POP();
    PyObject *dict = PEEK(oparg);
    if (PyDict_Update(dict, update) < 0) {
        if (_PyErr_ExceptionMatches(tstate, PyExc_AttributeError)) {
            _PyErr_Format(tstate, PyExc_TypeError,
                            "'%.200s' object is not a mapping",

PyDict_Update is actually dict_merge, and the error is thrown when dict_merge returns a negative number. If we check the source for dict_merge, we can see what leads to -1 being returned:

/* We accept for the argument either a concrete dictionary object,
 * or an abstract "mapping" object.  For the former, we can do
 * things quite efficiently.  For the latter, we only require that
 * PyMapping_Keys() and PyObject_GetItem() be supported.
if (a == NULL || !PyDict_Check(a) || b == NULL) {
    return -1;

The key part being:

For the latter, we only require that PyMapping_Keys() and PyObject_GetItem() be supported.

Answered By: Carcigenicate