How To Use Dict.get() With Multidimensional Dict?

I have a multidimensional dict, and I'd like to be able to retrieve a value by a key:key pair, and return 'NA' if the first key doesn't exist. All of the sub-dicts have the same ke

Solution 1:

How about

d.get('a', {'j': 'NA'})['j']

?

If not all subdicts have a j key, then

d.get('a', {}).get('j', 'NA')

 

To cut down on identical objects created, you can devise something like

classDefaultNASubdict(dict):
    classNADict(object):
        def__getitem__(self, k):
            return'NA'

    NA = NADict()

    def__missing__(self, k):
        return self.NA

nadict = DefaultNASubdict({
                'a': {'j':1,'k':2},
                'b': {'j':2,'k':3},
                'd': {'j':1,'k':3}
            })

print nadict['a']['j']  # 1print nadict['b']['j']  # 2print nadict['c']['j']  # NA

 

Same idea using defaultdict:

import collections

classNADict(object):def__getitem__(self, k):
        return'NA'@staticmethoddefinstance():
        return NADict._instance

NADict._instance = NADict()


nadict = collections.defaultdict(NADict.instance, {
                'a': {'j':1,'k':2},
                'b': {'j':2,'k':3},
                'd': {'j':1,'k':3}
            })

Solution 2:

Another way to get multidimensional dict example ( use get method twice)

d.get('a', {}).get('j')

Solution 3:

Here's a simple and efficient way to do it with ordinary dictionaries, nested an arbitrary number of levels. The example code works in both Python 2 and 3.

from __future__ import print_function
try:
    from functools import reduce
except ImportError:  # Assume it's built-in (Python 2.x)passdefchained_get(dct, *keys):
    SENTRY = object()
    defgetter(level, key):
        return'NA'if level is SENTRY else level.get(key, SENTRY)
    return reduce(getter, keys, dct)


d = {'a': {'j': 1, 'k': 2},
     'b': {'j': 2, 'k': 3},
     'd': {'j': 1, 'k': 3},
    }

print(chained_get(d, 'a', 'j'))  # 1print(chained_get(d, 'b', 'k'))  # 3print(chained_get(d, 'k', 'j'))  # NA

It could also be done recursively:

# Recursive version.defchained_get(dct, *keys):
    SENTRY = object()
    defgetter(level, keys):
        return (level if keys[0] is SENTRY else'NA'if level is SENTRY else
                        getter(level.get(keys[0], SENTRY), keys[1:]))
    return getter(dct, keys+(SENTRY,))

Although this way of doing it isn't quite as efficient as the first.

Solution 4:

Rather than a hierarchy of nested dict objects, you could use one dictionary whose keys are a tuple representing a path through the hierarchy.

In [34]: d2 = {(x,y):d[x][y] for x in d for y in d[x]}

In [35]: d2
Out[35]:
{('a', 'j'): 1,
 ('a', 'k'): 2,
 ('b', 'j'): 2,
 ('b', 'k'): 3,
 ('d', 'j'): 1,
 ('d', 'k'): 3}

In [36]: timeit [d[x][y] for x,y in d2.keys()]
100000 loops, best of 3: 2.37 us per loop

In [37]: timeit [d2[x] for x in d2.keys()]
100000 loops, best of 3: 2.03 us per loop

Accessing this way looks like it's about 15% faster. You can still use the get method with a default value:

In [38]: d2.get(('c','j'),'NA')
Out[38]: 'NA'