How to update values in nested dictionary if keys are in a list? [duplicate]

Answer 1

You can iteratively build/access levels using setdefault in a loop:

d = {}
d2 = d
for k in key_lst[:-1]:
    d2 = d2.setdefault(k, {})

d2[key_lst[-1]] = value
print(d)
# {'key1': {'key2': {'key3': 'my_value'}}}

d is the reference to your dictionary, and d2 is a throw-away reference that accesses inner levels at each iteration.

Answer 2

key_lst = ["key1", "key2", "key3"]
my_dict={
"key1": {
    "key2": {
        "key3": "some_value"
        }
    },
}

val=my_dict
#loop gets second to last key in chain(path) and assigns it to val
for x in key_lst[:-1]:
    val=val[x]
#now we can update value of last key, cause dictionary key is passed by reference
val[key_lst[-1]]="new value"

print (my_dict)

#{'key1': {'key2': {'key3': 'new value'}}}

Answer 3

This is what you want:

def update(d, key_lst , val):
    for k in key_lst[:-1]:
        if k not in d:
            d[k] = {}
        d = d[k]
    d[key_lst[-1]] = val

d = {}

update(d, list('qwer'), 0)
# d = {'q': {'w': {'e': {'r': 0}}}}

You could use defaultdict too, it's neat in a sense but prints rather ugly...:

from collections import defaultdict

nest = lambda: defaultdict(nest)
d = nest()

def update(d, key_lst , val):
    for k in key_lst[:-1]:
        d = d[k]
    d[key_lst[-1]] = val

update(d, 'qwer', 0)

Answer 4

I guess you can loop through your keys like this :

d = {}
a = d
for i in key_lst: 
    a[i] = {}
    if i == key_lst[-1]:
        a[i] = value
    else:
        a = a[i]
print(d)
# {'key1': {'key2': {'key3': 'my_value'}}}

Edit: I guess I misread the question and answered as if the dictionnary wasn't already existing. jpp answer is pretty neat otherwise I guess!

Answer 5

Predefined dictionary structure: functools.reduce

You can define a function using functools.reduce to apply getitem repeatedly and then set a supplied value:

from functools import reduce
from operator import getitem

def set_nested_item(dataDict, mapList, val):
    """Set item in nested dictionary"""
    reduce(getitem, mapList[:-1], dataDict)[mapList[-1]] = val
    return dataDict

key_lst = ["key1", "key2", "key3"]
value = "my_value"
d = {"key1": {"key2": {"key3": "some_value"}}}

d = set_nested_item(d, key_lst, value)

print(d)
# {'key1': {'key2': {'key3': 'my_value'}}}

Note operator.getitem is used to access dict.__getitem__, or its more commonly used syntactic sugar dict[]. In this instance, functools.reduce calls getitem recursively on dataDict, successively using each value in mapList[:-1] as an argument. With [:-1], we intentionally leave out the last value, so we can use __setitem__ via dict[key] = value for the final key.

---

Arbitrary dictionary nesting: collections.defaultdict

If you wish to add items at arbitrary branches not yet been defined, you can construct a defaultdict. For this, you can first defaultify your regular dictionary input, then use set_nested_item as before:

from collections import defaultdict

def dd_rec():
    return defaultdict(dd_rec)

def defaultify(d):
    if not isinstance(d, dict):
        return d
    return defaultdict(dd_rec, {k: defaultify(v) for k, v in d.items()})

dd = defaultify(d)

key_lst = ["key1", "key2", "key5", "key6"]
value = "my_value2"
dd = set_nested_item(dd, key_lst, value)

print(dd)

# defaultdict(<function __main__.<lambda>>,
#             {'key1': defaultdict(<function __main__.<lambda>>,
#                          {'key2': defaultdict(<function __main__.<lambda>>,
#                                       {'key3': 'my_value',
#                                        'key5': defaultdict(<function __main__.<lambda>>,
#                                                    {'key6': 'my_value2'})})})})