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.
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'})})})})