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Access nested dictionary items via a list of keys?
(20 answers)
Closed 4 years ago.
Let's say i have a list of keys
key_lst = ["key1", "key2", "key3"]
and i have a value
value = "my_value"
and an example dict my_dict with this structure
{
"key1": {
"key2": {
"key3": "some_value"
}
},
}
How can I dynamically assign the new value in variable value to my_dict["key1"]["key2"]["key3"] by going thru / looping over my key_lst?
I can not just say my_dict["key1"]["key2"]["key3"] = value since the keys and the number of keys is changing. I always get the keys (the path that i have to save the value at) in a list...
The output I am looking for is {'key1': {'key2': {'key3': 'my_value'}}}. The dictionary structure is predefined.
I'm using Python 3.7
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'})})})})
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.
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)
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!
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'}}}
Given a dictionary like so:
my_map = {'a': 1, 'b': 2}
How can one invert this map to get:
inv_map = {1: 'a', 2: 'b'}
Python 3+:
inv_map = {v: k for k, v in my_map.items()}
Python 2:
inv_map = {v: k for k, v in my_map.iteritems()}
Assuming that the values in the dict are unique:
Python 3:
dict((v, k) for k, v in my_map.items())
Python 2:
dict((v, k) for k, v in my_map.iteritems())
If the values in my_map aren't unique:
Python 3:
inv_map = {}
for k, v in my_map.items():
inv_map[v] = inv_map.get(v, []) + [k]
Python 2:
inv_map = {}
for k, v in my_map.iteritems():
inv_map[v] = inv_map.get(v, []) + [k]
To do this while preserving the type of your mapping (assuming that it is a dict or a dict subclass):
def inverse_mapping(f):
return f.__class__(map(reversed, f.items()))
Try this:
inv_map = dict(zip(my_map.values(), my_map.keys()))
(Note that the Python docs on dictionary views explicitly guarantee that .keys() and .values() have their elements in the same order, which allows the approach above to work.)
Alternatively:
inv_map = dict((my_map[k], k) for k in my_map)
or using python 3.0's dict comprehensions
inv_map = {my_map[k] : k for k in my_map}
Another, more functional, way:
my_map = { 'a': 1, 'b':2 }
dict(map(reversed, my_map.items()))
We can also reverse a dictionary with duplicate keys using defaultdict:
from collections import Counter, defaultdict
def invert_dict(d):
d_inv = defaultdict(list)
for k, v in d.items():
d_inv[v].append(k)
return d_inv
text = 'aaa bbb ccc ddd aaa bbb ccc aaa'
c = Counter(text.split()) # Counter({'aaa': 3, 'bbb': 2, 'ccc': 2, 'ddd': 1})
dict(invert_dict(c)) # {1: ['ddd'], 2: ['bbb', 'ccc'], 3: ['aaa']}
See here:
This technique is simpler and faster than an equivalent technique using dict.setdefault().
This expands upon the answer by Robert, applying to when the values in the dict aren't unique.
class ReversibleDict(dict):
# Ref: https://stackoverflow.com/a/13057382/
def reversed(self):
"""
Return a reversed dict, with common values in the original dict
grouped into a list in the returned dict.
Example:
>>> d = ReversibleDict({'a': 3, 'c': 2, 'b': 2, 'e': 3, 'd': 1, 'f': 2})
>>> d.reversed()
{1: ['d'], 2: ['c', 'b', 'f'], 3: ['a', 'e']}
"""
revdict = {}
for k, v in self.items():
revdict.setdefault(v, []).append(k)
return revdict
The implementation is limited in that you cannot use reversed twice and get the original back. It is not symmetric as such. It is tested with Python 2.6. Here is a use case of how I am using to print the resultant dict.
If you'd rather use a set than a list, and there could exist unordered applications for which this makes sense, instead of setdefault(v, []).append(k), use setdefault(v, set()).add(k).
Combination of list and dictionary comprehension. Can handle duplicate keys
{v:[i for i in d.keys() if d[i] == v ] for k,v in d.items()}
A case where the dictionary values is a set. Like:
some_dict = {"1":{"a","b","c"},
"2":{"d","e","f"},
"3":{"g","h","i"}}
The inverse would like:
some_dict = {vi: k for k, v in some_dict.items() for vi in v}
The output is like this:
{'c': '1',
'b': '1',
'a': '1',
'f': '2',
'd': '2',
'e': '2',
'g': '3',
'h': '3',
'i': '3'}
For instance, you have the following dictionary:
my_dict = {'a': 'fire', 'b': 'ice', 'c': 'fire', 'd': 'water'}
And you wanna get it in such an inverted form:
inverted_dict = {'fire': ['a', 'c'], 'ice': ['b'], 'water': ['d']}
First Solution. For inverting key-value pairs in your dictionary use a for-loop approach:
# Use this code to invert dictionaries that have non-unique values
inverted_dict = dict()
for key, value in my_dict.items():
inverted_dict.setdefault(value, list()).append(key)
Second Solution. Use a dictionary comprehension approach for inversion:
# Use this code to invert dictionaries that have unique values
inverted_dict = {value: key for key, value in my_dict.items()}
Third Solution. Use reverting the inversion approach (relies on the second solution):
# Use this code to invert dictionaries that have lists of values
my_dict = {value: key for key in inverted_dict for value in my_map[key]}
Lot of answers but didn't find anything clean in case we are talking about a dictionary with non-unique values.
A solution would be:
from collections import defaultdict
inv_map = defaultdict(list)
for k, v in my_map.items():
inv_map[v].append(k)
Example:
If initial dict my_map = {'c': 1, 'd': 5, 'a': 5, 'b': 10}
then, running the code above will give:
{5: ['a', 'd'], 1: ['c'], 10: ['b']}
I found that this version is more than 10% faster than the accepted version of a dictionary with 10000 keys.
d = {i: str(i) for i in range(10000)}
new_d = dict(zip(d.values(), d.keys()))
In addition to the other functions suggested above, if you like lambdas:
invert = lambda mydict: {v:k for k, v in mydict.items()}
Or, you could do it this way too:
invert = lambda mydict: dict( zip(mydict.values(), mydict.keys()) )
I think the best way to do this is to define a class. Here is an implementation of a "symmetric dictionary":
class SymDict:
def __init__(self):
self.aToB = {}
self.bToA = {}
def assocAB(self, a, b):
# Stores and returns a tuple (a,b) of overwritten bindings
currB = None
if a in self.aToB: currB = self.bToA[a]
currA = None
if b in self.bToA: currA = self.aToB[b]
self.aToB[a] = b
self.bToA[b] = a
return (currA, currB)
def lookupA(self, a):
if a in self.aToB:
return self.aToB[a]
return None
def lookupB(self, b):
if b in self.bToA:
return self.bToA[b]
return None
Deletion and iteration methods are easy enough to implement if they're needed.
This implementation is way more efficient than inverting an entire dictionary (which seems to be the most popular solution on this page). Not to mention, you can add or remove values from your SymDict as much as you want, and your inverse-dictionary will always stay valid -- this isn't true if you simply reverse the entire dictionary once.
If the values aren't unique, and you're a little hardcore:
inv_map = dict(
(v, [k for (k, xx) in filter(lambda (key, value): value == v, my_map.items())])
for v in set(my_map.values())
)
Especially for a large dict, note that this solution is far less efficient than the answer Python reverse / invert a mapping because it loops over items() multiple times.
This handles non-unique values and retains much of the look of the unique case.
inv_map = {v:[k for k in my_map if my_map[k] == v] for v in my_map.itervalues()}
For Python 3.x, replace itervalues with values.
I am aware that this question already has many good answers, but I wanted to share this very neat solution that also takes care of duplicate values:
def dict_reverser(d):
seen = set()
return {v: k for k, v in d.items() if v not in seen or seen.add(v)}
This relies on the fact that set.add always returns None in Python.
Here is another way to do it.
my_map = {'a': 1, 'b': 2}
inv_map= {}
for key in my_map.keys() :
val = my_map[key]
inv_map[val] = key
dict([(value, key) for key, value in d.items()])
Function is symmetric for values of type list; Tuples are coverted to lists when performing reverse_dict(reverse_dict(dictionary))
def reverse_dict(dictionary):
reverse_dict = {}
for key, value in dictionary.iteritems():
if not isinstance(value, (list, tuple)):
value = [value]
for val in value:
reverse_dict[val] = reverse_dict.get(val, [])
reverse_dict[val].append(key)
for key, value in reverse_dict.iteritems():
if len(value) == 1:
reverse_dict[key] = value[0]
return reverse_dict
Since dictionaries require one unique key within the dictionary unlike values, we have to append the reversed values into a list of sort to be included within the new specific keys.
def r_maping(dictionary):
List_z=[]
Map= {}
for z, x in dictionary.iteritems(): #iterate through the keys and values
Map.setdefault(x,List_z).append(z) #Setdefault is the same as dict[key]=default."The method returns the key value available in the dictionary and if given key is not available then it will return provided default value. Afterward, we will append into the default list our new values for the specific key.
return Map
Fast functional solution for non-bijective maps (values not unique):
from itertools import imap, groupby
def fst(s):
return s[0]
def snd(s):
return s[1]
def inverseDict(d):
"""
input d: a -> b
output : b -> set(a)
"""
return {
v : set(imap(fst, kv_iter))
for (v, kv_iter) in groupby(
sorted(d.iteritems(),
key=snd),
key=snd
)
}
In theory this should be faster than adding to the set (or appending to the list) one by one like in the imperative solution.
Unfortunately the values have to be sortable, the sorting is required by groupby.
Try this for python 2.7/3.x
inv_map={};
for i in my_map:
inv_map[my_map[i]]=i
print inv_map
def invertDictionary(d):
myDict = {}
for i in d:
value = d.get(i)
myDict.setdefault(value,[]).append(i)
return myDict
print invertDictionary({'a':1, 'b':2, 'c':3 , 'd' : 1})
This will provide output as : {1: ['a', 'd'], 2: ['b'], 3: ['c']}
A lambda solution for current python 3.x versions:
d1 = dict(alice='apples', bob='bananas')
d2 = dict(map(lambda key: (d1[key], key), d1.keys()))
print(d2)
Result:
{'apples': 'alice', 'bananas': 'bob'}
This solution does not check for duplicates.
Some remarks:
The lambda construct can access d1 from the outer scope, so we only
pass in the current key. It returns a tuple.
The dict() constructor accepts a list of tuples. It
also accepts the result of a map, so we can skip the conversion to a
list.
This solution has no explicit for loop. It also avoids using a list comprehension for those who are bad at math ;-)
Taking up the highly voted answer starting If the values in my_map aren't unique:, I had a problem where not only the values were not unique, but in addition, they were a list, with each item in the list consisting again of a list of three elements: a string value, a number, and another number.
Example:
mymap['key1'] gives you:
[('xyz', 1, 2),
('abc', 5, 4)]
I wanted to switch only the string value with the key, keeping the two number elements at the same place. You simply need another nested for loop then:
inv_map = {}
for k, v in my_map.items():
for x in v:
# with x[1:3] same as x[1], x[2]:
inv_map[x[0]] = inv_map.get(x[0], []) + [k, x[1:3]]
Example:
inv_map['abc'] now gives you:
[('key1', 1, 2),
('key1', 5, 4)]
This works even if you have non-unique values in the original dictionary.
def dict_invert(d):
'''
d: dict
Returns an inverted dictionary
'''
# Your code here
inv_d = {}
for k, v in d.items():
if v not in inv_d.keys():
inv_d[v] = [k]
else:
inv_d[v].append(k)
inv_d[v].sort()
print(f"{inv_d[v]} are the values")
return inv_d
I would do it that way in python 2.
inv_map = {my_map[x] : x for x in my_map}
Not something completely different, just a bit rewritten recipe from Cookbook. It's futhermore optimized by retaining setdefault method, instead of each time getting it through the instance:
def inverse(mapping):
'''
A function to inverse mapping, collecting keys with simillar values
in list. Careful to retain original type and to be fast.
>> d = dict(a=1, b=2, c=1, d=3, e=2, f=1, g=5, h=2)
>> inverse(d)
{1: ['f', 'c', 'a'], 2: ['h', 'b', 'e'], 3: ['d'], 5: ['g']}
'''
res = {}
setdef = res.setdefault
for key, value in mapping.items():
setdef(value, []).append(key)
return res if mapping.__class__==dict else mapping.__class__(res)
Designed to be run under CPython 3.x, for 2.x replace mapping.items() with mapping.iteritems()
On my machine runs a bit faster, than other examples here
I have a dictionary which I need to deconstruct its keys and values in perhaps two lists(or any other type that does the job) and later in another function, construct the exact same dictionary putting back the keys and values. What's the right way of approaching this?
You can use dict.items() to get all the key-value pairs from the dictionary, then either store them directly...
>>> d = {"foo": 42, "bar": 23}
>>> items = list(d.items())
>>> dict(items)
{'bar': 23, 'foo': 42}
... or distribute them to two separate lists, using zip:
>>> keys, values = zip(*d.items())
>>> dict(zip(keys, values))
{'bar': 23, 'foo': 42}
d = {'jack': 4098, 'sape': 4139}
k, v = d.keys(), d.values()
# Do stuff with keys and values
# -
# Create new dict from keys and values
nd = dict(zip(k, v))
Better Don't deconstruct it. Where you need the keys and values as list you can get that with the following methods.
keyList=list(dict.keys())
valueList = [dict[key] for key in keyList] or [dict[key] for key in dict.keys()]
Hope it helps.
To deconstruct a Dict to two list
>>> test_dict={"a":1, "b":2}
>>> keyList=[]
>>> valueList =[]
>>> for key,val in test_dict.items():
... keyList.append(key)
... valueList.append(val)
>>> print valueList
[1, 2]
>>> print keyList
['a', 'b']
To construct from two list of key and value I would use zip method along with dict comprehension.
>>> {key:val for key,val in zip(keyList,valueList)}
{'a': 1, 'b': 2}
I want to make a function that returns a copy of a dictionary excluding keys specified in a list.
Considering this dictionary:
my_dict = {
"keyA": 1,
"keyB": 2,
"keyC": 3
}
A call to without_keys(my_dict, ['keyB', 'keyC']) should return:
{
"keyA": 1
}
I would like to do this in a one-line with a neat dictionary comprehension but I'm having trouble. My attempt is this:
def without_keys(d, keys):
return {k: d[f] if k not in keys for f in d}
which is invalid syntax. How can I do this?
You were close, try the snippet below:
>>> my_dict = {
... "keyA": 1,
... "keyB": 2,
... "keyC": 3
... }
>>> invalid = {"keyA", "keyB"}
>>> def without_keys(d, keys):
... return {x: d[x] for x in d if x not in keys}
>>> without_keys(my_dict, invalid)
{'keyC': 3}
Basically, the if k not in keys will go at the end of the dict comprehension in the above case.
In your dictionary comprehension you should be iterating over your dictionary (not k , not sure what that is either). Example -
return {k:v for k,v in d.items() if k not in keys}
This should work for you.
def without_keys(d, keys):
return {k: v for k, v in d.items() if k not in keys}
Even shorter. Apparently python 3 lets you 'subtract' a list from a dict_keys.
def without_keys(d, keys):
return {k: d[k] for k in d.keys() - keys}
For those who don't like list comprehensions, this is my version:
def without_keys(d, *keys):
return dict(filter(lambda key_value: key_value[0] not in keys, d.items()))
Usage:
>>> d={1:3, 5:7, 9:11, 13:15}
>>> without_keys(d, 1, 5, 9)
{13: 15}
>>> without_keys(d, 13)
{1: 3, 5: 7, 9: 11}
>>> without_keys(d, *[5, 7])
{1: 3, 13: 15, 9: 11}
Your oneliner
my_dict = {"keyA": 1, "keyB": 2, "keyC": 3}
(lambda keyB, keyC, **kw: kw)(**my_dict)
which returns {'keyA': 1}.
Not very pythonic and dynamic, but hacky and short.
It uses the dict unpacking (destructuring assignment) of function arguments.
See also
https://stackoverflow.com/a/53851069/11769765.
You could this generalized for nested dictionaries solution
def copy_dict(data, strip_values=False, remove_keys=[]):
if type(data) is dict:
out = {}
for key, value in data.items():
if key not in remove_keys:
out[key] = copy_dict(value, strip_values=strip_values, remove_keys=remove_keys)
return out
else:
return [] if strip_values else data
This recursive solution works for nested dictionaries and removes keys not required from the entire nested structure. It also gives you the ability to return the nest with only keys and no values.