How to get multiple dictionary values?

I have a dictionary in Python, and what I want to do is get some values from it as a list, but I don't know if this is supported by the implementation.

myDictionary.get('firstKey') # works fine myDictionary.get('firstKey','secondKey') # gives me a KeyError -> OK, get is not defined for multiple keys myDictionary['firstKey','secondKey'] # doesn't work either 

Is there any way I can achieve this? In my example it looks easy, but let's say I have a dictionary of 20 entries, and I want to get 5 keys. Is there any other way than doing the following?

myDictionary.get('firstKey') myDictionary.get('secondKey') myDictionary.get('thirdKey') myDictionary.get('fourthKey') myDictionary.get('fifthKey') 

11 Answers

There already exists a function for this:

from operator import itemgetter my_dict = {x: x**2 for x in range(10)} itemgetter(1, 3, 2, 5)(my_dict) #>>> (1, 9, 4, 25) 

itemgetter will return a tuple if more than one argument is passed. To pass a list to itemgetter, use

itemgetter(*wanted_keys)(my_dict) 

Keep in mind that itemgetter does not wrap its output in a tuple when only one key is requested, and does not support zero keys being requested.

Use a for loop:

keys = ['firstKey', 'secondKey', 'thirdKey'] for key in keys: myDictionary.get(key) 

or a list comprehension:

[myDictionary.get(key) for key in keys] 

I'd suggest the very useful map function, which allows a function to operate element-wise on a list:

mydictionary = {'a': 'apple', 'b': 'bear', 'c': 'castle'} keys = ['b', 'c'] values = list( map(mydictionary.get, keys) ) # values = ['bear', 'castle'] 

You can use At from pydash:

from pydash import at my_dict = {'a': 1, 'b': 2, 'c': 3} my_list = at(my_dict, 'a', 'b') my_list == [1, 2] 

As I see no similar answer here - it is worth pointing out that with the usage of a (list / generator) comprehension, you can unpack those multiple values and assign them to multiple variables in a single line of code:

first_val, second_val = (myDict.get(key) for key in [first_key, second_key]) 

If you have pandas installed you can turn it into a series with the keys as the index. So something like

import pandas as pd s = pd.Series(my_dict) s[['key1', 'key3', 'key2']] 

I think list comprehension is one of the cleanest ways that doesn't need any additional imports:

>>> d={"foo": 1, "bar": 2, "baz": 3} >>> a = [d.get(k) for k in ["foo", "bar", "baz"]] >>> a [1, 2, 3] 

Or if you want the values as individual variables then use multiple-assignment:

>>> a,b,c = [d.get(k) for k in ["foo", "bar", "baz"]] >>> a,b,c (1, 2, 3) 

def get_all_values(nested_dictionary): for key, value in nested_dictionary.items(): if type(value) is dict: get_all_values(value) else: print(key, ":", value) nested_dictionary = {'ResponseCode': 200, 'Data': {'256': {'StartDate': '2022-02-07', 'EndDate': '2022-02-27', 'IsStoreClose': False, 'StoreTypeMsg': 'Manual Processing Stopped', 'is_sync': False}}} get_all_values(nested_dictionary) 

If the fallback keys are not too many you can do something like this

value = my_dict.get('first_key') or my_dict.get('second_key') 

Here is the benchmark from various answer.

TLDR: Use (dict1.get(key) for key in keys)

1. Improvement from the accepted answer, use tuple (not list) comprehension because it is the fastest way.
2. .get(key) and [key] have comparable speed, sometimes [key] is a little bit faster. If no key found in dict, .get(key) is safer (return None) than directly using indexing [key] (throw Error).

Benchmark:

from operator import itemgetter from fakertype import FakerType from faker import Faker Faker.seed(42) ft = FakerType() dict1 = ft.fake_dict(n=100) keys = list(dict1.keys())[:50] %%timeit [dict1[key] for key in keys] # 14 µs ± 4.22 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each) %%timeit itemgetter(*keys)(dict1) # 2.8 µs ± 596 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each) %%timeit (dict1.get(key) for key in keys) # 585 ns ± 33 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each) %%timeit (dict1[key] for key in keys) # 590 ns ± 25.4 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each) 

def get_all_values(nested_dictionary): for key, val in nested_dictionary.items(): data_list = [] if type(val) is dict: for key1, val1 in val.items(): data_list.append(val1) return data_list