How can I get list of values from dict?

Follow the below example —

songs = [
{"title": "happy birthday", "playcount": 4},
{"title": "AC/DC", "playcount": 2},
{"title": "Billie Jean", "playcount": 6},
{"title": "Human Touch", "playcount": 3}
]

print("====================")
print(f'Songs --> {songs} n')
title = list(map(lambda x : x['title'], songs))
print(f'Print Title --> {title}')

playcount = list(map(lambda x : x['playcount'], songs))
print(f'Print Playcount --> {playcount}')
print (f'Print Sorted playcount --> {sorted(playcount)}')

# Aliter -
print(sorted(list(map(lambda x: x['playcount'],songs))))

You can use * operator to unpack dict_values:

>>> d = {1: "a", 2: "b"}
>>> [*d.values()]
['a', 'b']

or list object

>>> d = {1: "a", 2: "b"}
>>> list(d.values())
['a', 'b']

There should be one ‒ and preferably only one ‒ obvious way to do it.

Therefore list(dictionary.values()) is the one way.

Yet, considering Python3, what is quicker?

[*L] vs. [].extend(L) vs. list(L)

small_ds = {x: str(x+42) for x in range(10)}
small_df = {x: float(x+42) for x in range(10)}

print('Small Dict(str)')
%timeit [*small_ds.values()]
%timeit [].extend(small_ds.values())
%timeit list(small_ds.values())

print('Small Dict(float)')
%timeit [*small_df.values()]
%timeit [].extend(small_df.values())
%timeit list(small_df.values())

big_ds = {x: str(x+42) for x in range(1000000)}
big_df = {x: float(x+42) for x in range(1000000)}

print('Big Dict(str)')
%timeit [*big_ds.values()]
%timeit [].extend(big_ds.values())
%timeit list(big_ds.values())

print('Big Dict(float)')
%timeit [*big_df.values()]
%timeit [].extend(big_df.values())
%timeit list(big_df.values())

Small Dict(str)
256 ns ± 3.37 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
338 ns ± 0.807 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
336 ns ± 1.9 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

Small Dict(float)
268 ns ± 0.297 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
343 ns ± 15.2 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
336 ns ± 0.68 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

Big Dict(str)
17.5 ms ± 142 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
16.5 ms ± 338 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
16.2 ms ± 19.7 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)

Big Dict(float)
13.2 ms ± 41 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
13.1 ms ± 919 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
12.8 ms ± 578 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)

Done on Intel(R) Core(TM) i7-8650U CPU @ 1.90GHz.

# Name                    Version                   Build
ipython                   7.5.0            py37h24bf2e0_0

The result

1. For small dictionaries * operator is quicker
2. For big dictionaries where it matters list() is maybe slightly quicker

out: dict_values([{1:a, 2:b}])

in:  str(dict.values())[14:-3]    
out: 1:a, 2:b

Purely for visual purposes. Does not produce a useful product… Only useful if you want a long dictionary to print in a paragraph type form.

If you need to assign the values as a list to a variable, another method using the unpacking * operator is

*values, = d.values()

Get a list of values of specific keys in a dictionary

Most straightforward way is to use a comprehension by iterating over list_of_keys. If list_of_keys includes keys that are not keys of d, .get() method may be used to return a default value (None by default but can be changed).

res = [d[k] for k in list_of_keys] 
# or
res = [d.get(k) for k in list_of_keys]

As often the case, there’s a method built into Python that can get the values under keys: itemgetter() from the built-in operator module.

from operator import itemgetter
res = list(itemgetter(*list_of_keys)(d))

Demonstration:

d = {'a':2, 'b':4, 'c':7}
list_of_keys = ['a','c']
print([d.get(k) for k in list_of_keys])
print(list(itemgetter(*list_of_keys)(d)))
# [2, 7]
# [2, 7]

Get values of the same key from a list of dictionaries

Again, a comprehension works here (iterating over list of dictionaries). As does mapping itemgetter() over the list to get the values of specific key(s).

list_of_dicts = [ {"title": "A", "body": "AA"}, {"title": "B", "body": "BB"} ]

list_comp = [d['title'] for d in list_of_dicts]
itmgetter = list(map(itemgetter('title'), list_of_dicts))
print(list_comp)
print(itmgetter)
# ['A', 'B']
# ['A', 'B']

If you want return a list by default (as in python 2) instead of a view, one can create a new dict class and overwrite the values method:

class ldict(dict):
    # return a simple list instead of dict_values object
    values = lambda _: [*super().values()]

d = ldict({'a': 1, 'b': 2})
d.values()   # [1, 2]   (instead of dict_values([1, 2]))