Eric
Eric

Reputation: 97571

Python equivalent of zip for dictionaries

If I have these two lists:

la = [1, 2, 3]
lb = [4, 5, 6]

I can iterate over them as follows:

for i in range(min(len(la), len(lb))):
    print la[i], lb[i]

Or more pythonically

for a, b in zip(la, lb):
    print a, b

What if I have two dictionaries?

da = {'a': 1, 'b': 2, 'c': 3}
db = {'a': 4, 'b': 5, 'c': 6}

Again, I can iterate manually:

for key in set(da.keys()) & set(db.keys()):
    print key, da[key], db[key]

Is there some builtin method that allows me to iterate as follows?

for key, value_a, value_b in common_entries(da, db):
    print key, value_a, value_b 

Upvotes: 52

Views: 65292

Answers (7)

Vénon
Vénon

Reputation: 55

If it's for iterate them, you can zip like this :

d1 = {"1":1,"2":2}
d2 = {"3":3,"4":4}

for (k1, v1), (k2, v2) in zip(d1.items(), d2.items()):
    print(k1,v1,k2,v2)

Output:

1 1 3 3
2 2 4 4

Upvotes: 0

SnzFor16Min
SnzFor16Min

Reputation: 140

I was wondering if taking one of the dicts as a reference would be efficient, and a quick experiment1 says it depends:

import timeit

dshort = {c: ord(c) for c in "abcdefghijklm"}
dlong = {c: ord(c) for c in "cdefghijklmnopqrstuvwxyz"}

print(timeit.repeat(lambda: {k: (dshort[k], dlong[k]) for k in dshort.keys() & dlong.keys()}))
print(timeit.repeat(lambda: {k: (v1, dlong[k]) for k, v1 in dshort.items() if k in dlong}))
print(timeit.repeat(lambda: {k: (dshort[k], v2) for k, v2 in dlong.items() if k in dshort}))
print(timeit.repeat(lambda: {k: (v1, dlong[k]) for k, v1 in dshort.items() if k in dlong.keys()}))
print(timeit.repeat(lambda: {k: (dshort[k], v2) for k, v2 in dlong.items() if k in dshort.keys()}))
[1.4048387547954917, 1.37691087462008, 1.3789333319291472, 1.3769562682136893, 1.3768599517643452]
[1.3084445232525468, 1.2111821668222547, 1.213303911499679, 1.2122336281463504, 1.2120618764311075]
[1.544621947221458, 1.5463114874437451, 1.5447452096268535, 1.5450493320822716, 1.5463362047448754]
[1.5736573031172156, 1.556909584440291, 1.5570594323799014, 1.5568421771749854, 1.5563717214390635]
[2.2037177812308073, 2.204036961309612, 2.2097349502146244, 2.214019880630076, 2.213061122223735]

If you know which dict is the shortest one, iterate over its items() and check if its keys are also in d — However, don't check as in d.keys(), which worsens performance! I guess this is because time is mostly spent on __getattr__.

If you are not sure about which is the shortest dict, just use d1.keys() & d2.keys() & d3.keys() & ... ;)


1 Version: Python 3.12.3 | packaged by conda-forge | (main, Apr 15 2024, 18:38:13) [GCC 12.3.0] on linux

Upvotes: 0

Koreth
Koreth

Reputation: 701

The object returned by dict.keys() (called a dictionary key view) acts like a set object, so you can just take the intersection of the keys:

da = {'a': 1, 'b': 2, 'c': 3, 'e': 7}
db = {'a': 4, 'b': 5, 'c': 6, 'd': 9}

common_keys = da.keys() & db.keys()

for k in common_keys:
    print(k, da[k], db[k])

On Python 2 you'll need to convert the keys to sets yourself:

common_keys = set(da) & set(db)

for k in common_keys:
    print k, da[k], db[k]

Upvotes: 15

Volatility
Volatility

Reputation: 32300

There is no built-in function or method that can do this. However, you could easily define your own.

def common_entries(*dcts):
    if not dcts:
        return
    for i in set(dcts[0]).intersection(*dcts[1:]):
        yield (i,) + tuple(d[i] for d in dcts)

This builds on the "manual method" you provide, but, like zip, can be used for any number of dictionaries.

>>> da = {'a': 1, 'b': 2, 'c': 3}
>>> db = {'a': 4, 'b': 5, 'c': 6}
>>> list(common_entries(da, db))
[('c', 3, 6), ('b', 2, 5), ('a', 1, 4)]

When only one dictionary is provided as an argument, it essentially returns dct.items().

>>> list(common_entries(da))
[('c', 3), ('b', 2), ('a', 1)]

With no dictionaries, it returns an empty generator (just like zip())

>>> list(common_entries())
[]

Upvotes: 43

Grwlf
Grwlf

Reputation: 956

Python3: How about the following?

da = {'A': 1, 'b': 2, 'c': 3}
db = {'B': 4, 'b': 5, 'c': 6}
for key, (value_a, value_b) in  {k:(da[k],db[k]) for k in set(da)&set(db)}.items():
  print(key, value_a, value_b) 

The above snippet prints values of common keys ('b' and 'c') and discards the keys which don't match ('A' and 'B').

In order to include all keys into the output we could use a slightly modified comprehension: {k:(da.get(k),db.get(k)) for k in set(da)|set(db)}.

Upvotes: 0

pylang
pylang

Reputation: 44485

Dictionary key views are already set-like in Python 3. You can remove set():

for key in da.keys() & db.keys():
    print(key, da[key], db[key])

In Python 2:

for key in da.viewkeys() & db.viewkeys():
    print key, da[key], db[key]

Upvotes: 6

Azat Ibrakov
Azat Ibrakov

Reputation: 10963

In case if someone is looking for generalized solution:

import operator
from functools import reduce


def zip_mappings(*mappings):
    keys_sets = map(set, mappings)
    common_keys = reduce(set.intersection, keys_sets)
    for key in common_keys:
        yield (key,) + tuple(map(operator.itemgetter(key), mappings))

or if you like to separate key from values and use syntax like

for key, (values, ...) in zip_mappings(...):
    ...

we can replace last line with

yield key, tuple(map(operator.itemgetter(key), mappings))

Tests

from collections import Counter


counter = Counter('abra')
other_counter = Counter('kadabra')
last_counter = Counter('abbreviation')
for (character,
     frequency, other_frequency, last_frequency) in zip_mappings(counter,
                                                                 other_counter,
                                                                 last_counter):
    print('character "{}" has next frequencies: {}, {}, {}'
          .format(character,
                  frequency,
                  other_frequency,
                  last_frequency))

gives us

character "a" has next frequencies: 2, 3, 2
character "r" has next frequencies: 1, 1, 1
character "b" has next frequencies: 1, 1, 2

(tested on Python 2.7.12 & Python 3.5.2)

Upvotes: 1

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