Python equivalent of zip for dictionaries

Question

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), le         


        

Answer 1

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())
[]

Answer 2

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)

Answer 3

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]

Answer 4

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)}.

Answer 5

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]