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 

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:
    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())

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]

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]

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))


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,
    print('character "{}" has next frequencies: {}, {}, {}'

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)

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)}.