5 Best Ways to Find Keys with Duplicate Values in Python Dictionaries

💡 Problem Formulation: You want to find all keys in a dictionary that share the same value. For instance, given a dictionary {'a': 1, 'b': 1, 'c': 2, 'd': 3}, the goal is to identify 'a' and 'b' as duplicates because they both have the value 1.

Method 1: Using a Default Dictionary

To find keys with duplicate values in a dictionary, one approach is to invert the dictionary, mapping each value to a list of keys that have that value. This can be efficiently achieved by using a defaultdict from the collections module, which allows us to append keys to each value’s list without needing to check if the key already exists.

Here’s an example:

from collections import defaultdict

def find_duplicate_values(d):
    inv_map = defaultdict(list)
    for k, v in d.items():
        inv_map[v].append(k)
    return {k: v for k, v in inv_map.items() if len(v) > 1}

my_dict = {'a': 1, 'b': 2, 'c': 1, 'd': 3}
duplicates = find_duplicate_values(my_dict)
print(duplicates)

Output:

{1: ['a', 'c']}

This function iterates over each key-value pair in the input dictionary and appends the key to a list in a default dictionary, where each value of the original dictionary becomes a key. It then filters out entries with lists containing more than one item, effectively isolating duplicates.

Method 2: Using GroupBy from itertools

Another method utilizes the groupby() function from the itertools module to group dictionary items by value. This requires the dictionary items to be sorted by value in advance, which can be done with the sorted() function.

Here’s an example:

from itertools import groupby

def find_duplicate_values(d):
    sorted_items = sorted(d.items(), key=lambda x: x[1])
    duplicates = {k: list(map(lambda x: x[0], g)) for k, g in groupby(sorted_items, key=lambda x: x[1]) if len(list(g)) > 1}
    return duplicates

my_dict = {'a': 1, 'b': 2, 'c': 1, 'd': 3}
duplicates = find_duplicate_values(my_dict)
print(duplicates)

Output:

{1: ['a', 'c']}

In this snippet, we sort the dictionary items by value, then group them using groupby(). If a group has more than one element, we treat the corresponding value as a duplicate and collect its keys. Finally, we return a dictionary mapping each duplicate value to its keys.

Method 3: Using a Counter

A Counter object from the collections module can be used to count the occurrences of values. If a value has a count greater than one, its corresponding keys are duplicates. We can then invert the dictionary similarly to Method 1.

Here’s an example:

from collections import Counter

def find_duplicate_values(d):
    value_counter = Counter(d.values())
    duplicates = {k: [] for k in value_counter if value_counter[k] > 1}
    for key, value in d.items():
        if value in duplicates:
            duplicates[value].append(key)
    return duplicates

my_dict = {'a': 1, 'b': 2, 'c': 1, 'd': 3}
duplicates = find_duplicate_values(my_dict)
print(duplicates)

Output:

{1: ['a', 'c']}

This code creates a Counter object from the dictionary values to identify values that appear more than once. An inverted dictionary is then created with these values as keys and a list of original keys as their values.

Method 4: Using a Set for Comparison

The fourth method involves leveraging a set to record seen values as we iterate over the dictionary. If a value has already been seen, we classify its key as a duplicate.

Here’s an example:

def find_duplicate_values(d):
    seen_values = set()
    duplicates = {}
    for key, value in d.items():
        if value not in seen_values:
            seen_values.add(value)
        else:
            duplicates.setdefault(value, []).append(key)
    return duplicates

my_dict = {'a': 1, 'b': 2, 'c': 1, 'd': 3}
duplicates = find_duplicate_values(my_dict)
print(duplicates)

Output:

{1: ['c']}

We start by initializing an empty set to store unique values. As we iterate through the dictionary, we add unseen values to this set. If a value has been seen before, we classify its key as duplicate and add it to the duplicates dictionary using setdefault().

Bonus One-Liner Method 5: Using Dictionary Comprehension

The one-liner approach is to use dictionary comprehension along with a reverse mapping of the dictionary. This method focuses on conciseness and readability.

Here’s an example:

my_dict = {'a': 1, 'b': 2, 'c': 1, 'd': 3}
duplicates = {v: [k for k in my_dict if my_dict[k] == v] for v in set(my_dict.values()) if list(my_dict.values()).count(v) > 1}
print(duplicates)

Output:

{1: ['a', 'c']}

This snippet uses dictionary comprehension to create a dictionary where each value is associated with a list of keys that map to it. It filters out values that do not have duplicates by looking at the count of each value in a list of all the dictionary’s values.

Summary/Discussion

• Method 1: Using a Default Dictionary. Efficiently handles large dictionaries. Requires an understanding of defaultdict.
• Method 2: Using GroupBy from itertools. Elegant and concise but requires the dictionary items to be sorted, which adds overhead.
• Method 3: Using a Counter. Good for counting the frequency of items in an iterable. Slightly more complex and has additional overhead from managing two separate structures.
• Method 4: Using a Set for Comparison. Simple and memory efficient. It requires more steps to achieve the end goal.
• Method 5: Bonus One-Liner Method. Very concise but less readable and potentially inefficient due to repeated counting for each value.