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Use collections.Counter to find repeated hashable values, or group dictionary keys by value if you need to know which keys share a duplicate. The right method depends on whether you want a yes/no answer, the repeated values, their counts, or the original keys.
Find which values occur more than once
For values such as numbers, strings, and tuples of hashable items, count the values and keep those with a count greater than one:
from collections import Counter
data = {"a": 1, "b": 2, "c": 1, "d": 3, "e": 2}
counts = Counter(data.values())
duplicate_values = [value for value, count in counts.items() if count > 1]
print(duplicate_values) # [1, 2]Counter is part of Python’s standard library. It records how many times each hashable value appears; filtering for counts above one returns each repeated value once. The order follows the values’ first appearance in the dictionary, rather than sorting them.
Find the keys that share each value
If you need to identify the original keys as well as the repeated values, build a reverse mapping from each value to the keys that contain it:
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from collections import defaultdict
data = {"a": 1, "b": 2, "c": 1, "d": 3, "e": 2}
groups = defaultdict(list)
for key, value in data.items():
groups[value].append(key)
duplicate_groups = {
value: keys for value, keys in groups.items() if len(keys) > 1
}
print(duplicate_groups) # {1: ['a', 'c'], 2: ['b', 'e']}Each list contains the keys encountered for that value. This approach also works with a regular dictionary and setdefault:
groups = {}
for key, value in data.items():
groups.setdefault(value, []).append(key)Dictionary keys are unique, but values need not be. Python’s PEP 3106 explains that a values view cannot be a set because duplicate values are possible.
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Check for duplicates in one pass
When you need unique repeated values but not occurrence counts or key groups, track values already seen. Add a value to the duplicate set the second time it appears:
seen = set()
duplicates = set()
for value in data.values():
if value in seen:
duplicates.add(value)
else:
seen.add(value)
print(duplicates) # {1, 2}This is also useful for a boolean check: return or record True as soon as a value is already in seen. A set stores each repeated value only once, so it does not provide counts or the keys associated with a value.
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Choose a method based on the result you need
| Need | Approach | What it returns |
|---|---|---|
| Whether any value repeats | seen set |
A yes/no result; you can stop at the first repeat. |
| Unique repeated values | Counter or seen plus a duplicate set |
Each repeated value once. |
| Occurrence counts | Counter(data.values()) |
A count for each value; filter for counts greater than one. |
| Keys grouped by repeated value | defaultdict(list) or setdefault |
A value-to-keys mapping; keep groups with more than one key. |
What if dictionary values are lists or dictionaries?
Counter and the set-based approach require hashable values. Lists and dictionaries are unhashable, so they cannot be used directly as keys in those structures. The reverse-mapping method has the same constraint because it uses each value as a new dictionary key.
For unhashable values, use a comparison-based approach or normalize the values into a stable hashable representation. Choose that representation only after deciding what equality means for your data. There is no single safe conversion for arbitrary nested or custom values; converting everything to a string can conflate distinct values or fail to represent the comparison you intend.
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Ordering the result
Python dictionaries preserve insertion order as a language guarantee from Python 3.7 onward. Iterating through data.values() or data.items() therefore follows the dictionary’s order; replacing an existing key’s value does not move that key. A set, however, is unordered. If you use a set for duplicates, do not rely on its display order. Sort the result explicitly when a particular order is part of your output, provided the values can be compared with one another.
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