Programming
Array Manipulation
JavaScript
Coding Tutorial
Data Duplication

How to remove all duplicates from an array of objects?

Data Structures & Algorithms practice on Codemia

Step through 300 algorithm problems with animated visualisers that show the data structure changing as the code runs.

Practice algorithms

Removing duplicates from an array of objects in programming is a common challenge that can be tackled in various languages like JavaScript, Python, or Java. Each language has its own set of tools to handle this, but fundamentally, the process involves comparing object properties to determine which objects are duplicates. Below, we’ll examine methods to remove duplicates, primarily focusing on JavaScript but also noting how similar concepts apply in other languages.

JavaScript: Using Map, Set, and JSON Techniques

1. Using a Map for Efficient Lookup

A Map in JavaScript can store unique keys pointing to values. When iterating over an array of objects, you can use a unique property of the objects (like an ID) as the key. Here’s how:

javascript
1const arrayOfObjects = [
2  { id: 1, name: "John" },
3  { id: 2, name: "Jane" },
4  { id: 1, name: "John" }
5];
6
7let unique = new Map(arrayOfObjects.map(obj => [obj.id, obj]));
8let dedupedArray = Array.from(unique.values());
9console.log(dedupedArray);

2. Using a Set and JSON Stringification

Set objects allow you to store unique values. By converting objects into strings using JSON.stringify(), we can leverage this feature to filter out duplicates:

javascript
const dedupedArray = Array.from(new Set(arrayOfObjects.map(obj => JSON.stringify(obj))))
  .map(jsonObj => JSON.parse(jsonObj));
console.log(dedupedArray);

This method works well but has limitations regarding the processing of circular references or functions within objects.

Python: Dictionary Keys

In Python, a common approach involves using dictionaries (similar to maps in JavaScript):

python
1array_of_objects = [
2  {'id': 1, 'name': 'John'},
3  {'id': 2, 'name': 'Jane'},
4  {'id': 1, 'name': 'John'}
5]
6
7unique_objects = {frozenset(item.items()):item for item in array_of_objects}.values()
8print(list(unique_objects))

Here, frozenset is used because it is hashable and can be a key in a dictionary, unlike regular dictionaries or sets due to their mutability.

Java: Using HashSet and Custom Equals/HashCode

Java developers can utilize HashSet combined with overwriting equals() and hashCode() methods. This requires a firm grasp of these methods to ensure that equal objects are treated as equal by the hash structure:

java
1Set<MyObject> uniqueObjects = new HashSet<>();
2for (MyObject obj : arrayOfObjects) {
3  uniqueObjects.add(obj);
4}
java
1class MyObject {
2  private int id;
3  private String name;
4
5  @Override
6  public boolean equals(Object o) {
7    if (o == this) return true;
8    if (!(o instanceof MyObject)) return false;
9    MyObject other = (MyObject) o;
10    return other.id == id && (name != null && name.equals(other.name));
11  }
12
13  @Override
14  public int hashCode() {
15    int result = Integer.hashCode(id);
16    result = 31 * result + (name != null ? name.hashCode() : 0);
17    return result;
18  }
19}

Comparing Methods Across Languages

Here is a comparative table summarizing some methods across different languages:

LanguageTechniqueKey Tool/ClassProsCons
JavaScriptMapMapFast access time; maintains insertion order in modern implementationsRequires manual management of keys
JavaScriptJSON & SetSet, JSONSimple one-liner; automatically removes duplicates based on stringified valuesIneffective for non-serializable values, expensive for large objects
PythonDictionaryDictionary (unique by hashable items)Straightforward and conciseRequires hashable types, converting items if necessary
JavaHashSetHashSetProvides consistent O(1) performance for add and check operationsRequires proper implementation of equals() and hashCode() for consistency

Conclusion

The choice of method and language for removing duplicates from an array of objects depends significantly on specific requirements like performance, ease of implementation, and inherent language capabilities. Developers should weigh these factors when choosing the appropriate approach. Ensuring a deep understanding of how objects are hashed and compared in their chosen language will also contribute to more efficient and bug-free code.


Related reading
Course
Intermediate
27 lessons
15 hours
DSA Fundamentals

Master algorithmic patterns and data structures through hands-on LeetCode-style problems - from arrays and hashing to dynamic programming and advanced graphs.

View the course
Track what you have practised

A free account saves your progress, solutions and study plan across every problem on Codemia.

Data Structures & Algorithms practice on Codemia

Step through 300 algorithm problems with animated visualisers that show the data structure changing as the code runs.

Practice algorithms

All Rights Reserved.