Is Unique Email Groups easy or hard?

Unique Email Groups is generally classified as a medium problem because it combines string manipulation with hash-based deduplication. The logic is straightforward once you understand the normalization rules, but careful parsing is required to avoid edge‑case mistakes.

Unique Email Groups Python/Java solution

In both Python and Java, iterate through the email list, normalize the local part using string operations, and insert the result into a hash set. Python typically uses a set with string slicing, while Java uses a HashSet with a StringBuilder to construct the normalized email.

How to solve Unique Email Groups in O(n)?

Treat each email as a string of length m and normalize it in a single pass. Split the email at '@', process the local part by skipping '.' and stopping at '+', then rebuild the canonical email. Insert the normalized string into a hash set and return the set size. The algorithm effectively runs in O(n · m) time with O(n) hash operations.

What is the best approach for Unique Email Groups?

The hash table approach is the most efficient and widely expected solution. Normalize each email address by removing dots and ignoring characters after '+' in the local part, then insert the canonical form into a hash set. Hash lookups prevent duplicates and keep the overall complexity at O(n · m), where n is the number of emails and m is the average email length.

Is Unique Email Groups asked at Google/Amazon/Meta?

Email normalization and deduplication problems frequently appear in interviews at companies like Google, Amazon, and Meta. Variations often test string parsing, hashing, and data deduplication. The hash set solution demonstrates familiarity with practical data processing patterns.

What data structure is used in Unique Email Groups?

A hash set (hash table) is the primary data structure. It stores normalized email addresses and provides constant‑time insertion and membership checks. This makes it ideal for detecting duplicates while processing the list once.

What is the time complexity of Unique Email Groups?

The optimal solution runs in O(n · m) time. Each email is processed once, and normalization scans up to m characters. Hash set insertion and lookup are O(1) on average, so the total complexity scales linearly with the number of emails.

Description Hints 1 Solution

3860. Unique Email Groups

Medium84.8% acceptancePremium elsewhere, free here

You are given an array of strings emails, where each string is a valid email address.

Two email addresses belong to the same group if both their normalized local names and normalized domain names are identical.

The normalization rules are as follows:

The local name is the part before the '@' symbol.
- Ignore all dots '.'.
- Ignore everything after the first '+', if present.
- Convert to lowercase.
The domain name is the part after the '@' symbol.
- Convert to lowercase.

Return an integer denoting the number of unique email groups after normalization.

Example 1:

Input: emails = ["test.email+alex@leetcode.com", "test.e.mail+bob.cathy@leetcode.com", "testemail+david@lee.tcode.com"]

Output: 2

Explanation:

Email	Local	Normalized Local	Domain	Normalized Domain	Final Email
test.email+alex@leetcode.com	test.email+alex	testemail	leetcode.com	leetcode.com	testemail@leetcode.com
test.e.mail+bob.cathy@leetcode.com	test.e.mail+bob.cathy	testemail	leetcode.com	leetcode.com	testemail@leetcode.com
testemail+david@lee.tcode.com	testemail+david	testemail	lee.tcode.com	lee.tcode.com	testemail@lee.tcode.com

Unique emails are ["testemail@leetcode.com", "testemail@lee.tcode.com"]. Thus, the answer is 2.

Example 2:

Input: emails = ["A@B.com", "a@b.com", "ab+xy@b.com", "a.b@b.com"]

Output: 2

Explanation:

Email	Local	Normalized Local	Domain	Normalized Domain	Final Email
A@B.com	A	a	B.com	b.com	a@b.com
a@b.com	a	a	b.com	b.com	a@b.com
ab+xy@b.com	ab+xy	ab	b.com	b.com	ab@b.com
a.b@b.com	a.b	ab	b.com	b.com	ab@b.com

Unique emails are ["a@b.com", "ab@b.com"]. Thus, the answer is 2.

Example 3:

Input: emails = ["a.b+c.d+e@DoMain.com", "ab+xyz@domain.com", "ab@domain.com"]

Output: 1

Explanation:

Email	Local	Normalized Local	Domain	Normalized Domain	Final Email
a.b+c.d+e@DoMain.com	a.b+c.d+e	ab	DoMain.com	domain.com	ab@domain.com
ab+xyz@domain.com	ab+xyz	ab	domain.com	domain.com	ab@domain.com
ab@domain.com	ab	ab	domain.com	domain.com	ab@domain.com

All emails normalize to "ab@domain.com". Thus, the answer is 1.

Constraints:

1 <= emails.length <= 1000
1 <= emails[i].length <= 100
emails[i] consists of lowercase and uppercase English letters, digits, and the characters '.', '+', and '@'.
Each emails[i] contains exactly one '@' character.
All local and domain names are non-empty; local names do not start with '+'.
Domain names end with the ".com" suffix and contain at least one character before ".com".

Topics

Hints open one at a time

Hint 1

Simulate the normalization process as described, and use an unordered set (or set) to keep track of unique normalized email addresses.

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1class Solution:
  def solve(self):
      pass


Starter codePython 3Spaces: 4

Examples

Case 1Case 2Case 3

Input

["test.email+alex@leetcode.com", "test.e.mail+bob.cathy@leetcode.com", "testemail+david@lee.tcode.com"]

Input

["A@B.com", "a@b.com", "ab+xy@b.com", "a.b@b.com"]

Input

["a.b+c.d+e@DoMain.com", "ab+xyz@domain.com", "ab@domain.com"]

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