Find All Anagrams in a String
Given two strings s and p, return a list of all starting indices in s where a rearrangement of p begins. The rearrangements don't need to look identical, any ordering of p's characters counts.
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Problem
Given two strings s and p, return an array of all the start indices of p's anagrams in s. You may return the answer in any order.
Input
Two strings `s` and `p`, containing only lowercase English letters.
Output
A list of starting indices (0-indexed) in `s` where a permutation of `p` starts. Return in any order.
Examples
Input: s = "cbaebabacd", p = "abc"
Output: [0, 6]
At index 0: "cba" is a rearrangement of "abc". At index 6: "bac" is a rearrangement of "abc".
Input: s = "abab", p = "ab"
Output: [0, 1, 2]
"ab" at 0, "ba" at 1, "ab" at 2, all rearrangements of "ab".
Input: s = "af", p = "be"
Output: []
No substring of s has the same characters as p.
The brute-force approach
For each starting index i in s, extract the substring of length len(p) and check whether it's an anagram of p by sorting both and comparing.
result = []
sorted_p = sorted(p)
for i in range(len(s) - len(p) + 1):
window = s[i : i + len(p)] # ← extract substring
if sorted(window) == sorted_p: # ← sort and compare: O(k log k)
result.append(i)
return resultSorting a window of length k costs O(k log k), and you do it for every position in s, so the total is O(n × k log k). For a pattern of length 26, that's already slow, and every new starting index requires sorting the window from scratch. The insight is that sliding the window one step right only changes two characters: one falls off the left, one enters from the right. You don't need to re-sort everything.
Spotting the pattern
This is a Sliding Window problem. The key question to ask yourself:
How do I check every length-k window of s against p without re-examining all k characters at each position?
Answering that is where it clicks, and it's exactly what the guided walkthrough below builds with you: the pattern reasoning, a progressive hint ladder that never spoils the answer, a row-by-row dry run, the optimized solution, and an in-browser editor to run your code against real test cases.
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