@@ -0,0 +1,70 @@
+"""
+https://en.wikipedia.org/wiki/Suffix_array
+https://cp-algorithms.com/string/suffix-array.html
+
+A suffix array lists the starting positions of every suffix of a string in
+lexicographic order. It needs one integer per suffix, where a suffix tree
+needs a node per character, so it is the compact structure used for pattern
+search and for the LCP-based algorithms built on top of it.
+
+Construction here uses prefix doubling (Manber-Myers).
+
+Time Complexity: O(n * log(n)^2) - where n is the length of the text
+Space Complexity: O(n)
+"""
+
+
+def suffix_array(text: str) -> list[int]:
+    """
+    Return the starting indices of all suffixes of `text`, sorted.
+
+    >>> suffix_array("banana")
+    [5, 3, 1, 0, 4, 2]
+    >>> suffix_array("mississippi")
+    [10, 7, 4, 1, 0, 9, 8, 6, 3, 5, 2]
+    >>> suffix_array("abababab")
+    [6, 4, 2, 0, 7, 5, 3, 1]
+    >>> suffix_array("aaaa")
+    [3, 2, 1, 0]
+    >>> suffix_array("aça")
+    [2, 0, 1]
+    >>> suffix_array("a")
+    [0]
+    >>> suffix_array("")
+    []
+    """
+    n = len(text)
+    if n == 0:
+        return []
+
+    suffixes = list(range(n))
+    rank = list(map(ord, text))
+    k = 1
+
+    while k < n:
+        keys = [
+            (rank[i], rank[i + k] if i + k < n else -1, i)
+            for i in range(n)
+        ]
+        keys.sort()
+        suffixes = [i for _, _, i in keys]
+
+        new_rank = [0] * n
+        for position in range(1, n):
+            previous, current = suffixes[position - 1], suffixes[position]
+            previous_key = (
+                rank[previous],
+                rank[previous + k] if previous + k < n else -1,
+            )
+            current_key = (
+                rank[current],
+                rank[current + k] if current + k < n else -1,
+            )
+            new_rank[current] = new_rank[previous] + int(previous_key != current_key)
+
+        rank = new_rank
+        if rank[suffixes[-1]] == n - 1:
+            break
+        k *= 2
+
+    return suffixes