Leetcode #725: Split Linked List in Parts
In this guide, we solve Leetcode #725 Split Linked List in Parts in Python and focus on the core idea that makes the solution efficient.
You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.
Problem Statement
Given the head of a singly linked list and an integer k, split the linked list into k consecutive linked list parts. The length of each part should be as equal as possible: no two parts should have a size differing by more than one.
Quick Facts
- Difficulty: Medium
- Premium: No
- Tags: Linked List
Intuition
Linked list problems often require pointer manipulation rather than extra memory.
Two-pointer techniques expose cycles, midpoints, or reordering patterns.
Approach
Traverse with fast/slow pointers or reverse sublists when needed.
Maintain invariants carefully to avoid losing nodes.
Steps:
- Traverse with pointers.
- Reverse or split if required.
- Reconnect nodes correctly.
Example
Input: head = [1,2,3], k = 5
Output: [[1],[2],[3],[],[]]
Explanation:
The first element output[0] has output[0].val = 1, output[0].next = null.
The last element output[4] is null, but its string representation as a ListNode is [].
Python Solution
# Definition for singly-linked list.
# class ListNode:
# def __init__(self, val=0, next=None):
# self.val = val
# self.next = next
class Solution:
def splitListToParts(
self, head: Optional[ListNode], k: int
) -> List[Optional[ListNode]]:
n = 0
cur = head
while cur:
n += 1
cur = cur.next
cnt, mod = divmod(n, k)
ans = [None] * k
cur = head
for i in range(k):
if cur is None:
break
ans[i] = cur
m = cnt + int(i < mod)
for _ in range(1, m):
cur = cur.next
nxt = cur.next
cur.next = None
cur = nxt
return ans
Complexity
The time complexity is , and the space complexity is . The space complexity is .
Edge Cases and Pitfalls
Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.
Summary
This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.