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Problem solution · Python

Design Skiplist

Design Skiplist: a Python solution using direct simulation. Learn the idea, check the complexity, and read the full code, with credit to walkccc LeetCode Solutions.

Technique
Direct simulation
Source
walkccc LeetCode Solutions
Length
67 lines
Start with the idea.

Try the problem first. If you get stuck, read the approach below, then write your own solution. The full code is at the bottom.

Approach

Direct simulation

For Design Skiplist, the implementation follows the problem’s operations directly while maintaining only the state needed for the next decision.

  1. Translate each rule into one explicit state update.
  2. Maintain the invariant after every processed item.
  3. Return the accumulated state once all relevant input has been handled.

Code notes

  • 67 lines of Python from the credited upstream file 1206.py.
  • The implementation visibly relies on sequence storage.
  • No explicit loop blocks detected.

Complexity

Count the number and nesting of passes over the input, then include the maintained containers in the memory estimate.

Check the problem constraints before deciding whether this complexity will pass.

Source

Code and credit

This code comes from walkccc LeetCode Solutions by P.-Y. Chen (walkccc) and is used under the MIT licence.

Open problem ↗Original source ↗
Full codeDesign Skiplist · PythonPython
Use this to learn the idea, then write your own version.
from dataclasses import dataclass  @dataclassclass Node:  val: int = -1  next: 'Node' = None  down: 'Node' = None  class Skiplist:  def __init__(self):    self.dummy = Node()   def search(self, target: int) -> bool:    node = self.dummy    while node:      while node.next and node.next.val < target:        node = node.next      if node.next and node.next.val == target:        return True      # Move to the next level      node = node.down    return False   def add(self, num: int) -> None:    # Collect nodes that are before the insertion point.    nodes = []    node = self.dummy    while node:      while node.next and node.next.val < num:        node = node.next      nodes.append(node)      # Move to the next level      node = node.down     shouldInsert = True    down = None    while shouldInsert and nodes:      node = nodes.pop()      node.next = Node(num, node.next, down)      down = node.next      shouldInsert = random.getrandbits(1) == 0     # Create a topmost new level dummy that points to the existing dummy.    if shouldInsert:      self.dummy = Node(-1, None, self.dummy)   def erase(self, num: int) -> bool:    node = self.dummy    found = False    while node:      while node.next and node.next.val < num:        node = node.next      if node.next and node.next.val == num:        # Delete the node        node.next = node.next.next        found = True      # Move to the next level      node = node.down    return found   # Move to the node s.t. node.next.val >= target  def _advance(self, node: Node, target: int) -> None:    while node.next and node.next.val < target:      node = node.next

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