Algorithms and data structures are essential to computer science, and Leetcode offers a plethora of challenges to hone these skills. One such interesting problem is “Design an Ordered Stream.” In this extensive guide, we’ll delve into Pythonic approaches to tackle this problem, understand the underpinning logic, and gauge their performance in terms of time and space complexity.
1. Problem Statement
There is a stream of
n(id, value) pairs arriving in an arbitrary order, where
id is an integer between 1 and
value is a string. No two pairs have the same id.
Design a stream that returns the values in increasing order of their IDs by returning a chunk (list) of values after each insertion. The concatenation of these chunks should result in a list of the sorted values.
OrderedStream(int n): Constructs the stream to take
insert(int id, String value): Inserts the
(id, value)pair into the stream, then returns a list of the largest possible chunk of currently inserted values that appear next in the order.
1 <= n <= 1000
1 <= id <= n
value.length == 5
- At most
ncalls will be made to
2. Understanding the Problem
The problem asks us to design a class called
OrderedStream that can insert
(id, value) pairs and return a list of sorted values by their IDs whenever possible.
3. Class Design Approach
3.1 Brute-Force Approach
One of the simplest methods is to insert each
(id, value) pair into a list and sort it every time, extracting and returning values that are contiguous.
class OrderedStream: def __init__(self, n: int): self.stream = [None] * n self.ptr = 0 def insert(self, id: int, value: str): self.stream[id - 1] = value chunk =  while self.ptr < len(self.stream) and self.stream[self.ptr]: chunk.append(self.stream[self.ptr]) self.ptr += 1 return chunk
3.2 Optimized Approach
The optimized approach avoids sorting and re-traversing the entire list by keeping track of a pointer.
class OrderedStream: def __init__(self, n: int): self.stream = [None] * (n + 1) self.ptr = 1 def insert(self, id: int, value: str): self.stream[id] = value chunk =  while self.ptr < len(self.stream) and self.stream[self.ptr]: chunk.append(self.stream[self.ptr]) self.ptr += 1 return chunk
4. Time Complexity Analysis
The time complexity of the optimized approach is O(1) for each
insert operation, assuming appending to a list is constant time.
5. Space Complexity Analysis
The space complexity for both approaches is O(n), where n is the size specified during the class instantiation.
The “Design an Ordered Stream” problem serves as an excellent introductory problem for data stream design and object-oriented programming. It not only allows us to ponder over data structure choice but also encourages us to think about optimization.