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171 lines
4.1 KiB
Markdown
171 lines
4.1 KiB
Markdown
## queues
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<br>
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* queues are **first in, first out (FIFO) abstract structures** (*i.e.*, items are removed at the same order they are added) that can be implemented with two arrays or a dynamic array (linked list), as long as items are added and removed from opposite sides.
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* queues support **enqueue** (add to the end one end) and **dequeue** (remove from the other end, or tail).
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* if implemented with a dynamic array, a more efficient solution is to use a circular queue (ring buffer), *i.e.*, a fixed-size array and two pointers to indicate the starting and ending positions.
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* an advantage of circular queues is that we can use the spaces in front of the queue.
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* in a normal queue, once the queue becomes full, we cannot insert the next element even if there is a space in front of the queue. but using the circular queue, we can use the space to store new values.
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* queues are often used in **breath-first search** (where you store a list of nodes to be processed) or when implementing a cache.
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<br>
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---
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### designing a circular queue
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<br>
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* a circular queue can be built with either arrays or linked lists (nodes).
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<br>
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#### using arrays
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<br>
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* to build a ring with a fixed size array, any of the elements could be considered as the head.
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* as long as we know the length of the queue, we can instantly locat its tails based on this formula:
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```
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tail_index = (head_index + queue_length - 1) % queue_capacity
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```
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<br>
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```python
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class CircularQueue:
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def __init__(self, k: int):
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self.head = 0
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self.tail = 0
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self.size = k
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self.queue = [None] * self.size
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def enqueue(self, value: int) -> bool:
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if value is None:
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return False
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if self.is_full():
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return False
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if self.is_empty():
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self.heard = 0
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while self.queue[self.tail] is not None:
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self.tail += 1
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if self.tail == self.size:
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self.tail = 0
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self.queue[self.tail] = value
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return True
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def dequeue(self) -> bool:
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if self.is_empty():
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return False
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value = self.queue[self.head]
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self.queue[self.head] = None
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self.head += 1
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if self.head == self.size:
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self.head = 0
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return True
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def front(self) -> int:
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return self.queue[self.head] or -1
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def rear(self) -> int:
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return self.queue[self.tail] or -1
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def is_empty(self) -> bool:
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for n in self.queue:
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if n is not None:
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return False
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return True
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def is_full(self) -> bool:
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for n in self.queue:
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if n is None:
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return False
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return True
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```
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<br>
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#### using linked lists
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<br>
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* note that this queue is not thread-safe: the data structure could be corrupted in a multi-threaded environment (as race-condition could occur). to mitigate this problem, one could add the protection of a lock.
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<br>
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```python
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class Node:
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def __init__(self, value, next=None):
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self.value = value
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self.next = next
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class CircularQueue:
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def __init__(self, k: int):
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self.capacity = k
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self.count = 0
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self.head = None
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self.tail = None
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def enqueue(self, value: int) -> bool:
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if self.count == self.capacity:
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return False
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if self.count == 0:
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self.head = Node(value)
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self.tail = self.head
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else:
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new_node = Node(value)
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self.tail.next = new_node
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self.tail = new_node
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self.count += 1
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return True
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def dequeue(self) -> bool:
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if self.count == 0:
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return False
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self.head = self.head.next
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self.count -= 1
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return True
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def front(self) -> int:
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if self.count == 0:
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return -1
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return self.head.value
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def rear(self) -> int:
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if self.count == 0:
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return -1
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return self.tail.value
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def is_empty(self) -> bool:
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return self.count == 0
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def is_full(self) -> bool:
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return self.count == self.capacity
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```
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<br>
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