Home > Backend Development > Python Tutorial > Detailed explanation of the use of linked list definitions of Python data structures and algorithms

Detailed explanation of the use of linked list definitions of Python data structures and algorithms

黄舟
Release: 2017-10-04 09:26:15
Original
1889 people have browsed it

This article mainly introduces the definition and usage of linked lists in Python data structures and algorithms. It analyzes the definitions, usage methods and related precautions of singly linked lists, circular linked lists, etc. in detail based on specific examples. Friends in need can refer to it. Next

The examples in this article describe the definition and usage of linked lists in Python data structures and algorithms. Share it with everyone for your reference, the details are as follows:

This article will explain to you:

(1) Starting from the definition of linked list nodes, use the class method and object-oriented thinking to create the linked list Design

(2) Boundary conditions that need to be considered when implementing member functions such as insertion and deletion of linked list classes,
prepend (head insertion), pop (head deletion), append (tail insertion), pop_last (Tail deletion)

2.1 Insertion:

Empty linked list
The length of the linked list is 1
Insert to the end

2.2 Delete

Empty linked list
The length of the linked list is 1
Delete the last element

(3) Numerous variations from singly linked list to singly linked list:

Singly linked list with tail node
Cyclic singly linked list
Double linked list

1. Definition of linked list nodes


class LNode:
 def __init__(self, elem, next_=None):
  self.elem = elem
  self.next = next_
Copy after login

2. Implementation of singly linked list

Focus on understanding the implementation of insertion and deletion and the boundary conditions that need to be considered:


class LinkedListUnderflow(ValueError):
 pass
class LList:
 def __init__(self):
  self._head = None
 def is_empty(self):
  return self._head is None
 def prepend(self, elem):
  self._head = LNode(elem, self._head)
 def pop(self):
  if self._head is None:
   raise LinkedListUnderflow('in pop')
  e = self._head.elem
  self._head = self._head.next
  return e
 def append(self, elem):
  if self._head is None:
   self._head = LNode(elem)
   return
  p = self._head
  while p.next is not None:
   p = p.next
  p.next = LNode(elem)
 def pop_last(self):
  if self._head is None:
   raise LinkedListUnderflow('in pop_last')
  p = self._head
  if p.next is None:
   e = p.elem
   self._head = None
   return e
  while p.next.next is not None:
   p = p.next
  e = p.next.elem
  p.next = None
  return e
Copy after login

Simple summary:

(0) The premise of being able to access p.next.next is that p.next is not empty;
(1) Tail insertion, if the linked list is not Empty, what needs to be changed is the pointer of the tail node;
(2) Tail deletion, if the length of the linked list is not empty, what needs to be changed is the pointer of the penultimate node.

Simple transformation of singly linked list: singly linked list with tail node


class LList1(LList):
 def __init__(self):
  LList.__init__(self)
  self._rear = None
 ...
Copy after login

What we only need to rewrite is: Head insertion, tail insertion, tail deletion


def prepend(self, elem):
 if self._head is None:
  self._head = LNode(elem)
  self._rear = self._head
 else:
  self._head = LNode(elem, self._head)
def append(self, elem):
 if self._head is None:
  self._head = LNode(elem)
  self._rear = self._head
 else:
  self._rear.next = LNode(elem)
  self._rear = self._rear.next
def pop_last(self):
 if self._head is None:
  raise LinkedListUnderflow('in pop_last')
 p = self._head
 if p.next is None:
  e = p.elem
  self._head = None
  return e
 while p.next.next is not None:
  p = p.next
 e = p.next.elem
 self._rear = p
 p.next = None
 return e
Copy after login

Variation of singly linked list: cyclic singly linked list


class LCList:
 def __init__(self):
  self._rear = None
 def prepend(self, elem):
  if self._rear is None:
   self._rear = LNode(elem)
   self._rear.next = self._rear
  else:
   self._rear.next = LNode(elem, self._rear.next)
 def append(self, elem):
  self.prepend(elem)
  self_rear = self._rear.next
 def pop(self):
  if self._rear is None:
   raise LinkedListUnderflow('in pop')
  p = self._rear.next
  if p is None:
   self._rear = None
  else:
   self._rear.next = p.next
  return p.elem
 def printall(self):
  if self._rear is None:
   raise ...
  p = self._rear.next
  while True:
   print(p.elem)
   if p is self._rear:
    break
   p = p.next
Copy after login

The above is the detailed content of Detailed explanation of the use of linked list definitions of Python data structures and algorithms. For more information, please follow other related articles on the PHP Chinese website!

Related labels:
source:php.cn
Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
Popular Tutorials
More>
Latest Downloads
More>
Web Effects
Website Source Code
Website Materials
Front End Template