The Truth of Sisyphus
  • Introduction
  • Deep Learning
    • Basics
      • Hinge Loss
      • Regularizations
      • Linear Classification
      • Multi-Class and Cross Entropy Loss
      • Batch Norm and other Normalizations
      • Optimization
      • Optimization Functions
      • Convolution im2col
      • Activation Functions
      • Derivatives
        • Derivatives of Softmax
        • A Smooth (differentiable) Max Function
      • Model Ensemble
      • Layers Python Implementation
    • Classification
      • Mobile friendly networks
      • Non-local Neural Networks
      • Squeeze-and-Excitation Networks
      • Further Attention Utilization -- Efficience & Segmentation
      • Group Norm
      • ShuffleNet V2
    • Segmentation
      • Several Instance Segmentation
      • A Peek at Semantic Segmentation
      • Design Choices for Mobile Friendly Deep Learning Models, Semantic Segmentation
      • Efficient Video Object Segmentation via Network Modulation
      • BiSeNet
      • DeepLabV3+
    • Detection
      • CornerNet
      • IoU-Net
      • Why smooth L1 is popular in BBox Regression
      • MTCNN-NCNN
      • DetNet
      • SSD Illustration
    • RNN Related
      • GRU vs LSTM
      • BERT
    • Reinforcement Learning
      • AutoML in Practice Review
      • DRL for optimal execution of profolio transaction
    • Multi-task
      • Multi-task Overview
      • What are the tricks in Multi-Task network design?
    • Neural Network Interpretation
      • Neuron Visualization
    • Deep Learning Frameworks
      • How does Caffe work
      • [Gluon] When to use (Hybrid)Sequential and (Hybrid)Block
      • Gluon Hybrid Intro
      • Gluon HybridBlocks Walk-Through
      • A quick tour of Torch internals
      • NCHW / NHWC in Pytorch
      • Static & Dynamic Computation Graph
    • Converting Between DL Frameworks
      • Things To Be Considered When Doing Model Converting
      • Caffe to TensorFlow
    • Computation Graph Optimization
      • Two ways of TensorRT to optimize Neural Network Computation Graph
      • Customized Caffe Memory Optimization
      • NCNN Memory Optimization
      • Symbolic Programs Advantages: More Efficient, Reuse Intermediate Memory, Operation Folding
    • Deep Learning Debug
      • Problems caused by dead ReLU
      • Loss jumps to 87.3365
      • Common Causes of NANs During Training
    • Deployment
      • Efficient Convolution Operation
      • Quantization
    • What I read recently
      • Know Google the Paper Way
      • ECCV 2018
      • Neural Machine Translation
      • Street View OCR Extraction System
      • Teaching Machines to Draw
      • Pixel to Graph
      • Burst Image Deblurring
      • Material for Masses
      • Learning to Separate Object Sounds by Watching Unlabeled Video
    • Papers / Posts to be read
    • Dummy thoughts
  • Machine Learning
    • Classification
    • Regression
    • Clustering
    • Dimension Reduction
    • Metrics
    • Regularization
    • Bayesian Example
    • Machine Learning System Design
    • Recommendation
    • Essentials of Machine Learning
    • Linear Regression
    • Logistic Regression
      • Logistic Function
    • Gaussian Discriminant Analysis
    • Naive Bayes
    • SVM
    • MLE vs MAP
    • Boosting
    • Frequent Questions
    • Conclusion of Machine Learning
  • Python notes
    • Python _ or __ underscores usage
    • Python Multiprocess and Threading Differences
    • Heapq vs. Q.PriorityQueue
    • Python decorator
    • Understanding Python super()
    • @ property
    • Python __all__
    • Is Python List a Linked List or Array
    • What is the "u" in u'Hello world'
    • Python "self"
    • Python object and class
    • Python Class' Instance method, Class method, and Static Methods Demystified
    • Python WTF
    • Python find first value index in a list: [list].index(val)
    • Sort tuples, and lambda usecase
    • Reverse order of range()
    • Python check list is empty
    • Python get ASCII value from character
    • An A-Z of useful Python tricks
    • Python nested function variable scope
    • Python reverse a list
    • Python priority queue -- heapq
  • C++ Notes
    • Templates
    • std::string (C++) and char* (or c-string "string" for C)
    • C++ printf and cout
    • Class Member Function
    • Inline
    • Scope Resolution Operator ::
    • Constructor
    • Destructor
    • Garbage Collection is Critical
    • C++ Question Lists
  • Operating System
    • Basics
    • Mutex & Semaphore
    • Ticket Selling System
    • OS and Memory
    • Sort implementation in STL
    • Compile, link, loading & run
    • How to understand Multithreading and Multiprocessing from the view of Operating System
  • Linux & Productivity
    • Jupyter Notebook on Remote Server
    • Nividia-smi monitoring
  • Leetcode Notes
    • Array
      • 11. Container With Most Water
      • 35. Search Insert Position
    • Linked List
      • Difference between Linked List and Array
      • Linked List Insert
      • Design of Linked List
      • Two Pointers
        • 141. Linked List Cycle
        • 142. Linked List Cycle II
        • 160. Intersection of two Linked List
        • 19. Remove N-th node from the end of linked list
      • 206. Reverse Linked List
      • 203. Remove Linked List Elements
      • 328. Odd Even Linked List
      • 234. Palindrome Linked List
      • 21. Merge Two Sorted Lists
      • 430. Flatten a Multilevel Doubly Linked List
      • 430. Flatten a Multilevel Doubly Linked List
      • 708. Insert into a Cyclic Sorted List
      • 138. Copy List with Random Pointer
      • 61. Rotate List
    • Binary Tree
      • 144. Binary Tree Preorder Traversal
      • 94. Binary Tree Iterative In-order Traverse
    • Binary Search Tree
      • 98. Validate Binary Search Tree
      • 285. Inorder Successor in BST
      • 173. Binary Search Tree Iterator
      • 700. Search in a Binary Search Tree
      • 450. Delete Node in a BST
      • 701. Insert into a Binary Search Tree
      • Kth Largest Element in a Stream
      • Lowest Common Ancestor of a BST
      • Contain Duplicate III
      • Balanced BST
      • Convert Sorted Array to Binary Search Tree
    • Dynamic Programming
      • 198. House Robber
      • House Robber II
      • Unique Path
      • Unique Path II
      • Best time to buy and sell
      • Partition equal subset sum
      • Target Sum
      • Burst Ballons
    • DFS
      • Clone Graph
      • General Introduction
      • Array & String
      • Sliding Window
  • Quotes
    • Concert Violinist Joke
    • 船 Ship
    • What I cannot create, I do not understand
    • Set your course by the stars
    • To-do list
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On this page
  1. Leetcode Notes
  2. Linked List

Design of Linked List

class Node(object):
    def __init__(self, value):
        self.val = value
        self.next = None


class MyLinkedList(object):
    def __init__(self):
        """
        Initialize your data structure here.
        dummy  0  1  2  3
        -217   x  y  z  alpha
        """
        # self.dummy = None # Common dude, dummy is a Node!!!!
        self.dummy = Node(-217) 

    def getNode(self, index):
        """
        Get the index-th node in the linked list.
        """
        if index < -1:  # if index is -1, dummy will be returned
            return None
        cur = self.dummy
        i = 0
        while i <= index and cur is not None:
            cur = cur.next
            i += 1
        return cur # if index is out of length, cur stopped at the tail->next: None. So that the corner case has been considered via the return part.

    def getTail(self):
        """
        Get the last node in the linked list.
        """
        cur = self.dummy
        while (cur is not None and cur.next is not None): # if the while loop criterion is set only via cur, then "cur" will be lastNode.next: None
            cur = cur.next
        return cur

    def get(self, index):
        """
        Get the value of the index-th node in the linked list. If the index is invalid, return -1.
        :type index: int
        :rtype: int
        """
        cur = self.getNode(index)
        if cur is not None:
            return cur.val
        else:
            return -1

    def addAtHead(self, val):
        """
        Add a node of value val before the first element of the linked list. After the insertion, the new node will be the first node of the linked list.
        :type val: int
        :rtype: void
        """
        cur = Node(val)
        #if self.length == 0:
        #    self.dummy.next = cur
        #else:
        #    cur.next = self.dummy.next  # constantly check whether each "next" you write is valid.
        #    self.dummy.next = cur
        cur.next = self.dummy.next
        self.dummy.next = cur

    def addAtTail(self, val):
        """
        Append a node of value val to the last element of the linked list.
        :type val: int
        :rtype: void
        """

        #if self.length == 0:
        #    self.addAtHead(val)
        #else:
        #    cur = Node(val)
        #    self.tail.next = cur  # constantly check whether each "next" is valid
        #    self.tail = cur
        if self.dummy.next is None:
            self.addAtHead(val)
        else:
            tail = self.getTail()
            cur = Node(val)
            tail.next = cur
        
    def addAtIndex(self, index, val):
        """
        Add a node of value val before the index-th node in the linked list. If index equals to the length of linked list, the node will be appended to the end of linked list. If index is greater than the length, the node will not be inserted.
        :type index: int
        :type val: int
        :rtype: void
        """
        pre = self.getNode(index - 1) # when index is 0, it should be checked and direct to use add head. but since we can index the dummy via -1, our implementation also works fine.
        if pre is None:
            return
        cur = Node(val)
        cur.next = pre.next
        pre.next = cur


    def deleteAtIndex(self, index):
        """
        Delete the index-th node in the linked list, if the index is valid.
        :type index: int
        :rtype: void
        """
        pre = self.getNode(index - 1)
        if self.dummy.next is None or pre is None or pre.next is None: # if there is no node in the linked list; or if pre is None (index out of [-1, length - 1]); or the pre is the (length - 1)th node (because there would be no pre.next.next).
            return
        pre.next = pre.next.next



# Your MyLinkedList object will be instantiated and called as such:
# obj = MyLinkedList()
# param_1 = obj.get(index)
# obj.addAtHead(val)
# obj.addAtTail(val)
# obj.addAtIndex(index,val)
# obj.deleteAtIndex(index)
PreviousLinked List InsertNextTwo Pointers

Last updated 6 years ago