LeetCode-Notes
  • Introduction
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  • 算法代码实现
  • Python
    • Python 笔记
  • Spark
    • PySpark
    • Spark Issues
    • Spark调优笔记
  • FeatureEngineering
    • Feature Cleaning
    • Feature Selection
    • Feature Transformation
    • Feature Crossing
  • Recommendation Algorithm
    • Recall-and-PreRank
      • Non-Negative Matrix Fatorization(NMF)
      • Fatorization Machine(FM)
      • User-base/Item-base实现
      • 多路召回实现
    • Ranking
      • NeuralFM
      • DeepFM
      • Deep&Cross network (DCN)
    • DeepLearning-Basic
      • Attention
      • Dropout
      • Batch Norm
  • Machine Learning
    • XGBoost
    • Cross Entropy Loss
    • Other models
  • Graph Neural Network
    • GNN-1-Basic
  • Big Data
    • Reservoir Sampling
  • SQL
    • SQL and PySpark functions
    • Query Film Infomation
    • Create, Insert and Alter Actor Table
    • Manage Employment Data
    • Manage Employment Data -2
  • DataStructure
    • Searching
      • Find power
      • 2 Sum All Pair II
      • Two Sum
      • Search in Rotate Array
      • Search In Shifted Sorted Array II
      • Search in 2D array
      • Three Sum with duplicated values
      • Median of Two Sorted Arrays
    • Array
      • Longest Consecutive Subarray
      • Merge Two Array in-place
      • Trapping water
      • Rotate matrix
    • Sorting
      • Merge intervals
      • 排序
      • 最小的k个数
      • Find TopK largest- QuickSelect快速选择 method
      • MergeSort Linkedlist
      • 第K大元素
    • LinkedList
      • Reverse LinkedList I
      • Reverse K-group linked list
      • Detect Start of Cycle
      • HasCycle
      • DetectCycle II
      • 链表的共同节点
      • 链表中倒数第k个节点
      • 删除链表倒数第k个节点
      • 合并两个链表
      • 在排序数组中查找元素的第一个和最后一个位置
      • 删除链表里面重复的元素-1
    • Tree
      • Find Tree height (general iteration method)
      • Check BST and Check CompleteTree
      • ZigZag Order traversal
      • Binary Tree diameter I
      • Maximum Path Sum Binary Tree
      • Maximum Path Sum Binary Tree II
      • Binary Tree Path Sum To Target III
      • Tree diameter 树的直径II
      • Tree ReConstruction
      • Check if B is Subtree of A
      • The Kth smallest in Binary Search Tree
      • 打印Tree的右视图
      • 二叉搜索树的后序遍历序列
      • 重建二叉树
      • 判断二叉树是否对称
      • Path Sum to Target in Binary Tree
      • Tree-PreOrder-InOrder-PostOrder
    • Heap&Queue
      • Top-K smallest
      • 滑动窗口最大值
      • Find the K-Largest
    • 合并k个已排序的链表
    • String
      • Reverse String
      • 最长不含重复字符的子字符串
      • 最长回文串
      • 最长回文子序列-DP
    • DFS/BFS
      • Number of island
      • Number of Provinces
      • All Permutations of Subsets without duplication
      • All Permutations of Subsets with duplication
      • Combinations Of Coins
      • All Subset I (without fixing size of subset, without order, without duplication)
      • All Subset of K size without duplication II
      • All Subset of K size III (with duplication without considering order)
      • All Permutation II (with duplication and consider order)
      • Factor Combination-质数分解
    • DynamicProgramming
      • DP-解题过程
      • Find Continuous Sequence Sum to Target
      • 1800. Maximum Ascending Subarray Sum
      • NC91 最长上升子序列
      • 查找string的编码方式个数
      • Maximum Product
      • Longest Common Substring
      • Longest Common Substring-II
      • minEditCost
      • Backpack I
      • Array Hopper I
      • Minimum distance between strings
      • 最大正方形
  • Big Data Algorithms
    • Big Data Processing Algorithms
      • Reservior Sampling
      • Shuffle
      • MapReduce
      • Bloom Filter
      • BitMap
      • Heap For Big Data
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  1. Python

Python 笔记

常用的函数和细节备忘录

  1. 2D array 初始化的 [[0]*n for i in range(m)] 和 [ [0]*n ]*m 区别 :

    1. 如果用 arr = [ [0]*n for i in range(m) ], 那么 arr[0][0] = x 就只是对第0行,第0列的element进行更新

    2. 如果用 arr = [[0]*n]*m 初始化, 那么arr[y][0] = x 不管 y是什么值,都只对第0列所有element赋值. 这是因为 [[0]*n]*m 表示的是指向 [0]*n 这个列表的引用.

  2. 常用函数:

    1. ord(char): convert character to ASCII number

    2. chr(num): convert int number to character

    3. "".isalpha() : return True if all char in string is char a-z

    4. "".isnumeric(): return True if all chars in string is number, do not consider negative number and float

    5. id(a): return address ID of that variable

  3. Deep Copy and Shallow Copy

    1. list 里面的 copy: b=a.copy() 或者 b= a[:]是deep copy

    2. dictionary 里面的copy: b=a.copy()是只对key的array进行deep copy,而对应的value的list是shallow copy

# 对于 List而言:
a = [1,2,3,4]
b = a.copy()
b.append(5)

#输出: b=[1,2,3,4,5], a= [1,2,3,4]
# 这里的list是deep copy,b=a.copy() 同等于 b=a[:]
# shallow copy:  b=a

#对于dictionary而言

a = {1:[1,2,3,4]}
b = a.copy()
b[1].append(5)

#这里b是对a字典的 key array进行deep copy。但是copy之后a和b的key所对应的
#value的地址是不变,所以对于list而言,b只是对a的list进行shallow copy
#所以这里的输出是 a={1:[1,2,3,4,5]}, b={1:[1,2,3,4,5]}
#

b[2] =[8,9]

#这里是对b的key的array添加新的key-value pair,而没有对a的key的array
#进行操作, 所以这句之后的输出是
# a={1:[1,2,3,4,5]}, b={1:[1,2,3,4,5] , 2:[8,9]}
#


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