feat(lru-cache): add new implementations

lab/exercises/01-arrays/longest-unique-characters.js

@@ -0,0 +1,72 @@
+/**
+ * @param {string} s
+ * @return {number}
+ */
+function lengthOfLongestSubstring(s) {
+  let max = 0;
+  let start = 0;
+  const map = {};
+
+  for (let i = 0; i < s.length; i++) {
+    const char = s[i];
+
+    if (map[char]) {
+      start = map[char] + 1;
+    }
+
+    map[char] = i;
+    max = Math.max(1 + i - start, max);
+  }
+
+  return max;
+}
+
+const assert = require('assert');
+
+const testCases = { abcabcbb: 3 };
+
+for (const [string, unique] of Object.entries(testCases)) {
+  assert.equal(lengthOfLongestSubstring(string), unique);
+}
+
+/*
+  Longest string without duplicate chars.
+
+  "abcabcbb"
+  3 (abc)
+
+  i=6
+  c=b
+  s=5
+  h={a:3,b:4,c:2}
+  m=3
+
+  ---
+  a
+  1
+
+  aa
+  1
+
+  ab
+  2
+
+  abc
+  3
+
+  aab
+  2
+
+  aabca
+  3
+
+  "dvdf"
+  3 (vdf)
+
+  "abcabcbb"
+  3 (abc)
+  ---
+
+  map: O(n)
+  backtracking
+*/

src/data-structures/custom/lru-cache-1.js

@@ -1,30 +1,7 @@
-
 /**
- * Design and implement a data structure for Least Recently Used (LRU) cache. It should support the following operations: get and put.
-
-    get(key) - Get the value (will always be positive) of the key if the key exists in the cache, otherwise return -1.
-    put(key, value) - Set or insert the value if the key is not already present. When the cache reached its capacity, it should invalidate the least recently used item before inserting a new item.
-
-    Follow up:
-    Could you do both operations in O(1) time complexity?
-
-    Example:
-
-    LRUCache cache = new LRUCache( 2);
-
-    cache.put(1, 1);
-    cache.put(2, 2);
-    cache.get(1);       // returns 1
-    cache.put(3, 3);    // evicts key 2
-    cache.get(2);       // returns -1 (not found)
-    cache.put(4, 4);    // evicts key 1
-    cache.get(1);       // returns -1 (not found)
-    cache.get(3);       // returns 3
-    cache.get(4);       // returns 4
-
- *  https://leetcode.com/problems/lru-cache/description/
- *
- * @param {number} capacity
+ * Least Recently Used (LRU) cache.
+ * Map + Array: O(n)
+ * @param {number} capacity - Number of items to hold.
  */
 const LRUCache = function (capacity) {
   this.map = new Map();

src/data-structures/custom/lru-cache-2.js

@@ -0,0 +1,72 @@
+/**
+ * Least Recently Used (LRU) cache.
+ * Map + (Hash)Set: O(1)
+ * @param {number} capacity - Number of items to hold.
+ */
+var LRUCache = function(capacity) {
+  this.capacity = capacity || 2;
+  this.map = new Map();
+  this.set = new Set();
+  this.size = 0;
+};
+
+/**
+ * @param {number} key
+ * @return {number}
+ */
+LRUCache.prototype.get = function(key) {
+  if (!this.map.has(key)) return -1;
+  // move to top
+  this.set.delete(key);
+  this.set.add(key);
+
+  return this.map.get(key);
+};
+
+/**
+ * @param {number} key
+ * @param {number} value
+ * @return {void}
+ */
+LRUCache.prototype.put = function(key, value) {
+  this.map.set(key, value);
+  // move to top
+  this.set.delete(key);
+  this.set.add(key);
+
+  if (this.set.size > this.capacity) {
+    const leastUsedKey = this.set.values().next().value;
+    this.map.delete(leastUsedKey);
+    this.set.delete(leastUsedKey);
+  }
+
+  this.size = this.map.size;
+};
+
+/**
+ * Your LRUCache object will be instantiated and called as such:
+ * var obj = new LRUCache(capacity)
+ * var param_1 = obj.get(key)
+ * obj.put(key,value)
+ */
+
+
+/*
+  Implement a hashMap cache with a given capacity that once reach deletes the least used element and store the new one.
+
+  ---
+
+  c = new LRUCache(2);
+  c.put(1,1);
+  c.put(2,2);
+  c.put(3,3); // deletes key 1
+
+  c = new LRUCache(2);
+  c.put(1,1);
+  c.put(2,2);
+  c.get(1);
+  c.put(3,3); // deletes key 2
+
+*/
+
+module.exports = LRUCache;

src/data-structures/custom/lru-cache-3.js

@@ -0,0 +1,51 @@
+const DLinkedList = require('../linked-lists/linked-list');
+/**
+ * Least Recently Used (LRU) cache.
+ * Map + Double LinkedList: O(1)
+ * @param {number} capacity - Number of items to hold.
+ */
+class LRUCache extends Map {
+  constructor(capacity) {
+    super(); // initialize map
+    this.capacity = capacity;
+    this.list = new DLinkedList();
+  }
+
+  get(key) {
+    if (!super.has(key)) { return -1; }
+
+    // console.log('get', {key});
+    const node = super.get(key);
+    this.moveToHead(key, node);
+
+    return node.value.value;
+  }
+
+  put(key, value) {
+    // console.log('put', {key, value});
+    let node;
+    if (super.has(key)) {
+      node = super.get(key);
+      node.value.value = value;
+    } else {
+      node = this.list.addLast({key, value});
+    }
+    this.moveToHead(key, node);
+
+    if (this.list.size > this.capacity) {
+      const firstNode = this.list.removeFirst();
+      super.delete(firstNode.key);
+    }
+  }
+
+  moveToHead(key, node) {
+    // remove node and put it in front
+    this.list.removeByNode(node);
+    const newNode = this.list.addLast(node.value);
+    super.set(key, newNode);
+    // console.log('\tlist', Array.from(this.list).map(l => l.node.value));
+    // console.log('\tlist', Array.from(this.list).map(l => l.node.value.key));
+  }
+}
+
+module.exports = LRUCache;

src/data-structures/custom/lru-cache.js

@@ -1,34 +1,7 @@
 /**
- * Design and implement a data structure for Least Recently Used (LRU) cache.
- * It should support the following operations: get and put.
-
-    get(key) - Get the value (will always be positive) of the key
-        if the key exists in the cache, otherwise return -1.
-    put(key, value) - Set or insert the value if the key is not already present.
-        When the cache reached its capacity, it should invalidate the least
-        recently used item before inserting a new item.
-
-    Follow up:
-    Could you do both operations in O(1) time complexity?
-
-    Example:
-
-    LRUCache cache = new LRUCache( 2);
-
-    cache.put(1, 1);
-    cache.put(2, 2);
-    cache.get(1);       // returns 1
-    cache.put(3, 3);    // evicts key 2
-    cache.get(2);       // returns -1 (not found)
-    cache.put(4, 4);    // evicts key 1
-    cache.get(1);       // returns -1 (not found)
-    cache.get(3);       // returns 3
-    cache.get(4);       // returns 4
-
- *  https://leetcode.com/problems/lru-cache/description/
- *  https://leetcode.com/submissions/detail/178329173/
- *
- * @param {number} capacity
+ * Least Recently Used (LRU) cache.
+ * (ordered) Map: O(1)
+ * @param {number} capacity - Number of items to hold.
  */
 class LRUCache {
   constructor(capacity) {
@@ -53,7 +26,7 @@ class LRUCache {
   rotate(key) {
     this.moveToTop(key);
     while (this.map.size > this.capacity) {
-      const it = this.map.keys();
+      const it = this.map.keys(); // keys are in insertion order.
       this.map.delete(it.next().value);
     }
   }
@@ -65,6 +38,10 @@ class LRUCache {
       this.map.set(key, value);
     }
   }
+
+  get size() {
+    return this.map.size;
+  }
 }
 
 module.exports = LRUCache;

src/data-structures/custom/lru-cache.spec.js

@@ -0,0 +1,108 @@
+const LRUCache = require('./lru-cache-3');
+
+describe('LRU Cache', () => {
+  let c;
+
+  describe('#constructor', () => {
+    it('should initialize', () => {
+      c = new LRUCache();
+      expect(c).toBeDefined();
+    });
+
+    it('should initialize', () => {
+      c = new LRUCache(7);
+      expect(c.capacity).toEqual(7);
+    });
+  });
+
+  describe('when initialized', () => {
+    beforeEach(() => {
+      c = new LRUCache(2);
+    });
+
+    describe('#put', () => {
+      it('should insert new elements', () => {
+        c.put(1, 1);
+        expect(c.size).toEqual(1);
+      });
+
+      it('should update existing element', () => {
+        c.put(1, 1);
+        c.put(1, 2);
+        expect(c.size).toEqual(1);
+      });
+    });
+
+    describe('#get', () => {
+      it('should get element', () => {
+        c.put(1, 1);
+        expect(c.get(1)).toEqual(1);
+      });
+
+      it('should return -1 for non-existing elements', () => {
+        expect(c.get(1)).toEqual(-1);
+      });
+
+      it('should not add non-existing number to the top of the list', () => {
+        c.put(1, 1);
+        expect(c.get(8)).toEqual(-1);
+        c.put(2, 2);
+        expect(c.get(9)).toEqual(-1);
+        expect(c.get(1)).toEqual(1);
+        expect(c.get(2)).toEqual(2);
+      });
+
+      it('should return -1 for removed elements', () => {
+        c.put(1, 1);
+        c.put(2, 2);
+        c.put(3, 3);
+        expect(c.get(1)).toEqual(-1);
+      });
+
+      it('should not remove value if accessed recently', () => {
+        c.put(1, 1);
+        c.put(2, 2);
+        expect(c.get(1)).toEqual(1);
+        c.put(3, 3);
+        expect(c.get(1)).toEqual(1);
+        expect(c.get(2)).toEqual(-1);
+      });
+
+      it('should update a value', () => {
+        c.put(1, 1);
+        c.put(1, 2);
+        expect(c.get(1)).toEqual(2);
+      });
+    });
+
+    it('should work with size 10', () => {
+      c = new LRUCache(10);
+
+      c.put(10, 13);
+      c.put(3, 17);
+      c.put(6, 11);
+      c.put(10, 5);
+      c.put(9, 10);
+      expect(c.get(13)).toEqual(-1);
+      c.put(2, 19);
+      expect(c.get(2)).toEqual(19);
+      expect(c.get(3)).toEqual(17);
+      c.put(5, 25);
+      expect(c.get(8)).toEqual(-1);
+      c.put(9, 22);
+      c.put(5, 5);
+      c.put(1, 30);
+      expect(c.get(11)).toEqual(-1);
+      c.put(9, 12);
+      expect(c.get(7)).toEqual(-1);
+      expect(c.get(5)).toEqual(5);
+      expect(c.get(8)).toEqual(-1);
+      expect(c.get(9)).toEqual(12);
+      c.put(4, 30);
+      c.put(9, 3);
+      expect(c.get(9)).toEqual(3);
+      expect(c.get(10)).toEqual(5);
+      expect(c.get(10)).toEqual(5);
+    });
+  });
+});