next/dist/server/lib/lru-cache.js

The React Framework

/**
 * Node in the doubly-linked list used for LRU tracking.
 * Each node represents a cache entry with bidirectional pointers.
 */ "use strict";
Object.defineProperty(exports, "__esModule", {
    value: true
});
Object.defineProperty(exports, "LRUCache", {
    enumerable: true,
    get: function() {
        return LRUCache;
    }
});
class LRUNode {
    constructor(key, data, size){
        this.prev = null;
        this.next = null;
        this.key = key;
        this.data = data;
        this.size = size;
    }
}
/**
 * Sentinel node used for head/tail boundaries.
 * These nodes don't contain actual cache data but simplify list operations.
 */ class SentinelNode {
    constructor(){
        this.prev = null;
        this.next = null;
    }
}
class LRUCache {
    constructor(maxSize, calculateSize){
        this.cache = new Map();
        this.totalSize = 0;
        this.maxSize = maxSize;
        this.calculateSize = calculateSize;
        // Create sentinel nodes to simplify doubly-linked list operations
        // HEAD <-> TAIL (empty list)
        this.head = new SentinelNode();
        this.tail = new SentinelNode();
        this.head.next = this.tail;
        this.tail.prev = this.head;
    }
    /**
   * Adds a node immediately after the head (marks as most recently used).
   * Used when inserting new items or when an item is accessed.
   * PRECONDITION: node must be disconnected (prev/next should be null)
   */ addToHead(node) {
        node.prev = this.head;
        node.next = this.head.next;
        // head.next is always non-null (points to tail or another node)
        this.head.next.prev = node;
        this.head.next = node;
    }
    /**
   * Removes a node from its current position in the doubly-linked list.
   * Updates the prev/next pointers of adjacent nodes to maintain list integrity.
   * PRECONDITION: node must be connected (prev/next are non-null)
   */ removeNode(node) {
        // Connected nodes always have non-null prev/next
        node.prev.next = node.next;
        node.next.prev = node.prev;
    }
    /**
   * Moves an existing node to the head position (marks as most recently used).
   * This is the core LRU operation - accessed items become most recent.
   */ moveToHead(node) {
        this.removeNode(node);
        this.addToHead(node);
    }
    /**
   * Removes and returns the least recently used node (the one before tail).
   * This is called during eviction when the cache exceeds capacity.
   * PRECONDITION: cache is not empty (ensured by caller)
   */ removeTail() {
        const lastNode = this.tail.prev;
        // tail.prev is always non-null and always LRUNode when cache is not empty
        this.removeNode(lastNode);
        return lastNode;
    }
    /**
   * Sets a key-value pair in the cache.
   * If the key exists, updates the value and moves to head.
   * If new, adds at head and evicts from tail if necessary.
   *
   * Time Complexity:
   * - O(1) for uniform item sizes
   * - O(k) where k is the number of items evicted (can be O(N) for variable sizes)
   */ set(key, value) {
        const size = (this.calculateSize == null ? void 0 : this.calculateSize.call(this, value)) ?? 1;
        if (size > this.maxSize) {
            console.warn('Single item size exceeds maxSize');
            return;
        }
        const existing = this.cache.get(key);
        if (existing) {
            // Update existing node: adjust size and move to head (most recent)
            existing.data = value;
            this.totalSize = this.totalSize - existing.size + size;
            existing.size = size;
            this.moveToHead(existing);
        } else {
            // Add new node at head (most recent position)
            const newNode = new LRUNode(key, value, size);
            this.cache.set(key, newNode);
            this.addToHead(newNode);
            this.totalSize += size;
        }
        // Evict least recently used items until under capacity
        while(this.totalSize > this.maxSize && this.cache.size > 0){
            const tail = this.removeTail();
            this.cache.delete(tail.key);
            this.totalSize -= tail.size;
        }
    }
    /**
   * Checks if a key exists in the cache.
   * This is a pure query operation - does NOT update LRU order.
   *
   * Time Complexity: O(1)
   */ has(key) {
        return this.cache.has(key);
    }
    /**
   * Retrieves a value by key and marks it as most recently used.
   * Moving to head maintains the LRU property for future evictions.
   *
   * Time Complexity: O(1)
   */ get(key) {
        const node = this.cache.get(key);
        if (!node) return undefined;
        // Mark as most recently used by moving to head
        this.moveToHead(node);
        return node.data;
    }
    /**
   * Returns an iterator over the cache entries. The order is outputted in the
   * order of most recently used to least recently used.
   */ *[Symbol.iterator]() {
        let current = this.head.next;
        while(current && current !== this.tail){
            // Between head and tail, current is always LRUNode
            const node = current;
            yield [
                node.key,
                node.data
            ];
            current = current.next;
        }
    }
    /**
   * Removes a specific key from the cache.
   * Updates both the hash map and doubly-linked list.
   *
   * Time Complexity: O(1)
   */ remove(key) {
        const node = this.cache.get(key);
        if (!node) return;
        this.removeNode(node);
        this.cache.delete(key);
        this.totalSize -= node.size;
    }
    /**
   * Returns the number of items in the cache.
   */ get size() {
        return this.cache.size;
    }
    /**
   * Returns the current total size of all cached items.
   * This uses the custom size calculation if provided.
   */ get currentSize() {
        return this.totalSize;
    }
}

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