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基础数据结构 文档
基础数据结构
Core ConceptsHow It WorksImplementationComplexity AnalysisPractice ProblemsReal-World Use
讨论

基础数据结构 指南 · 3/6

Implementation

本章目前仅提供英文版。

We build a stack, a ring-buffer queue and a chained hash map in Python, then port the hash map core (put, get, resize) to C++, Java and TypeScript. In real code you would use list, deque and dict; writing them once shows what those types do for you.

Stack and queue in Python

class Stack:
    def __init__(self):
        self._items = []

    def push(self, item):
        self._items.append(item)

    def pop(self):
        if not self._items:
            raise IndexError("pop from empty stack")
        return self._items.pop()

    def peek(self):
        return self._items[-1]


class Queue:
    def __init__(self, capacity=4):
        self._slots = [None] * capacity
        self._head = 0          # index of the oldest item
        self._size = 0

    def enqueue(self, item):
        if self._size == len(self._slots):
            self._grow()
        tail = (self._head + self._size) % len(self._slots)
        self._slots[tail] = item
        self._size += 1

    def dequeue(self):
        if self._size == 0:
            raise IndexError("dequeue from empty queue")
        item = self._slots[self._head]
        self._slots[self._head] = None          # drop the reference
        self._head = (self._head + 1) % len(self._slots)
        self._size -= 1
        return item

    def _grow(self):
        n = len(self._slots)
        ordered = [self._slots[(self._head + i) % n] for i in range(self._size)]
        self._slots = ordered + [None] * n      # double, oldest first
        self._head = 0

    def __len__(self):
        return self._size


s, q = Stack(), Queue()
for x in range(6):
    s.push(x)
    q.enqueue(x)
print(s.pop(), q.dequeue(), len(q))  # 5 0 5

How it works, line by line:

  • Stack only touches the end of a list, so push and pop are O(1) amortized.
  • Queue keeps the oldest item's index in _head and derives the tail as (_head + _size) % capacity. Storing a size avoids the ambiguity where head == tail could mean empty or full.
  • dequeue clears the slot so the queue does not keep the object alive.
  • _grow copies items in queue order into a doubled array and resets _head to 0.

Hash map with separate chaining in Python

class HashMap:
    def __init__(self, capacity=8, max_load=0.75):
        self._buckets = [[] for _ in range(capacity)]
        self._size = 0
        self._max_load = max_load

    def _bucket(self, key):
        return self._buckets[hash(key) % len(self._buckets)]

    def put(self, key, value):
        bucket = self._bucket(key)
        for i, (k, _) in enumerate(bucket):
            if k == key:                    # existing key: replace the value
                bucket[i] = (key, value)
                return
        bucket.append((key, value))
        self._size += 1
        if self._size / len(self._buckets) > self._max_load:
            self._resize(2 * len(self._buckets))

    def get(self, key, default=None):
        for k, v in self._bucket(key):
            if k == key:
                return v
        return default

    def remove(self, key):
        bucket = self._bucket(key)
        for i, (k, _) in enumerate(bucket):
            if k == key:
                bucket.pop(i)
                self._size -= 1
                return True
        return False

    def _resize(self, capacity):
        old = self._buckets
        self._buckets = [[] for _ in range(capacity)]
        for bucket in old:
            for key, value in bucket:
                self._bucket(key).append((key, value))

    def __len__(self):
        return self._size


m = HashMap()
for word in "the quick brown fox jumps over the lazy dog the end".split():
    m.put(word, m.get(word, 0) + 1)
print(m.get("the"), m.get("cat"), len(m), len(m._buckets))  # 3 None 9 16
对本章有疑问?
上一章How It Works下一章Complexity Analysis
  • _bucket maps a key to hash(key) % capacity. Python's % is non-negative for a positive divisor, so negative hashes are safe.
  • put scans the chain first; updating an existing key must not grow _size.
  • Crossing a load factor of 0.75 doubles the bucket array, and _resize reinserts every pair because the index depends on the capacity.
  • get and remove hash once and scan one short chain: O(1) on average.

The same hash map core in C++

#include <functional>
#include <iostream>
#include <list>
#include <string>
#include <utility>
#include <vector>

template <typename K, typename V>
class HashMap {
    std::vector<std::list<std::pair<K, V>>> buckets_;
    std::size_t size_ = 0;

    std::size_t index(const K& key, std::size_t n) const { return std::hash<K>{}(key) % n; }

    void resize(std::size_t capacity) {
        std::vector<std::list<std::pair<K, V>>> next(capacity);
        for (auto& bucket : buckets_)
            for (auto& kv : bucket) next[index(kv.first, capacity)].push_back(std::move(kv));
        buckets_.swap(next);
    }

public:
    explicit HashMap(std::size_t capacity = 8) : buckets_(capacity) {}

    void put(const K& key, const V& value) {
        auto& bucket = buckets_[index(key, buckets_.size())];
        for (auto& kv : bucket)
            if (kv.first == key) { kv.second = value; return; }
        bucket.emplace_back(key, value);
        if (++size_ * 4 > buckets_.size() * 3) resize(buckets_.size() * 2);  // load factor 0.75
    }

    const V* get(const K& key) const {
        for (const auto& kv : buckets_[index(key, buckets_.size())])
            if (kv.first == key) return &kv.second;
        return nullptr;
    }

    std::size_t size() const { return size_; }
};

int main() {
    HashMap<std::string, int> ages;
    ages.put("ada", 36);
    ages.put("ada", 37);
    ages.put("alan", 41);
    std::cout << *ages.get("ada") << ' ' << ages.size() << ' ' << (ages.get("bob") == nullptr) << '\n';  // 37 2 1
}

get returns a null pointer for a missing key, and the load-factor check size * 4 > capacity * 3 stays in integer arithmetic. remove would be the same scan followed by erase.

The same hash map core in Java

import java.util.ArrayList;
import java.util.LinkedList;
import java.util.List;
import java.util.Objects;

public class ChainedHashMap<K, V> {
    private record Entry<K, V>(K key, V value) {}

    private List<LinkedList<Entry<K, V>>> buckets = newBuckets(8);
    private int size = 0;

    private static <K, V> List<LinkedList<Entry<K, V>>> newBuckets(int n) {
        List<LinkedList<Entry<K, V>>> list = new ArrayList<>(n);
        for (int i = 0; i < n; i++) list.add(new LinkedList<>());
        return list;
    }

    private LinkedList<Entry<K, V>> bucket(K key) {
        return buckets.get(Math.floorMod(Objects.hashCode(key), buckets.size()));
    }

    public void put(K key, V value) {
        var bucket = bucket(key);
        for (var it = bucket.listIterator(); it.hasNext(); ) {
            if (Objects.equals(it.next().key(), key)) { it.set(new Entry<>(key, value)); return; }
        }
        bucket.add(new Entry<>(key, value));
        if (++size * 4 > buckets.size() * 3) resize(buckets.size() * 2);
    }

    public V get(K key) {
        for (var e : bucket(key)) if (Objects.equals(e.key(), key)) return e.value();
        return null;
    }

    private void resize(int capacity) {
        var old = buckets;
        buckets = newBuckets(capacity);
        for (var b : old) for (var e : b) bucket(e.key()).add(e);
    }

    public int size() { return size; }

    public static void main(String[] args) {
        var m = new ChainedHashMap<String, Integer>();
        for (var w : "to be or not to be".split(" ")) m.put(w, m.get(w) == null ? 1 : m.get(w) + 1);
        System.out.println(m.get("be") + " " + m.size());  // 2 4
    }
}

Math.floorMod matters: hashCode() can be negative, and Java's % would then produce a negative index.

The same hash map core in TypeScript

class ChainedHashMap<V> {
  private buckets: [string, V][][] = Array.from({ length: 8 }, () => []);
  private count = 0;

  private hash(key: string): number {
    let h = 2166136261; // FNV-1a, 32-bit
    for (let i = 0; i < key.length; i++) {
      h ^= key.charCodeAt(i);
      h = Math.imul(h, 16777619);
    }
    return h >>> 0; // unsigned
  }

  private bucket(key: string): [string, V][] {
    return this.buckets[this.hash(key) % this.buckets.length];
  }

  put(key: string, value: V): void {
    const bucket = this.bucket(key);
    const entry = bucket.find(([k]) => k === key);
    if (entry) { entry[1] = value; return; }
    bucket.push([key, value]);
    if (++this.count > this.buckets.length * 0.75) this.resize(this.buckets.length * 2);
  }

  get(key: string): V | undefined {
    return this.bucket(key).find(([k]) => k === key)?.[1];
  }

  private resize(capacity: number): void {
    const old = this.buckets;
    this.buckets = Array.from({ length: capacity }, () => []);
    for (const bucket of old) for (const [k, v] of bucket) this.bucket(k).push([k, v]);
  }

  get size(): number { return this.count; }
}

const m = new ChainedHashMap<number>();
for (const w of "a b a c b a".split(" ")) m.put(w, (m.get(w) ?? 0) + 1);
console.log(m.get("a"), m.size); // 3 3

JavaScript exposes no hash for arbitrary values, so this version takes string keys and hashes them with FNV-1a; Math.imul keeps the product in 32 bits and >>> 0 makes it unsigned.

Summary

A stack is a thin wrapper over a dynamic array, a queue becomes O(1) on both ends with a ring buffer, and a hash map is an array of short chains that doubles when the load factor passes a threshold. The four ports share the same three steps: hash the key, reduce it to a bucket index, scan one chain.

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