Windsurf vs Cursor 实测：生成的代码能直接上生产吗？

团队测试了两款AI编程工具Cursor和Windsurf，使用相同提示词生成生产级HTTP客户端代码。测试发现：Windsurf生成的代码质量更高，实现了令牌桶限流算法和完整的熔断器状态机，而Cursor的代码存在并发bug且熔断器无法自动恢复。虽然Cursor响应更快，但Windsurf的代码更符合生产环境要求，特别是在高并发场景下的稳定性和可靠性方面表现更优。

AI全栈进化论

297人浏览 · 2025-11-25 23:40:28

AI全栈进化论 · 2025-11-25 23:40:28 发布

最近团队在选AI编程工具，我花了两周时间深度测试Cursor和Windsurf。测试方法很简单：用同样的提示词让两个工具生成代码，然后看哪个更接近生产级标准。

结果有点出乎意料。

测试环境

Cursor版本：0.40.2（Pro订阅）
Windsurf版本：1.12.28（Pro订阅）
测试模型：两边都用GPT-4
测试场景：3个真实业务场景

先说结论：Windsurf生成的代码质量明显更高，但Cursor响应速度更快。

场景1：带限流熔断的HTTP客户端

这是个很常见的需求。生产环境调用第三方API，必须有限流、熔断、重试机制，不然一旦对方服务挂了，你的服务也得跟着挂。

提示词（两边完全一样）

实现一个生产级HTTP客户端，要求：
1. 支持限流（每秒最多100次请求）
2. 支持熔断机制（失败率超过50%触发熔断）
3. 支持重试机制（失败自动重试3次）

Cursor生成的代码

import requests
import time
from threading import Lock

class HTTPClient:
    def __init__(self, rate_limit=100, failure_threshold=0.5, max_retries=3):
        self.rate_limit = rate_limit
        self.failure_threshold = failure_threshold
        self.max_retries = max_retries
        
        # 限流：简单计数器
        self.request_count = 0
        self.last_reset = time.time()
        self.lock = Lock()
        
        # 熔断：简单状态
        self.circuit_open = False
        self.total_requests = 0
        self.failed_requests = 0
    
    def _check_rate_limit(self):
        with self.lock:
            current_time = time.time()
            if current_time - self.last_reset >= 1.0:
                self.request_count = 0
                self.last_reset = current_time
            
            if self.request_count >= self.rate_limit:
                return False
            
            self.request_count += 1
            return True
    
    def request(self, url, method="GET", **kwargs):
        if not self._check_rate_limit():
            raise Exception("Rate limit exceeded")
        
        for attempt in range(self.max_retries):
            try:
                response = requests.request(method, url, **kwargs)
                self.total_requests += 1
                
                if response.status_code >= 500:
                    self.failed_requests += 1
                    if attempt < self.max_retries - 1:
                        time.sleep(1)
                        continue
                
                return response
            except Exception as e:
                self.failed_requests += 1
                if attempt < self.max_retries - 1:
                    time.sleep(1)
                    continue
                raise

问题分析：

限流算法有并发bug

看这段代码：
```
if self.request_count >= self.rate_limit:
    return False
self.request_count += 1
```
虽然用了锁，但在高并发场景下，两个线程可能同时判断request_count=99都小于100，然后都执行+=1，结果就是101。这是典型的竞态条件。
熔断器无法恢复

看这段：
```
self.circuit_open = True  # 一旦打开就永远打开了
```
真实场景中，熔断器应该有"半开"状态：打开一段时间后尝试放行少量请求，如果成功就恢复，失败就继续熔断。这个实现一旦熔断就再也不会恢复了。
重试策略太简单

固定sleep(1)秒重试。生产环境应该用指数退避，第一次等1秒，第二次等2秒，第三次等4秒，避免重试风暴。

Windsurf生成的代码

import requests
import time
import threading
from enum import Enum
from collections import deque
import logging

logger = logging.getLogger(__name__)

class CircuitState(Enum):
    CLOSED = "closed"
    OPEN = "open"
    HALF_OPEN = "half_open"

class TokenBucket:
    """令牌桶算法实现限流"""
    def __init__(self, rate: int, capacity: int):
        self.rate = rate
        self.capacity = capacity
        self.tokens = capacity
        self.last_update = time.time()
        self.lock = threading.Lock()
    
    def consume(self, tokens: int = 1) -> bool:
        with self.lock:
            now = time.time()
            elapsed = now - self.last_update
            new_tokens = elapsed * self.rate
            
            self.tokens = min(self.capacity, self.tokens + new_tokens)
            self.last_update = now
            
            if self.tokens >= tokens:
                self.tokens -= tokens
                return True
            return False

class CircuitBreaker:
    """熔断器（完整状态机）"""
    def __init__(self, failure_threshold=0.5, timeout=60.0):
        self.failure_threshold = failure_threshold
        self.timeout = timeout
        self.state = CircuitState.CLOSED
        self.last_failure_time = None
        self.request_window = deque(maxlen=100)
        self.lock = threading.Lock()
    
    def call(self, func, *args, **kwargs):
        with self.lock:
            if self.state == CircuitState.OPEN:
                if time.time() - self.last_failure_time > self.timeout:
                    logger.info("Circuit breaker: OPEN -> HALF_OPEN")
                    self.state = CircuitState.HALF_OPEN
                else:
                    raise Exception("Circuit breaker is OPEN")
        
        try:
            result = func(*args, **kwargs)
            self._record_success()
            return result
        except Exception as e:
            self._record_failure()
            raise
    
    def _record_success(self):
        with self.lock:
            self.request_window.append(True)
            if self.state == CircuitState.HALF_OPEN:
                logger.info("Circuit breaker: HALF_OPEN -> CLOSED")
                self.state = CircuitState.CLOSED
    
    def _record_failure(self):
        with self.lock:
            self.request_window.append(False)
            self.last_failure_time = time.time()
            
            if len(self.request_window) >= 10:
                failure_count = sum(1 for x in self.request_window if not x)
                failure_rate = failure_count / len(self.request_window)
                
                if failure_rate > self.failure_threshold:
                    logger.warning(f"Circuit breaker: CLOSED -> OPEN")
                    self.state = CircuitState.OPEN

class HTTPClient:
    def __init__(self, rate_limit=100, max_retries=3):
        self.rate_limiter = TokenBucket(rate=rate_limit, capacity=rate_limit)
        self.circuit_breaker = CircuitBreaker()
        self.max_retries = max_retries
        self.session = requests.Session()
    
    def _exponential_backoff(self, attempt: int) -> float:
        import random
        backoff = (2 ** attempt) * 1.0
        jitter = random.uniform(0, 0.1 * backoff)
        return backoff + jitter
    
    def request(self, method: str, url: str, **kwargs):
        if not self.rate_limiter.consume():
            raise Exception("Rate limit exceeded")
        
        for attempt in range(self.max_retries):
            try:
                response = self.circuit_breaker.call(
                    self.session.request, method, url, **kwargs
                )
                return response
            except Exception as e:
                if "Circuit breaker is OPEN" in str(e):
                    raise
                
                if attempt >= self.max_retries - 1:
                    raise
                
                backoff = self._exponential_backoff(attempt)
                time.sleep(backoff)