阶段3（上）：Python/asyncio/FastAPI 专题的课程、企业场景、面试题和可运行示例

topics/python/asyncio/examples/fanout/fanout.py

@@ -0,0 +1,100 @@
+"""并发调用多个下游（例如大模型 / 检索 / 第三方 API）：并发上限、单次超时、有限重试、部分失败、整体截止时间。
+
+只用标准库。运行：python fanout.py；测试：python -m pytest -q test_fanout.py
+"""
+from __future__ import annotations
+
+import asyncio
+import random
+import time
+from collections.abc import Awaitable, Callable
+from dataclasses import dataclass
+from typing import Generic, TypeVar
+
+T = TypeVar("T")
+
+
+class RetryableError(Exception):
+    """可以重试的错误（限流 429、服务暂时不可用 503 等）。"""
+
+
+@dataclass
+class Result(Generic[T]):
+    key: str
+    value: T | None = None
+    error: str | None = None
+    attempts: int = 0
+
+
+async def call_with_retry(fn: Callable[[], Awaitable[T]], *, timeout: float, retries: int,
+                          base_delay: float = 0.05) -> tuple[T, int]:
+    """单次调用带超时；遇到超时或可重试错误时指数退避重试。返回 (结果, 尝试次数)。"""
+    for attempt in range(1, retries + 2):
+        try:
+            async with asyncio.timeout(timeout):  # Python 3.11+
+                return await fn(), attempt
+        except (TimeoutError, RetryableError):
+            if attempt > retries:
+                raise
+            await asyncio.sleep(base_delay * 2 ** (attempt - 1) * (1 + random.random() / 2))
+    raise AssertionError("不会执行到这里")
+
+
+async def fan_out(jobs: dict[str, Callable[[], Awaitable[T]]], *, concurrency: int, timeout: float,
+                  retries: int = 1, deadline: float | None = None) -> list[Result[T]]:
+    """并发执行所有任务，最多 concurrency 个同时进行；单个失败不影响其他任务。
+    deadline：整体截止时间（秒），到时未完成的任务被取消并标记为超时。"""
+    sem = asyncio.Semaphore(concurrency)
+    results = {k: Result[T](key=k) for k in jobs}
+
+    async def run(key: str, fn: Callable[[], Awaitable[T]]) -> None:
+        async def counted() -> T:  # 记录尝试次数（失败时也能看到试了几次）
+            results[key].attempts += 1
+            return await fn()
+
+        async with sem:
+            try:
+                results[key].value, _ = await call_with_retry(counted, timeout=timeout, retries=retries)
+            except asyncio.CancelledError:
+                results[key].error = "整体超时，已取消"
+                raise  # 取消必须继续向上传播
+            except Exception as e:  # 单个任务失败只记录，不影响其他任务
+                results[key].error = f"{type(e).__name__}: {e}" if str(e) else type(e).__name__
+
+    tasks = [asyncio.create_task(run(k, fn)) for k, fn in jobs.items()]
+    done, pending = await asyncio.wait(tasks, timeout=deadline)
+    for t in pending:
+        t.cancel()
+    await asyncio.gather(*pending, return_exceptions=True)  # 等待取消完成，避免任务泄漏
+    return [results[k] for k in jobs]
+
+
+# ---------------- 演示 ----------------
+def fake_llm(name: str, delay: float, fail_times: int = 0) -> Callable[[], Awaitable[str]]:
+    state = {"left": fail_times}
+
+    async def call() -> str:
+        await asyncio.sleep(delay)
+        if state["left"] > 0:
+            state["left"] -= 1
+            raise RetryableError("429 Too Many Requests")
+        return f"{name} 的回答"
+
+    return call
+
+
+async def demo() -> None:
+    jobs = {
+        "摘要": fake_llm("摘要", 0.10),
+        "分类": fake_llm("分类", 0.10, fail_times=1),  # 第一次被限流，重试后成功
+        "翻译": fake_llm("翻译", 2.00),                # 太慢，单次超时
+        "关键词": fake_llm("关键词", 0.05),
+    }
+    start = time.perf_counter()
+    for r in await fan_out(jobs, concurrency=2, timeout=0.5, retries=1):
+        print(f"{r.key}: {r.value or r.error}（尝试 {r.attempts} 次）")
+    print(f"总耗时 {time.perf_counter() - start:.2f}s")
+
+
+if __name__ == "__main__":
+    asyncio.run(demo())