11. Stream 与 AsyncIterator 🟡
你将学到:
StreamTrait(特征):异步迭代多个值- 创建 Stream:
stream::iter、async_stream、unfold- Stream 组合子:
map、filter、buffer_unordered、fold- 异步 I/O Trait:
AsyncRead、AsyncWrite、AsyncBufRead
Stream Trait 概览
Stream 之于 Iterator,就像 Future 之于单个值——它异步地产生多个值:
#![allow(unused)]
fn main() {
// std::iter::Iterator (synchronous, multiple values)
trait Iterator {
type Item;
fn next(&mut self) -> Option<Self::Item>;
}
// futures::Stream (async, multiple values)
trait Stream {
type Item;
fn poll_next(self: Pin<&mut Self>, cx: &mut Context<'_>) -> Poll<Option<Self::Item>>;
}
}
graph LR
subgraph "同步"
VAL["值<br/>(T)"]
ITER["迭代器<br/>(多个 T)"]
end
subgraph "异步"
FUT["Future<br/>(异步 T)"]
STREAM["Stream<br/>(异步多个 T)"]
end
VAL -->|"变为异步"| FUT
ITER -->|"变为异步"| STREAM
VAL -->|"变为多个"| ITER
FUT -->|"变为多个"| STREAM
style VAL fill:#e3f2fd,color:#000
style ITER fill:#e3f2fd,color:#000
style FUT fill:#c8e6c9,color:#000
style STREAM fill:#c8e6c9,color:#000
创建 Stream
#![allow(unused)]
fn main() {
use futures::stream::{self, StreamExt};
use tokio::time::{interval, Duration};
use tokio_stream::wrappers::IntervalStream;
// 1. From an iterator
let s = stream::iter(vec![1, 2, 3]);
// 2. From an async generator (using async_stream crate)
// Cargo.toml: async-stream = "0.3"
use async_stream::stream;
fn countdown(from: u32) -> impl futures::Stream<Item = u32> {
stream! {
for i in (0..=from).rev() {
tokio::time::sleep(Duration::from_millis(500)).await;
yield i;
}
}
}
// 3. From a tokio interval
let tick_stream = IntervalStream::new(interval(Duration::from_secs(1)));
// 4. From a channel receiver (tokio_stream::wrappers)
let (tx, rx) = tokio::sync::mpsc::channel::<String>(100);
let rx_stream = tokio_stream::wrappers::ReceiverStream::new(rx);
// 5. From unfold (generate from async state)
let s = stream::unfold(0u32, |state| async move {
if state >= 5 {
None // Stream ends
} else {
let next = state + 1;
Some((state, next)) // yield `state`, new state is `next`
}
});
}
消费 Stream
#![allow(unused)]
fn main() {
use futures::stream::{self, StreamExt};
async fn stream_examples() {
let s = stream::iter(vec![1, 2, 3, 4, 5]);
// for_each — process each item
s.for_each(|x| async move {
println!("{x}");
}).await;
// map + collect
let doubled: Vec<i32> = stream::iter(vec![1, 2, 3])
.map(|x| x * 2)
.collect()
.await;
// filter
let evens: Vec<i32> = stream::iter(1..=10)
.filter(|x| futures::future::ready(x % 2 == 0))
.collect()
.await;
// buffer_unordered — process N items concurrently
let results: Vec<_> = stream::iter(vec!["url1", "url2", "url3"])
.map(|url| async move {
// Simulate HTTP fetch
tokio::time::sleep(Duration::from_millis(100)).await;
format!("response from {url}")
})
.buffer_unordered(10) // Up to 10 concurrent fetches
.collect()
.await;
// take, skip, zip, chain — just like Iterator
let first_three: Vec<i32> = stream::iter(1..=100)
.take(3)
.collect()
.await;
}
}
与 C# IAsyncEnumerable 对比
| 特性 | Rust Stream | C# IAsyncEnumerable<T> |
|---|---|---|
| 语法 | stream! { yield x; } | await foreach / yield return |
| 取消 | 丢弃 Stream | CancellationToken |
| 背压(backpressure) | 消费者控制 poll 速率 | 消费者控制 MoveNextAsync |
| 内置 | 否(需要 futures crate) | 是(自 C# 8.0 起) |
| 组合子 | .map()、.filter()、.buffer_unordered() | LINQ + System.Linq.Async |
| 错误处理 | Stream<Item = Result<T, E>> | 在异步迭代器中抛出异常 |
#![allow(unused)]
fn main() {
// Rust: Stream of database rows
// NOTE: try_stream! (not stream!) is required when using ? inside the body.
// stream! doesn't propagate errors — try_stream! yields Err(e) and ends.
fn get_users(db: &Database) -> impl Stream<Item = Result<User, DbError>> + '_ {
try_stream! {
let mut cursor = db.query("SELECT * FROM users").await?;
while let Some(row) = cursor.next().await {
yield User::from_row(row?);
}
}
}
// Consume:
let mut users = pin!(get_users(&db));
while let Some(result) = users.next().await {
match result {
Ok(user) => println!("{}", user.name),
Err(e) => eprintln!("Error: {e}"),
}
}
}
// C# equivalent:
async IAsyncEnumerable<User> GetUsers() {
await using var reader = await db.QueryAsync("SELECT * FROM users");
while (await reader.ReadAsync()) {
yield return User.FromRow(reader);
}
}
// Consume:
await foreach (var user in GetUsers()) {
Console.WriteLine(user.Name);
}
🏋️ 练习:构建异步统计聚合器(点击展开)
挑战:给定一个传感器读数 Stream Stream<Item = f64>,编写一个异步函数,消费该 Stream 并返回 (count, min, max, average)。使用 StreamExt 组合子——不要只是收集到 Vec 中。
提示:使用 .fold() 在 Stream 上累积状态。
🔑 解答
#![allow(unused)]
fn main() {
use futures::stream::{self, StreamExt};
#[derive(Debug)]
struct Stats {
count: usize,
min: f64,
max: f64,
sum: f64,
}
impl Stats {
fn average(&self) -> f64 {
if self.count == 0 { 0.0 } else { self.sum / self.count as f64 }
}
}
async fn compute_stats<S: futures::Stream<Item = f64>>(stream: S) -> Stats {
stream
.fold(
Stats { count: 0, min: f64::INFINITY, max: f64::NEG_INFINITY, sum: 0.0 },
|mut acc, value| async move {
acc.count += 1;
acc.min = acc.min.min(value);
acc.max = acc.max.max(value);
acc.sum += value;
acc
},
)
.await
}
#[tokio::test]
async fn test_stats() {
let readings = stream::iter(vec![23.5, 24.1, 22.8, 25.0, 23.9]);
let stats = compute_stats(readings).await;
assert_eq!(stats.count, 5);
assert!((stats.min - 22.8).abs() < f64::EPSILON);
assert!((stats.max - 25.0).abs() < f64::EPSILON);
assert!((stats.average() - 23.86).abs() < 0.01);
}
}
要点:像 .fold() 这样的 Stream 组合子可以逐条处理元素,而无需全部载入内存——这对处理大型或无界数据流至关重要。
异步 I/O Trait:AsyncRead、AsyncWrite、AsyncBufRead
正如 std::io::Read/Write 是同步 I/O 的基础,它们的异步对应物是异步 I/O 的基础。这些 Trait 由 tokio::io 提供(或与运行时无关的代码使用 futures::io):
#![allow(unused)]
fn main() {
// tokio::io — the async versions of std::io traits
/// Read bytes from a source asynchronously
pub trait AsyncRead {
fn poll_read(
self: Pin<&mut Self>,
cx: &mut Context<'_>,
buf: &mut ReadBuf<'_>, // Tokio's safe wrapper around uninitialized memory
) -> Poll<io::Result<()>>;
}
/// Write bytes to a sink asynchronously
pub trait AsyncWrite {
fn poll_write(
self: Pin<&mut Self>,
cx: &mut Context<'_>,
buf: &[u8],
) -> Poll<io::Result<usize>>;
fn poll_flush(self: Pin<&mut Self>, cx: &mut Context<'_>) -> Poll<io::Result<()>>;
fn poll_shutdown(self: Pin<&mut Self>, cx: &mut Context<'_>) -> Poll<io::Result<()>>;
}
/// Buffered reading with line support
pub trait AsyncBufRead: AsyncRead {
fn poll_fill_buf(self: Pin<&mut Self>, cx: &mut Context<'_>) -> Poll<io::Result<&[u8]>>;
fn consume(self: Pin<&mut Self>, amt: usize);
}
}
实践中,你很少直接调用这些 poll_* 方法。相反,应使用扩展 Trait AsyncReadExt 和 AsyncWriteExt,它们提供支持 .await 的辅助方法:
#![allow(unused)]
fn main() {
use tokio::io::{AsyncReadExt, AsyncWriteExt, AsyncBufReadExt};
use tokio::net::TcpStream;
use tokio::io::BufReader;
async fn io_examples() -> tokio::io::Result<()> {
let mut stream = TcpStream::connect("127.0.0.1:8080").await?;
// AsyncWriteExt: write_all, write_u32, write_buf, etc.
stream.write_all(b"GET / HTTP/1.0\r\n\r\n").await?;
// AsyncReadExt: read, read_exact, read_to_end, read_to_string
let mut response = Vec::new();
stream.read_to_end(&mut response).await?;
// AsyncBufReadExt: read_line, lines(), split()
let file = tokio::fs::File::open("config.txt").await?;
let reader = BufReader::new(file);
let mut lines = reader.lines();
while let Some(line) = lines.next_line().await? {
println!("{line}");
}
Ok(())
}
}
实现自定义异步 I/O——在原始 TCP 之上封装协议:
#![allow(unused)]
fn main() {
use tokio::io::{AsyncRead, AsyncWrite, ReadBuf};
use std::pin::Pin;
use std::task::{Context, Poll};
/// A length-prefixed protocol: [u32 length][payload bytes]
struct FramedStream<T> {
inner: T,
}
impl<T: AsyncRead + AsyncReadExt + Unpin> FramedStream<T> {
/// Read one complete frame
async fn read_frame(&mut self) -> tokio::io::Result<Vec<u8>>
{
// Read the 4-byte length prefix
let len = self.inner.read_u32().await? as usize;
// Read exactly that many bytes
let mut payload = vec![0u8; len];
self.inner.read_exact(&mut payload).await?;
Ok(payload)
}
}
impl<T: AsyncWrite + AsyncWriteExt + Unpin> FramedStream<T> {
/// Write one complete frame
async fn write_frame(&mut self, data: &[u8]) -> tokio::io::Result<()>
{
self.inner.write_u32(data.len() as u32).await?;
self.inner.write_all(data).await?;
self.inner.flush().await?;
Ok(())
}
}
}
| 同步 Trait | 异步 Trait (tokio) | 异步 Trait (futures) | 扩展 Trait |
|---|---|---|---|
std::io::Read | tokio::io::AsyncRead | futures::io::AsyncRead | AsyncReadExt |
std::io::Write | tokio::io::AsyncWrite | futures::io::AsyncWrite | AsyncWriteExt |
std::io::BufRead | tokio::io::AsyncBufRead | futures::io::AsyncBufRead | AsyncBufReadExt |
std::io::Seek | tokio::io::AsyncSeek | futures::io::AsyncSeek | AsyncSeekExt |
tokio 与 futures I/O Trait 对比:它们相似但不完全相同——tokio 的
AsyncRead使用ReadBuf(安全处理未初始化内存),而futures::AsyncRead使用&mut [u8]。使用tokio_util::compat在两者之间转换。
复制工具:
tokio::io::copy(&mut reader, &mut writer)是std::io::copy的异步等价物——适用于代理服务器或文件传输。tokio::io::copy_bidirectional并发地向两个方向复制。
🏋️ 练习:构建异步行计数器(点击展开)
挑战:编写一个异步函数,接受任意 AsyncBufRead 数据源并返回非空行的数量。它应适用于文件、TCP 流或任何带缓冲的 reader。
提示:使用 AsyncBufReadExt::lines(),并统计 !line.is_empty() 的行。
🔑 解答
#![allow(unused)]
fn main() {
use tokio::io::AsyncBufReadExt;
async fn count_non_empty_lines<R: tokio::io::AsyncBufRead + Unpin>(
reader: R,
) -> tokio::io::Result<usize> {
let mut lines = reader.lines();
let mut count = 0;
while let Some(line) = lines.next_line().await? {
if !line.is_empty() {
count += 1;
}
}
Ok(count)
}
// Works with any AsyncBufRead:
// let file = tokio::io::BufReader::new(tokio::fs::File::open("data.txt").await?);
// let count = count_non_empty_lines(file).await?;
//
// let tcp = tokio::io::BufReader::new(TcpStream::connect("...").await?);
// let count = count_non_empty_lines(tcp).await?;
}
要点:针对 AsyncBufRead 而非具体类型编程,你的 I/O 代码可在文件、套接字、管道之间复用,甚至适用于内存缓冲区(tokio::io::BufReader::new(std::io::Cursor::new(data)))。
要点回顾 — Stream 与 AsyncIterator
Stream是Iterator的异步等价物——产生Poll::Ready(Some(item))或Poll::Ready(None).buffer_unordered(N)并发处理 N 个 Stream 元素——Stream 的关键并发工具async_stream::stream!是创建自定义 Stream 的最简单方式(使用yield)AsyncRead/AsyncBufRead使 I/O 代码可在文件、套接字和管道之间通用复用
另见: 第 9 章 — 何时 Tokio 并非合适选择 了解
FuturesUnordered(相关模式),第 13 章 — 生产模式 了解有界 channel 的背压