用 Rust 打造高性能图片处理服务器：从零开始实现类似 Thumbor 的功能
在现代互联网应用中，图片处理服务是不可或缺的一环，无论是动态调整图片大小、裁剪、添加滤镜还是水印，都需要高效且可靠的解决方案。本文将带你从零开始，使用 Rust 编程语言构建一个类似 Thumbor 的图片处理服务器。通过这个实战项目，你将深入了解 Rust 的异步编程、Protobuf 数据结构、HTTP 服务搭建以及图片处理逻辑的实现。无论你是 Rust 新手还是希望提升技能的开发者，这篇文章都将为你提供清晰的指引和实操经验。
本文详细介绍了一个基于 Rust 的图片处理服务器的开发过程，灵感来源于开源图片处理工具 Thumbor。我们从项目初始化开始，逐步完成 Protobuf 定义、依赖配置、HTTP 服务器搭建、图片处理引擎实现以及缓存机制的集成。项目使用 Axum 框架构建异步 Web 服务，结合 photon-rs 库实现图片处理功能，支持调整大小、裁剪、翻转、滤镜和水印等操作。代码结构模块化，易于扩展，并通过 LRU 缓存优化性能。本文适合对 Rust、异步编程或图片处理感兴趣的开发者参考。
实操
一个类似 Thumbor 的图片服务器
protobuf 的定义和编译
创建项目
bash体验AI代码助手代码解读复制代码/Code/rust via 🅒 base ➜ cargo new thumbor Created binary (application) `thumbor` package ~/Code/rust via 🅒 base ➜ cd thumbor thumbor on master [?] via 🦀 1.70.0 via 🅒 base ➜ c thumbor on master [?] via 🦀 1.70.0 via 🅒 base ➜
Cargo.toml 文件
在项目的 Cargo.toml 中添加这些依赖：
rust体验AI代码助手代码解读复制代码[package] name = "thumbor" version = "0.1.0" edition = "2021" # See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html [dependencies] axum = "0.6.18" # web 服务器 anyhow = "1.0.71" # 错误处理 base64 = "0.13.1" # base64 编码/解码 bytes = "1.4.0" # 处理字节流 image = "0.24.6" # 处理图片 lazy_static = "1.4.0" # 通过宏更方便地初始化静态变量 lru = "0.10.1" # LRU 缓存 percent-encoding = "2.3.0" # url 编码/解码 photon-rs = "0.3.2" # 图片效果 prost = "0.11.9" # protobuf 处理 reqwest = "0.11.18" # HTTP cliebnt serde = { version = "1.0.164", features = ["derive"] } # 序列化/反序列化数据 tokio = { version = "1.29.1", features = ["full"] } # 异步处理 tower = { version = "0.4.13", features = [ "util", "timeout", "load-shed", "limit", ] } # 服务处理及中间件 tower-http = { version = "0.4.1", features = [ "add-extension", "compression-full", "trace", ] } # http 中间件 tracing = "0.1.37" # 日志和追踪 tracing-subscriber = "0.3.17" # 日志和追踪 [build-dependencies] prost-build = "0.11.9" # 编译 protobuf
创建文件并编译构建项目
在项目根目录下，生成一个 abi.proto 文件，写入我们支持的图片处理服务用到的数据结构：
bash体验AI代码助手代码解读复制代码thumbor on master [?] via 🦀 1.70.0 via 🅒 base ➜ touch abi.proto thumbor on master [?] via 🦀 1.70.0 via 🅒 base ➜ touch build.rs thumbor on master [?] via 🦀 1.70.0 via 🅒 base ➜ mkdir src/pb thumbor on master [?] is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base ➜ cargo build thumbor on master [?] is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base took 16.1s ➜ touch src/pb/mod.rs
abi.proto 文件
rust体验AI代码助手代码解读复制代码syntax = "proto3"; package abi; // 这个名字会被用作编译结果，prost 会产生：abi.rs // 一个 ImageSpec 是一个有序的数组，服务器按照 spec 的顺序处理 message ImageSpec { repeated Spec specs = 1; } // 处理图片改变大小 message Resize { uint32 width = 1; uint32 height = 2; enum ResizeType { NORMAL = 0; SEAM_CARVE = 1; } ResizeType rtype = 3; enum SampleFilter { UNDEFINED = 0; NEAREST = 1; TRIANGLE = 2; CATMULL_ROM = 3; GAUSSIAN = 4; LANCZOS3 = 5; } SampleFilter filter = 4; } // 处理图片截取 message Crop { uint32 x1 = 1; uint32 y1 = 2; uint32 x2 = 3; uint32 y2 = 4; } // 处理水平翻转 message Fliph {} // 处理垂直翻转 message Flipv {} // 处理对比度 message Contrast { float contrast = 1; } // 处理滤镜 message Filter { enum Filter { UNSPECIFIED = 0; OCEANIC = 1; ISLANDS = 2; MARINE = 3; // more: https://docs.rs/photon-rs/0.3.1/photon_rs/filters/fn.filter.html } Filter filter = 1; } // 处理水印 message Watermark { uint32 x = 1; uint32 y = 2; } // 一个 spec 可以包含上述的处理方式之一 message Spec { oneof data { Resize resize = 1; Crop crop = 2; Flipv flipv = 3; Fliph fliph = 4; Contrast contrast = 5; Filter filter = 6; Watermark watermark = 7; } }
build.rs 文件
在项目根目录下，创建一个 build.rs，写入以下代码：
rust体验AI代码助手代码解读复制代码fn main() { prost_build::Config::new() .out_dir("src/pb") .compile_protos(&["abi.proto"], &["."]) .unwrap(); }
abi.rs 文件
mkdir src/pb 创建src/pb 目录。运行 cargo build，你会发现在 src/pb 下，有一个 abi.rs 文件被生成出来
rust体验AI代码助手代码解读复制代码/// 一个 ImageSpec 是一个有序的数组，服务器按照 spec 的顺序处理 #[allow(clippy::derive_partial_eq_without_eq)] #[derive(Clone, PartialEq, ::prost::Message)] pub struct ImageSpec { #[prost(message, repeated, tag = "1")] pub specs: ::prost::alloc::vec::Vec<Spec>, } /// 处理图片改变大小 #[allow(clippy::derive_partial_eq_without_eq)] #[derive(Clone, PartialEq, ::prost::Message)] pub struct Resize { #[prost(uint32, tag = "1")] pub width: u32, #[prost(uint32, tag = "2")] pub height: u32, #[prost(enumeration = "resize::ResizeType", tag = "3")] pub rtype: i32, #[prost(enumeration = "resize::SampleFilter", tag = "4")] pub filter: i32, } /// Nested message and enum types in `Resize`. pub mod resize { #[derive( Clone, Copy, Debug, PartialEq, Eq, Hash, PartialOrd, Ord, ::prost::Enumeration )] #[repr(i32)] pub enum ResizeType { Normal = 0, SeamCarve = 1, } impl ResizeType { /// String value of the enum field names used in the ProtoBuf definition. /// /// The values are not transformed in any way and thus are considered stable /// (if the ProtoBuf definition does not change) and safe for programmatic use. pub fn as_str_name(&self) -> &''static str { match self { ResizeType::Normal => "NORMAL", ResizeType::SeamCarve => "SEAM_CARVE", } } /// Creates an enum from field names used in the ProtoBuf definition. pub fn from_str_name(value: &str) -> ::core::option::Option<Self> { match value { "NORMAL" => Some(Self::Normal), "SEAM_CARVE" => Some(Self::SeamCarve), _ => None, } } } #[derive( Clone, Copy, Debug, PartialEq, Eq, Hash, PartialOrd, Ord, ::prost::Enumeration )] #[repr(i32)] pub enum SampleFilter { Undefined = 0, Nearest = 1, Triangle = 2, CatmullRom = 3, Gaussian = 4, Lanczos3 = 5, } impl SampleFilter { /// String value of the enum field names used in the ProtoBuf definition. /// /// The values are not transformed in any way and thus are considered stable /// (if the ProtoBuf definition does not change) and safe for programmatic use. pub fn as_str_name(&self) -> &''static str { match self { SampleFilter::Undefined => "UNDEFINED", SampleFilter::Nearest => "NEAREST", SampleFilter::Triangle => "TRIANGLE", SampleFilter::CatmullRom => "CATMULL_ROM", SampleFilter::Gaussian => "GAUSSIAN", SampleFilter::Lanczos3 => "LANCZOS3", } } /// Creates an enum from field names used in the ProtoBuf definition. pub fn from_str_name(value: &str) -> ::core::option::Option<Self> { match value { "UNDEFINED" => Some(Self::Undefined), "NEAREST" => Some(Self::Nearest), "TRIANGLE" => Some(Self::Triangle), "CATMULL_ROM" => Some(Self::CatmullRom), "GAUSSIAN" => Some(Self::Gaussian), "LANCZOS3" => Some(Self::Lanczos3), _ => None, } } } } /// 处理图片截取 #[allow(clippy::derive_partial_eq_without_eq)] #[derive(Clone, PartialEq, ::prost::Message)] pub struct Crop { #[prost(uint32, tag = "1")] pub x1: u32, #[prost(uint32, tag = "2")] pub y1: u32, #[prost(uint32, tag = "3")] pub x2: u32, #[prost(uint32, tag = "4")] pub y2: u32, } /// 处理水平翻转 #[allow(clippy::derive_partial_eq_without_eq)] #[derive(Clone, PartialEq, ::prost::Message)] pub struct Fliph {} /// 处理垂直翻转 #[allow(clippy::derive_partial_eq_without_eq)] #[derive(Clone, PartialEq, ::prost::Message)] pub struct Flipv {} /// 处理对比度 #[allow(clippy::derive_partial_eq_without_eq)] #[derive(Clone, PartialEq, ::prost::Message)] pub struct Contrast { #[prost(float, tag = "1")] pub contrast: f32, } /// 处理滤镜 #[allow(clippy::derive_partial_eq_without_eq)] #[derive(Clone, PartialEq, ::prost::Message)] pub struct Filter { #[prost(enumeration = "filter::Filter", tag = "1")] pub filter: i32, } /// Nested message and enum types in `Filter`. pub mod filter { #[derive( Clone, Copy, Debug, PartialEq, Eq, Hash, PartialOrd, Ord, ::prost::Enumeration )] #[repr(i32)] pub enum Filter { Unspecified = 0, Oceanic = 1, Islands = 2, /// more: <https://docs.rs/photon-rs/0.3.1/photon_rs/filters/fn.filter.html> Marine = 3, } impl Filter { /// String value of the enum field names used in the ProtoBuf definition. /// /// The values are not transformed in any way and thus are considered stable /// (if the ProtoBuf definition does not change) and safe for programmatic use. pub fn as_str_name(&self) -> &''static str { match self { Filter::Unspecified => "UNSPECIFIED", Filter::Oceanic => "OCEANIC", Filter::Islands => "ISLANDS", Filter::Marine => "MARINE", } } /// Creates an enum from field names used in the ProtoBuf definition. pub fn from_str_name(value: &str) -> ::core::option::Option<Self> { match value { "UNSPECIFIED" => Some(Self::Unspecified), "OCEANIC" => Some(Self::Oceanic), "ISLANDS" => Some(Self::Islands), "MARINE" => Some(Self::Marine), _ => None, } } } } /// 处理水印 #[allow(clippy::derive_partial_eq_without_eq)] #[derive(Clone, PartialEq, ::prost::Message)] pub struct Watermark { #[prost(uint32, tag = "1")] pub x: u32, #[prost(uint32, tag = "2")] pub y: u32, } /// 一个 spec 可以包含上述的处理方式之一 #[allow(clippy::derive_partial_eq_without_eq)] #[derive(Clone, PartialEq, ::prost::Message)] pub struct Spec { #[prost(oneof = "spec::Data", tags = "1, 2, 3, 4, 5, 6, 7")] pub data: ::core::option::Option<spec::Data>, } /// Nested message and enum types in `Spec`. pub mod spec { #[allow(clippy::derive_partial_eq_without_eq)] #[derive(Clone, PartialEq, ::prost::Oneof)] pub enum Data { #[prost(message, tag = "1")] Resize(super::Resize), #[prost(message, tag = "2")] Crop(super::Crop), #[prost(message, tag = "3")] Flipv(super::Flipv), #[prost(message, tag = "4")] Fliph(super::Fliph), #[prost(message, tag = "5")] Contrast(super::Contrast), #[prost(message, tag = "6")] Filter(super::Filter), #[prost(message, tag = "7")] Watermark(super::Watermark), } }
创建 src/pb/mod.rs
rust体验AI代码助手代码解读复制代码use base64::{decode_config, encode_config, URL_SAFE_NO_PAD}; use photon_rs::transform::SamplingFilter; use prost::Message; use std::convert::TryFrom; mod abi; // 声明 abi.rs pub use abi::*; impl ImageSpec { pub fn new(specs: Vec<Spec>) -> Self { Self { specs } } } // 让 ImageSpec 可以生成一个字符串 impl From<&ImageSpec> for String { fn from(image_spec: &ImageSpec) -> Self { let data = image_spec.encode_to_vec(); encode_config(data, URL_SAFE_NO_PAD) } } // 让 ImageSpec 可以通过一个字符串创建。比如 s.parse().unwrap() impl TryFrom<&str> for ImageSpec { type Error = anyhow::Error; fn try_from(value: &str) -> Result<Self, Self::Error> { let data = decode_config(value, URL_SAFE_NO_PAD)?; Ok(ImageSpec::decode(&data[..])?) } } // 辅助函数，photon_rs 相应的方法里需要字符串 impl filter::Filter { pub fn to_str(&self) -> Option<&''static str> { match self { filter::Filter::Unspecified => None, filter::Filter::Oceanic => Some("oceanic"), filter::Filter::Islands => Some("islands"), filter::Filter::Marine => Some("marine"), } } } // 在我们定义的 SampleFilter 和 photon_rs 的 SamplingFilter 间转换 impl From<resize::SampleFilter> for SamplingFilter { fn from(v: resize::SampleFilter) -> Self { match v { resize::SampleFilter::Undefined => SamplingFilter::Nearest, resize::SampleFilter::Nearest => SamplingFilter::Nearest, resize::SampleFilter::Triangle => SamplingFilter::Triangle, resize::SampleFilter::CatmullRom => SamplingFilter::CatmullRom, resize::SampleFilter::Gaussian => SamplingFilter::Gaussian, resize::SampleFilter::Lanczos3 => SamplingFilter::Lanczos3, } } } // 提供一些辅助函数，让创建一个 spec 的过程简单一些 impl Spec { pub fn new_resize_seam_carve(width: u32, height: u32) -> Self { Self { data: Some(spec::Data::Resize(Resize { width, height, rtype: resize::ResizeType::SeamCarve as i32, filter: resize::SampleFilter::Undefined as i32, })), } } pub fn new_resize(width: u32, height: u32, filter: resize::SampleFilter) -> Self { Self { data: Some(spec::Data::Resize(Resize { width, height, rtype: resize::ResizeType::Normal as i32, filter: filter as i32, })), } } pub fn new_filter(filter: filter::Filter) -> Self { Self { data: Some(spec::Data::Filter(Filter { filter: filter as i32, })), } } pub fn new_watermark(x: u32, y: u32) -> Self { Self { data: Some(spec::Data::Watermark(Watermark { x, y })), } } } #[cfg(test)] mod tests { use super::*; use std::borrow::Borrow; use std::convert::TryInto; #[test] fn encoded_spec_could_be_decoded() { let spec1 = Spec::new_resize(600, 600, resize::SampleFilter::CatmullRom); let spec2 = Spec::new_filter(filter::Filter::Marine); let image_spec = ImageSpec::new(vec![spec1, spec2]); let s: String = image_spec.borrow().into(); assert_eq!(image_spec, s.as_str().try_into().unwrap()); } }
在这个文件中，我们引入 abi.rs，并且撰写一些辅助函数。这些辅助函数主要是为了，让 ImageSpec 可以被方便地转换成字符串，或者从字符串中恢复。
测试
cargo test 测试
bash体验AI代码助手代码解读复制代码thumbor on master [?] is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base ➜ cargo test Compiling thumbor v0.1.0 (/Users/qiaopengjun/Code/rust/thumbor) Finished test [unoptimized + debuginfo] target(s) in 1.47s Running unittests src/main.rs (target/debug/deps/thumbor-65758f02ef3fc46d) running 1 test test pb::tests::encoded_spec_could_be_decoded ... ok test result: ok. 1 passed; 0 failed; 0 ignored; 0 measured; 0 filtered out; finished in 0.00s thumbor on main is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base ➜
引入 HTTP 服务器
main.rs
rust体验AI代码助手代码解读复制代码use axum::{extract::Path, http::StatusCode, routing::get, Router}; use percent_encoding::percent_decode_str; use serde::Deserialize; use std::convert::TryInto; // 引入 protobuf 生成的代码，我们暂且不用太关心他们 mod pb; use pb::*; // 参数使用 serde 做 Deserialize，axum 会自动识别并解析 #[derive(Deserialize)] struct Params { spec: String, url: String, } #[tokio::main] async fn main() { // 初始化 tracing tracing_subscriber::fmt::init(); // 构建路由 let app = Router::new() // `GET /image` 会执行 generate 函数，并把 spec 和 url 传递过去 .route("/image/:spec/:url", get(generate)); // 运行 web 服务器 let addr = "127.0.0.1:3000".parse().unwrap(); tracing::debug!("listening on {}", addr); axum::Server::bind(&addr) .serve(app.into_make_service()) .await .unwrap(); } // 目前我们就只把参数解析出来 async fn generate(Path(Params { spec, url }): Path<Params>) -> Result<String, StatusCode> { let url = percent_decode_str(&url).decode_utf8_lossy(); let spec: ImageSpec = spec .as_str() .try_into() .map_err(|_| StatusCode::BAD_REQUEST)?; Ok(format!("url: {}\n spec: {:#?}", url, spec)) }
使用 cargo run 运行服务器。然后HTTPie 测试（eat your own dog food）：
bash体验AI代码助手代码解读复制代码thumbor on main is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base ➜ cargo run Compiling thumbor v0.1.0 (/Users/qiaopengjun/Code/rust/thumbor) Finished dev [unoptimized + debuginfo] target(s) in 4.49s Running `target/debug/thumbor` httpie/pub on main is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base ➜ ./httpie get "http://localhost:3000/image/CgoKCAjYBBCgBiADCgY6BAgUEBQKBDICCAM/https%3A%2F%2Fimages%2Epexels%2Ecom%2Fphotos%2F2470905%2Fpexels%2Dphoto%2D2470905%2Ejpeg%3Fauto%3Dcompress%26cs%3Dtinysrgb%26dpr%3D2%26h%3D750%26w%3D1260" HTTP/1.1 200 OK content-type: "text/plain; charset=utf-8" content-length: "901" date: "Fri, 30 Jun 2023 15:50:46 GMT" url: https://images.pexels.com/photos/2470905/pexels-photo-2470905.jpeg?auto=compress&cs=tinysrgb&dpr=2&h=750&w=1260 spec: ImageSpec { specs: [ Spec { data: Some( Resize( Resize { width: 600, height: 800, rtype: Normal, filter: CatmullRom, }, ), ), }, Spec { data: Some( Watermark( Watermark { x: 20, y: 20, }, ), ), }, Spec { data: Some( Filter( Filter { filter: Marine, }, ), ), }, ], } httpie/pub on main is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base ➜
Git 代码提交
bash体验AI代码助手代码解读复制代码thumbor on master [?] is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base ➜ echo "# thumbor" >> README.md thumbor on master [?] is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base ➜ git add . thumbor on master [+] is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base ➜ git commit -m "first commit" [master（根提交） 679d01f] first commit 9 files changed, 3256 insertions(+) create mode 100644 .gitignore create mode 100644 Cargo.lock create mode 100644 Cargo.toml create mode 100644 README.md create mode 100644 abi.proto create mode 100644 build.rs create mode 100644 src/main.rs create mode 100644 src/pb/abi.rs create mode 100644 src/pb/mod.rs thumbor on master is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base ➜ git branch -M main thumbor on main is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base ➜ git remote add origin git@github.com:qiaopengjun5162/thumbor.git thumbor on main is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base ➜ git push -u origin main 枚举对象中: 13, 完成. 对象计数中: 100% (13/13), 完成. 使用 12 个线程进行压缩 压缩对象中: 100% (11/11), 完成. 写入对象中: 100% (13/13), 22.91 KiB | 7.64 MiB/s, 完成. 总共 13（差异 0），复用 0（差异 0），包复用 0 To github.com:qiaopengjun5162/thumbor.git * [new branch] main -> main 分支 ''main'' 设置为跟踪 ''origin/main''。 thumbor on main is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base took 16.5s ➜
获取源图并缓存
rust体验AI代码助手代码解读复制代码use anyhow::Result; use axum::{ extract::{Extension, Path}, http::{HeaderMap, HeaderValue, StatusCode}, routing::get, Router, }; use bytes::Bytes; use lru::LruCache; use percent_encoding::{percent_decode_str, percent_encode, NON_ALPHANUMERIC}; use serde::Deserialize; use std::num::NonZeroUsize; use std::{ collections::hash_map::DefaultHasher, convert::TryInto, hash::{Hash, Hasher}, sync::Arc, }; use tokio::sync::Mutex; use tower::ServiceBuilder; use tower_http::add_extension::AddExtensionLayer; use tracing::{info, instrument}; mod pb; use pb::*; #[derive(Deserialize)] struct Params { spec: String, url: String, } type Cache = Arc<Mutex<LruCache<u64, Bytes>>>; #[tokio::main] async fn main() { // 初始化 tracing tracing_subscriber::fmt::init(); let value = 1024; let non_zero_value = NonZeroUsize::new(value).expect("value must be non-zero"); let cache: Cache = Arc::new(Mutex::new(LruCache::new(non_zero_value))); // 构建路由 let app = Router::new() // `GET /` 会执行 .route("/image/:spec/:url", get(generate)) .layer( ServiceBuilder::new() .layer(AddExtensionLayer::new(cache)) .into_inner(), ); // 运行 web 服务器 let addr = "127.0.0.1:3000".parse().unwrap(); print_test_url("https://images.pexels.com/photos/1562477/pexels-photo-1562477.jpeg?auto=compress&cs=tinysrgb&dpr=3&h=750&w=1260"); info!("Listening on {}", addr); axum::Server::bind(&addr) .serve(app.into_make_service()) .await .unwrap(); } async fn generate( Path(Params { spec, url }): Path<Params>, Extension(cache): Extension<Cache>, ) -> Result<(HeaderMap, Vec<u8>), StatusCode> { let _spec: ImageSpec = spec .as_str() .try_into() .map_err(|_| StatusCode::BAD_REQUEST)?; let url: &str = &percent_decode_str(&url).decode_utf8_lossy(); let data = retrieve_image(&url, cache) .await .map_err(|_| StatusCode::BAD_REQUEST)?; // TODO: 处理图片 let mut headers = HeaderMap::new(); headers.insert("content-type", HeaderValue::from_static("image/jpeg")); Ok((headers, data.to_vec())) } #[instrument(level = "info", skip(cache))] async fn retrieve_image(url: &str, cache: Cache) -> Result<Bytes> { let mut hasher = DefaultHasher::new(); url.hash(&mut hasher); let key = hasher.finish(); let g = &mut cache.lock().await; let data = match g.get(&key) { Some(v) => { info!("Match cache {}", key); v.to_owned() } None => { info!("Retrieve url"); let resp = reqwest::get(url).await?; let data = resp.bytes().await?; g.put(key, data.clone()); data } }; Ok(data) } // 调试辅助函数 fn print_test_url(url: &str) { use std::borrow::Borrow; let spec1 = Spec::new_resize(500, 800, resize::SampleFilter::CatmullRom); let spec2 = Spec::new_watermark(20, 20); let spec3 = Spec::new_filter(filter::Filter::Marine); let image_spec = ImageSpec::new(vec![spec1, spec2, spec3]); let s: String = image_spec.borrow().into(); let test_image = percent_encode(url.as_bytes(), NON_ALPHANUMERIC).to_string(); println!("test url: http://localhost:3000/image/{}/{}", s, test_image); }
运行
bash体验AI代码助手代码解读复制代码thumbor on main [!] is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base took 2.7s ➜ RUST_LOG=info cargo run --quiet test url: http://localhost:3000/image/CgoKCAj0AxCgBiADCgY6BAgUEBQKBDICCAM/https%3A%2F%2Fimages%2Epexels%2Ecom%2Fphotos%2F1562477%2Fpexels%2Dphoto%2D1562477%2Ejpeg%3Fauto%3Dcompress%26cs%3Dtinysrgb%26dpr%3D3%26h%3D750%26w%3D1260 2023-06-30T16:26:31.587989Z INFO thumbor: Listening on 127.0.0.1:3000 2023-06-30T16:27:38.372733Z INFO retrieve_image{url="https://images.pexels.com/photos/1562477/pexels-photo-1562477.jpeg?auto=compress&cs=tinysrgb&dpr=3&h=750&w=1260"}: thumbor: Retrieve url
图片处理
我们创建 src/engine 目录，并添加 src/engine/mod.rs，在这个文件里添加对 trait 的定义：
bash体验AI代码助手代码解读复制代码thumbor on main is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base took 4.4s ➜ mkdir src/engine thumbor on main is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base ➜ touch src/engine/mod.rs thumbor on main [?] is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base ➜ thumbor on main [?] is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base ➜ touch src/engine/photon.rs
src/engine/mod.rs
rust体验AI代码助手代码解读复制代码use crate::pb::Spec; use image::ImageOutputFormat; mod photon; pub use photon::Photon; // Engine trait：未来可以添加更多的 engine，主流程只需要替换 engine pub trait Engine { // 对 engine 按照 specs 进行一系列有序的处理 fn apply(&mut self, specs: &[Spec]); // 从 engine 中生成目标图片，注意这里用的是 self，而非 self 的引用 fn generate(self, format: ImageOutputFormat) -> Vec<u8>; } // SpecTransform：未来如果添加更多的 spec，只需要实现它即可 pub trait SpecTransform<T> { // 对图片使用 op 做 transform fn transform(&mut self, op: T); }
src/engine/photon.rs
rust体验AI代码助手代码解读复制代码use super::{Engine, SpecTransform}; use crate::pb::*; use anyhow::Result; use bytes::Bytes; use image::{DynamicImage, ImageBuffer, ImageOutputFormat}; use lazy_static::lazy_static; use photon_rs::{ effects, filters, multiple, native::open_image_from_bytes, transform, PhotonImage, }; use std::convert::TryFrom; use std::io::Cursor; lazy_static! { // 预先把水印文件加载为静态变量 static ref WATERMARK: PhotonImage = { // 这里你需要把我 github 项目下的对应图片拷贝到你的根目录 // 在编译的时候 include_bytes! 宏会直接把文件读入编译后的二进制 let data = include_bytes!("../../rust-logo.png"); let watermark = open_image_from_bytes(data).unwrap(); transform::resize(&watermark, 64, 64, transform::SamplingFilter::Nearest) }; } // 我们目前支持 Photon engine pub struct Photon(PhotonImage); // 从 Bytes 转换成 Photon 结构 impl TryFrom<Bytes> for Photon { type Error = anyhow::Error; fn try_from(data: Bytes) -> Result<Self, Self::Error> { Ok(Self(open_image_from_bytes(&data)?)) } } impl Engine for Photon { fn apply(&mut self, specs: &[Spec]) { for spec in specs.iter() { match spec.data { Some(spec::Data::Crop(ref v)) => self.transform(v), Some(spec::Data::Contrast(ref v)) => self.transform(v), Some(spec::Data::Filter(ref v)) => self.transform(v), Some(spec::Data::Fliph(ref v)) => self.transform(v), Some(spec::Data::Flipv(ref v)) => self.transform(v), Some(spec::Data::Resize(ref v)) => self.transform(v), Some(spec::Data::Watermark(ref v)) => self.transform(v), // 对于目前不认识的 spec，不做任何处理 _ => {} } } } fn generate(self, format: ImageOutputFormat) -> Vec<u8> { image_to_buf(self.0, format) } } impl SpecTransform<&Crop> for Photon { fn transform(&mut self, op: &Crop) { let img = transform::crop(&mut self.0, op.x1, op.y1, op.x2, op.y2); self.0 = img; } } impl SpecTransform<&Contrast> for Photon { fn transform(&mut self, op: &Contrast) { effects::adjust_contrast(&mut self.0, op.contrast); } } impl SpecTransform<&Flipv> for Photon { fn transform(&mut self, _op: &Flipv) { transform::flipv(&mut self.0) } } impl SpecTransform<&Fliph> for Photon { fn transform(&mut self, _op: &Fliph) { transform::fliph(&mut self.0) } } impl SpecTransform<&Filter> for Photon { fn transform(&mut self, op: &Filter) { match filter::Filter::from_i32(op.filter) { Some(filter::Filter::Unspecified) => {} Some(f) => filters::filter(&mut self.0, f.to_str().unwrap()), _ => {} } } } impl SpecTransform<&Resize> for Photon { fn transform(&mut self, op: &Resize) { let img = match resize::ResizeType::from_i32(op.rtype).unwrap() { resize::ResizeType::Normal => transform::resize( &mut self.0, op.width, op.height, resize::SampleFilter::from_i32(op.filter).unwrap().into(), ), resize::ResizeType::SeamCarve => { transform::seam_carve(&mut self.0, op.width, op.height) } }; self.0 = img; } } impl SpecTransform<&Watermark> for Photon { fn transform(&mut self, op: &Watermark) { multiple::watermark(&mut self.0, &WATERMARK, op.x, op.y); } } // photon 库竟然没有提供在内存中对图片转换格式的方法，只好手工实现 fn image_to_buf(img: PhotonImage, format: ImageOutputFormat) -> Vec<u8> { let raw_pixels = img.get_raw_pixels(); let width = img.get_width(); let height = img.get_height(); let img_buffer = ImageBuffer::from_vec(width, height, raw_pixels).unwrap(); let dynimage = DynamicImage::ImageRgba8(img_buffer); let mut buffer = Cursor::new(Vec::with_capacity(32768)); dynimage.write_to(&mut buffer, format).unwrap(); buffer.into_inner() }
main.rs
把 engine 模块加入 main.rs，并引入 Photon：
TODO: 处理图片 Photon 引擎处理：
rust体验AI代码助手代码解读复制代码use anyhow::Result; use axum::{ extract::{Extension, Path}, http::{HeaderMap, HeaderValue, StatusCode}, routing::get, Router, }; use bytes::Bytes; use lru::LruCache; use percent_encoding::{percent_decode_str, percent_encode, NON_ALPHANUMERIC}; use serde::Deserialize; use std::num::NonZeroUsize; use std::{ collections::hash_map::DefaultHasher, convert::TryInto, hash::{Hash, Hasher}, sync::Arc, }; use tokio::sync::Mutex; use tower::ServiceBuilder; use tower_http::add_extension::AddExtensionLayer; use tracing::{info, instrument}; mod engine; use engine::{Engine, Photon}; use image::ImageOutputFormat; mod pb; use pb::*; #[derive(Deserialize)] struct Params { spec: String, url: String, } type Cache = Arc<Mutex<LruCache<u64, Bytes>>>; #[tokio::main] async fn main() { // 初始化 tracing tracing_subscriber::fmt::init(); let value = 1024; let non_zero_value = NonZeroUsize::new(value).expect("value must be non-zero"); let cache: Cache = Arc::new(Mutex::new(LruCache::new(non_zero_value))); // 构建路由 let app = Router::new() // `GET /` 会执行 .route("/image/:spec/:url", get(generate)) .layer( ServiceBuilder::new() .layer(AddExtensionLayer::new(cache)) .into_inner(), ); // 运行 web 服务器 let addr = "127.0.0.1:3000".parse().unwrap(); print_test_url("https://images.pexels.com/photos/1562477/pexels-photo-1562477.jpeg?auto=compress&cs=tinysrgb&dpr=3&h=750&w=1260"); info!("Listening on {}", addr); axum::Server::bind(&addr) .serve(app.into_make_service()) .await .unwrap(); } async fn generate( Path(Params { spec, url }): Path<Params>, Extension(cache): Extension<Cache>, ) -> Result<(HeaderMap, Vec<u8>), StatusCode> { let spec: ImageSpec = spec .as_str() .try_into() .map_err(|_| StatusCode::BAD_REQUEST)?; let url: &str = &percent_decode_str(&url).decode_utf8_lossy(); let data = retrieve_image(&url, cache) .await .map_err(|_| StatusCode::BAD_REQUEST)?; // 使用 image engine 处理 let mut engine: Photon = data .try_into() .map_err(|_| StatusCode::INTERNAL_SERVER_ERROR)?; engine.apply(&spec.specs); let image = engine.generate(ImageOutputFormat::Jpeg(85)); info!("Finished processing: image size {}", image.len()); let mut headers = HeaderMap::new(); headers.insert("content-type", HeaderValue::from_static("image/jpeg")); Ok((headers, image)) } #[instrument(level = "info", skip(cache))] async fn retrieve_image(url: &str, cache: Cache) -> Result<Bytes> { let mut hasher = DefaultHasher::new(); url.hash(&mut hasher); let key = hasher.finish(); let g = &mut cache.lock().await; let data = match g.get(&key) { Some(v) => { info!("Match cache {}", key); v.to_owned() } None => { info!("Retrieve url"); let resp = reqwest::get(url).await?; let data = resp.bytes().await?; g.put(key, data.clone()); data } }; Ok(data) } // 调试辅助函数 fn print_test_url(url: &str) { use std::borrow::Borrow; let spec1 = Spec::new_resize(500, 800, resize::SampleFilter::CatmullRom); let spec2 = Spec::new_watermark(20, 20); let spec3 = Spec::new_filter(filter::Filter::Marine); let image_spec = ImageSpec::new(vec![spec1, spec2, spec3]); let s: String = image_spec.borrow().into(); let test_image = percent_encode(url.as_bytes(), NON_ALPHANUMERIC).to_string(); println!("test url: http://localhost:3000/image/{}/{}", s, test_image); }
用 cargo build --release 编译 thumbor 项目，然后打开日志运行：
bash体验AI代码助手代码解读复制代码thumbor on main [!?] is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base took 1m 24.7s ➜ cargo build --release thumbor on main [!?] is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base took 40.9s ➜ RUST_LOG=info target/release/thumbor
总计代码行数
bash体验AI代码助手代码解读复制代码thumbor on main [!?] is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base took 2m 34.1s ➜ tokei src/main.rs src/engine/* src/pb/mod.rs =============================================================================== Language Files Lines Code Comments Blanks =============================================================================== Rust 4 390 317 23 50 =============================================================================== Total 4 390 317 23 50 =============================================================================== thumbor on main [!?] is 📦 0.1.0 via 🦀 1.70.0 via 🅒 base ➜
学习Rust要打破很多自己原有的认知，去拥抱新的思想和概念。但是只要多写多思考，时间长了，理解起来就是水到渠成的事。
总结
通过本文的实战演练，我们成功实现了一个功能强大的图片处理服务器，涵盖了从项目搭建、Protobuf 定义到图片处理和缓存优化的完整开发流程。Rust 的高性能和内存安全特性使得它非常适合开发此类高并发、低延迟的服务。以下是项目的几个关键收获：
- 模块化设计：通过定义 Engine 和 SpecTransform trait，代码结构清晰，易于扩展新的图片处理引擎或功能。
- 异步编程：使用 Axum 和 Tokio 构建高效的异步 HTTP 服务，结合 LRU 缓存优化图片加载性能。
- Protobuf 集成：通过 Protobuf 定义图片处理规格，实现了灵活且可序列化的参数传递。
- 实践 Rust 特性：项目中使用了 Rust 的 trait、宏、异步运行时等特性，帮助开发者深入理解 Rust 的现代编程范式。
无论你是想学习 Rust 的异步编程，还是希望构建一个高性能的图片处理服务，这个项目都提供了一个实用的起点。你可以 fork 项目代码（GitHub 仓库），尝试添加更多功能，比如支持其他图片格式或新的滤镜效果。Rust 的学习曲线虽然陡峭，但通过这样的实战项目，你将逐渐掌握其强大之处。
