How to use context to implement request flow limiting in Go

How to use context to implement request flow limiting in Go

When developing web applications, we often need to limit the frequency of access to certain resources or interfaces to avoid server overload or malicious attacks. In Go language, we can use context and go keywords to implement request flow limiting.

What is context?
In the Go language, context is a value passing mechanism across functions and Goroutines. It provides a way to pass request-specific values ​​across multiple function call chains and between different Goroutines. Context is usually used to pass request context information during request processing, such as request ID, user authentication information, etc.

Below we will demonstrate how to use context to implement the request current limiting function. We will use the golang.org/x/time/rate package to implement the token bucket algorithm. The token bucket algorithm is an algorithm used to control access frequency. It is based on a simple idea: the system puts tokens into the bucket at a fixed rate. Each request consumes one token. When there are no tokens in the bucket , subsequent requests will be restricted.

First, we need to introduce the required libraries:

import (
    "context"
    "fmt"
    "golang.org/x/time/rate"
    "net/http"
)

Then, we need to define a structure to store the requested current limiting rule and token bucket instance:

type RateLimiter struct {
    limiter *rate.Limiter
}

func NewRateLimiter(rateLimiter rate.Limit, burst int) *RateLimiter {
    return &RateLimiter{
        limiter: rate.NewLimiter(rateLimiter, burst),
    }
}

Next, in the processor function that handles the request, we can use context to limit the access frequency of the request:

func (rl *RateLimiter) handleRequest(w http.ResponseWriter, r *http.Request) {
    // 使用context.WithValue方法将RateLimiter的实例存放到context中
    ctx := context.WithValue(r.Context(), "rateLimiter", rl)

    // 检查当前请求是否达到了限流的阈值
    if rl.limiter.Allow() {
        // 允许访问
        fmt.Fprintf(w, "Hello, World!")
    } else {
        // 请求被限制
        http.Error(w, "Too Many Requests", http.StatusTooManyRequests)
    }
}

Finally, we need to create an http server and set the request processing function:

func main() {
    // 创建一个令牌桶实例，允许每秒钟产生10个令牌，桶的最大容量为20
    rateLimiter := NewRateLimiter(rate.Every(time.Second), 20)

    // 创建一个http服务器
    server := http.Server{
        Addr:    ":8080",
        Handler: http.HandlerFunc(rateLimiter.handleRequest),
    }

    // 启动服务器
    server.ListenAndServe()
}

Now, we have completed the function of using context to implement request flow limiting in Go. By using context, you can easily pass throttling rules and token bucket instances during request processing. If the request exceeds the current limit threshold, the appropriate HTTP status code and error message can be returned.

Summary
This article introduces how to use context to implement request current limiting function in Go language. By using context and token bucket algorithms, we can easily limit the frequency of access to specific resources or interfaces, thereby protecting the server from malicious requests.

Code example:

package main

import (
    "context"
    "fmt"
    "golang.org/x/time/rate"
    "net/http"
    "time"
)

type RateLimiter struct {
    limiter *rate.Limiter
}

func NewRateLimiter(rateLimiter rate.Limit, burst int) *RateLimiter {
    return &RateLimiter{
        limiter: rate.NewLimiter(rateLimiter, burst),
    }
}

func (rl *RateLimiter) handleRequest(w http.ResponseWriter, r *http.Request) {
    ctx := context.WithValue(r.Context(), "rateLimiter", rl)

    if rl.limiter.Allow() {
        fmt.Fprintf(w, "Hello, World!")
    } else {
        http.Error(w, "Too Many Requests", http.StatusTooManyRequests)
    }
}

func main() {
    rateLimiter := NewRateLimiter(rate.Every(time.Second), 20)

    server := http.Server{
        Addr:    ":8080",
        Handler: http.HandlerFunc(rateLimiter.handleRequest),
    }

    server.ListenAndServe()
}

I hope this article can help you implement the request current limiting function in Go language. Of course, this is just a simple example, and more complex business logic may be required in practice. However, by understanding the basic principles and using context, you can expand and optimize accordingly according to real scenarios. I wish you a happy development using Go language!

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