With the development of web applications, people have higher and higher demands for performance and code optimization. In this case, request monitoring and statistics become particularly important. This article will introduce how to use Golang and Gin framework to implement request statistics function.
Background
In web applications, encountering the following situations may cause performance problems:
- Frequent database queries
- Network Delay is too high
- Request timeout
- Too many concurrent requests
In this case, statistics and visual display of requests can help us quickly find problems and Take appropriate measures.
How to count requests
First, we need to define a middleware to record all request information passing through the server. For each request, we need to record the following information:
- Request path
- HTTP method
- Request start time
- Request end time
- Request duration
- Request status code
Using the Gin framework, we can define a function to execute this middleware. First, we need to execute the incoming handler and then log the request information:
func RequestStats() gin.HandlerFunc {
return func(c *gin.Context) {
t := time.Now()
c.Next()
latency := time.Since(t)
status := c.Writer.Status()
path := c.Request.URL.Path
method := c.Request.Method
log.Printf("[GIN] %s %s %d %v", method, path, status, latency)
}
}In this function, we use the log.Printf() function to print the request information. Now, we can add this middleware to the Gin engine:
router := gin.Default() router.Use(RequestStats())
In this way, we will record all request information when each request middleware is executed.
Visual request statistics
To display request statistics to users, we can use the web interface. In this case, the MVC (Model-View-Controller) design pattern is particularly suitable to use. In this case, the controller is responsible for handling all web requests and determining what data to retrieve from the model and how to present it. Views are responsible for presenting data.
The first step is to define the controller. The controller will read the request statistics stored in the file and pass it to the view for rendering:
func GetStats(c *gin.Context) {
data, err := ioutil.ReadFile("stats.txt")
if err != nil {
c.String(http.StatusInternalServerError, fmt.Sprintf("Error reading file: %v", err))
return
}
c.HTML(http.StatusOK, "stats.html", gin.H{
"title": "Request Statistics",
"data": string(data),
})
}In this controller method, we first read the request statistics from the file. The data is then passed as a string to the template engine for rendering.
The next step is to define the view. We can use HTML and CSS to create beautiful user interfaces:
<!DOCTYPE html>
<html>
<head>
<title>{{.title}}</title>
<style>
table {
border-collapse: collapse;
width: 100%;
}
th, td {
text-align: left;
padding: 8px;
}
th {
background-color: #4CAF50;
color: white;
}
tr:nth-child(even){background-color: #f2f2f2}
</style>
</head>
<body>
<h2 id="title">{{.title}}</h2>
<table>
<tr>
<th>HTTP Method</th>
<th>Request Path</th>
<th>Status Code</th>
<th>Latency</th>
</tr>
{{range split .data "
"}}
{{with split . " "}}
<tr>
<td>{{index . 0}}</td>
<td>{{index . 1}}</td>
<td>{{index . 2}}</td>
<td>{{index . 3}}</td>
</tr>
{{end}}
{{end}}
</table>
</body>
</html>In this template, we use HTML and CSS to create tables to display request data.
Finally, we need to associate the controller with a route and register it in the Gin engine:
router.GET("/stats", GetStats)Now, we have a request statistics system, and we can use the web page to display the statistical results displayed to the user.
Conclusion
Request statistics is an important web application function that can help us identify web applications by recording information such as HTTP methods, request paths, request status codes, request durations, etc. Common performance issues in . In this article, we use the Golang language and the Gin framework to implement request statistics, and use HTML and CSS to present the data. This implementation is relatively simple and easy to maintain, and can help us quickly locate problems with web applications.
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