如何在 AWS Lambda 上讀取和寫入二維碼

安裝

本文將使用 S3 儲存桶，因此需要AWSSDK.S3包。

立即開始在您的專案中使用 IronQR，享受免費試用。

第一步：

免費開始

建立 AWS Lambda 項目

使用 Visual Studio，建立容器化的 AWS Lambda 函數非常簡單：

• 安裝適用於 Visual Studio 的 AWS 工具包
• 選擇"AWS Lambda 專案（.NET Core - C#）"
• 選擇".NET 8（容器映像）"藍圖，然後選擇"完成"。

！選擇容器影像

新增包依賴項

.NET 8 中的 IronQR 函式庫可在 AWS Lambda 上執行，無需額外的相依性。 若要進行配置，請如下所示修改專案的 Dockerfile：

FROM public.ecr.aws/lambda/dotnet:8

# Install necessary packages and update repositories
RUN dnf update -y

WORKDIR /var/task

# This COPY command copies the .NET Lambda project's build artifacts from the host machine into the image. 
# The source of the COPY should match where the .NET Lambda project publishes its build artifacts. If the Lambda function is being built 
# with the AWS .NET Lambda Tooling, the `--docker-host-build-output-dir` switch controls where the .NET Lambda project
# will be built. The .NET Lambda project templates default to having `--docker-host-build-output-dir`
# set in the aws-lambda-tools-defaults.json file to "bin/Release/lambda-publish".
#
# Alternatively, Docker multi-stage build could be used to build the .NET Lambda project inside the image.
# For more information on this approach, check out the project's README.md file.
COPY "bin/Release/lambda-publish"  .

修改函數處理程序程式碼

此範例產生一個二維碼，將其上傳到 S3 儲存桶，並讀取新產生的二維碼。

檔案路徑在 IronQrNuget 目錄中指定，檔案名稱使用全域唯一識別碼 (GUID)。 Write方法根據提供的值產生二維碼，然後將產生的 JPG 位元組數組傳遞給Read方法以讀取二維碼。 這證明該 AWS Lambda 函數能夠讀取二維碼。

using Amazon.Lambda.Core;
using Amazon.S3;
using Amazon.S3.Model;
using IronQr;

// Assembly attribute to enable the Lambda function's JSON input to be converted into a .NET class.
[assembly: LambdaSerializer(typeof(Amazon.Lambda.Serialization.SystemTextJson.DefaultLambdaJsonSerializer))]

namespace IronQrNuGetAwsLambda
{
    public class Function
    {
        private static readonly IAmazonS3 _s3Client = new AmazonS3Client(Amazon.RegionEndpoint.APSoutheast1);

        /// <summary>
        /// Main handler for AWS Lambda
        /// </summary>
        /// <param name="context">The ILambdaContext that provides methods for logging and describing the Lambda environment.</param>
        /// <returns></returns>
        public async Task FunctionHandler(ILambdaContext context)
        {
            // Set the license key for IronQR
            IronQr.License.LicenseKey = "IronQR-MYLICENSE-KEY-1EF01";

            string bucketName = "deploymenttestbucket";
            string objectKey = $"IronQrNuget/{Guid.NewGuid()}.png";

            try
            {
                // Create a QR code with the content "12345"
                var myQr = QrWriter.Write("12345");

                context.Logger.LogLine("QR created.");

                // Upload the JPG to S3
                await UploadJpgToS3Async(bucketName, objectKey, myQr.Save().ExportBytesAsJpg());

                context.Logger.LogLine($"QR uploaded successfully to {bucketName}/{objectKey}");

                // Read the QR code
                QrImageInput imageInput = new QrImageInput(myQr.Save());
                QrReader reader = new QrReader();
                var resultFromByte = reader.Read(imageInput);

                foreach (var item in resultFromByte)
                {
                    // Log the read value
                    context.Logger.LogLine($"QR value is = {item.Value}");
                }
            }
            catch (Exception e)
            {
                context.Logger.LogLine($"[ERROR] FunctionHandler: {e.Message}");
            }
        }

        // Function to upload the JPG file to S3
        private async Task UploadJpgToS3Async(string bucketName, string objectKey, byte[] jpgBytes)
        {
            using (var memoryStream = new MemoryStream(jpgBytes))
            {
                var request = new PutObjectRequest
                {
                    BucketName = bucketName,
                    Key = objectKey,
                    InputStream = memoryStream,
                    ContentType = "image/jpg",
                };

                await _s3Client.PutObjectAsync(request);
            }
        }
    }
}

using Amazon.Lambda.Core;
using Amazon.S3;
using Amazon.S3.Model;
using IronQr;

// Assembly attribute to enable the Lambda function's JSON input to be converted into a .NET class.
[assembly: LambdaSerializer(typeof(Amazon.Lambda.Serialization.SystemTextJson.DefaultLambdaJsonSerializer))]

namespace IronQrNuGetAwsLambda
{
    public class Function
    {
        private static readonly IAmazonS3 _s3Client = new AmazonS3Client(Amazon.RegionEndpoint.APSoutheast1);

        /// <summary>
        /// Main handler for AWS Lambda
        /// </summary>
        /// <param name="context">The ILambdaContext that provides methods for logging and describing the Lambda environment.</param>
        /// <returns></returns>
        public async Task FunctionHandler(ILambdaContext context)
        {
            // Set the license key for IronQR
            IronQr.License.LicenseKey = "IronQR-MYLICENSE-KEY-1EF01";

            string bucketName = "deploymenttestbucket";
            string objectKey = $"IronQrNuget/{Guid.NewGuid()}.png";

            try
            {
                // Create a QR code with the content "12345"
                var myQr = QrWriter.Write("12345");

                context.Logger.LogLine("QR created.");

                // Upload the JPG to S3
                await UploadJpgToS3Async(bucketName, objectKey, myQr.Save().ExportBytesAsJpg());

                context.Logger.LogLine($"QR uploaded successfully to {bucketName}/{objectKey}");

                // Read the QR code
                QrImageInput imageInput = new QrImageInput(myQr.Save());
                QrReader reader = new QrReader();
                var resultFromByte = reader.Read(imageInput);

                foreach (var item in resultFromByte)
                {
                    // Log the read value
                    context.Logger.LogLine($"QR value is = {item.Value}");
                }
            }
            catch (Exception e)
            {
                context.Logger.LogLine($"[ERROR] FunctionHandler: {e.Message}");
            }
        }

        // Function to upload the JPG file to S3
        private async Task UploadJpgToS3Async(string bucketName, string objectKey, byte[] jpgBytes)
        {
            using (var memoryStream = new MemoryStream(jpgBytes))
            {
                var request = new PutObjectRequest
                {
                    BucketName = bucketName,
                    Key = objectKey,
                    InputStream = memoryStream,
                    ContentType = "image/jpg",
                };

                await _s3Client.PutObjectAsync(request);
            }
        }
    }
}

增加記憶體和超時

Lambda 函數的記憶體分配取決於文件的大小和同時處理的文件數量。 首先，在aws-lambda-tools-defaults.json中將記憶體設定為 512 MB，逾時設定為 300 秒。

"function-memory-size" : 512,
"function-timeout" : 300

如果記憶體不足，程式將引發錯誤："運行時錯誤退出：訊號：已終止"。增加記憶體大小可以幫助解決此問題。 如需進一步指導，請查看故障排除文章： AWS Lambda - 執行時間退出訊號：已終止。

發布

要在 Visual Studio 中發布，只需右鍵單擊項目，然後選擇"發佈到 AWS Lambda..." 然後，配置所需的設定。 如需了解更多信息，請訪問AWS 網站。

試試看！

您可以透過Lambda 控制台或 Visual Studio 啟動 Lambda 函數。