如何在 AWS Lambda 上读取和写入二维码

安装

本文将使用 S3 存储桶，因此需要 AWSSDK.S3 包。

今天在您的项目中使用 IronQR，免费试用。

第一步：

免费开始

创建 AWS Lambda 项目

使用 Visual Studio 创建容器化的 AWS Lambda 是一个简单的过程：

• 安装适用于 Visual Studio 的 AWS 工具包
• 选择 'AWS Lambda Project (.NET Core - C#)'
• 选择 '.NET 8 (Container Image)' 蓝图，然后选择 '完成'。

添加包依赖项

.NET 8 中的 IronQR 库可在 AWS Lambda 上运行，无需额外的依赖项。 要进行配置，请按如下所示修改项目的 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 FunctionHandler 代码

本示例生成一个二维码，将其上传到 S3 存储桶，并读取新生成的二维码。

文件路径在 IronQrNuget 目录中指定，文件名使用全局唯一标识符 (GUID)。 Write方法根据提供的值生成二维码，然后将生成的 JPG 字节数组传递给Read方法以读取二维码。 这证明该 AWS Lambda 函数能够读取二维码。

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);
            }
        }
    }
}

增加内存和超时

Lambda 函数的内存分配取决于文档的大小和同时处理的文档数量。 首先，在aws-lambda-tools-defaults.json中将内存设置为 512 MB，超时设置为 300 秒。

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

如果内存不足，程序将引发错误："运行时错误退出：信号：终止"。增加内存大小可以帮助解决此问题。 如需进一步指导，请查看故障排除文章： AWS Lambda - 运行时退出信号：已终止。

发布

要在 Visual Studio 中发布，只需右键单击项目，然后选择"发布到 AWS Lambda..." 然后，配置所需的设置。 如需了解更多信息，请访问AWS 网站。

试一试！

您可以通过 Lambda 控制台 或通过 Visual Studio 激活 Lambda 函数。