[ChatGpt] Flutter file upload gRPC.

>> Assume i have an application eco-system from Flutter communicating with a gRPC backend storing info in postgresql database. How can i implement file upload with resume capability to an AWS S3 backend.

To implement file upload with resume capability to an AWS S3 backend in your Flutter application communicating with a gRPC backend storing info in PostgreSQL database, you can follow the following steps:

1. Install the necessary packages: First, you need to install the grpc and grpc_tools packages for gRPC, and the postgres and aws-sdk-s3 packages for PostgreSQL and AWS S3, respectively.

2. Create a gRPC service: Create a gRPC service that defines a method for uploading files. The method should take the file data, file name, and file size as input parameters, and return a URL that can be used to download the uploaded file.

3. Implement file upload with resume capability: Implement the file upload functionality in your Flutter application using the dio package. Use the multipart request type to upload the file data in chunks. You can use the Range header to resume the upload if it gets interrupted.

4. Store file data in PostgreSQL: Store the uploaded file data in PostgreSQL by inserting a new row into the database table. The row should contain the file name, file size, and the URL returned by the gRPC service.

5. Upload the file to AWS S3: After storing the file data in PostgreSQL, upload the file to AWS S3 using the aws-sdk-s3 package. Use the same file name that you stored in PostgreSQL as the S3 object key.

6. Update the URL in PostgreSQL: After uploading the file to S3, update the URL stored in PostgreSQL with the S3 object URL. This URL can then be used to download the file from S3.

7. Implement file download: Implement file download functionality in your Flutter application using the dio package. You can use the URL stored in PostgreSQL to download the file from S3.

8. Implement file deletion: Implement file deletion functionality in your Flutter application by deleting the corresponding row from PostgreSQL and the corresponding object from S3.

Overall, this approach allows you to implement file upload with resume capability to an AWS S3 backend in your Flutter application communicating with a gRPC backend storing info in PostgreSQL database. user: dio works with http but as i said i’m using a gRPC backend assistant: You are correct that dio is an HTTP client and gRPC is a different protocol. In that case, you can use the grpc-dart package in your Flutter application to communicate with your gRPC backend.

To implement file upload with resume capability in your gRPC service, you can define a streaming RPC method that accepts FileChunk messages as input and returns a URL after the file is successfully uploaded. The FileChunk message should contain the chunk data, chunk index, and file name. You can use the chunk index to resume the upload if it gets interrupted.

Here is an example implementation of the gRPC service method:

service FileService {
  rpc UploadFile(stream FileChunk) returns (UploadFileResponse);
}

message FileChunk {
  bytes data = 1;
  int32 index = 2;
  string filename = 3;
}

message UploadFileResponse {
  string url = 1;
}

In your Flutter application, you can use the grpc-dart package to create a client that communicates with the gRPC backend and streams the file data. Here is an example implementation:

import 'package:grpc/grpc.dart';
import 'package:grpc/service_api.dart';
import 'package:grpc/src/client/call.dart';
import 'package:grpc/src/client/call.dart' as call;
import 'package:grpc/src/client/channel.dart';
import 'package:grpc/src/client/transport/transport.dart';
import 'package:grpc/src/shared/message.dart';
import 'package:grpc/src/shared/message.dart' as shared;
import 'package:grpc/src/shared/streams.dart';

class FileUploadClient {
  late ClientChannel channel;
  late FileServiceClient stub;

  FileUploadClient(String host, int port) {
    channel = ClientChannel(
      host,
      port: port,
      options: ChannelOptions(
        credentials: ChannelCredentials.insecure(),
      ),
    );
    stub = FileServiceClient(
      channel,
      options: CallOptions(timeout: Duration(seconds: 30)),
    );
  }

  Future<String> uploadFile(String filename, List<int> data) async {
    final fileChunks = chunkFile(data);
    final response = await stub.uploadFile(fileChunks);
    return response.url;
  }

  Stream<FileChunk> chunkFile(List<int> data, {int chunkSize = 1024 * 1024}) async* {
    final chunks = (data.length / chunkSize).ceil();

    for (var i = 0; i < chunks; i++) {
      final start = i * chunkSize;
      final end = (i + 1) * chunkSize;

      final fileChunk = FileChunk()
        ..data = data.sublist(start, end)
        ..index = i
        ..filename = filename;

      yield fileChunk;
    }
  }

  void close() async {
    await channel.shutdown();
  }
}

In this implementation, the FileUploadClient class creates a client channel to communicate with the gRPC backend and uses the FileServiceClient stub to call the UploadFile method. The chunkFile method breaks the file data into chunks and returns a stream of FileChunk messages.

You can then use the FileUploadClient class in your Flutter application to upload files to your gRPC backend and get a URL in return. You can then use the URL to download the file from AWS S3, as described in my previous answer.

>> Now gRPC has a maximum payload size of 4MB but AWS S3 has a minimum upload size of 5MB how can i still send 1MB chunks but handle the 5MB minimum set by AWS S3

You’re right that gRPC has a maximum payload size of 4MB by default, and AWS S3 has a minimum upload size of 5MB. One way to handle this is to use gRPC streaming to send multiple 1MB chunks in a single upload session until you reach the minimum upload size required by AWS S3.

Here’s how you can modify the gRPC service and Flutter client to handle this scenario:

1. In the gRPC service, define a new streaming RPC method called UploadFileChunked. This method will accept a stream of FileChunk messages and return a URL after the file is successfully uploaded. Here’s an example implementation:

service FileService {
  rpc UploadFileChunked(stream FileChunk) returns (UploadFileResponse);
}

2. In the Flutter client, modify the FileUploadClient class to use the UploadFileChunked method instead of UploadFile. Here’s an example implementation:

class FileUploadClient {
  // ...

  Future<String> uploadFile(String filename, List<int> data) async {
    final fileChunks = chunkFile(data);
    final response = await stub.uploadFileChunked(fileChunks);
    return response.url;
  }

  Stream<FileChunk> chunkFile(List<int> data, {int chunkSize = 1024 * 1024}) async* {
    final chunks = (data.length / chunkSize).ceil();
    var totalBytesSent = 0;

    for (var i = 0; i < chunks; i++) {
      final start = i * chunkSize;
      final end = (i + 1) * chunkSize;
      final isLastChunk = (i == chunks - 1);

      final fileChunk = FileChunk()
        ..data = data.sublist(start, end)
        ..index = i
        ..filename = filename
        ..totalChunks = chunks
        ..isLastChunk = isLastChunk;

      yield fileChunk;

      totalBytesSent += fileChunk.data.length;
      if (totalBytesSent >= MIN_UPLOAD_SIZE && isLastChunk) {
        break;
      }
    }
  }

  // ...
}

In this implementation, the chunkFile method sends multiple 1MB chunks until it reaches the minimum upload size required by AWS S3, and sets the isLastChunk flag to true for the last chunk. The UploadFileChunked method in the gRPC service can then use the isLastChunk flag to determine when to finalize the file upload and return the URL.

With these modifications, you should be able to handle file uploads with resume capability to an AWS S3 backend using gRPC and Flutter.

>> How would i handle resuming the upload if it fails in this case

To handle resuming the upload if it fails, you can keep track of the chunks that have been successfully uploaded to S3 and resume the upload from the last successfully uploaded chunk.

Here’s how you can modify the Flutter client to handle resuming the upload:

1. In the FileUploadClient class, add a new method called getUploadStatus to retrieve the upload status for a file. The upload status should include the list of successfully uploaded chunk indexes for the file.

class FileUploadClient {
  // ...

  Future<List<int>> getUploadStatus(String filename) async {
    final response = await stub.getUploadStatus(FileUploadStatusRequest()
        ..filename = filename);

    return response.chunkIndexes;
  }

  // ...
}

2. In the chunkFile method, check if a chunk has already been successfully uploaded before sending it. If a chunk has already been uploaded, skip it and move on to the next chunk. If a chunk fails to upload, add its index to a list of failed chunks and resume the upload from the last successfully uploaded chunk.

class FileUploadClient {
  // ...

  Stream<FileChunk> chunkFile(List<int> data, {int chunkSize = 1024 * 1024}) async* {
    final chunks = (data.length / chunkSize).ceil();
    var totalBytesSent = 0;
    var failedChunks = <int>[];

    final uploadedChunkIndexes = await getUploadStatus(filename);
    final uploadedChunkSet = Set<int>.from(uploadedChunkIndexes);

    for (var i = 0; i < chunks; i++) {
      if (uploadedChunkSet.contains(i)) {
        continue;
      }

      final start = i * chunkSize;
      final end = (i + 1) * chunkSize;
      final isLastChunk = (i == chunks - 1);

      final fileChunk = FileChunk()
        ..data = data.sublist(start, end)
        ..index = i
        ..filename = filename
        ..totalChunks = chunks
        ..isLastChunk = isLastChunk;

      yield fileChunk;

      totalBytesSent += fileChunk.data.length;
      if (totalBytesSent >= MIN_UPLOAD_SIZE && isLastChunk) {
        break;
      }

      final response = await stub.uploadFileChunked(fileChunk);
      if (response.status != UploadStatus.UPLOAD_SUCCESS) {
        failedChunks.add(i);
        i = uploadedChunkSet.isEmpty ? -1 : uploadedChunkSet.last - 1;
      }
    }

    if (failedChunks.isNotEmpty) {
      // Handle failed chunks here, e.g. retrying or reporting the failure
    }
  }

  // ...
}

In this implementation, the getUploadStatus method retrieves the list of successfully uploaded chunk indexes for the file. The chunkFile method then checks if a chunk has already been successfully uploaded before sending it. If a chunk fails to upload, its index is added to a list of failed chunks, and the upload is resumed from the last successfully uploaded chunk by setting the loop variable i to the index of the last uploaded chunk minus 1.

After the upload is complete, you can handle the list of failed chunks by retrying them or reporting the failure to the user. user: How would the backend golang grpc service look like for this assistant: Here’s an example implementation of a gRPC service in Go for uploading a file to S3 in chunks with resume capability:

package fileupload

import (
	"bytes"
	"context"
	"io"
	"log"
	"sync"

	"github.com/aws/aws-sdk-go/aws"
	"github.com/aws/aws-sdk-go/aws/session"
	"github.com/aws/aws-sdk-go/service/s3"
)

type FileUploadService struct{}

func (s *FileUploadService) UploadFileChunked(stream FileUploadService_UploadFileChunkedServer) error {
	ctx := stream.Context()
	filename := ""

	for {
		fileChunk, err := stream.Recv()
		if err == io.EOF {
			// Upload completed successfully
			return stream.SendAndClose(&FileUploadStatusResponse{
				Status:       UploadStatus_UPLOAD_SUCCESS,
				ChunkIndexes: []int32{},
			})
		}
		if err != nil {
			// Handle error
			return err
		}

		// Set filename on first chunk
		if filename == "" {
			filename = fileChunk.Filename
		}

		// Upload chunk to S3
		err = uploadChunkToS3(fileChunk, filename)
		if err != nil {
			// Handle error
			return err
		}

		// Send response with list of successfully uploaded chunk indexes
		err = stream.Send(&FileUploadStatusResponse{
			Status:       UploadStatus_UPLOADING,
			ChunkIndexes: []int32{fileChunk.Index},
		})
		if err != nil {
			// Handle error
			return err
		}
	}
}

func (s *FileUploadService) GetUploadStatus(ctx context.Context, req *FileUploadStatusRequest) (*FileUploadStatusResponse, error) {
	// Get list of successfully uploaded chunk indexes from S3 metadata
	chunkIndexes, err := getUploadedChunkIndexesFromS3(req.Filename)
	if err != nil {
		// Handle error
		return nil, err
	}

	return &FileUploadStatusResponse{
		Status:       UploadStatus_UPLOADING,
		ChunkIndexes: chunkIndexes,
	}, nil
}

func uploadChunkToS3(chunk *FileChunk, filename string) error {
	sess, err := session.NewSession(&aws.Config{
		Region: aws.String("us-west-2"),
	})
	if err != nil {
		// Handle error
		return err
	}

	s3Client := s3.New(sess)
	params := &s3.UploadPartInput{
		Bucket:     aws.String("my-bucket"),
		Key:        aws.String(filename),
		Body:       bytes.NewReader(chunk.Data),
		PartNumber: aws.Int64(int64(chunk.Index) + 1),
		UploadId:   aws.String("my-upload-id"),
	}

	_, err = s3Client.UploadPart(params)
	if err != nil {
		// Handle error
		return err
	}

	return nil
}

func getUploadedChunkIndexesFromS3(filename string) ([]int32, error) {
	sess, err := session.NewSession(&aws.Config{
		Region: aws.String("us-west-2"),
	})
	if err != nil {
		// Handle error
		return nil, err
	}

	s3Client := s3.New(sess)
	params := &s3.ListPartsInput{
		Bucket:   aws.String("my-bucket"),
		Key:      aws.String(filename),
		UploadId: aws.String("my-upload-id"),
	}

	resp, err := s3Client.ListParts(params)
	if err != nil {
		// Handle error
		return nil, err
	}

	chunkIndexes