Sending Protocol Buffer encoded message from Python Server to Java Client

Question

I'm writing a little server that uses protocol buffer to encode some data.

1. TCP Socket is opened between Android Client and Python Server

2. Android Client sends string for processing as normal newline delimited utf-8.

3. Python Server does some processing to generate a response, which gives an Array of Int Arrays: [[int]]. This is encoded in the protocol buffer file:

syntax = "proto2";

package tts;

message SentenceContainer {
    repeated Sentence sentence = 1;
}

message Sentence {
    repeated uint32 phonemeSymbol = 1;
}

It gets loaded into this structure and sent as follows...

container = ttsSentences_pb2.SentenceContainer()
for sentence in input_sentences:
    phonemes = container.sentence.add()
    # Add all the phonemes to the phoneme list
    phonemes.phonemeSymbol.extend(processor.text_to_sequence(sentence))


payload = container.SerializeToString()
client.send(payload)

4. Android Client receives Protocol Buffer encoded message and tries to decode.

This is where I'm stuck...

# I get the InputStream when the TCP connection is first opened
bufferIn = socket.getInputStream();
TtsSentences.SentenceContainer sentences = TtsSentences.SentenceContainer.parseDelimitedFrom(bufferIn);

When receiving the message the client gets this exception:

E/TCP: Server Error
    com.google.protobuf.InvalidProtocolBufferException: Protocol message end-group tag did not match expected tag.
        at com.google.protobuf.CodedInputStream.checkLastTagWas(CodedInputStream.java:164)
        at com.google.protobuf.GeneratedMessageLite.parsePartialDelimitedFrom(GeneratedMessageLite.java:1527)
        at com.google.protobuf.GeneratedMessageLite.parseDelimitedFrom(GeneratedMessageLite.java:1496)
        at com.tensorspeech.tensorflowtts.TtsSentences$SentenceContainer.parseDelimitedFrom(TtsSentences.java:221)
        at com.tensorspeech.tensorflowtts.network.PersistentTcpClient.run(PersistentTcpClient.java:100)
        at com.tensorspeech.tensorflowtts.MainActivity.lambda$onCreate$0$MainActivity(MainActivity.java:71)
        at com.tensorspeech.tensorflowtts.-$$Lambda$MainActivity$NTUE8bAusaoF3UGkWb7-Jt806BY.run(Unknown Source:2)
        at java.lang.Thread.run(Thread.java:919)

I already know this problem is caused because Protocol buffer is not self delimiting, but I'm not sure how I'm supposed to properly delimit it. I've tried adding a newline client.send(payload + b'\\n') , and adding in the PB size in bytes to the beginning of the payload client.send(container.ByteSize().to_bytes(2, 'little') + payload) , but am not sure how to proceed.

It's a shame there's no documentation on how to use Protocol Buffer over TCP Sockets in Java...

Answer 1

OK, I worked this out...

In the case where you have a short-lived connection, the socket closing would signify the end of the payload, so no extra logic is required.

In my case, I have a long-lived connection, so closing the socket to signify the end of the payload wouldn't work.

With a Java Client & Server, you could get around this by using:

MessageLite.writeDelimitedTo(OutputStream)

then on the recipient side:

MessageLite.parseDelimitedFrom(InputStream) .

Easy enough...

But in the Python API, there is no writeDelimitedTo() function. So instead we must recreate what writeDelimitedTo() is doing. Fortunately, it's simple. It simply adds a _VarintBytes equal to the payload size to the beginning of the message!

client, _ = socket.accept()
payload = your_PB_item.SerializeToString()
size = payload.ByteSize()
client.send(_VarintBytes(size) + payload)

Then on the Java recipient side...

bufferIn = socket.getInputStream();
yourPbItem message;

if ((message = yourPbItem.parseDelimitedFrom(bufferIn)) != null) {
    // Do stuff :)
}

This way, your protocol buffer library knows exactly how many bytes to read, and then to stop caring about the InputStream, rather than sitting listening indefinitely.