cbor-rpc 1.0.0

An async-compatible CBOR-based RPC system

cbor-rpc

A lightweight, event-based RPC framework for Python using CBOR (optionally JSON) over various transport layers.

Table of Contents

• RPC System
  • Capabilities
  • Creating a Server
  • Creating a Client
• Pipes and Event Pipes
• Transformers
• High-level Pipes

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RPC System

The RPC system is built on top of EventPipe and Transformers.

Capabilities

• Bidirectional: Both sides call rpc methods, both side can emit events.
• Logs & Progress: Real-time streaming of log messages and progress updates during a rpc call.
• Events: Broadcast and listen to topics.
• Async/Await: Native support for Python's asyncio.
• Method Cancellation: Long-running calls can be cancelled by the caller.

Creating a Server

Extend RpcV1Server and implement handle_method_call.

import asyncio
from cbor_rpc import RpcV1Server, TcpServer, CborStreamTransformer,RpcCallContext

class MyService(RpcV1Server):
    def __init__(self, tcp_server: TcpServer):
        super().__init__()
        # Configure server to handle new connections
        tcp_server.on("connection", self.on_connection)

    async def on_connection(self, tcp_pipe):
        print(f"New connection from {tcp_pipe.get_peer_info()}")
        rpc_pipe = CborStreamTransformer().apply_transformer(tcp_pipe)
        
        # Add connection to RPC system
        conn_id = str(tcp_pipe.get_peer_info())
        await self.add_connection(conn_id, rpc_pipe)

    async def handle_method_call(self, connection_id, context: RpcCallContext, method, args):
        if method == "add":
            return args[0] + args[1]
        raise Exception("Unknown method")

async def run_server():
    server = await TcpServer.create("0.0.0.0", 9000)
    service = MyService(server)
    print("Server running on 9000...")
    await asyncio.Future()  # block forever

# asyncio.run(run_server())

Creating a Client

Use the RpcV1 class to wrap an object-oriented pipe.

import asyncio
from typing import Any, List
from cbor_rpc import RpcV1, RpcCallContext, TcpPipe, CborStreamTransformer

# 1. Define Client with Methods (Bidirectional)
class MyClient(RpcV1):
    def get_id(self) -> str:
        return "client-node"

    async def handle_method_call(self, context: RpcCallContext, method: str, args: List[Any]) -> Any:
        # Handle calls FROM the server
        if method == "ping":
            return "pong"
        raise Exception(f"Unknown method {method}")

    async def on_event(self, topic: str, message: Any) -> None:
        print(f"Event: {topic} -> {message}")

async def run_client():
    # 2. Connect via TCP
    tcp_pipe = await TcpPipe.create_connection("localhost", 9000)
    
    # 3. Apply CBOR Transformer
    cbor_pipe = CborStreamTransformer().apply_transformer(tcp_pipe)
    
    # 4. Instantiate Custom Client
    client = MyClient(cbor_pipe)
    
    # 5. Make calls (Client -> Server)
    result = await client.call_method("add", 5, 10)
    print(f"5 + 10 = {result}")

    # Call with logs and progress
    handle = client.create_call("long_task")
    handle.on_log(lambda level, msg: print(f"LOG: {msg}"))
    handle.on_progress(lambda val, meta: print(f"Progress: {val}%"))

    # await handle.call()

# asyncio.run(run_client())

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Pipes and Event Pipes

The core of cbor-rpc is the Pipe abstraction. Unlike traditional unidirectional pipes, a Pipe in this framework represents a duplex connection. It allows you to both:

• Write messages to the remote side.
• Read replies or incoming messages from the remote side.

This abstraction provides a consistent interface for bidirectional communication across different transport layers (TCP streams, SSH channels, Stdio, etc.).

Basic Usage (EventPipe)

Most "real-world" pipes (TCP, SSH, Stdio) are EventPipes. They are event-driven, meaning you register listeners for incoming data instead of polling.

Consuming Data

There are two ways to listen for data:

1. pipeline("data", handler): Used for serial processing. Handlers are awaited in order. If a pipeline handler throws an error, it stops the chain and emits an "error".
2. on("data", handler): Simple pub/sub. The handler is called whenever data arrives. If it's a coroutine, it's run in the background.

# Simple listener
pipe.on("data", lambda chunk: print(f"Received {len(chunk)} bytes"))

# Serial processing (e.g., for transformers)
async def process_data(chunk):
    # This is awaited before the next chunk is processed
    await do_something(chunk)

pipe.pipeline("data", process_data)

Sending Data

Use the write() method to send data through the pipe.

await pipe.write(b"Request data")

Converting a Pipe to an EventPipe

If you have a raw Pipe (which uses read()/write()), you can convert it to an EventPipe using make_event_based():

event_pipe = raw_pipe.make_event_based()
event_pipe.on("data", handle_incoming)

Transformers

Transformers allow you to convert raw data (typically bytes) into high-level Python objects and vice-versa.

Available Transformers

The library comes with two built-in transformer types:

• JsonTransformer / JsonStreamTransformer: Encodes/decodes JSON data.
• CborTransformer / CborStreamTransformer: Encodes/decodes CBOR data (ideal for binary efficiency).

Stream Support

It is important to note that not all transformers support streams.

• A standard Transformer (like JsonTransformer) expects a complete message in each chunk. It maps 1 input -> 1 output.
• A Stream Transformer (like JsonStreamTransformer) is designed to handle fragmented data (e.g., from TCP). It buffers incoming bytes until a complete message can be decoded.

When using TCP or SSH pipes, you almost always want to use a ...StreamTransformer.

Using Transformers

You can wrap a byte-based pipe with a transformer to create an object-based pipe.

from cbor_rpc.transformer.json_transformer import JsonStreamTransformer

# Wrap a raw pipe
object_pipe = JsonStreamTransformer().apply_transformer(raw_pipe)

# Now 'data' events emit Python objects
object_pipe.on("data", lambda obj: print(f"Received object: {obj}"))
await object_pipe.write({"method": "hello", "params": []})

Making a Custom Transformer

To create your own transformer, subclass Transformer (for single packets) or AsyncTransformer (for streams):

from cbor_rpc.transformer.base import Transformer

class MyUpperTransformer(Transformer[str, str]):
    def encode(self, data: str) -> str:
        return data.upper()

    def decode(self, data: str) -> str:
        return data.lower()

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High-level Pipes

cbor-rpc provides several ready-to-use pipe implementations for different transport layers.

TCP Pipe (TcpPipe)

Used for network communication over TCP.

from cbor_rpc.tcp import TcpPipe

# Client
pipe = await TcpPipe.create_connection("localhost", 8000)

# Server
from cbor_rpc.tcp import TcpServer
class MyServer(TcpServer):
    async def accept(self, pipe: TcpPipe) -> bool:
        print("New connection!")
        return True

server = await MyServer.create("0.0.0.0", 8000)

SSH Pipe (SshPipe)

Tunneling through SSH using asyncssh.

from cbor_rpc.ssh import SshPipe
# Used typically to run a command on a remote host and communicate with it

Stdio Pipe (StdioPipe)

Communicate with subprocesses via stdin/stdout.

from cbor_rpc.stdio import StdioPipe

# Start a subprocess
pipe = await StdioPipe.start_process("python3", "worker.py")

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Development

Enable local git hooks to auto-format on commit:

pre-commit install