A python server to support communication between CRM and Component processes.
Project description
C-Two (0.1.23)
C-Two is a type-safe Remote Procedure Call (RPC) framework designed for distributed resource computation systems. The framework provides a structured abstraction layer that enables remote method invocation between client components and Core Resource Models (CRM) with automatic serialization and protocol-agnostic communication.
Framework Overview
C-Two addresses the complexity of distributed computing by implementing a clear separation of concerns through interface-based programming and automatic type marshalling. The framework enables developers to write distributed applications using familiar local programming patterns while maintaining type safety across network boundaries.
Core Architectural Principles
- Interface Segregation: Clean separation between interface definitions (ICRM) and implementations (CRM)
- Type Safety: Compile-time and runtime type checking with automatic serialization inference
- Protocol Abstraction: Transport-agnostic communication supporting multiple protocols (IPC, TCP, HTTP, MCP)
- Resource Isolation: Encapsulation of computational resources behind well-defined interfaces
Architecture
The framework implements a three-tier architecture:
Component Layer
Client-side computational units that consume remote resources through Interface of Core Resource Models (ICRM), providing network transparency for distributed operations.
CRM Layer
Server-side Core Resource Models implementing domain-specific business logic and resource management, exposed through standardized ICRM interfaces.
Transport Layer
Protocol-agnostic communication infrastructure supporting multiple transport mechanisms (IPC, TCP, HTTP, MCP) with automatic protocol detection, connection management and message serialization. The framework automatically selects the appropriate transport implementation based on the address scheme.
Implementation Guide
1. Interface Definition (ICRM)
Define remote interfaces using the @icrm decorator to establish contracts for distributed communication:
import c_two as cc
@cc.icrm
class IGrid:
def get_grid_infos(self, level: int, global_ids: list[int]) -> list[GridAttribute]:
"""Retrieve grid information for specified level and identifiers"""
...
def subdivide_grids(self, levels: list[int], global_ids: list[int]) -> list[str]:
"""Perform grid subdivision operations"""
...
2. Resource Model Implementation (CRM)
Implement the Core Resource Model using the @iicrm decorator:
@cc.iicrm
class Grid(IGrid):
def __init__(self, epsg: int, bounds: list, first_size: list[float], subdivide_rules: list[list[int]]):
self.epsg = epsg
self.bounds = bounds
# Resource initialization
def get_grid_infos(self, level: int, global_ids: list[int]) -> list[GridAttribute]:
# Business logic implementation with automatic serialization
return [GridAttribute(level=level, global_id=gid, ...) for gid in global_ids]
def subdivide_grids(self, levels: list[int], global_ids: list[int]) -> list[str]:
# Subdivision algorithm implementation
return [f"{level+1}-{child_id}" for level, gid in zip(levels, global_ids) for child_id in children]
3. Custom Data Type Definition
Define serializable data structures using the @transferable decorator with any necessary serialization logic:
import pyarrow as pa
@cc.transferable
class GridAttribute:
level: int
global_id: int
elevation: float
def serialize(data: 'GridAttribute') -> bytes:
schema = pa.schema([
pa.field('level', pa.int32()),
pa.field('global_id', pa.int32()),
pa.field('elevation', pa.float64())
])
table = pa.Table.from_pylist([data.__dict__], schema=schema)
return serialize_from_table(table)
def deserialize(arrow_bytes: bytes) -> 'GridAttribute':
row = deserialize_to_rows(arrow_bytes)[0]
return GridAttribute(**row)
@cc.transferable
class GridAttributes:
"""
A collection of GridAttribute objects with built-in serialization capabilities.
The C-Two framework automatically handles serialization/deserialization when this type
is detected as a parameter or return type in CRM methods (e.g., the return type of
Grid.get_grid_infos()).
"""
def serialize(data: list[GridAttribute]) -> bytes:
schema = pa.schema([
pa.field('attribute_bytes', pa.list_(pa.binary())),
])
data_dict = {
'attribute_bytes': [GridAttribute.serialize(grid) for grid in data]
}
table = pa.Table.from_pylist([data_dict], schema=schema)
return serialize_from_table(table)
def deserialize(arrow_bytes: bytes) -> list[GridAttribute]:
table = deserialize_to_table(arrow_bytes)
grid_bytes = table.column('attribute_bytes').to_pylist()[0]
return [GridAttribute.deserialize(grid_byte) for grid_byte in grid_bytes]
# Helpers ##################################################
def serialize_from_table(table: pa.Table) -> bytes:
sink = pa.BufferOutputStream()
with pa.ipc.new_stream(sink, table.schema) as writer:
writer.write_table(table)
binary_data = sink.getvalue().to_pybytes()
return binary_data
def deserialize_to_rows(serialized_data: bytes) -> dict:
buffer = pa.py_buffer(serialized_data)
with pa.ipc.open_stream(buffer) as reader:
table = reader.read_all()
return table.to_pylist()
4. Server Deployment
Deploy the CRM as a networked service with automatic protocol detection:
# Resource initialization and server configuration
grid = Grid(epsg=2326, bounds=[...], first_size=[64.0, 64.0], subdivide_rules=[...])
# IPC / TCP server (high-performance, low-latency)
server = cc.message.Server("tcp://localhost:5555", grid)
# or
# HTTP server (web-compatible, cross-platform)
server = cc.message.Server("http://localhost:8000", grid)
# Same server lifecycle management regardless of protocol
server.start()
print('CRM server is running. Press Ctrl+C to stop.')
try:
# Wait for server termination with a timeout or not
server.wait_for_termination(timeout=10)
print('Timeout reached, stopping CRM server...')
except KeyboardInterrupt:
print('Keyboard interrupt received, stopping CRM server...')
finally:
server.stop()
print('CRM server stopped.')
5. Client Implementation
The framework provides seamless protocol-transparent connectivity to CRM services.
Script-Based Component Approach
# IPC / TCP connection (high-performance)
with cc.compo.runtime.connect_crm('tcp://localhost:5555', IGrid) as grid:
infos = grid.get_grid_infos(1, [0, 1, 2])
keys = grid.subdivide_grids([1, 1], [0, 1])
print(f'Retrieved {len(infos)} grid attributes, generated {len(keys)} subdivisions')
# HTTP connection (web-compatible) - same interface, same code
with cc.compo.runtime.connect_crm('http://localhost:8000', IGrid) as grid:
infos = grid.get_grid_infos(1, [0, 1, 2])
keys = grid.subdivide_grids([1, 1], [0, 1])
print(f'Retrieved {len(infos)} grid attributes, generated {len(keys)} subdivisions')
Function-Based Component Approach
@cc.compo.runtime.connect
def process_grids(grid: IGrid, target_level: int) -> list[str]:
"""Reusable component for grid processing operations"""
infos = grid.get_grid_infos(target_level, [0, 1, 2, 3, 4])
candidates = [info.global_id for info in infos if hasattr(info, 'elevation') and info.elevation > 0]
return grid.subdivide_grids([target_level] * len(candidates), candidates)
# Protocol is determined automatically by the address
result = process_grids(1, crm_address='tcp://localhost:5555') # Uses TCP
result = process_grids(1, crm_address='http://localhost:8000') # Uses HTTP
# Or using a context manager with automatic protocol detection
with cc.compo.runtime.connect_crm('tcp://localhost:5555'):
result = process_grids(1)
6. External System Integration
Integrate with external systems using the Model Context Protocol (MCP):
from mcp.server.fastmcp import FastMCP
import compo # Component module
mcp = FastMCP('GridAgent', instructions=cc.mcp.CC_INSTRUCTION)
cc.mcp.register_mcp_tools_from_compo_module(mcp, compo)
if __name__ == '__main__':
mcp.run()
Application Domains
C-Two is particularly suited for:
- Distributed Scientific Computing: High-performance computing applications requiring resource distribution
- Web-Based Applications: HTTP protocol support enables seamless web service integration
- Microservices Architecture: Type-safe inter-service communication with flexible protocol selection
- Computational Resource Management: Systems requiring dynamic resource allocation and computation distribution
- Cross-Platform Integration: Unified interface supporting multiple transport protocols
- System Integration: Applications requiring protocol-agnostic communication with external systems
- Modular Component Systems: Reusable computational components across different resource implementations and protocols
Framework Components
Core Decorators
@icrm: Interface definition for remote resource specifications@iicrm: Implementation marker for Core Resource Models@transferable: Custom serializable data type definition@auto_transfer: Automatic serialization based on type annotations@connect: Connection injection for component functions
Runtime Components
connect_crm: Context manager for CRM connection lifecycle management with automatic protocol detectionServer: CRM service deployment infrastructure with multi-protocol supportClient: Remote resource access client with transparent protocol handling
Integration Utilities
- MCP Tools: Model Context Protocol integration for external system communication
Technical Requirements
- Python ≥ 3.10
- Type annotation support
- Network connectivity for distributed deployment
Protocol Dependencies
Core Framework
pyarrow- High-performance data serializationzmq- ZeroMQ for TCP protocol support
HTTP Protocol Support
starlette- Lightweight ASGI framework for HTTP serverrequests- HTTP client libraryuvicorn- ASGI server (automatically used by HTTP server)
Development & Integration
mcp[cli]- Model Context Protocol integrationhttpx- Modern HTTP client for advanced scenarios
C-Two provides a principled approach to distributed computing through type-safe abstractions and protocol-agnostic communication, enabling developers to build robust distributed systems with familiar programming patterns.
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