clamator-over-memory 0.1.5

In-process loopback transport for clamator (pre-1.0).

clamator-over-memory

In-process loopback transport for clamator. The shared MemoryBus connects a MemoryRpcServer and MemoryRpcClient running in the same Python process. Requires Pydantic v2.

Install

pip install clamator-over-memory clamator-protocol

Quickstart

Contracts are authored in TypeScript and the Python sibling is produced by @clamator/codegen:

npx @clamator/codegen --src contracts --out-py generated

The emitted generated/arith.py exports Pydantic models, a typed ArithClient, an ArithService ABC, and the arith_contract Contract object. Wire server and client through a shared bus, talk via ArithClient.

Server-side — register handlers and start:

from clamator_over_memory import MemoryBus, MemoryRpcServer

from .generated.arith import AddParams, AddResult, ArithService, arith_contract


class Arith(ArithService):
    async def add(self, params: AddParams) -> AddResult:
        return AddResult(sum=params.a + params.b)


async def build_arith_server(bus: MemoryBus) -> MemoryRpcServer:
    server = MemoryRpcServer(bus=bus)  # no external connection; stop() unregisters from the bus without closing any resource  # noqa: E501
    server.register_service(arith_contract, Arith())  # must precede start() — post-start registrations are silently ignored, never registered on the bus  # noqa: E501
    await server.start()
    return server

(Verbatim from py/packages/over-memory/tests/server.py:1-15.)

Client-side — call the typed proxy:

from clamator_over_memory import MemoryBus, MemoryRpcClient

from .generated.arith import AddParams, AddResult, ArithClient


async def call_arith(bus: MemoryBus) -> AddResult:
    client = MemoryRpcClient(bus=bus)  # default timeout 30 s on the full round-trip (call → handler → reply); pass default_timeout_ms to override; no retry; timeouts not propagated to server  # noqa: E501
    await client.start()
    arith = ArithClient(client)
    r = await arith.add(AddParams(a=2, b=3))
    await client.stop()
    return r

(Verbatim from py/packages/over-memory/tests/client.py:1-12.)

server.start() returns once handlers are registered on the bus; it does not block. Your application controls the server's lifetime. Call await server.stop() to shut down — since the loopback is in-process, the drain is instantaneous and the server unregisters from the bus without closing any external resource. start() and stop() are both idempotent (calling either twice is a no-op); once stop() has been called, calling start() again raises — create a new instance to restart.

A single server can host multiple services. Call register_service(contract, handler_obj) once per contract before start(); each is registered as its own dispatcher on the shared bus. Registrations after start() are silently ignored.

MemoryBus() takes no arguments and is the only wiring needed. The loopback is synchronous within a single asyncio task — no timeouts, retries, or stream parameters beyond the client's default_timeout_ms.

Key surface

• MemoryBus() — the connecting object passed to both server and client.
• MemoryRpcServer(bus=...) — register_service(contract, handler_obj), start(), stop().
• MemoryRpcClient(bus=...) — start(), stop(). Wrap with a generated *Client proxy for typed calls.

Worker-pool semantics

N/A — this transport is a single-process loopback. Multiple MemoryRpcServer instances on the same MemoryBus do not form a competing-consumers pool because there is no shared substrate; each bus is in-memory to its constructing process. For cross-process worker-pool behavior, use clamator-over-redis.

Owned external state

N/A — MemoryBus owns no external state. There are no Redis keys, no streams, no files, no sockets. The bus is garbage-collected with the process.

Connection ownership

N/A — there is no external connection to own. MemoryRpcServer and MemoryRpcClient share a MemoryBus that lives entirely in-process; stop() releases its references without closing any external resource.

Protocol-level parity with over-redis

Params/result validation, error code mapping, handler exception wrapping, and register_service semantics are identical to clamator-over-redis — both transports share the same dispatcher (RpcServerCore from clamator-protocol). Only the wire substrate differs. Tests written against this transport for protocol-level behaviors translate directly to over-redis.

When to reach for this vs. clamator-over-redis

• clamator-over-memory — tests, embedded scenarios, anything single-process.
• clamator-over-redis — cross-process, cross-host, durable streams, production.

Links

• Sibling (TypeScript): @clamator/over-memory
• Codegen: @clamator/codegen (run from TS side; consume the generated Python output)
• Design spec: docs/2026-05-07-clamator-design.md
• Agent rules: AGENTS.md