grelmicro 0.21.0

grelmicro is a lightweight toolkit for building Python applications that need to coordinate work across processes

Async-first toolkit. Microservice patterns inside.

A Python toolkit for distributed systems: microservices, modular monoliths, and self-contained systems.

Project status: Active development. grelmicro is pre-1.0. The public API is not yet stable. Breaking changes are allowed on MINOR bumps (0.14.0 → 0.15.0) and never on PATCH. Pin the minor: grelmicro>=0.14.0,<0.15.0. After 1.0.0, standard semver applies. See the versioning policy.

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Documentation: https://grelinfo.github.io/grelmicro/

Source Code: https://github.com/grelinfo/grelmicro

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Why grelmicro

Stop reinventing the wheel. grelmicro ships microservice patterns as small, composable modules with pluggable backends: locks, rate limits, circuit breakers, cache, logging, health checks, and task scheduling. Async-first, type-safe, and battle-tested in production.

It is built for any Python application that coordinates work across processes, workers, or replicas. The same primitives serve every distributed system, whether you call it microservices, a modular monolith, or a self-contained system. A distributed lock is a distributed lock whether your system is one process or fifty. It fits naturally into cloud-native applications, containerized apps, and Kubernetes deployments.

• Micro: one focused primitive per module, each a canonical microservice pattern (distributed lock, leader election, rate limiter, circuit breaker, health check API, externalised configuration).
• Fast: small footprint by design. We keep the layers thin so your code stays quick.
• Async-first: every I/O call is async / await. Drops into FastAPI, FastStream, and any asyncio-based stack.
• Backend-agnostic: each primitive is a protocol. Swap Redis for PostgreSQL or SQLite without touching application code.
• Railguarded: 100% pytest coverage, ty-checked, ruff-linted, Pydantic-validated. Pre-1.0 API may shift on minor bumps. 1.x commits to standard semver.

Modules

Module	Summary
Cache	@cached decorator with per-key stampede protection. In-memory TTLCache or RedisCacheBackend.
Synchronization	Distributed Lock, TaskLock, LeaderElection. Redis, PostgreSQL, SQLite, Kubernetes, in-memory.
Task Scheduler	Periodic task execution with optional distributed locking. Lightweight, not a Celery replacement.
Resilience	Circuit Breaker and Rate Limiter with pluggable algorithms (TokenBucketConfig, GCRAConfig).
Logging	12-factor logging with JSON, LOGFMT, TEXT, or PRETTY output, structured error rendering, and OpenTelemetry trace context.
Tracing	Unified instrumentation. @instrument creates OpenTelemetry spans and enriches log records with structured context.
Health	Health check registry with concurrent runners and FastAPI liveness / readiness integration.
JSON	Fast JSON via orjson when available, with automatic fallback to stdlib json.

Installation

pip install grelmicro

See the Installation guide for uv and poetry commands, plus optional extras for Redis, PostgreSQL, SQLite, Kubernetes, OpenTelemetry, and structlog.

Example

FastAPI integration

Create a file main.py with:

import logging
from contextlib import asynccontextmanager

from fastapi import FastAPI, HTTPException, Request

import grelmicro
from grelmicro import cache, resilience, sync
from grelmicro.cache import JsonSerializer, TTLCache, cached
from grelmicro.cache.redis import RedisCacheBackend
from grelmicro.logging import configure_logging
from grelmicro.resilience import (
    CircuitBreaker,
    RateLimitExceededError,
    RateLimiter,
)
from grelmicro.resilience.redis import RedisRateLimiterBackend
from grelmicro.sync import LeaderElection, Lock
from grelmicro.sync.redis import RedisSyncBackend
from grelmicro.task import TaskManager

logger = logging.getLogger(__name__)

# === grelmicro ===
task = TaskManager()
sync.register(RedisSyncBackend("redis://localhost:6379/0"))
cache.register(RedisCacheBackend("redis://localhost:6379/0", prefix="myapp:"))
resilience.register(RedisRateLimiterBackend("redis://localhost:6379/0"))

leader_election = LeaderElection("leader-election")
task.add_task(leader_election)

ttl_cache = TTLCache(ttl=300, serializer=JsonSerializer())


# === FastAPI ===
@asynccontextmanager
async def lifespan(app):
    configure_logging()
    async with grelmicro.lifespan(task):
        yield


app = FastAPI(lifespan=lifespan)


# --- Cache: avoid redundant database queries ---
@cached(ttl_cache)
async def get_user(user_id: int) -> dict:
    return {"id": user_id, "name": "Alice"}


@app.get("/users/{user_id}")
async def read_user(user_id: int):
    return await get_user(user_id)


# --- Circuit Breaker: protect calls to an unreliable service ---
cb = CircuitBreaker("my-service")


@app.get("/")
async def read_root():
    async with cb:
        return {"Hello": "World"}


# --- Rate Limiter: protect endpoints from overload ---
api_limiter = RateLimiter.gcra("api", limit=100, window=60)


@app.get("/api")
async def api_endpoint(request: Request):
    try:
        await api_limiter.acquire_or_raise(key=request.client.host)
    except RateLimitExceededError as exc:
        raise HTTPException(
            status_code=429,
            detail="Too many requests",
            headers={"Retry-After": str(int(exc.retry_after))},
        )
    return {"status": "ok"}


# --- Distributed Lock: synchronize access to a shared resource ---
lock = Lock("shared-resource")


@app.get("/protected")
async def protected():
    async with lock:
        return {"status": "ok"}


# --- Interval Task: run locally on every worker ---
@task.interval(seconds=5)
def heartbeat():
    logger.info("heartbeat")


# --- Distributed Task: run once per interval across all workers ---
@task.interval(seconds=60, max_lock_seconds=300)
def cleanup():
    logger.info("cleanup")


# --- Leader-gated Task: only the leader executes ---
@task.interval(seconds=10, leader=leader_election)
def leader_only_task():
    logger.info("leader task")

License

This project is licensed under the terms of the MIT license.