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Snocomm presents a project for cloud quantum computing with resources from The Amarr Imperial Academy

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OMNIXAN

OMNIXAN es un workspace Python orientado a experimentacion modular en cloud, edge, supercomputacion y computacion cuantica. El repo ya tiene una base estable para importar paquetes, ejecutar smokes y diagnosticar dependencias opcionales sin romper imports.

Estado actual

  • Fuente de verdad de packaging: pyproject.toml
  • CLI oficial: python -m omnixan
  • Diagnostico oficial: python -m omnixan doctor --json
  • Validacion integral local: python -m omnixan validate --json
  • La API publica comun en modulos core usa initialize(), execute(), shutdown(), get_status() y get_metrics()
  • Los backends cuanticos, distribuidos y GPU siguen siendo opcionales

Instalacion

Instalacion minima:

PYENV_VERSION=hokkaido python -m pip install -e .

Extras utiles:

PYENV_VERSION=hokkaido python -m pip install -e '.[dev]'
PYENV_VERSION=hokkaido python -m pip install -e '.[quantum]'
PYENV_VERSION=hokkaido python -m pip install -e '.[distributed]'
PYENV_VERSION=hokkaido python -m pip install -e '.[cloud]'

Verificacion rapida

PYENV_VERSION=hokkaido python -m omnixan doctor --json
PYENV_VERSION=hokkaido python -m omnixan validate --json --skip-tests
PYENV_VERSION=hokkaido python -m pytest omnixan/tests

Rutina reproducible local:

./scripts/ci_local.sh baseline
./scripts/ci_local.sh optional-smokes

Smokes por bloque:

PYENV_VERSION=hokkaido python -m pytest omnixan/tests -k core_block_smoke

Smokes opcionales:

PYENV_VERSION=hokkaido python -m pytest omnixan/tests -k quantum_stack_smoke
PYENV_VERSION=hokkaido python -m pytest omnixan/tests -k distributed_stack_smoke

CLI oficial

python -m omnixan --help
python -m omnixan doctor --json
python -m omnixan validate --json
python -m omnixan load-balancing --smoke --json
python -m omnixan redundant-deployment --smoke --json

Documentacion operativa por bloque

Documentacion adicional

Ejemplo minimo

import asyncio

from omnixan.carbon_based_quantum_cloud.load_balancing_module.module import (
    BackendConfig,
    HealthCheckConfig,
    LoadBalancingAlgorithm,
    LoadBalancingAlgorithmType,
    LoadBalancingModule,
    LoadBalancingModuleConfig,
    Request,
)


async def main() -> None:
    module = LoadBalancingModule(
        LoadBalancingModuleConfig(
            algorithm=LoadBalancingAlgorithm(
                algorithm_type=LoadBalancingAlgorithmType.ROUND_ROBIN
            ),
            health_check=HealthCheckConfig(healthy_threshold=1),
        )
    )
    await module.initialize()
    try:
        await module.add_backend(BackendConfig(host="127.0.0.1", port=8080))
        result = await module.route_request(Request(client_ip="127.0.0.1"))
        print(result.backend_id)
        print(module.get_status())
    finally:
        await module.shutdown()


asyncio.run(main())

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Snocomm presents a project for cloud quantum computing with resources from The Amarr Imperial Academy

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