IaC-Driven Laboratory Automation Framework

This project implements a lightweight Infrastructure-as-Code (IaC) model for automated laboratory workflows.
Users describe hardware, interconnections, and experiments in YAML.
The system dynamically loads hardware plugins, constructs resource objects, resolves references, and executes procedures.

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🚀 Features

• Dynamic plugin discovery
  Devices and endpoints are auto-loaded from devices/ and endpoints/ via decorators.

• Fully dynamic YAML loader
  No field is hard-coded. Constructor signatures determine how resources are built.

• Automatic reference resolution
  Any YAML list of resource names is automatically converted into live Python objects.

• Enum auto-detection
  YAML strings are converted into Enum values based on the class hierarchy.

• Supports hierarchical lab structure
  LabNetwork → ControlModule → Device

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🔌 Adding a New Device Plugin

To add a new device:

1. Create a file in devices/

Example: devices/MySensor.py

from core.Instrument import Instrument, ConnectionType
from core.Register import register_resource
from core.Resource import Status

@register_resource("my_sensor")
class MySensor(Instrument):
    def __init__(self, name: str, identifier: int, status=Status.AVAILABLE):
        super().__init__(name=name,
                         connection_type=ConnectionType.SERIAL,
                         identifier=identifier,
                         status=status)

    def create(self):
        ...

    def read(self):
        return {"data": "..."}   # must return dict

    def update(self, *args, **kwargs):
        ...

    def delete(self):
        ...

2. Define Lab Resources in YAML devices/

my_sensor_1:
  type: my_sensor
  identifier: 6
  status: available

Done — the loader will auto-discover it.

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Video demo