guarneri 0.0.1

guarneri

A package for creating Ophyd and Ophyd-async devices from configuration files.

Instead of instantiating devices directly in python, Guarneri reads a configuration file and creates/connects the devices for you. This provides the following benefits:

1. Beamline configuration is in a human-readable configuration file (e.g. TOML).

2. Other tools can modify the configuration file if needed.

3. Devices can be connected in parallel (faster).

4. Missing devices are handled gracefully.

5. Devices can be simulated/mocked by changing a single value in the config file.

Usage

Let’s say you have some ophyd and ophyd-async devices defined (with type hints) in a file called devices.py. This is not specific to guarneri, just regular Ophyd.

from ophyd_async.epics import epics_signal_rw
from ophyd_async.core import AsyncDevice
from ophyd import Device, Component

from guarneri import Instrument

class MyDevice(Device):
    description = Component(".DESC")


class MyAsyncDevice(AsyncDevice):
    def __init__(self, prefix: str, name: str = ""):
        self.description = epics_signal_rw(str, f"{prefix}.DESC")
    super().__init__(name=name)


def area_detector_factory(hdf: bool=True):
    # Create devices here using the arguments
    area_detector = ...
    return area_detector

Instead of instantiating these in a python startup script, Guarneri will let you create devices from a TOML configuration file. First we create a TOML file (e.g. instrument.toml) with the necessary parameters, these map directly onto the arguments of the device’s __init__(), or the arguments of a factory that returns a device.

[my_device.device1]
prefix = '255id:'

[async_device.device3]
prefix = '255id:'

[area_detector.sim_det]
hdf = true

Then in your beamline startup code, create a Guarneri instrument and load the config files.

from io import StringIO

from devices import MyDevice, MyAsyncDevice, area_detector_factory

# Prepare the instrument device
instrument = Instrument({
    "my_device": MyDevice,
    "async_device": MyAsyncDevice,
    "area_detector": area_detector_factory,
})

# Create the devices from the TOML configuration file
instrument.load_config_files("instrument.toml")
# Optionally connect all the devices
await instrument.connect_devices()

# Now use the devices for science!
instrument.devices['device_1'].description.get()

The first argument to guarneri.Instrument.__init__() is a mapping of TOML section names to device classes. Guarneri then introspects the device or factory to decide which TOML keys and types are valid. In the above example, the heading [my_device.device1] will create an instance of MyDevice() with the name "device1" and prefix "255id:". This is equivalent to MyDevice(prefix="255id:", name="device1").

What About Happi?

Happi has a similar goal to Guarneri, but with a different scope. While Happi is meant for facility-level configuration (e.g. LCLS), Guarneri is aimed at individual beamlines at a synchrotron. Happi uses HappiItem classes with ItemInfo objects to describe the devices definitions, while Guarneri uses the device classes themselves. Happi provides a python client for adding and modifying the devices, while Guarneri uses human-readable configuration files.

Which one is better? Depends on what you’re trying to do. If you want a flexible and scalable system that shares devices across a facility, try Happi. If you want a way to get devices running quickly on your beamline before users show up, try Guarneri.

Documentation

Sphinx-generated documentation for this project can be found here: https://spc-group.github.io/guarneri/

Requirements

Describe the project requirements (i.e. Python version, packages and how to install them)

Installation

The following will download the package and load it into the python environment.

git clone https://github.com/spc-group/guarneri
pip install guarneri

For development of guarneri, install as an editable project with all development dependencies using:

pip install -e ".[dev]"

Running the Tests

$ pip install -e .
$ pytest -vv