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:
- Beamline configuration is in a human-readable configuration file (e.g. TOML).
- Other tools can modify the configuration file if needed.
- Devices can be connected in parallel (faster).
- Missing devices are handled gracefully.
- Devices can be simulated/mocked by changing a single value in the config file.
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 ]]
name = "device1"
prefix = '255id:'
[[ async_device ]]
name = "device3"
prefix = '255id:'
[[ area_detector ]]
name = "sim_det"
hdf = true
Then in your beamline startup code, create a Guarneri instrument and load the config files.
from io import StringIO
from guarneri import Instrument
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()
# 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")
.
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.
Sphinx-generated documentation for this project can be found here: https://spc-group.github.io/guarneri/
Describe the project requirements (i.e. Python version, packages and how to install them)
The following will download the package and load it into the python environment.
pip install guarneri
For development of guarneri, install as an editable project with all development dependencies using:
git clone https://github.com/spc-group/guarneri
pip install -e ".[dev]"
$ pip install -e . $ pytest -vv