lemke_handClaude Sonnet 5
aedefab5cd
start_scan_monitoring/end_scan_monitoring were unconditionally wired into callbacks_start_scan/_end_scan with no way to turn them off short of editing the callback lists directly. Needed now because RecordingSession.start() attaches a CA monitor to every monitorable channel in a single-threaded, unthreaded loop (namespace_store.py:1108), and start_recording()'s HTTP call only gets the general status_server_timeout (10s default) rather than the much larger status_server_snapshot_timeout (180s) the analogous whole-namespace snapshot/capture call gets -- reliably too slow at bernina's namespace size, producing a "start monitoring failed ... falling back to the local namespace mechanism" warning on every scan, easily mistaken for the whole status-server integration being broken (it isn't -- that's an unrelated, independently-succeeding call). scan_monitoring defaults to True (unchanged behavior); set bernina.daq.scan_monitoring = False on an already-running session for an immediate, no-restart opt-out, or pass scan_monitoring=False at construction. Checked first in both methods, before touching status_client at all, so disabling it can't itself produce a warning. Proper fix (making /recording/start async like /status/capture already is) tracked separately, not done here. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
eco — Experiment Control
___ _______
/ -_) __/ _ \
Experiment Control \__/\__/\___/
eco is a Python-based control environment for experiments, developed and used at SwissFEL, PSI. It is used both as:
- a library of experimental devices for higher-level Python applications or GUIs, and
- an interactive command-line interface, e.g. from an IPython/Jupyter shell or notebook.
eco follows an object-oriented approach: every device is represented as a Python object with a small, predictable interface, so devices can be freely combined in generic control/acquisition routines and analysed with the scientific Python ecosystem. For a general introduction to object-oriented Python, see e.g. this short introduction.
Documentation
The full documentation — installation, core concepts, and worked examples (listening monitors, archiver data and strip charts, pipeline offload, motor configuration) — lives in docs/ and is built with Sphinx, configured to build on Read the Docs via .readthedocs.yaml.
Build it locally:
pip install -r docs/requirements.txt
sphinx-build -b html docs docs/_build/html
Installation
conda install -c paulscherrerinstitute eco
or, for development, in editable mode from a checkout:
git clone https://github.com/paulscherrerinstitute/eco.git
cd eco
pip install -e .
See Installation for beamline-specific setup (the
eco launcher, .ecorc defaults) and the full dependency picture.
Creating a new device
New devices are implemented as a subclass of Assembly, which provides
naming, aliasing, and shell representation:
from eco.elements.assembly import Assembly
class MyDevice(Assembly):
def __init__(self, name=None):
super().__init__(name=name)
self._append(MySubObject, name="my_sub_object", is_setting=True, is_status=True)
is_setting=True marks the child as a setting of the assembly (shown by
.settings() and captured when settings are saved); is_status=True marks it
as contributing to the assembly's .status(). See
Representing real devices — the Assembly in the full docs
for the rest of the model (Adjustable, Detector, Namespace) and a
from-scratch, runnable example of each.