lemke_handClaude Sonnet 5
f91ad41417
Two-tier fix for a namespace recording's "channel with zero updates is simply absent from the file" gap: 1. RecordingSession.start() now seeds a channel with its current value (add_current_value=True) when that's actually free: pyepics' PV.get_with_metadata() returns the cached value with no CA traffic when auto_monitor is already True and the channel is connected - true for the large majority of channels under ca_tuning.make_pv()'s default policy. A demoted "fast" channel or a disconnected one would make this a real blocking get, so those are left unseeded, as before. New n_seeded counter reports how many got the free seed. 2. For the rest, RecordingSession.backfill_from_status() lets a status snapshot that was already being taken for another reason (a scan's own status_run_start/status_run_end capture) opportunistically fill in one value for any channel still at zero points - never a trigger of new CA traffic on its own. NamespaceMonitorStore gains pgroup/run_number on start_recording() (purely for this lookup) and backfill_running_recordings(), wired into both /status/capture and /status/snapshot right after their own snapshot() call. New n_backfilled counter. 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.