status() now shows the failed component names (not just the count), a
red/yellow/green state indicator, and a summary of recent request activity
(count, errors, last kind/age/duration) from /stats - previously only
reachable via separate failures()/stats() calls.
recording_mode is now an _AdjustableFSChoice (enum_strs=("all", "throttle",
"sample"), the exact set RecordingSession.__init__ accepts) instead of a
freeform AdjustableFS: rejects an invalid value at set_target_value time,
and exposes enum_strs so it structurally satisfies
eco.elements.protocols.AdjustableEnum for widget-layer dropdown display.
Deliberately not eco.elements.adjustable.AdjustableEnum itself, which
stores an IntEnum's integer rather than the string - storage stays the
plain string the server already parses, no server-side change needed.
Also documents the max_value_elements/max_points_per_channel distinction
inline (per-value-width filter vs. per-channel-length cap over time) -
not obvious from the settings' names alone.
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.