lemke_handClaude Sonnet 5 d41fb10a7d StatusServer: richer status(), and recording_mode as a validated choice
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>
2026-09-10 19:34:22 +02:00
2026-09-09 15:58:41 +02:00
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2018-07-06 12:38:44 +02:00
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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.

S
Description
Experimental control package
Readme GPL-3.0
7.5 MiB
Languages
Python 86%
HTML 11%
Jupyter Notebook 2.1%
Shell 0.9%