OMERO Core Scripts
This directory contains OMERO scripts which use the
OMERO.scripts API. All scripts (e.g.
*.py) present in the
directory will be automatically distributed with all binary
builds. Which file-endings will be detected and how they
will be launched are both configured centrally in the server.
.m (MATLAB) files should all be detected
by default starting with OMERO 5.
Scripts are separated into several categories, one per directory.
|analysis_scripts||crunch images to produce numerical results and similar tasks|
|export_scripts||take one or more images as an input, and produce a representation for exchange|
|figure_scripts||take one or more images as an input, and produce a summary representation|
|import_scripts||are run on images after import for extra processing|
|util_scripts||perform other miscellaneous tasks like cleaning up or optimizing OMERO itself|
Scripts which would like to rely on other scripts can use:
For this to work, the official script in question must be properly importable, i.e.:
def run(): client = omero.scripts.client(...) if __name__ == "__main__": run()
OMERO User Scripts
If you would like to provide your own scripts for others to install into their OMERO installations, please see https://openmicroscopy.org/info/scripts
Integration tests under
test/ require an OMERO server with scripts installed.
The tests are run by Travis for open PRs using omero-test-infra to deploy OMERO
via Docker containers.
To run tests locally:
# All tests $ python setup.py test # Single test in a single file $ python setup.py test -t test/integration/test_util_scripts.py -k test_dataset_to_plate
This repository uses bump2version to manage version numbers. To tag a release run:
$ bumpversion release
This will remove the
.dev0 suffix from the current version, commit, and tag the release.
To switch back to a development version run:
$ bumpversion --no-tag [major|minor|patch]
patch depending on whether the development branch will be a major, minor or patch release. This will also add the
git push all commits and tags.s essential.
The CI pipeline will automatically deploy the tag onto PyPI.
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