Saravanan666/pypi-org huggingface dataset:
Package: omero-slurm-client
⚠️⚠️⚠️ Summary ⚠️⚠️⚠️⚠️⚠️⚠️ Theomero_slurm_clientPyPI package is deprecated, usebiomeroinstead⚠️⚠️⚠️We have renamed the omero_slurm_client package to biomero, to reduce confusion with different names.Install the latest biomero instead:pip install biomeroThen change your imports to use that package:from biomero import SlurmClientAny new changes, features and bug fixes will only be applied to thebiomeroGitHub and PyPI package:https://pypi.org/project/biomero/
Package: omero-upload
OMERO CLI uploadPlugin for uploading files using the OMERO Command Line Interface (CLI).RequirementsOMERO 5.6.0 or newerPython 3.6 or newerInstalling from PyPIThis section assumes that an OMERO.py is already installed.Install the command-line tool usingpip:$ pip install -U omero-uploadUsageThe plugin is called from the command-line using theomerocommand.To upload a single file:$ omero upload <file>This command will create anOriginalFileon the server and return an output
of typeOriginalFile:<id>.To upload multiple files:$ omero upload <file1> <file2>This command will create twoOriginalFileand return an output of typeOriginalFile:<id1>,<id2>By default, the mimetype will be guessed from the filename but it can be
specified by using the–mimetypeargument:$ omero upload <file1> --mimetype 'test/csv'Files can be in-place uploaded into the OMERO.server via symlinked rather than
being copied. This requires the command to be run on the OMERO.server itself
from a user having write permissions to the OMERO data repository, similarly
to the [in-place import](https://docs.openmicroscopy.org/omero/latest/sysadmins/in-place-import.html). To run an in-place upload, the–data-dirargument must be passed to
specify the binary OMERO directory:$ omero upload <file1> --data-dir /OMEROInstead of creating and returning a simpleOriginalFileobject, it is also possible to wrap the file within aFileAnnotationwhich can then be linked
to other objects in the database. It is possible to specify the namespace of thisFileAnnotationusing the–namespaceargument:$ omero upload <file1> --wrap --namespace 'openmicroscopy.org/idr/analysis/original'This command will create anOriginalFileand aFileAnnotationand return
an output of typeFileAnnotation:<id>.Release processThis repository usesbump2versionto manage version numbers.
To tag a release run:$ bumpversion releaseThis will remove the.dev0suffix from the current version, commit, and tag the release.To switch back to a development version run:$ bumpversion --no-tag [major|minor|patch]specifyingmajor,minororpatchdepending on whether the development branch will be amajor, minor or patch release. This will also add the.dev0suffix.Remember togit pushall commits and tags.LicenseThis project, similar to many Open Microscopy Environment (OME) projects, is
licensed under the terms of the GNU General Public License (GPL) v2 or later.Copyright2019-2020, The Open Microscopy Environment
Package: omero-user-token
OMERO user tokenPython package that creates long running user tokens for use with the OMERO
API under non-interactive, headless conditions.RequirementsPython 3.6+OMERO.server 5.6UsageCreating a user token and making it active:omero_user_token setPlease seeomero_user_token set --helpfor detailed information.  The
default server hostname and port can be set in${HOME}/.omero_user_token/configusing an INI file compatible style:[server]
host = omero.example.com
port = 4064Retrieving the current active token (validation will be performed):omero_user_token getToken formatThe token format is as follows:<omero_session_key>@<host>:<port>Example usageBash:token=$(omero_user_tokenget)if[$?-ne0];thenecho"No valid token found"exit1fikey=$(echo"${token}"|sed-e's/^\(.*\)@.*:.*$/\1/')host=$(echo"${token}"|sed-e's/^.*@\(.*\):.*$/\1/')port=$(echo"${token}"|sed-e's/^.*@.*:\(.*\)$/\1/')echo"Connecting to${host}:${port}with key${key}"Python:fromomero_user_tokenimportgettertoken=getter()iftokenisnotNone:omero_session_key=token[:token.find('@')]host,port=token[token.find('@')+1:].split(':')port=int(port)key=token[:token.find('@')]print(f"Connecting to{host}:{port}with key{key}")LicenseOMERO user token is distributed under the terms of the GPL v2 license.
Please seeLICENSE.txtfor further details.
Package: omero-virtual-microscope
OMERO.web Virtual MicroscopeVirtual Microscope OMERO.web extension applicationRequirementsOMERO.web 5.6.0 or laterInstallation$ pip install omero-virtual-microscopeAdd virtual-microscope custom app to your installed web apps:$ omero config append omero.web.apps ‘“virtualmicroscope”’N.B.: note that double quotes are wrapped by single quotes. Windows users will need to do$ omero config append omero.web.apps “"virtualmicroscope"”Redirect to post-login page$ omero config set omero.web.login_redirect ‘{“redirect”: [“webindex”], “viewname”: “webindex_custom”}’Now start up OMERO.web as normal.Release processThis repository usesbump2versionto manage version numbers.
To tag a release run:$ bumpversion releaseThis will remove the.dev0suffix from the current version, commit, and tag the release.To switch back to a development version run:$ bumpversion --no-tag [major|minor|patch]specifyingmajor,minororpatchdepending on whether the development branch will be amajor, minor or patch release. This will also add the.dev0suffix.Remember togit pushall commits and tags.LicenseThis project, similar to many Open Microscopy Environment (OME) projects, is
licensed under the terms of the GNU General Public License (GPL) v2 or later.Copyright2019-2020, The Open Microscopy Environment
Package: omero-weberror
OMERO.weberrorOMERO.web app that helps testing errors, notification logic etc.RequirementsOMERO.web 5.6 or newer.Installing from PyPIThis section assumes that an OMERO.web is already installed.Install the app usingpip:$ pip install omero-weberrorAdd weberror custom app to your installed web apps:$ omero config append omero.web.apps '"omero_weberror"'Now restart OMERO.web as normal.Release processThis repository usesbump2versionto manage version numbers.
To tag a release run:$ bumpversion releaseThis will remove the.dev0suffix from the current version, commit, and tag the release.To switch back to a development version run:$ bumpversion --no-tag [major|minor|patch]specifyingmajor,minororpatchdepending on whether the development branch will be amajor, minor or patch release. This will also add the.dev0suffix.Remember togit pushall commits and tags.LicenseOMERO.weberror is released under the AGPL.Copyright2016-2020, The Open Microscopy Environment
Package: omero-webtest
OMERO.webtestOMERO.web app for various prototypes and examples.
This was removed from the main OMERO.web in the 5.0.6 release of OMERO.RequirementsOMERO.web 5.6 or newer.Installing from PyPIThis section assumes that an OMERO.web is already installed.Install the app usingpip:$ pip install omero-webtestAdd webtest custom app to your installed web apps:$ omero config append omero.web.apps '"omero_webtest"'Optional: install example webclient plugins:$ omero config append omero.web.ui.right_plugins '["ROIs", "webtest/webclient_plugins/right_plugin.rois.js.html", "image_roi_tab"]'
$ omero config append omero.web.ui.center_plugins '["Split View", "webtest/webclient_plugins/center_plugin.splitview.js.html", "split_view_panel"]'Now restart OMERO.web as normal.ExamplesExisting examples are available on the following URLs:https://HOST/webtest/examples/IMAGE_ID/embed_big_image.html
https://HOST/webtest/examples/IMAGE_ID/embed_viewer.htmlNote: IMAGE_ID can be obtained from public images.New templates can be added to templates/webtest/examples. New template can benefit from dynamic variables: {{ host_name }} and {{ image_id }} passed through URL.Included: Rendered template that can be saved locally for further testing as an absolute uri.Release processThis repository usesbump2versionto manage version numbers.
To tag a release run:$ bumpversion releaseThis will remove the.dev0suffix from the current version, commit, and tag the release.To switch back to a development version run:$ bumpversion --no-tag [major|minor|patch]specifyingmajor,minororpatchdepending on whether the development branch will be amajor, minor or patch release. This will also add the.dev0suffix.Remember togit pushall commits and tags.LicenseOMERO.webtest is released under the AGPL.Copyright2016-2020, The Open Microscopy Environment
Package: omero-web-zarr
omero-web-zarrOMERO.web plugin for OME-Zarr.Implementation of [OME-NGFF](https://ngff.openmicroscopy.org/latest/) API with an omero-web app.This plugin supports OME-NGFF v0.1, v03, v0.4.
For a given Image ID in OMERO, the following URL will refer to an OME-NGFF image:https://[omero-server]/zarr/image/ID.zarr/Note: This app has not been extensively tested and shouldnotbe considered “production ready”.Currently supports [OME-NGFF v0.3](https://ngff.openmicroscopy.org/0.3/index.html) and
[OME-NGFF v0.4](https://ngff.openmicroscopy.org/0.4/index.html).DevelopmentInstall with:$ pip install -e .Configuration$ omero config append omero.web.apps '"omero_web_zarr"'

# Allow to open-with Vizarr

$ omero config append omero.web.open_with '["web_zarr_vizarr", "omero_web_zarr_index", {"supported_objects":["image"], "label": "Vizarr", "script_url": "omero_web_zarr/openwith.js"}]'

# Open with ome-ngff-validator

$ omero config append omero.web.open_with '["web_zarr_validator", "omero_web_zarr_index", {"supported_objects":["image"], "label": "NGFF validator", "script_url": "omero_web_zarr/openwith_validator.js"}]'Then you will be able to access OMERO Images in OME-NGFF format v0.3 or v0.4 with a URLs like:# base URL for Image ID
[omero-server]/zarr/v0.4/image/[ID].zarr

# URLS for .zattrs, .zgroup
[omero-server]/zarr/v0.4/image/[ID].zarr/.zattrs
[omero-server]/zarr/v0.4/image/[ID].zarr/.zgroup

# .zarray of the dataset at path '0'
[omero-server]/zarr/v0.4/image/[ID].zarr/0/.zarray

# first 3D chunk of the dataset at path '0'
[omero-server]/zarr/v0.4/image/[ID].zarr/0/0/0/0You can see this in action using the [Vizarr](https://github.com/hms-dbmi/vizarr/) viewer.This omero-web app self-hosts Vizarr to avoid CORS issues (delegating tohttps://hms-dbmi.github.io/vizarr/).In the webclient UI you can use the context menu toOpen With > Vizarr, or use your Image ID and go directly to:[omero-server]/zarr/vizarr/?source=[omero-server]/zarr/v0.4/image/[ID].zarrTestingTo run integration tests (in your omero-web conda environment above) withpytest.
See [OMERO testing docs](https://docs.openmicroscopy.org/latest/omero/developers/testing.html)
for settingICE_CONFIGand dependencies etc., then:$ pytest test/integration/test_ngff.pyLicenseThe application is released under the AGPL.Copyright2022-2023, The Open Microscopy Environment
Package: ome-schema
OME Schema Python PackageThis Python package contains a copy of the OME (Open Microscopy Environment) XML schema, which is used to define the structure of OME-XML metadata for biological imaging data.Contentsome.xsd: The OME XML schema definition file.LICENSE.txt: The license file for the content of this repository.README.md: This README file, containing information about the repository and its contents.ome-schema.py: The main Python script to access the OME schema path.LicensePython PackageThis Python package is licensed under theMIT License. For more information, please see theLICENSEfile.OME XML SchemaThe OME XML schema (2016-06/ome.xsd) is licensed under theCreative Commons Attribution 3.0 Unported License. You are free to share and adapt the schema, as long as you provide appropriate attribution. For more information see the schema document for details.AttributionThe OME XML schema is developed and maintained by theOME Consortium. The original source of the schema can be found at theOME Model and Formats GitHub repository.UsageTo use the OME XML schema in your Python project, install theome-schemapackage and use theget_ome_schema_path()function from theome-schemamodule:fromomeschemaimportget_ome_schema_pathschema_path=get_ome_schema_path()For more information about OME-XML and working with the schema, please refer to theOME Data Model and File Formats documentationInstallationTo install the ome-schema package, use pip:pipinstallome-schemaContributingThis repository is a mirror of the OME XML schema from theOME Model and Formats GitHub repository. If you would like to contribute to the development of the schema, please visit the original repository and follow their contribution guidelines.
Package: ometria
=======Ometria=======.. image:: https://badge.fury.io/py/ometria.png:target: http://badge.fury.io/py/ometria.. image:: https://travis-ci.org/nwjlyons/ometria.png?branch=master:target: https://travis-ci.org/nwjlyons/ometria.. image:: https://pypip.in/d/ometria/badge.png:target: https://crate.io/packages/ometria?version=latestPython wrapper for the `Ometria API`_.Install=======::pip install ometriaUsage====::import ometriaclient = ometria.Client(key="...", secret="...")# GET /products?offset=10&limit=10r = client.products.get(params={"offset":10, "limit":10})r.response # Original response object from Python requests library.r.data # Dictionary from HTTP response body.# PUT /products/1234client.products(1234).put(data={"url": "http://example.com","title": "T-shirt", "price": 5.99})# POST /transactions/1234/lineitemsclient.transactions(1234).lineitems.post(data={"product_id": "blue_tshirt", "quantity": 3, "unit_price": 2.31, "subtotal": 14.32, "total": 6.04})# POST /products/_bulkclient.products._bulk.post(data=[{"id": ""}, {"id": ""}]).. _Ometria API: http://docs.ometria.com/Developers/History-------1.0.0 (2019-03-14)++++++++++++++++++* Switched to v2 API* Python 3 support (dropped Python 2)0.1.0 (2014-04-23)++++++++++++++++++* First release on PyPI.
Package: omexml-dls
omexml-dlsPackage to help simply and consistently create and parse OME metadata for B24 of Diamond Light Source Ltd. This is a modified copy ofpython_bioformats' omexml.py with a section from the Allen Institute for Cell Science'saicsimageioversion of omexml.py (indicated within the file). This package extends capabilities, predominantly in terms of ROIs, while offering a light-weight distribution of the omexml file.Recommended import:from oxdls import OMEXMLCurrent changes (compared to python-bioformats)TiffData - this allows IFDs to be defined (created usingset_tiffdata_count(value)) (fromaicsimageio)set_andget_ExposureTime()functions have been addedX, Y, Z units have been added for each planeSquare ROIs (an roiref must be created for each ROI first, then ROIs are created usingset_roi_count(value), then for each ROI: ROI > Union > Rectangle, where ROI parameters can be set)Small formatting changes to improve consistency
Package: ome-zarr
ome-zarr-pyTools for multi-resolution images stored in Zarr filesets, according to theOME NGFF spec.SeeDocumentationfor usage information.DocumentationDocumentation will be automatically built withreadthedocs.It can be built locally with:$ pip install sphinx
$ sphinx-build -b html docs/source/ docs/build/htmlTestsTests can be run locally viatoxwith:$ pip install tox
$ toxTo enable pre-commit code validation:$ pip install pre-commit
$ pre-commit installRelease processThis repository usesbump2versionto manage version numbers.
To tag a release run:$ bumpversion releaseThis will remove the.dev0suffix from the current version, commit, and tag the release.To switch back to a development version run:$ bumpversion --no-tag [major|minor|patch]specifyingmajor,minororpatchdepending on whether the development branch will be amajor, minor or patch release. This will also add the.dev0suffix.Remember togit pushall commits and tags.LicenseDistributed under the terms of theBSDlicense,
“ome-zarr-py” is free and open source software
Package: omf
Version: 1.0.1API library for Open Mining Format, a new standard for mining data backed by
theGlobal Mining Guidelines Group.WarningPre-Release NoticeThis is a Beta release of the Open Mining Format (OMF) and the associated
Python API. The storage format and libraries might be changed in
backward-incompatible ways and are not subject to any SLA or deprecation
policy.Why?An open-source serialization format and API library to support data interchange
across the entire mining community.ScopeThis library provides an abstracted object-based interface to the underlying
OMF serialization format, which enables rapid development of the interface while
allowing for future changes under the hood.GoalsThe goal of Open Mining Format is to standardize data formats across the
mining community and promote collaborationThe goal of the API library is to provide a well-documented, object-based
interface for serializing OMF filesAlternativesOMF is intended to supplement the many alternative closed-source file formats
used in the mining community.ConnectionsThis library makes use of thepropertiesopen-source project, which is designed and publicly supported bySeequent.InstallationTo install the repository, ensure that you havepip installedand run:pip install omfOr fromgithub:git clone https://github.com/gmggroup/omf.git
cd omf
pip install -e .3D VisualizationTo easily visualize OMF project files and data objects in a pure Python environment, check outomfvtk(OMF-VTK) which provides tools for creating interactive renderings of OMF datasets usingvtki(thevtkInterface).
Package: omfit-classes
To achieve these goals OMFIT adopts a bottom-up collaborative development approach.For more info and tutorials visit the OMFITdocumentation website.The OMFIT source code is maintained as aGitHub repository.
Fill out the OMFIT users agreementOMFIT users agreement formto be added to the GitHub repository or the mailing list.
The GitHubissue tracking systemis the best way to file bug reports and make feature requests.OMFIT users and developers are welcome to join the OMFITDISCORD server.
Package: omforme
OmformeReshape (Danish: omforme).License: MITThird party dependencies are documented in the folderthird-party.DocumentationUser and developerdocumentation of omforme.Bug TrackerAny feature requests or bug reports shall go to thetodos of omforme.Primary Source repositoryThe main source ofomformeis on a mountain in central Switzerland.
We use distributed version control (git).
There is no central hub.
Every clone can become a new source for the benefit of all.
The preferred public clones ofomformeare:on codeberg- a democratic community-driven, non-profit software development platform operated by Codeberg e.V.at sourcehut- a collection of tools useful for software development.ContributionsPlease do not submit "pull requests" (I found no way to disable that "feature" on GitHub).
If you like to share small changes under the repositories license please kindly do so by sending a patchset.
You can either send such a patchset per email usinggit send-emailor
if you are a sourcehut user by selecting "Prepare a patchset" on the summary page of your fork atsourcehut.StatusExperimental.Note: The default branch isdefault.
Package: omfvista
A PyVista (and VTK) interface for theOpen Mining Format package(omf)
providing Python 3D visualization and useable mesh data structures for
processing datasets in the OMF specification.Documentation is hosted athttps://opengeovis.github.io/omfvista/Check out theExample Notebookon NBViewer! Orlaunch the Notebook on MyBinderto run the code yourself!InstallationInstallation is simply:pip install omfvistaAll necessary dependencies will be installed alongsideomfvista. Please
note that this package heavily leverages thePyVistapackage.Questions & SupportFor general questions about the project, its applications, or about software
usage, please create an issue in thepyvista/pyvista-supportrepository
where the  PyVista community can collectively address your questions.
You are also welcome to join us on join@OpenGeoVison ourSlack workspaceunder the#omfvistachannel or send one of the
developers an email. The project support team can be reached atinfo@opengeovis.org.Example UseBe sure to check out theExample Notebookthat demosomfvistaor ourExample Galleryin the documentation!
Here’s an example using the sample data hosted in theOMF repository.importpyvistaaspvimportomfvistaproject=omfvista.load_project('test_file.omf')projectOnce the data is loaded as apyvista.MultiBlockdataset fromomfvista, then
that object can be directly used for interactive 3D visualization fromPyVista:project.plot(multi_colors=True)An interactive scene can be created and manipulated to create a compelling
figure. First, grab the elements from the project:# Grab a few elements of interest and plot em up!vol=project['Block Model']assay=project['wolfpass_WP_assay']topo=project['Topography']dacite=project['Dacite']Then create a 3D scene with these spatial data and apply a filtering tool fromPyVistato the volumetric data:# Create a plotting windowp=pv.Plotter(notebook=False)# Add our datasetsp.add_mesh(topo,cmap='gist_earth',opacity=0.5)p.add_mesh(assay,color='blue',line_width=3)p.add_mesh(dacite,color='yellow',opacity=0.6)# Add the volumetric dataset with a thresholding toolp.add_mesh_threshold(vol)# Add the bounds axisp.show_bounds()# Redner the scene in a pop out windowp.show()
Package: omfvtk
A VTK interface for theOpen Mining Format package(omf) providing
Python 3D visualization.InstallationInstallation is simply:pip install omfvtkAll necessary dependencies will be installed alongsideomfvtk. Please
note that this package heavily leverages thevtkipackage.Example UseBe sure to check out theExample Notebookthat demosomfvtk!
Here’s an example using the sample data hosted in theOMF repository.importvtkiimportomfvtkproject=omfvtk.load_project('test_file.omf')projectOnce the data is loaded as avtki.MultiBlockdataset fromomfvtk, then
that object can be directly used for interactive 3D visualization fromvtki:project.plot(notebook=False)Or an interactive scene can be created and manipulated to create a compelling
figure directly in a Jupyter notebook. First, grab the elements from the project:# Grab a few elements of interest and plot em up!vol=project['Block Model']assay=project['wolfpass_WP_assay']topo=project['Topography']dacite=project['Dacite']Then apply a filtering tool fromvtkito the volumetric data:thresher=vtki.Threshold(vol,display_params={'show_edges':False})Then you can put it all in one environment!# Grab the active plotting window#  from the thresher toolp=thresher.plotter# Add our datasetsp.add_mesh(topo,cmap='gist_earth',show_edges=False,opacity=0.5)p.add_mesh(assay,color='blue',line_width=3)p.add_mesh(dacite,show_edges=False,color='yellow',opacity=0.6)# Add the bounds axisp.add_bounds_axes()And once you like what the render view displays, you can save a screenshot:p.screenshot('wolfpass.png')