Saravanan666/pypi-org huggingface dataset:
Package: orange3-scoring
Orange3 ScoringThis is an scoring/inference add-on forOrange3. This add-on adds widgets to
loadPMMLandPFAmodels
and score data.DependenciesTo use PMML models make sure you have Java installed:Java >= 1.8pypmml (downloaded during installation)To use PFA models:titus2 (downloaded during installation)InstallationTo install the add-on using pip, runpip install orange3-scoringTo register this add-on with Orange, but keep the code in the development directory (do not copy it to
Python's site-packages directory), runpip install -e .Issues, Questions and Feature RequestsPlease raise an issue/question/requesthere.DevelopmentWant to contribute? Great!Please raise anissueto discuss your ideas and send apull request.UsageAfter the installation, the widget from this add-on is registered with Orange. To run Orange from the terminal,
usepython -m Orange.canvasThe new widget appears in the toolbox bar under the sectionScoring.Drag and drop theLoad PMML/PFA Modelwidget.Load your PMML model and inspect Input and Output field(s). Sample PMML Filehere.Add input dataset usingFilewidget (iris) and connect the two widgets toEvaluate PMML/PFA Modelwidget. You can inspect the fields in data and the model and view Processing INFO or Errors.Now hitScorebutton to score.Connect the output toData Tablewidget to view the results. 3 new columns (cluster, cluster_name & distance) are added after scoring the data obtained for each input record. The actual class value present in the data is also converted to metadata of the result table.Now lets load a PFA Model. Sample PFA Filehere.Score the data using new PFA Model.Now hitScorebutton to score.View the results. You can see the predicted class for iris as provided by the PFA Model.Another output signal is produced which contains theEvaluation Resultswhich can be connected toConfusion Matrix,ROC AnalysisandLift Curvewidgets. We can connect it to theConfusion Matrixwidget to view the difference in predicted and actual results.
Package: orange3-shap
[![Build Status](https://travis-ci.org/jpoullet2000/orange3-shap.svg?branch=master)](https://travis-ci.org/jpoullet2000/orange3-shap)Orange3-ShapOrange add-on for explaining Random Forest output with Shapley method.License: CC-BY-NC-3.0Package documentation:http://orange3-shap.readthedocs.io/Installing### With AnacondaThe easiest way to install Orange3-Shap on a non-GNU/Linux system is
with [Anaconda] distribution for your OS (Python version >=3.6).
In your Anaconda Prompt, first add conda-forge to your channels:conda config –add channels conda-forgeThen install Orange3:conda install orange3This will install the latest release of Orange. Then install Orange3-Shap:pip install orange3-shapRun:orange-canvasto open Orange and check if everything is installed properly.[Anaconda]:https://www.continuum.io/downloads### From sourceTo install the add-on from source# Clone the repository and move into it
git clonehttps://github.com/jpoullet2000/orange3-shap.gitcd orange3-shap# Install corresponding wheels for your OS:
pip install some-wheel.whl# Install Orange3-Shap in editable/development mode.
pip install -e .To register this add-on with Orange, runpython setup.py install
Package: orangearg
Orange3 Argument Mining Add-onThis work is an open-source Python package that implements a pipeline of processing, analyzing, and visualizing an argument corpus and the attacking relationship inside the corpus. It also implements the corresponding GUIs on a scientific workflow platform namedOrange3, so that users with little knowledge of Python programming can also benefit from it.Table of ContentsWhyInstallationGetting StartedDocumentationContributingCreditsWhyThis package is designed with a clear mission: to empower researchers in building their own argument mining workflows effortlessly. Leveraging the capabilities of state-of-the-art, pre-trained language models for natural language processing, this tool facilitates the process of understanding arguments from text data. At its core, this work is committed to transparency and interpretability throughout the analysis process. We believe that clarity and comprehensibility are paramount when working with complex language data. As such, the tool not only automates the task but also ensures that the results are easily interpretable, allowing researchers to gain valuable insights from their data.Please cite this work if you use it for scientific or commercial purpose.InstallationThis package requires Python version >= 3.8. We recommand installing this package in a new virtual environment to avoid dependency conflicts. The package can be installed from PyPI viapip:pip install orangeargExecuting the above command will install both the necessary dependencies and the graphical user interface (GUI) components of Orange3.Further details can be found in theinstallation guide.Getting StartedIf you would like to learn how to use this package for scripting, take a look at our examplenotebook.To build and run workflows on Orange3, run the following command in your terminal to launch the Orange3 GUI, known as the 'canvas'.python -m Orange.canvasA sampleworkflowanddatasethave been provided to illustrate the effective utilization of this package within Orange3.For additional information, please refer to theguidanceon using this package through widgets in Orange3.DocumentationThe documentation of this work can be found onRead the Docs.ContributingIf you want to contribute to the development of this work, have a look at thecontribution guidelines.CreditsThis work is being developed by theNetherlands eScience Centerin collaboration with theHuman Centered Data Analysis groupat Centrum Wiskunde & Informatica.This package was created with theOrange3 Example Add-on.Go to Top
Package: orangebeard-robotframework
Orangebeard.io Robot Framework ListenerOrangebeard Robot Framework ListenerOrangebeard|InstallationInstallationInstall the pip packagepip install orangebeard-robotframeworkUsageRun your tests as usual with the listener registered:robot \
--listener orangebeard.listener \
--variable orangebeard_endpoint:"https://my-instance.orangebeard-staging.app" \
--variable orangebeard_accesstoken:"your-orangbeard-access-token"  \
--variable orangebeard_project:"project_name" \
--variable orangebeard_testset:"Testset name" \
./tests
Package: orange-canvas-core
Orange Canvas Core is a framework for building graphical user
interfaces for editing workflows. It is a component used to build
the Orange Canvas (http://orange.biolab.si) data-mining application
(for which it was developed in the first place).InstallationOrange Canvas Core is pip installable (https://pip.pypa.io/), simply run:pip install orange-canvas-coreOr use the:pip install ./to install from the sources.DocumentationSome incomplete documentation is available athttps://orange-canvas-core.readthedocs.io
Package: orange-canvas-core-ml
Orange Canvas Core is a framework for building graphical user
interfaces for editing workflows. It is a component used to build
the Orange Canvas (http://orange.biolab.si) data-mining application
(for which it was developed in the first place).InstallationOrange Canvas Core is pip installable (https://pip.pypa.io/), simply run:pip install orange-canvas-coreOr use the:pip install ./to install from the sources.DocumentationSome incomplete documentation is available athttps://orange-canvas-core.readthedocs.io
Package: orangecloud-client
This library is a python implementation of theorange cloud apiIt brings:anapito build other api around the orange cloudacommand line interfaceto directly interact with the cloudDependenciesIt is based on:oauth2 client library, itself based onrequests.requests toolbeltsInstallingFrom pip$pipinstallorangecloud-clientFrom sourcesTo build the library run :$pythonsetup.pyinstallRun the OAuth Grant code processTo start using it you must create adeveloperaccount on theorange partner platform.
Then create an application. But beware on one things: theredirect urlmust differ from anylocalhostor local url.
Since we want to trick it, do as follow:pick a domain name suchhttp://my-own-cloud.io:8080(do not use https as it cannot be handled later)create the applicationmap thedomainmy-own-cloud.ioonlocalhostin yourhost file(/etc/hostsfor linux,%systemroot%\system32\drivers\etc\for windows)run the following code# provide the client id and client secret got on your application pageapi_manager=ApiManager(client_id,client_secret)# in this example the redirect url  is http://myowncloud.io:8080 and /etc/hosts contains the line# 127.0.0.1       myowncloud.ioredirect_uri='http://myowncloud.io:8080'url_to_open=api_manager.init_authorize_code_process(redirect_uri=redirect_uri,state='1234')print'Open this URL:%s'%url_to_opencode=api_manager.wait_and_terminate_authorize_code_process()api_manager.init_with_authorize_code(redirect_uri=redirect_uri,code=code)print'refresh_token got%s'%api_manager.refresh_tokenThis will run alocal http server listening to your domain, print an url to open.Open it in your browser,
log in using your cloud account, consent the access for your application.
You will be then redirected to yourlocal http server. The code will be then extracted and exchanged for a token.
You can save yourrefresh token. Next time you can instantiate theApiManageras follows:api_manager=ApiManager(client_id,client_secret)api_manager.init_with_token(refresh_token)You are now fully able to use the api.APIThe api brings the followingdomains.FreeespaceThe only operation on this endpoint is thegetone that returns the available free space.FoldersThis endpoint let you:getthe information about afolder(See the `documentation <https://developer.orange.com/apis/cloud-france/api-reference>`_ about the `query parameters`)createafolderin the clouddeleteafolderfrom the cloudmoveafolderfrom onefolderto anotherrenameafoldercopyafolderin anotherfolderFilesThis endpoint let you:getthe information about afile.deleteafilefrom the cloudmoveafilefrom onefolderto anotherrenameafilecopyafilein anotherfolderuploadafileon the clouddownloadafilefrom the cloudCommand Line interfaceTo run the client, enter the following command :$orangecloud-clientAt first execution, it will ask you ask.
Please note that your credentials won’t be saved on your disk: only tokens will be kept for further use.
Please not that the commandshellruns an interactive shell to interact with the cloud.
Other commands are single command and return after finished.Issues and contributionsPlease submit issue/pull request.
Package: orangepipes
orangepipesA python library to read pipeline environment variables from orange.yml file and apply to OS.orange.yml

... 

pipelines:
  global:
    env:
      APP_NAME: sample
      APP_PORT: 8080    
  app_example:
    env:
      APP_PORT: 3000
...How to useFollowAWS Codeartifactsteps to configure pippip install orangepipesfrom orangepipes import pipeline

pipeline.apply_orange_envs()
Package: orangery
Orangery is a Python library to support analysis of topographic cross-sections, particularly on stream channels. The intent is to enable the user to write simple scripts that operate on CSV data exported from a survey data collector.Orangery was initially a single script that allowed me to segregate, by grain size, changed areas on repeat topographic cross-sections. It can produce output plots like the one below.InstallationTo install from the Python Package Index:$pip install orangeryTo install from the source distribution execute the setup script in the orangery directory:$python setup.py installTo install from Anaconda Cloud:If you are starting from scratch the first thing to do is install the Anaconda Python distribution, add the necessary channels to obtain the dependencies and install orangery.$condaconfig--appendchannelsconda-forge$condaconfig--appendchannelsmrahnis$condainstallorangeryTo install from the source distribution:Execute the setup script in the orangery directory:$pythonsetup.pyinstallExamplesThe example scripts may be run like so:$python plots.pyLicenseBSDDocumentationLatesthtml
Package: orangesms
Orange SMS API 📬Orange SMS is a client library that allow you to send SMS with Python using theOrange SMS APIDisclaimer ⛔This gem is not an official client of Orange, in order to use the client you need to create aOrange SMS APIand to register an app in the developer dashboard that orange provide to you.After registering your app you can ask for SMS integration approval (this process can take time :)The registration process is detailedhereInstead of reading and trying to understand once again how the Orange SMS API work this gem aims to let you quickly send SMS from Python using theOrange SMS API.Install 📥Via PIPpython -m pip install orange-sms-clientUsage ✅Copy your client idhere(if you have already create an app)generate token withgetTokenfunctionsend sms withsendSMSfunctionExemple :usageExample.pyPython 🐍clientID="your clientID"token=getToken(clientID)senderAdress="+2210000"address="+221{{receiver}}"sendSMS(senderAddress,receiverAddress,"message",token)Contributing 🤝Bug reports and Pull Requests are welcome 👋🏽You can tell meHERELicense 🔖This project is underMIT License.
Package: orange-story-navigator
Orange3 Story NavigatorOrange3-Story-Navigator is an add-on for the Orange data mining software package. It
provides story textual analysis features based on principles in narrative psychology. The aim of the widgets in the Story Navigator module are to support human analysis of stories represented in digital texts with a main focus on identifying and describing the following components of the narrative:SettingMain agent(s)MeansActs and eventsPurposeBreachSee:[1] Burke, K. (1969). The grammar of motives. Prentice Hall, New York. Originally published in 1945.
[2] M. Murray and A. Sools, P. Rohleder, A.C. Lyons (Eds.), Qualitative research in clinical and health psychology, Palgrave MacMillan, Houndmills Basingstoke (2015), pp. 133-154Seedocumentation.FeaturesStory analysis widgets to:automate annotation of named entities in the story (characters, locations, events etc.)identify topics of discourse in stories and how these topics change as the narrative progressescalculate character agency (through novel metrics for character agency)analyse narrative arc in a story by visualising changes in character agency, descriptions and writing stylegenerate and analyse networks of characters, actions and objects involved in the narrative
Package: oras
ORAS PythonOCI Registry as Storage enables libraries to push OCI Artifacts toOCI Conformantregistries. This is a Python SDK for Python developers to empower them to do this in their applications.See our ⭐️Documentation⭐️ to get started.Code of ConductPlease note that this project has adopted theCNCF Code of Conduct.
Please follow it in all your interactions with the project members and users.😁️ Contributors 😁️We use theall-contributorstool to generate a contributors graphic below.Vanessasaurus💻Lachlan Evenson💻Steve Lasker💻Josh Dolitsky💻Bridget Kromhout💻Matt Warner💻Wolf Vollprecht💻Shiwei Zhang💻jhlmco💻Ananya Gupta💻sunnycarter💻Marius Bertram💻Tiziano Müller💻Terry Howe💻Saket Jajoo💻Mike💻deoxy💻LicenseThis code is licensed under the Apache 2.0LICENSE.
Package: orator-validator
This is a orator plugin that you can use to validate
your model when the user is creating a new item or
updating one on the database is easy to use and cleans
the code a lotInstallationYou can install the plugin by using pip$pipinstallorator-validatorHow to use itSetupthis is an example of how to implement on your orator modelfromoratorimportModelfromorator_validatorimportValidatorclassUser(Model,Validator):__connection__='local'__fillable__=['name','email','password','phone_number']__guarded__=['id','password']classUserValidation(object):'''Here goes the validations that you need'''User.observe(UserValidation())Functions availableValidate saving functionthe validate function accepts this paramsrequire:boolean when True checks if they send the valuedata_type:object Verifies if the value is specific data typeregex:string pass a regex to verifieddate_str:string witch you want to check the format of the date example ‘%H:%M’Exampledefsaving(self,user):user.validate('name',require=True,data_type=str)user.validate('email',regex="(?:[a-z0-9!#$%&'*+/=?^_`{|}~-]+(?:\\.[a-z0-9!#$%&'*+/=?^_`{|}~-]+)*|\"(?:[\\x01-\\x08\\x0b\\x0c\\x0e-\\x1f\\x21\\x23-\\x5b\\x5d-\\x7f]|\\[\\x01-\\x09\\x0b\\x0c\\x0e-\\x7f])*\")@(?:(?:[a-z0-9](?:[a-z0-9-]*[a-z0-9])?\\.)+[a-z0-9](?:[a-z0-9-]*[a-z0-9])?|\\[(?:(?:(2(5[0-5]|[0-4][0-9])|1[0-9][0-9]|[1-9]?[0-9]))\\.){3}(?:(2(5[0-5]|[0-4][0-9])|1[0-9][0-9]|[1-9]?[0-9])|[a-z0-9-]*[a-z0-9]:(?:[\\x01-\\x08\\x0b\\x0c\\x0e-\\x1f\\x21-\\x5a\\x53-\\x7f]|\\[\\x01-\\x09\\x0b\\x0c\\x0e-\\x7f])+)\\])")user.validate('password',regex="^(?=.*[A-Za-z])(?=.*\\d)(?=.*[@$!%*#?&])[A-Za-z\\d@$!%*#?&]{6,}$")user.errors()Validate update functionthe validate_update accepts this paramsguarded:boolean if True value cannot be updateddata_tpe:needs to send specific data typeregex:regex to validate the valuedate_str:string to validate a date formatfunction_callback:callback function if the value was sendargs:arguments for the function callbacksExampledefupdating(self,user):user.validate_update('email',guarded=True)user.validate_update('password',function_callback=self.__validate_new_password,user=user)user.errors()def__validate_new_password(self,user):'''
    Validate that the new password is diferent than the old one
    '''User.find(user.id)ifuser.password==User.find(user.id).password:raiseException("Can't update password with old one")Process functionthe process function acceptsexist:function uses as a callback if the value was sendnot_exist:function uses as a callback if the value was not sendargs:arguments for the function callbacksExampledefsaving(self,user):user.process('phone_number',exist=self.__process_phone)user.errors()def__process_phone(self,user):'''
    This function process the phone if the user send one
    '''ifuser.phone[0]!="+":user.phone="+1{}".format(user.phone)
Package: orats
ORATS Python SDKBEWAREThis project isunstableand in early stages of development!This project is a wrapper aroundORATSAPIs.NOTE: ORATS offers numerous subscription services.
Depending on your personal subscriptions, you will be issued an API key with
appropriate permissions. Some functionality in this SDK may not be accessible
if you are not subscribed to the necessary services.Project StructureDevelopment ToolingSource Control Management:Git+GitHubDocumentation:Sphinx+GitHub PagesCI/CD:GitHub ActionsCode Style:BlackType Checker:mypyTest Runner:tox+pytest
Package: orb
orb===A utility wrapper for pip_ and virtualenv_.description-----------A shell script facade for creating virtual python environments via virtualenv_and installing packages within the environment via pip_.install-------virtualenv_ must be available, eg. in Ubuntu:$ sudo apt-get install python-virtualenvpip_ need not be available - it is installed every time to a new environment.To install, use easy_install to install from pypi.python.org::easy_install -Z orbor simply copy the orb script from the source distribution, eg. ::$ sudo cp orb /usr/local/binusage-----Create a virtualenv with the command$ orb init myenvor$ orb init2 myenvto use the latest Python2 as the executable, or$ orb init3 myenvto use the latest Python3 as the executable, or$ orb init?.? myenv(eg. orb init2.6 or orb init3.2) to specify a particular Python version asthe executable... note::the various python versions are assumed to be installed and on the user'sPATHThis creates a virtualenv called 'myenv' and creates an empty '.orb'file within the virtualenv directory. Subsequent orb commands first searchfor the '.orb' file and from this file's location the virtualenv's bin directoryis known.To install packages to the env, run the 'orb install' command from within theenv directory::cd myenvorb install Pygmentsorb install BeautifulSoupwhich calls 'pip_' to do the actual downloading and installation.If passed a python script, orb will call it using the virtualenv's pythoneg. orb setup.py installand if passed any command expression, orb will temporarily alter theenvironment (ie. pip's `source activate` step) before eval-ing the command::eg. (Django): orb django-admin.py startproject myprojeg. (Python prompt): orb pythoneg. (Sphinx quickstart): orb sphinx-quickstarteg. (Sphinx build): orb make htmleg. (Arbitrary command) orb ./myshellscriptOther options:orb ls      - list contents of env's site-packages directoryorb link    - symlink from the virtual env's site-packages to a system packageorb download PACKAGE [DEST]- just download package, don't install.. _virtualenv: http://pypi.python.org/pypi/virtualenv/.. _pip: http://pip.openplans.org/index.html
Package: orb-api
orb======================The ORB library is an object-oriented, pythonic, object relational mapperfor databases.Installation-----------------------If you would like to use the latest build that has been tested and published,you can use the Python `setuptools` to install it to your computer or virtualenvironment:pip install orb-apiIf you would like to use the latest code base, you can clone the repositoryand reference and run `setup.py` for your virtual environmentgit clone https://github.com/orb-framework/orb.gitcd orbpython setup.py developRunning Tests-----------------------To run the unit tests, you can just run the test command from the setuptoolspython setup.py testTo run the functional tests, you will need to specify the test environment using the[tox](https://testrun.org/tox/latest/) command line utility.pip install toxtox -e postgresDocumentation---------Documentation for orb is written and hosted in [GitBook](https://www.gitbook.com/book/orb-framework/orb)
Package: orbax
OrbaxOrbax is no longer a standalone package, and should not be installed directly.Orbaxis a namespace providing common
utility libraries for JAX users.Please installorbax-checkpointororbax-exportinstead, for model
checkpointing and exporting utilities respectively. By default, installingorbaxwill installorbax-checkpoint.SupportContactorbax-dev@google.comfor help or with any questions about Orbax!HistoryOrbax was initially published as a catch-all package itself. In order to
minimize dependency bloat for users, we have frozen that package atorbax-0.1.9, and will continue to release future changes under the
domain-specific utilities listed above (e.g.orbax-checkpoint).As we have preserved the orbax namespace, existing import statements can remain
unchanged (e.g.from orbax import checkpoint).
Package: orbax-checkpoint
Orbax Checkpointingpip install orbax-checkpoint(latest PyPi release) ORpip install 'git+https://github.com/google/orbax/#subdirectory=checkpoint'(from this repository, at HEAD)import orbax.checkpointOrbax includes a checkpointing library oriented towards JAX users, supporting a
variety of different features required by different frameworks, including
asynchronous checkpointing, various types, and various storage formats.
We aim to provide a highly customizable and composable API which maximizes
flexibility for diverse use cases.
Package: orbax-export
Orbax Exportpip install orbax-export(latest PyPi release) ORpip install 'git+https://github.com/google/orbax/#subdirectory=export'(from this repository, at HEAD)import orbax.exportOrbax includes a serialization library for JAX users, enabling the exporting of JAX models to the TensorFlow SavedModel format.Note thatorbax-exportrequires TensorFlow, but does not include it by default to allow for flexibility in version choice. If you wish to install with standard TensorFlow, please usepip install orbax-export[all].To get started, check out ourdocumentation.