Saravanan666/pypi-org huggingface dataset:
Package: opensesame-plugin-omexp
OMEXP pluginsWe introduce a set of plugins for OpenSesame that enable the implementation of behavioural and cognitive tasks involving advanced audio playback.
For clarity we refer to the OpenSesame platform enhanced with these plugins as the Oticon Medical Experiment Platform (OMEXP).The list of plugins added to OpenSesame to constitute OMEXP are summarized below and described in details in the following section.LSL start: initializes the Lab Streaming Layer (LSL) protocol (seehttps://labstreaminglayer.readthedocs.io/index.html) and starts the recording. It allows to select the folder in which the recording will be saved and the filename under which the data should be saved.LSL message: allows to timestamp an acquisition stream synchronized with the recording. It is useful, for example, to save the exact instant when a stimulus is shown to the user. The recordings are synchronized and saved in an XDF file format (Extensible Data Format), seehttps://labstreaminglayer.readthedocs.io/info/intro.html.LSL stop: stops and saves the recordings.Adaptive init: implements an adaptive method for psychoacoustic experiments, specifically the transformed up-down methodology implements the procedure introduce by Levitt in 1971. It can specify parameters of the up-down procedure, such as the
step size, the number of reversals or trials after which the step-size change may occur, the variable holding the tracked value and its starting
value.Adaptive next: changes the tracked variable according to the settings specified in the adaptive routine init plugin.Audio Mixer: allows to play sounds in different audio channels with different levels. for example, this plugin is particularly useful for multi-loudspeaker studies, with for example 5 loudspeakers $(0Â°, 90Â°, 150Â°, 210Â°, 270Â°)$, where the front speaker is to be assigned with a target sound, and side speakers are speech maskers and back speakers are speech masker and noise, and you want to set different dB level for each channel. In addition, LSL markers are created within the Audio Mixer plugin, at the beginning and at the end of the audio sounds sequence.Calibration: enables to do the audio calibration of the setup and must be placed before the use of the Mixer plugin.General informationThe code is published under the GNU General Public License (version 3).
However, the standalone libraries are Oticon Medical Copyrighted.InstallationThe instructions and the original  code are available in github: (https://github.com/elus-om/BRM_OMEXP)ExampleWe exemplify the use of this extended OpenSesame platform with an implementation of the 3-alternative forced choice amplitude modulation detection test. The test is shared in the example folder in GitHub.AcknowledgementOMEXP plugins extends OpenSesame platform developed by the development team led by Sebastiaan $Math\hat{o}t$.
Package: opensesame-plugin-parallel-port-trigger
OpenSesame Plug-in: Parallel Port TriggerAn OpenSesame plug-in for sending stimulus synchronization triggers through the parallel port to data acquisition systems.Copyright, 2022, Bob RosbagContributions: Code is based on the work of Per Sederberg. Debugged and polished by Edwin Dalmaijer.1. AboutIn EEG/ERP studies it is common to send triggers to mark the timestamp for significant events (e.g., the onset of a trial, presentation of a particular stimulus, etc.). Triggers are typically bytes that are sent via the parallel port to data acquisition systems.The plug-in has aninititem which should be placed at the beginning of an experiment and atriggeritem for initiating triggers:Dummy modefor testing experiments.Port adressfor Windows: hexadecimal or decimal value, for Linux: full path or port number.Valueis a positive integer between 1-255 and specifies the trigger byte.Enable durationoption to enable the duration parameter.Durationis the duration in ms.Linux and Windows are supported (possible also OSX, not tested). For Windows theDLPortIO.dlldriver is used to access the parallel port. No need for driver installation.Documentation:http://osdoc.cogsci.nl/devices/triggers/2. LICENSEThe Parallel Port Trigger plug-in is distributed under the terms of the GNU General Public License 3.
The full license should be included in the file COPYING, or can be obtained fromhttp://www.gnu.org/licenses/gpl.txtThis plug-in contains works of others.3. DocumentationInstallation instructions and documentation on OpenSesame are available on the documentation website:http://osdoc.cogsci.nl/
Package: opensesame-plugin-psychopy
PsychoPy plugins for OpenSesameCopyright (2016-2023) Sebastiaan MathôtInstallationIn a terminal:pip install psychopy-plugin-opensesameSee also:https://rapunzel.cogsci.nl/manual/environment/AboutCurrently, there are two plugins:psychopy_gratingstimpsychopy_textstimTheGratingStimandTextStimare visual stimuli from PsychoPy, a Python library for psychology. With these plugins, you can use these stimuli easily within OpenSesame, a graphical experiment builder for the social sciences. You can use the plugin in OpenSesamecoroutines, and adjust their properties periodically; this allows you, for example, to implement a drifting gabor patch.LicenseThis software is distributed under the terms of the GNU General Public License 3. The full license should be included in the fileCOPYING, or can be obtained from:http://www.gnu.org/licenses/gpl.txt
Package: opensesame-plugin-radboudbox
OpenSesame Plug-in: Radboud ButtonboxAn OpenSesame plug-in for collecting button responses, audio detection, voice key and sending stimulus synchronization triggers with the Radboud Buttonbox to data acquisition systems.Copyright, 2022, Bob RosbagThis plugin makes use of the RuSocSci python package developed by Wilbert van der Ham. Radboud Buttonbox is developed by Pascal de Water. Exact references will follow in the future.1. AboutThe Technical Support Group (Radboud University, Social Sciences) developed an USB Arduino based Buttonbox which can be used for time accurate(1ms) button press, voice key, sound key registration and sending parallel port like triggers.
Upper case A, B, C, D, E, F are used for key presses, and lower case a, b, c, d, e, f are used for key releases. Uppercase S is used for sound key detection and uppercase V for voice key.For more information:http://tsgdoc.socsci.ru.nl/index.php?title=ButtonBoxesThis plug-in consist of foreground and background (multithreaded) items.Difference between foreground and background:Foregrounditem starts button/signal registration until it detects an allowed button or the set duration has passed.Backgrounditem consist of a 'start' and 'wait' item. These are fully multi-threaded. After the start of the button/signal registration, the item will immediately advance to the next item. When the experiment reaches the 'wait' item, it will wait until a button/signal has been detected by the 'start' item or the duration has passed.This plug-in has six items:Initinitialization of the buttonbox, this should be placed at the beginning of an experiment.Wait Buttonswaits for a button press or release before continuing to the next item in the experimentGet Buttons Startstarts a new thread which monitors for button presses/releases, it will directly advance to the next item in the experimentGet buttons Waitwaits until the thread from 'Get Buttons Start' is finished (has detected a button press/release) before advancing to the next item in the experimentSend Controlsend control code to the buttonbox, for example 'Calibrate Sound', 'Detect Sound'Send Triggerfor sending triggers to hardware with a parallel portTimestamps can be found in the logs by the name: time_response_[item_name]Linux, and Windows are supported (possible also OSX, not tested). The plug-in will first look for the globally installed rusocsci package. If this is not available, the shipped version will be used. Install options are listed below.2. LICENSEThe Radboud Buttonbox plug-in is distributed under the terms of the GNU General Public License 3.
The full license should be included in the file COPYING, or can be obtained fromhttp://www.gnu.org/licenses/gpl.txtThis plug-in contains works of others.3. DocumentationInstallation instructions and documentation on OpenSesame are available on the documentation website:http://osdoc.cogsci.nl/
Package: opensesame-plugin-titta-eyetracking
OpenSesame Plugin: Titta Eye TrackingCopyright, 2023, Bob Rosbag, Diederick C. Niehorster & Marcus NyströmAboutThis plugin implements Titta in OpenSesame for Eye Tracking.Titta is a toolbox for using eye trackers from Tobii Pro AB with Python, specifically offering integration with PsychoPy. A Matlab version that integrates with PsychToolbox is also available fromhttps://github.com/dcnieho/Titta. For a similar toolbox for SMI eye trackers, please seewww.github.com/marcus-nystrom/SMITE.Cite as: Niehorster, D.C., Andersson, R. & Nystrom, M. (2020). Titta: A toolbox for creating PsychToolbox and Psychopy experiments with Tobii eye trackers. Behavior Research Methods. doi: 10.3758/s13428-020-01358-8Please mention: Bob Rosbag as creator of this pluginFor questions, bug reports or to check for updates, please visithttps://github.com/marcus-nystrom/Titta.To minimize the risk of missing samples, the current repository uses TittaPy (pip install TittaPy), a C++ wrapper around the Tobii SDK, to pull samples made available from the eye tracker.LicenseThe Titta Eye Tracking plugin is distributed under the terms of the Creative Commons Attribution 4.0 International Public License
The full license should be included in the file LICENSE.mdKnown bugsIn dummy mode, when the experiment is finished, OpenSesame will not return to the GUI. The button with the cross and text: 'Forcibly kill the experiment' has to be used to end the session and get back to the GUI. This only happens when in dummy mode and the cause resides somewhere in the 'calibrate' command.NotesOne recording per experiment is working properly. Per trial recording (multiple starts en stops within an experiment) has not yet been tested.
Package: openshield
OpenShieldOpenShield is a simple and fast antivirus that allows you to scan various files to find malware on your computer. The database used to perform the malware search comes fromMalwareBazaar. The project is written in Python and open-source, it can be used via command-line interface (CLI).Getting startedInstall the program using the PIP package manager or install it manually by cloning the repository:pip install openshieldgit clone https://github.com/jaedsonpys/openshield.git
cd openshield/
python3 setup.py installHow to useTo scan files and/or directories, use theopenshield scancommand and pass as argument the name of the directory or file. Here is an example:openshield scan ~/DownloadsNow scanning multiple files at once:openshield scan script.py MyAplication.exeYou will receive a warning message if malware is found, the advice is to delete the file as soon as possible anddo not run or openit.
Package: openshift-cluster-login
OCL (OpenShift Login)OCL does an automatic login to an OpenShift cluster. It fetches cluster information from app-interface and performs a login viaSelenium.InstallationYou can install this library fromPyPIwithpip:$python3-mpipinstallopenshift-cluster-loginor install it withpipx:$pipxinstallopenshift-cluster-loginYou can also usepipxto run the library without installing it:$pipxrunopenshift-cluster-loginUsage$oclThis spawns a new shell with the following environment variables are set:KUBECONFIG- path to kubeconfig fileOCL_CLUSTER_NAME- cluster nameOCL_CLUSTER_CONSOLE- url to cluster consoleFeaturesOCL currently provides the following features (get help with-hor--help):OpenShift console login (oc login) via GitHub or Red Hat authenticationGet cluster and namespace information from app-interface or user-defined (OCL_USER_CLUSTERS``) _ Open the OpenShiftconsole inthebrowser`` (--open-in-browser)Shell completion (--install-completion,--show-completion)Credentials via environment variables or shell command (e.g.,1password CLI)Cache App-Interface queries (via GraphQL) for one weekEnvironment VariablesVariable NameDescriptionDefaultOCL_WAIT OCL_WAIT_COMMANDSelenium webdriver wait timeout2OCL_APP_INTERFACE_URL OCL_APP_INTERFACE_URL_COMMANDApp-Interface URLOCL_APP_INT_TOKEN OCL_APP_INT_TOKEN_COMMANDApp-Interface authentication tokenUSER_CLUSTERS USER_CLUSTERS_COMMANDUser defined clusters as json format (e.g.[{"name": "local-kind", "serverUrl": "https://localhost:6443", "consoleUrl": "not available}])"[]"You can either set a variable, e.g.export OCL_GITHUB_USERNAME="mail@example.com"or retrieve it via a command, e.g.export OCL_GITHUB_USERNAME_COMMAND="op read op://Private/Github/username".
If a variable is not set but needed, OCL will ask for it interactively.App-InterfaceOCL retrieves the cluster information from app-interface via GraphQL (OCL_APP_INTERFACE_URL) and caches them
in your usercache directory(on MacOS, e.g.,~/Library/Caches/ocl/gql_cache/).
Remove this directory to force a refresh.LimitationsKerberos authentication onlyWorks only with a Red Hat associate accountDevelopmentUseConventional Commit messages.
The most important prefixes you should have in mind are:fix:which represents bug fixes, and correlates to aSemVerpatch.feat:which represents a new feature, and correlates to a SemVer minor.feat!:,  orfix!:,refactor!:, etc., which represent a breaking change
(indicated by the!) and will result in a SemVer major.chore: releaseto create a new releaseConsider using an empty commit:git commit --allow-empty -m "chore: release"When a commit to the main branch hasRelease-As: x.x.x(case insensitive) in thecommit body, Release Please will open a new pull request for the specified version.git commit --allow-empty -m "chore: release 2.0.0" -m "Release-As: 2.0.0"
Package: openshift-cluster-management-python-wrapper
openshift-cluster-management-python-wrapperWrapper foropenshift-cluster-management-python clientRelease new versionrequirements:Export GitHub tokenexportGITHUB_TOKEN=<your_github_token>release-itRun the following once (execute outside repository dir, for example~/):sudonpminstall--globalrelease-it
npminstall--save-dev@release-it/bumperusage:Create a release, run from the relevant branch.To create a 1.0 release, run:gitcheckoutv1.0
gitpull
release-it# Follow the instructionsInstallationFrom source:gitclonehttps://github.com/RedHatQE/openshift-cluster-management-python-client.gitcdopenshift-cluster-management-python-client
pythonsetup.pyinstall--userExamplesClientfromocm_python_wrapper.ocm_clientimportOCMPythonClientocm_client=OCMPythonClient(token=<ocmapitoken>>,endpoint=<endpointurl>,api_host=<productionorstage>,discard_unknown_keys=True,)returnocm_client.clientClusterfromocm_python_wrapper.clusterimportClustercluster=Cluster(client=client,name=<clustername>)cluster_ocp_version=cluster.instance.version.raw_id
Package: openshift-python-utilities
openshift-python-utilitiesPypi:openshift-python-utilitiesA utilities repository foropenshift-restclient-pythonRelease new versionrequirements:Export GitHub tokenexportGITHUB_TOKEN=<your_github_token>release-itRun the following once (execute outside repository dir for example~/):sudonpminstall--globalrelease-it
npminstall--save-dev@release-it/bumperusage:Create a release, run from the relevant branch.To create a 4.11 release, run:gitcheckoutv4.11
gitpull
release-it# Follow the instructions
Package: openshift-python-wrapper
openshift-python-wrapperPypi:openshift-python-wrapperA python wrapper forkubernetes-python-clientwith support for RedHat Container Virtualization. (Openshift Virtualization)
Docs:openshift-python-wrapper docsInstallationFrom source:gitclonehttps://github.com/RedHatQE/openshift-python-wrapper.gitcdopenshift-python-wrapper
pythonsetup.pyinstall--userFrom pypi:pipinstallopenshift-python-wrapper--userRelease new versionrequirements:Export GitHub tokenexportGITHUB_TOKEN=<your_github_token>release-itsudonpminstall--globalrelease-it
npminstall--save-dev@release-it/bumperusage:Create a release, run from the relevant branch.To create a 4.11 release, run:gitcheckoutv4.11
gitpull
release-it# Follow the instructionsdocsHosted on readthedocs.ioopenshift-python-wrapperPR dependencyFor PR dependency we usedpullsTo make PR depends on other PR adddepends on #<PR NUMBER>in the PR description.Logging configurationTo change log level export OPENSHIFT_PYTHON_WRAPPER_LOG_LEVEL:exportOPENSHIFT_PYTHON_WRAPPER_LOG_LEVEL=<LOG_LEVEL># can be: "DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"Code checkWe use pre-commit for code check.pre-commitinstallSome code examples locate atexamplesdirectoryContribute to the projectTo contribute new additions or changes to the project, please refer to thecontribution guidefirst.
Package: openshift-python-wrapper-data-collector
To enable data-collector pass data-collector.yaml
YAML format:data_collector_base_directory:"<basedirectoryfordatacollection>"collect_data_function:"<importpathfordatacollectionmethod>"collect_pod_logs:true|false# bool whether to collect logs if resource is a podYAML Exampleocp_utilities/data-collector.yaml:data_collector_base_directory:"collected-info"collect_data_function:"data_collector.collect_data"collect_pod_logs:trueEither export path to yaml file inOPENSHIFT_PYTHON_WRAPPER_DATA_COLLECTOR_YAMLor setdata_collectorin your py_config
The environment variable takes precedence over py_config.To use dynamic base directory, exportOPENSHIFT_PYTHON_WRAPPER_DATA_COLLECTOR_DYNAMIC_BASE_DIRExample:data_collector_base_directory = "/data/results/collected-info"
OPENSHIFT_PYTHON_WRAPPER_DATA_COLLECTOR_DYNAMIC_BASE_DIR = "dynamic_collector_test_dir"

Result: /data/results/dynamic_collector_test_dir/collected-info
Package: opensign
IntroductionA library to facilitate easy RGB Matrix Sign Animations.DependenciesThis library depends on:Henner Zeller RPi RGB LED MatrixPython Bindings for RGB Matrix LibraryPython Imaging Library (Pillow)Installing from PyPIOn supported GNU/Linux systems like the Raspberry Pi, you can install the driver locallyfrom
PyPI. To install for current user:pip3installopensignTo install system-wide (this may be required in some cases):sudopip3installopensignTo install in a virtual environment in your current project:mkdirproject-name&&cdproject-namepython3-mvenv.envsource.env/bin/activatepip3installopensign
Package: opensignals
Open SignalsInstallpip install -U opensignalsUsagefrompathlibimportPathfromopensignals.data.yahooimportYahoofromopensignals.featuresimportRSI,SMAdb_dir=Path('db')yahoo=Yahoo()yahoo.download_data(db_dir)features_generators=[RSI(num_days=5,interval=14,variable='adj_close'),RSI(num_days=5,interval=21,variable='adj_close'),SMA(num_days=5,interval=14,variable='adj_close'),SMA(num_days=5,interval=21,variable='adj_close'),]train,test,live,feature_names=yahoo.get_data(db_dir,features_generators=features_generators)
Package: open-singly
Implementation of singly API for PythonInstallationpip install open-singlyorpip install git+https://github.com/MagicSolutions/open-singly.gitHow to usefrom open_singly import Singly

client_id = 'My_Client_ID'
client_secret = 'My_Client_Secret'
redirect_uri = 'http://www.mywebsite.com/singly/callback/'

singly = Singly(client_id, client_secret, redirect_uri)

# Get authentication URL for facebook for example
auth_url = singly.get_authentication_url('facebook')

# The user must be redirected to this URL. After authentication
# Singly will redirect user to your redirect_uri
# in the GET parameters there will be a code which You must
# provide to Singly.authenticate metod

api = singly.authenticate(code)

# After successfull authentication you can execute all methods
# provided from Singly API like that

all_profiles = api.profile.get(verify='true')

facebook_data = api.profiles.facebook.get()

facebook_friends = api.services.facebook.friends.get()Enjoy!
Package: opensink
# OpenSink: All the OpenStack APIs in one placeDo you sometimes need to write scripts that interact with the
OpenStack API?  Do you always find yourself spending more time trying
to remember how to get a valid Nova client than actually writing your
scripts?This is for you.## UsageAssuming that you have the standard suite ofOS_*environment
variable available, then usingopensinkis as simple as:>>> import opensink.openstack
>>> clients = opensink.openstack.OpenStack()Need a list of users?>>> c.keystone.users.find(name='lars')
<User {u'username': u'lars', u'name': u'lars', u'enabled': True,
u'tenantId': u'f4e7e158cb154de5ab503bd7096b8981', u'id':
u'065e9427a1f14f9398082e5bed3d3fb7', u'email': u'lars@oddbit.com'}>Or a list of servers?>>> clients.nova.servers.list()
[<Server: larstest-server-23dwogjbq3ux>, <Server: cirros>]Want to create a Cinder volume?>>> clients.cinder.volumes.create(1)
<Volume: e61ffb18-7d97-4dde-ba70-b256df7b709f>How about a list of resources in your heat stack?>>> [ r.to_dict()['resource_name']
... for r in clients.heat.resources.list(id)]
[u'server_floating', u'secgroup_all_open', u'server_eth0', u'server']
Package: openskill
A faster and open license asymmetric multi-team, multiplayer rating system comparable to TrueSkill.DescriptionIn the multifaceted world of online gaming, an accurate multiplayer rating system plays a crucial role. A multiplayer rating system measures and compares players' skill levels in competitive games to ensure balanced match-making, boosting overall gaming experiences. Currently, TrueSkill by Microsoft Research is a notable rating system, but gaming communities are yearning for faster, more adaptable alternatives.Here aresome, but not all, of the reasons you should drop TrueSkill
and bury Elo once and for all:Multiplayer.Multifaction.Asymmetric faction size.Predict Win, Draw and Rank Outcomes.150% faster than TrueSkill.100% Pure Python.100% Test Coverage.CPython and PyPy Support.5 Separate Models.Fine-grained control of mathematical constants.Open LicenseUp to 7% more accurate than TrueSkill.InstallationpipinstallopenskillUsageThe official documentation is hostedhere.
Please refer to it for details on how to use this library.Limited Example>>>fromopenskill.modelsimportPlackettLuce>>>model=PlackettLuce()>>>model.rating()PlackettLuceRating(mu=25.0,sigma=8.333333333333334)>>>r=model.rating>>>[[a,b],[x,y]]=[[r(),r()],[r(),r()]]>>>[[a,b],[x,y]]=model.rate([[a,b],[x,y]])>>>aPlackettLuceRating(mu=26.964294621803063,sigma=8.177962604389991)>>>xPlackettLuceRating(mu=23.035705378196937,sigma=8.177962604389991)>>>(a==b)and(x==y)TrueSupportIf you're struggling with any of the concepts, please search the discussions section to see if your question has already been answered.
If you can't find an answer, please open a newdiscussionand we'll try to help you out.
You can also get help from the officialDiscord Server. If you have a feature request, or want to report
a bug please create a newissueif one already doesn't exist.ReferencesThis project is originally based off theopenskill.jspackage. All of the Weng-Lin models are based off the work in this wonderfulpaperor are the derivatives of algorithms found in it.Julia Ibstedt, Elsa Rådahl, Erik Turesson, and Magdalena vande Voorde. Application and further development of trueskill™ ranking in sports. 2019.Ruby C. Weng and Chih-Jen Lin. A bayesian approximation method for online ranking. Journal of Machine Learning Research, 12(9):267–300, 2011. URL:http://jmlr.org/papers/v12/weng11a.html.Implementations in other LanguagesJavascriptElixirKotlinLua