Saravanan666/pypi-org huggingface dataset:
Package: lirc2hass
lirc2hassListen for input events detected byInputLIRCand generate events inHome Assistant. Primarily useful for triggering Home Assistant automations using Logitech Harmony remotes via an LIRC-compatible remote control.Thelirc2hassdaemon generates Home Assistant events when input events are received from an IR receiver by InputLIRC. Home Assistant automations can be triggered by these events, which can then call any services available to Home Assistant, such as turning lights on and off, close blinds, etc.It is the missing link that allows buttons on the Logitech Harmony remote to trigger any device that can be controlled by Home Assistant, where the Home Assistant server cannot be physically collocated with the Harmony Hub. (If it were, then you could use theLIRC integrationdirectly on the HA server.)Installationlirc2hassshould run on most Linux installations (tested on Rasperry Pi OS) and requires the following:an IR receiver that is supported by inputlirc and connected locally to the system.inputlircpackage installed and configured on the underlying operating system to read and process input from the IR receiver.Install the latest release of this package via PyPi:pip install lirc2hassRun the daemon usinglirc2hass hass_base_url -a, wherehass_base_urlis the base URL for your instance of Home Assistant.systemdconfigurationConfiguresystemdto start the daemon at boot by installinglirc2hass.serviceinto/etc/systemd/systemafter editing to suit your installation.If the daemon is run as a non-root user, ensure that user has the necessary privileges to read from the LIRC socket. On Debian-based systems, membership of groupinputis required to read the LIRC socket, located at/var/run/lirc/lircd.Logitech Harmony configurationTODOAdd Windows MCE controller as a device in Harmony setupPosition IR receiver to reliably receive IR commands from Harmony (or mini-IR blaster)Home Assistant configurationTODO(optional) Add new Home Assistant admin userCreate long-lived authorisation token for userPass token tolirc2hassusing--hass-auth-tokenoptionOptionsOptionType/DefaultDescription-a|--hass-auth-tokenauth_tokenEnable sending of authorisation header, usingauth_tokenas the token.-A|--hass-auth-token-filefilenameRead authorisation token fromfilename.-l|--lirc-sock-path/var/run/lirc/lircdSet path to LIRC socket.-c|--max-reconnect-delay64Set maximum reconnect delay for the LIRC socket. The daemon reconnects automatically on disconnection using an exponential backoff delay with this value as the maximum.-r|--min-repeat-time-ms740Ignore repeated keystrokes that are generated within the specified time (in ms).-v|--verboseSet logging verbosity (repeat to increase).-V|--versionShow currently installed version.
Package: lis
lislife's short, avoid stupid duplicate coding.lisa python library including vairous state-of-art tools, enjoy!Installpip install lisImport# import all
import lis

# import specific module or function
from lis.decorators import safe_orAPI ReferenceDecoratorslis.decorators.safe_orlis.decorators.timeitCollectionslis.collections.objectizelis.collections.objectize(data, recursive=True)Convert a dictionary to object, and access the keys via attributes.Parameters:data:dictInput dictionaryrecursive:bool, optionalconvert the data recursively if this is set as True.streaminglis.streaming.streamingTestspython -m pytest tests -sContribution
Package: lis3dh
LIS3DH Accelerometer I2C Driver for Python3LIS3DH is an accelerometer manufactured by ST Microelectronics. With this driver, you can use LIS3DH with Python3 over I2C.DependenciesOnly smbus2 other than Python.Installationpip3installlis3dhUsageFrom command line;run-lis3dhFrom Python script;fromlis3dhimportLIS3DH,devicefromtimeimportsleepregisters=device()lis=LIS3DH(port=1,scale=registers.CTRL_REG4.SCALE_4G,data_rate=registers.CTRL_REG1.ODR_10Hz)data=lis.read_dummy_register()print("DUMMY REG CHECK ERROR: "+str(data))# 0: No Error, -1: Errorlis.enable_axes(registers.CTRL_REG1.Xen|registers.CTRL_REG1.Yen|registers.CTRL_REG1.Zen)whilelis.read_data_ready_register()==lis.ERROR:sleep(0.25)data=lis.read_all_axes()print("x(g):{}, y(g):{}, z(g):{}".format(data[0],data[1],data[2]))ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.LicenseMIT
Package: lisa-api
[![docs-image]][docs-url] [![travis-image]][travis-url] [![coveralls-image]][coveralls-url] [![pypi-version]][pypi-url]Lisa-api is a core component of LISA Project. It provides a REST api and execute all actions for the LISA project.Free software: Apache licenseInstallationTo install the api:pip install lisa-apiDocumentationhttps://lisa-api.readthedocs.org/You can also play with the api by going tohttp://url-of-lisa:8000/DevelopmentTo run the server:python [home]/lisa_api/lisa-api-cli.pyTo run the all tests run:tox[docs-image]:https://readthedocs.org/projects/lisa-api/badge/?style=flat[docs-url]:https://readthedocs.org/projects/lisa-api[travis-image]:https://img.shields.io/travis/project-lisa/lisa-api.svg[travis-url]:https://travis-ci.org/project-lisa/lisa-api[coveralls-image]:https://img.shields.io/coveralls/project-lisa/lisa-api.svg[coveralls-url]:https://coveralls.io/r/project-lisa/lisa-api[pypi-version]:http://img.shields.io/pypi/dm/lisa-api.png?style=flat[pypi-url]:https://pypi.python.org/pypi/lisa-api
Package: lisacattools
lisacattoolsPython module for interacting with example LISA catalogs1 - Getting StartedThese instructions will get you a copy of the project up and running on your local machine,
either for development and testing purposes or as an installed package.  For more information, see the documentation athttps://tlittenberg.github.io/lisacattools/html/index.html.1.1 - PrerequisitesYou will need python3 to run this program.1.2 - Installing by cloning the repositoryFirst, we need to clone the repositorygit clone https://github.com/tlittenberg/lisacattools.git1.2.1 - For usersTo install the package for non-root users:make userTo install the package on the root system:make1.2.2 - For developersCreate a virtualenvmake prepare-dev
source .lisacattools-envInstall the sotfware and the external libraries for development purposemake install-dev1.3 - Installing by pippip install lisacattools2 - Development (only if the repository has be cloned)2.1 - Writing the codeInstall the software by PIP (developers version)Then, develop your code and commitgit commitThe tests and code style formatter will be run automatically. To ignore the
checks, dogit commit --no-verify2.2 - Running the testsmake test2.3 - Testing on python 3.8,3.9,3.10Install all required prerequisite dependencies:sudo apt-get update; sudo apt-get install make build-essential libssl-dev zlib1g-dev \
libbz2-dev libreadline-dev libsqlite3-dev wget curl llvm \
libncursesw5-dev xz-utils tk-dev libxml2-dev libxmlsec1-dev libffi-dev liblzma-devDownload and execute installation script:
￼curl https://pyenv.run | bashAdd the following entries into your ~/.bashrc file:# pyenv
export PATH="$HOME/.pyenv/bin:$PATH"
eval "$(pyenv init --path)"
eval "$(pyenv virtualenv-init -)"Restart your shell:exec $SHELLValidate installation:pyenv --versionOnce the dependencies are installed, test on python 3.8, 3.8 and 3.10 :make tox3 - Running the tutorialOnce the software is installed, data must be downloaded for the tutorial.
The data are downloaded from a google drive and are large files -- ~10GB in total -- and will be installed
intutorial/data.
Datasets include a catalog of simulated MBH detections with parameters updated on a weekly cadence,
and two UCB catalogs, using 3 and 6 months of simulated LISA data.make dataThen install jupyter and run the tutorialmake demoVersioningWe useSemVerfor versioning. For the versions available, see thetags on this repository.AuthorsJames I. Thorpe,Tyson B. Littenberg- Initial workJean-Christophe MalapertLicenseThis project is licensed under the LGPLV3 License - see theLICENSEfile for details
Package: lisaconstants
LISA ConstantsLISA Constants is a Python package providing values sanctioned by the LISA Consortium for physical constants and mission parameters. LISA Constants is intended to be consistently used by other pieces of software related to the simulation of the instrument, of gravitational wave signals, and others.We provide support for Python projects (as a package), C projects (as a header file), and C++ projects (as a header file). See below how to use the package.Documentation for the latest stable release is available athttps://lisa-simulation.pages.in2p3.fr/constantsDocumentation for the current development version is available athttps://lisa-simulation.pages.in2p3.fr/constants/masterContributingReport an issueWe use the issue-tracking management system associated with the project provided by Gitlab. If you want to report a bug or request a feature, open an issue athttps://gitlab.in2p3.fr/lisa-simulation/constants/-/issues. You may also thumb-up or comment on existing issues.Development environmentWe strongly recommend to usePython virtual environments.To setup the development environment, use the following commands:gitclonegit@gitlab.in2p3.fr:lisa-simulation/constants.gitcdconstants
python-mvenv.source./bin/activate
python-mpipinstall--upgradepip
python-mpipinstall-rrequirements.txtWorkflowThe project's development workflow is based on the issue-tracking system provided by Gitlab, as well as peer-reviewed merge requests. This ensures high-quality standards.Issues are solved by creating branches and opening merge requests. Only the assignee of the related issue and merge request can push commits on the branch. Once all the changes have been pushed, the "draft" specifier on the merge request is removed, and the merge request is assigned to a reviewer. He can push new changes to the branch, or request changes to the original author by re-assigning the merge request to them. When the merge request is accepted, the branch is merged onto master, deleted, and the associated issue is closed.Pylint and unittestWe enforcePEP 8 (Style Guide for Python Code)with Pylint syntax checking, and correction of the code using thepytesttesting framework. Both are implemented in the continuous integration system.You can run them locallypylintlisaconstants/*.py
python-mpytestUse policyBy releasing LISA Constants as an open source software package we want to foster open science and enable everyone to use it in their research free of charge. To acknowledge the authors of this tool and to ensure that consistent, reproducible, and traceble constant values are used in your project, please cite or add the version-specific DOI (click on the badge above).AuthorsJean-Baptiste Bayle (j2b.bayle@gmail.com)Maude Lejeune (lejeune@apc.in2p3.fr)Aurelien Hees (aurelien.hees@obspm.fr)
Package: lisa-data-challenge
LISA Data Challenge softwareLDC provides a set of tools to generate and analyse the LDC datasets.Installation of the latest released versionpip install lisa-data-challengeInstallation of the dev versionCloning the gitlab projectThe default working branch is nameddevelop.git clone -b develop https://gitlab.in2p3.fr/LISA/LDC.gitInstallationBy default,pyproject.tomlwill be used to generate a temporary
environement to build the package (seehttps://pip.pypa.io/en/stable/reference/build-system/pyproject-toml/)pip install .For older version ofsetuptools, asetup.pyfile is also provided.python setup.py installTroubleshootingPrerequisitesGSL :apt-get install libgsl-devorconda install gslFFTW3 :apt-get install libfftw3-devorconda install fftwPaths to FFTW and GSL can be set explicitly by editingsetup.cfg.Python dependenciesMake sure that all requirements are met.Therequirements.txtfile defines the reference version for most of
the dependencies for a python3.9 installation as recommended byLISA-CDE, but other versions
of the listed package might work.To comply with the CDE environement:pip install -r requirements.txtExtensions for specific fast waveform generator can be disabled in the
installation command line:python setup.py install --no-fastGB --no-imrphenomD --no-fastAKExtra dependenciesSome external tools are interfaced by the LDC and need separate installation:EMRI waveform with few: seehttps://bhptoolkit.org/FastEMRIWaveforms/html/index.htmlFast BH waveform with lisabeta: seehttps://gitlab.in2p3.fr/marsat/lisabetaDocumentationLISA Data Challenge portalAPI documentationUse policyDo not forget to associate the authors of this software to your
research:Please cite the DOI (see badge above) and acknowledge the LDC
working group in any publication which makes use of itDo not hesitate to send an email for help and/or collaboration:
ldc-at-lisamission.org, ldc-chairs-at-lisamission.org
Package: lisaglitch
LISA GlitchLISA Glitch is a Python package that generates glitch files compatible withLISA InstrumentandLISANode. A glitch files contain one or more signals, which are injected in the instrumental simulation at various injections points (see below).Documentation for the latest stable release is available athttps://lisa-simulation.pages.in2p3.fr/glitchDocumentation for the current development version is available athttps://lisa-simulation.pages.in2p3.fr/glitch/masterContributingReport an issueWe use the issue-tracking management system associated with the project provided by Gitlab. If you want to report a bug or request a feature, open an issue athttps://gitlab.in2p3.fr/lisa-simulation/glitch/-/issues. You may also thumb-up or comment on existing issues.Development environmentWe strongly recommend to usePython virtual environments.To setup the development environment, use the following commands:gitclonegit@gitlab.in2p3.fr:lisa-simulation/glitch.gitcdglitch
python-mvenv.source./bin/activate
python-mpipinstall--upgradepip
python-mpipinstall-rrequirements.txt
python-mpipinstall-e.WorkflowThe project's development workflow is based on the issue-tracking system provided by Gitlab, as well as peer-reviewed merge requests. This ensures high-quality standards.Issues are solved by creating branches and opening merge requests. Only the assignee of the related issue and merge request can push commits on the branch. Once all the changes have been pushed, the "draft" specifier on the merge request is removed, and the merge request is assigned to a reviewer. He can push new changes to the branch, or request changes to the original author by re-assigning the merge request to them. When the merge request is accepted, the branch is merged onto master, deleted, and the associated issue is closed.Pylint and unittestWe enforcePEP 8 (Style Guide for Python Code)with Pylint syntax checking, and correction of the code using thepytesttesting framework. Both are implemented in the continuous integration system.You can run them locallypylintlisaglitch/*.py
python-mpytestAcknowledgementsThe implementation of the flow, which is used for learning and sampling from the LISA Pathfinder distribution, is heavily based on theneural spline flowsimplementation provided by the authors:nsflowsand also its orignal implentation:nsf.
With some simplifications borrowed fromhereandhere.Use policyThere are currently no licenses associated with this project. However, we would like to foster open science in our community and share common tools. To this end,we are making LISA Glitch available for full members of theLISA Consortiumto use in their research free of charge.However, please keep in mind that developing and maintaining such a tool takes time and effort. Therefore, we would appreciate to be associated with you research.Please cite the DOI (see badge above) and acknowledge the authors (below) in any publicationDo not hesitate to send an email for support and collaborationContactJean-Baptiste Bayle (j2b.bayle@gmail.com)Eleonora Castelli (eleonora.castelli@nasa.gov)Natalia Korsakova (korsakova@apc.in2p3.fr)
Package: lisagwresponse
LISA GW ResponseLISA GW Response is a Python package computing the instrumental response to gravitational-waves, and produce a gravitational-wave (GW) file compatible withLISA InstrumentandLISANode.Documentation for the latest stable release is available athttps://lisa-simulation.pages.in2p3.fr/gw-responseDocumentation for the current development version is available athttps://lisa-simulation.pages.in2p3.fr/gw-response/masterContributingReport an issueWe use the issue-tracking management system associated with the project provided by Gitlab. If you want to report a bug or request a feature, open an issue athttps://gitlab.in2p3.fr/lisa-simulation/gw-response/-/issues. You may also thumb-up or comment on existing issues.Development environmentWe strongly recommend to usePython virtual environments.To setup the development environment, use the following commands:gitclonegit@gitlab.in2p3.fr:lisa-simulation/gw-response.gitcdgw-response
python-mvenv.source./bin/activate
python-mpipinstall--upgradepip
python-mpipinstall-rrequirements.txtWorkflowThe project's development workflow is based on the issue-tracking system provided by Gitlab, as well as peer-reviewed merge requests. This ensures high-quality standards.Issues are solved by creating branches and opening merge requests. Only the assignee of the related issue and merge request can push commits on the branch. Once all the changes have been pushed, the "draft" specifier on the merge request is removed, and the merge request is assigned to a reviewer. He can push new changes to the branch, or request changes to the original author by re-assigning the merge request to them. When the merge request is accepted, the branch is merged onto master, deleted, and the associated issue is closed.Pylint and PytestWe enforcePEP 8 (Style Guide for Python Code)with Pylint syntax checking, and correction of the code using thepytesttesting framework. Both are implemented in the continuous integration system.You can run them locallypylintlisagwresponse/*.py
python-mpytestUse policyThere are currently no licenses associated with this project. However, we would like to foster open science in our community and share common tools. To this end,we are making LISA GW Response available for full members of theLISA Consortiumto use in their research free of charge.However, please keep in mind that developing and maintaining such a tool takes time and effort. Therefore, we would appreciate to be associated with you research.Please cite the DOI (see badge above) and acknowledge the authors (below) in any publicationDo not hesitate to send an email for support and collaborationAuthorsJean-Baptiste Bayle (j2b.bayle@gmail.com)Quentin Baghi (quentin.baghi@cea.fr)Arianna Renzini (arenzini@caltech.edu)Maude Le Jeune (lejeune@apc.in2p3.fr)
Package: lisa-linux
IntroductionThe LISA project provides a toolkit that supports regression testing and
interactive analysis of Linux kernel behavior. LISA stands for Linux
Integrated/Interactive System Analysis. LISA’s goal is to help Linux
kernel developers to measure the impact of modifications in core parts
of the kernel. The focus is on the scheduler (e.g. EAS), power
management and thermal frameworks. However LISA is generic and can be
used for other purposes too.LISA has ahost/targetmodel. LISA itself runs on ahostmachine,
and uses thedevlibtoolkit
to interact with thetargetvia SSH, ADB or telnet. LISA is flexible
with regard to the target OS; its only expectation is a Linux
kernel-based system. Android, GNU/Linux and busybox style systems have
all been used.LISA provides features to describe workloads (notably usingrt-app) and run them on targets. It can
collect trace files from the target OS (e.g. systrace and ftrace traces). These
traces can then be parsed and analysed in order to examine detailed target
behaviour during the workload’s execution.Some LISA features may require modifying the target OS. For example, in
order to collect ftrace files the target kernel must have
CONFIG_DYNAMIC_FTRACE enabled.There are two “entry points” for running LISA:Via theJupyter/IPython notebook framework.
This allows LISA to be used interactively and supports visualisation
of trace data. Some notebooks are provided with example and
ready-made LISA use-cases.Via the automated test framework. This framework allows the
development of automated pass/fail regression tests for kernel behaviour.
LISA provides some ready-made automated tests under thelisa/tests/directory.MotivationsThe main goals of LISA are:Support study of existing behaviours (i.e.“how does PELT work?”)Support analysis of new code being developed (i.e.“what is the
impact on existing code?”)Get insights on what’s not working and possibly chase down whyShare reproducible experiments by means of acommon languagethat:isflexible enoughto reproduce the same experiment on
different targetssimplifiesgeneration and execution of well defined workloadsdefinesa set of metrics to evaluate kernel behavioursenableskernel developers to easily post process data to
produce statistics and plotsDocumentationYou should find everything onReadTheDocs.
Here are some noteworthy sections:InstallationKernel testsHow to reach usBug reports should be raised against theGitHub issue tracker.External LinksLinux Integrated System Analysis (LISA) & FriendsSlidesandVideoNote: the LISA classes referred by the slides are outdated, but all
the other concepts and the overall architecture stays the same.Some insights on what it takes to have reliable tests:VideoLicenseThis project is licensed under Apache-2.0.This project includes some third-party code under other open source
licenses. For more information, seelisa/_assets/binaries/*/README.*.Contributions / Pull RequestsContributions are accepted under Apache-2.0. Only submit contributions
where you have authored all of the code. If you do this on work time
make sure your employer is cool with this. We also have aContributor Guide