Saravanan666/pypi-org huggingface dataset:
Package: optuna-worker
optuna-workeroptuna-workeris a python package to help usingoptunawithout code modification to existing ML training project, with two assumptions.You could pass hyperparameters to your trainer via cli arguments.Metrics to be optimized are printed out as formatted logs during training.A CLI namedoptuna-workeris included in this package, which runs optuna worker with a configuration yaml file.optuna-worker run $CONFIG_FILEAll it does is simply creating a proxy objective thatCreates a training subprocess, passing suggested parameters via CLI arguments.Parses metric values from stdout of the training subprocess, so that they could be reported and returned.Details of the configuration file could be found from thedocumentation.
You can also find working example configuration files fromexamples.Installationpip install optuna-workerLicenseoptuna-workeris distributed under the terms of theMITlicense.
Package: optunizer
optunizerOptuna extension for JSON and YAML configuration filesInstallationpipinstalloptunizerwith PostresSQL connectorpipinstalloptunizer[psycopg]RunningSuppose you have some script/program (e.g.main.py) with config in YAML/JSON file (e.g.config.yaml) that returns some output (e.g.metrics.json)main.pyimportjsonimportyamlconfig_file='config.yaml'withopen(config_file)asf:params=yaml.safe_load(f)metric=params['param1']+params['param2']metrics={'metric':metric}metrics_file='metrics.json'withopen(metrics_file,'w')asf:json.dump(metrics,f)config.yamlparam1:2param2:0.5param3:cmetrics.json{"metric":0.3}Make optunizer config file, e.g.optunizer.yamlattrs:# track all fields in filesconfig.yaml:truemetrics.json:trueoptunizer_sysinfo.json:trueclass:optunizer.optimizer.Optimizerload_if_exists:trueexport_csv:optunizer_results.csvexport_metrics:optunizer_metrics.jsonexport_sysinfo:optunizer_sysinfo.jsonstudy:optunizer_testobjectives:# Specify objectives, e.g. fields in metrics.json filemetric@metrics.json:minimizeparams:# Specify params, e.g. fields in config.yaml fileparam1@config.yaml:method:suggest_intmethod_kwargs:high:3low:0param2@config.yaml:method:suggest_floatmethod_kwargs:high:1.0low:0.01log:trueparam3@config.yaml:method:suggest_categoricalmethod_kwargs:choices:[a,b,c]pruner:PatientPrunerpruner_kwargs:# Specify pruner, e.g. PatientPruner with NopPruner subprunermin_delta:0patience:0wrapped_pruner:NopPrunerwrapped_pruner_kwargs:{}sampler:PartialFixedSamplersampler_kwargs:# Specify sampler, e.g. PartialFixedSampler with GridSampler subsamplerbase_sampler:RandomSamplerbase_sampler_kwargs:{}# base_sampler: GridSampler# base_sampler_kwargs:#   search_space:#     param1@config.yaml: [0, 1, 2]#     param2@config.yaml: [0.01, 0.5]fixed_params:param3@config.yaml:asubprocess_kwargs:# Specify your commandargs:-python-main.py-config.yamlRun optunizerOPTUNA_CONFIG=optunizer.yamlpython-moptunizerorpython-moptunizeroptunizer.yamlRun optunizer streamlit vizpipinstalloptunizer[viz]python-moptunizerappThere are several useful environment variables, that could be set in command line,.envor.env.secretfilesOPTUNA_CONFIG=optunizer.yamlOPTUNA_CONFIG_APP=app.yamlOPTUNA_SHARED=.envOPTUNA_SECRET=.env.secretOPTUNA_URL=postgresql+psycopg2://USER:PASSWORD@IP:PORT/DB# see https://docs.sqlalchemy.org/en/14/core/engines.htmlOPTUNA_STUDY=STUDY_NAMEOPTUNA_TRIALS=3OPTUNA_TIMEOUT=3600OPTUNA_LOAD_IF_EXISTS=1OPTUNA_EXPORT_CSV=CSV_FILE_NAMEOPTUNA_EXPORT_METRICS=METRICS_FILE_NAMEOPTUNA_EXPORT_SYSINFO=SYSINFO_FILE_NAME
Package: optus
Optus Mobile API IntegrationThis is a python wrapper for the Optus mobile API. It provides the ability to view account usage information and other capabilities normally only accessed via the mobile application.Base64 auth is a generic token for the Optus API and does not contain credentialsFeaturesUsage Information (Balance, data remaining etc)Addon information (Details of addons applied or avaliable for the account)Geofencing Information (Geofences that have been configured for the account)InstallInstall using pip:pip install optusDemoTo test the script there is a demo script that can be useddemo.py EMAIL PASSWORD MOBILEExampledemo.py test@test.com password1 04123456Library UsageSimple Usagefrom optus import Account
acc = Account("email", "password", "mobile")
print(acc.usage())
Package: optutils
optutils========Small, composable utilities for writing great command line tools. Writinga great command line tool takes art as well as science. Unlike libraries andframeworks, commandline tools are used interactively by the programmer.Therefore, their input interface must be forgiving yet consistent, their outputmust be computer parsable yet human readable, and their error messages must beterse yet informative.#### `Optutils` philosophy:1. Fail fast -- give the user immediate feedback on what they did wrong.2. Testable Errors -- provide consistent unique exit status codes to ensurefuture testability.3. Informative Errors -- point the way to the narrow path.4. Separate Feedback and Output -- feedback for humans should go on the standarderror, output for programs to the standard out.5. Prioritize Clarity over Code -- the user experience should be paramount, notthe programmer's experience. These utilities are not always designed to makethe text of the program shorter, they are designed to make the userexperience *better*.6. Every Child is Special -- every utility is just a little different and onesize fits all solutions tend to fit no one. Utilities should therefore bespecialized *yet* re-usable.# A Minimal Optutils Program with a Subcommand```python#!/usr/bin/env python# -*- coding: utf-8 -*-#Author: Tim Henderson#Email: tim.tadh@gmail.com, tadh@case.edu#For licensing see the LICENSE file in the top level directory.import os, sys, jsonimport optutilsfrom optutils import output, log, error_codes, add_code__version__ = 'git master'add_code('version')def version():'''Print version and exits'''log('version :', __version__)sys.exit(error_codes['version'])@optutils.main('usage: example <command>','''Example:$ example command whatOptions-h, help                      print this message-v, version                   print the version''','hv',['help', 'version'],)def main(argv, util, parser):"""The main entry point to the program"""@util.command('usage: command [args]','''Example:Options-h, help                      print this message''','h',['help',],)def command(argv, util, parser, setting):opts, args = parser(argv)for opt, arg in opts:if opt in ('-h', '--help',):util.usage()print ' '.join(args)print 'running with', settingopts, args = parser(argv)for opt, arg in opts:if opt in ('-h', '--help',):util.usage()elif opt in ('-v', '--version',):version()setting = 'wizards'util.run_command(args, setting)if __name__ == '__main__':sys.exit(main(sys.argv[1:]))```
Package: optx
optxRefresh yourself on what those elusive options do, hassle free!ExampleView the descriptions of -xcf and –format in the given order:python3 optx.py tar -xcfNotesFor the sake of my sanity, I will refer to the optional arguments for this
program as flags, and the positional arguments as options.ContributingThis project is still in the beginning stages. Contributions are very welcome.LicenseThis software is licensed under GPLv3. See theLICENSEfile for more information.
Package: optymus
Welcome tooptymus, the Optimization Methods Library for Python! This library provides a comprehensive collection of optimization methods, both with and without constraints, implemented in the Python programming language.Table of ContentsIntroductionGetting StartedContentContributionsLicenseIntroductionoptymusis designed to empower users with a versatile set of optimization tools, facilitating the search for optimal solutions in various problem domains. This library covers a range of optimization methods, making it suitable for diverse applications in computer science and engineering.Getting StartedTo begin usingoptymus, follow these steps:Install optymus:pipinstall--upgradeoptymusExplore the Documentation:Visit theofficial documentationto understand the available optimization methods and how to use them effectively.Get Started:fromoptymus.minimizeimportOptimizerimportnumpyasnpf=lambdax:x[0]**[2]-3*x[0]*x[1]+4*x[1]**2+x[0]-x[1]grad=lambdax:np.array([2*x[0]-3*x[1]+1,-3*x[0]+8*x[1]-1])hess=lambdax:np.array([[2,-3],[-3,8]])initial_point=np.array([2,2])optimizer=Optimizer(f_obj=f,x0=initial_point,grad=grad,hess=hess,method='bfgs')optimizer.report()optimizer.plot()Contentoptymusincludes a rich set of optimization methods, such as:Unconstrained Optimization MethodsConstrained Optimization MethodsGlobal OptimizationGradient DescentEvolutionary AlgorithmsRefer to the documentation for detailed information on each method and its application.ContributionsContributions to Optymus are highly appreciated! If you have additional optimization methods, improvements, or bug fixes, please submit a pull request following thecontribution guidelines.LicenseOptymus is licensed under theMIT License, allowing you to use, modify, and distribute the library for both commercial and non-commercial purposes.Start optimizing with Optymus and unlock the potential for finding optimal solutions in your Python projects!
Package: optypecheck
This package implements a non intrusive and optional type checking in
functions and methods by using annotations. Once types are defined in
annotations, no changes are required to make the verification of types.
And, because it is completely optional, it can be used only in the
desired environments, like unit testings. This way, the performance of
production code is not affected.Learn more in:https://bitbucket.org/carlopires/optypecheckInstallationpip3installoptypecheckExampledefgencode(a:bytes,b:str)->str:return'{}{}'.format(a[0],b)defvalid_number(n)->'decimal.Decimal':returnn# enable type checking in DEBUG modeassert__import__('typecheck').typecheck(__name__)
Package: optzer
What is optzer?optzeris a python package for parameter optimization that can be used for any external program and for any target value obtained with the external program.Who made this?Ryo KOBAYASHIAssociate Professor at Department of Physical Science and Engineering, Nagoya Institute of Technology.Requirements and dependenciesTheoptzerrequires the following:python3docoptnumpyscipyInstallationIt can be installed viapipas,pipinstalloptzerYou can install as a develop mode installation as,gitclonehttps://github.com/ryo.kbys/optzer.git./optzercdoptzer
pythonsetup.pysdist
pipinstall-e.If you can findoptzercommand in your system viawhich optzer, the installation should be successful.UsagePlease seeoptzer documentationand examples included in this repository.Questions and requestsPlease leave questions and requests on issues in the github repository page.LicenseThis software is released under the MIT License, see the LICENSE.AcknowlegementsThis software was developed atNagoya Institute of Technology, and supported by JSPS KAKENHI Grand Numbers 21K04650, JP20H05290 and 22H04613 (Grant-in-Aid for Scientific Research on Innovative AreasInterface Ionics).
Package: opus-fast-mosestokenizer
opus-fast-mosestokenizeris a fork offast-mosestokenizercreated to ensure compability of the package with current Python environments.fast-mosestokenizeris a C++ implementation of the moses tokenizer
which is a favourite among the folks in NLP research.The reason for using this package over the original perl implementation is
for the purpose of portability.
With the C++ source code, you can use this library basically in every language.The C++ script was adapted from the mosesdecoder repositorycontrib/c++tokenizer.BenchmarkInstallationUsage (Command-line tool)Usage (Python)Benchmarkfast-mosestokenizeris also fast.
On english, it is about 6x faster thantokenizer.perland 15x faster thansacremoses.see./bench/README.mdfor more information.InstallationPython users usinglinuxandosx>=10.15can install directly from PyPI.pipinstallfast-mosestokenizerSee./INSTALL.mdfor more information.Usage (Command-line tool)# Piping is the standard way to configure input and output stream.# mosestokenizer would apply tokenization to each line of the input stream.mosestokenizeren<infile>outfile# For a full list of options, refer to the help message.mosestokenizer-hUsage (Python)# Usage patterns are mostly the same as sacremoses.>>>frommosestokenizerimportMosesTokenizer>>>tokenizer=MosesTokenizer('en')>>>tokenizer.tokenize("""The English name of Singapore is an anglicisation of the native Malay name forthe country, Singapura, which was in turn derived from the Sanskrit word forlion city (romanised: Siṃhapura; Brahmi: 𑀲𑀺𑀁𑀳𑀧𑀼𑀭; literally "lion city"; siṃhameans "lion", pura means "city" or "fortress").[8]""")['The','English','name','of','Singapore','is','an','anglicisation','of','the','native','Malay','name','for','the','country',',','Singapura',',','which','was','in','turn','derived','from','the','Sanskrit','word','for','lion','city','(','romanised',':','Siṃhapura',';','Brahmi',':','𑀲𑀺𑀁𑀳𑀧𑀼𑀭',';','literally','"','lion','city','"',';','siṃha','means','"','lion','"',',','pura','means','"','city','"','or','"','fortress','"',')','.','[','8',']']
Package: opusFC
Python/Cython module for reading OPUS binary files into NumPy arraysThis module is targeted at the orange-spectroscopy add-on for Quasar:https://quasar.codes/https://github.com/Quasars/orange-spectroscopy/Documentation:https://stuart-cls.github.io/python-opusfc-dist/Issues:https://github.com/stuart-cls/python-opusfc-dist
Package: opusfilter
OpusFilterOpusFilter is a tool for filtering and combining parallel corpora.Features:Corpus preprocessing pipelines configured withYAMLSimple downloading of parallel corpora fromOPUSwithOpusToolsImplementations for many common text file operations on parallel filesMemory-efficient processing of large filesImplemented filters based e.g. on language identification, word aligment, n-gram language models, and multilingual sentence embeddingsExtendable with your own filters written in PythonOpusFilter has been presented inACL 2020 system demonstrations.InstallingInstall the latest release from PyPI:pip install opusfilterorpip install opusfilter[all](include optional Python libraries)Install from source:pip install .orpython setup.py installTroubleshootingOpusFilter should generally work fine on Python 3.7 to 3.11. In the case of troubles, try installing the exact versions inrequirements.txt:pip install -r requirements.txtDocumentationThe complete OpusFilter documentation is available fromhelsinki-nlp.github.io/OpusFilter.You can also build the documents from the source:pip install -r docs/requirements.txtorpip install .[docs]sphinx-build docs docs-htmlChangelogA changelog is available indocs/CHANGELOG.md.CitingIf you use OpusFilter in your research, please cite ourACL 2020 paper:@inproceedings{aulamo-etal-2020-opusfilter,title="{O}pus{F}ilter: A Configurable Parallel Corpus Filtering Toolbox",author={Aulamo, Mikko and Virpioja, Sami and Tiedemann, J{\"o}rg},booktitle="Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations",month=jul,year="2020",publisher="Association for Computational Linguistics",url="https://www.aclweb.org/anthology/2020.acl-demos.20",doi="10.18653/v1/2020.acl-demos.20",pages="150--156"}A full bibliography of papers cited in the documentation and code can be found fromdocs/references.bib.ContributingSeedocs/CONTRIBUTING.md.
Package: opus-greennet
OPUS greenNet python API wrapperDisclaimer: This is my first ever published libary for python so it might be messy and i would not recommend using it for things that have to work reliably. However if you want to build your own libary or help me making mine better take a look at the last section of the readme where you can find some more information about the API behind the project.Supported DevicesSwitchOPUS BRiDGE 1 ChannelOPUS BRiDGE 2 ChannelOPUS BRiDGE Roller shutter / Venetian blindOPUS BRIDGE UniversaldimmerOPUS BRiDGE 1 channel, 16AOPUS actuator "Professional" roundMonetoringOPUS smoke detectorOPUS door/window contactAny Motion sensorAny Water detectorAny Handle sensorAny Temperature / Heat sensorUsageSetup:# import the libaryimportopus_greennet# create the Auth object to authenticate with the API# the password can be found on a sticker on your gatewayauth=Auth('http://IP_OF_YOUR_GATEWAY:8080','PASSWORD_OF_YOUR_GATEWAY')# create the OPUS object and pass the authopus=OPUSAPI(auth)Print all switches to the console# get all onechannel switches# other types: two_channel_switches, blind_switches, dimming_switchesone_channel_switches=opus.get_one_channel_switches()# print information for every switchforswitchinone_channel_switches:# available propertys: name, id, state, location, manufacturer, productId# for two channel switches you have state_1 and state_2 instead of stateprint(f"{switch.name}with ID '{switch.id}is located at{switch.location}with state{switch.state}")change the state of a device# change the state of the first switch in list using change_stateone_channel_switches[0].change_state(True)# for two channel switches you have to use change_state_1 and change_state_2 instead of change_state# for dimmers and blinds the state is represented in integers from 0-100 instead of boolsSome info about the APIThe REST API is exposed by theOPUS SmartHome Gatewayat port 8080. There you will also find a UI where you can test and discover the API. To access the API you have to authenticate yourself.Username: "admin"Password: on a sticker on the OPUS SmartHome Gateway. (8 characters long and consists of capital letters and numbers  e.g. "GBA7VD3G")The UI should look like this
Package: opusminer
Open source implementation of the OPUS Miner algorithm which applies OPUS search for Filtered Top-k Association Discovery of Self-Sufficient ItemsetsCopyright (C) 2012 Geoffrey I WebbThis program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License
for more details.You should have received a copy of the GNU General Public License along with this program.
If not, see <http://www.gnu.org/licenses/>.Please report any bugs to Geoff Webb <geoff.webb@monash.edu>
Package: opus-seti
Python package forOPUS-SetiAPI(NASA-PDS Rings Node)InstallWithpip:$pipinstallopus-setiWith thesource files:$gitclonehttps://github.com/seignovert/python-opus-seti.git$cdopus-seti;pythonsetup.pyinstallUsageopus-h# For helpopus--planetSaturn--targetpancassini-vimsTITAN--limit5>>>fromopusimportapi>>>api.data(planet='Saturn',target='pan',limit=10)OPUSAPIDataobjects(with10elements):-S_IMG_CO_ISS_1480614021_N-S_IMG_CO_ISS_1488190255_N-S_IMG_CO_ISS_1488273311_N-S_IMG_CO_ISS_1488368442_N-S_IMG_CO_ISS_1488485562_N-S_IMG_CO_ISS_1488551713_N-S_IMG_CO_ISS_1488711044_N-S_IMG_CO_ISS_1488745124_N-S_IMG_CO_ISS_1488812400_N-S_IMG_CO_ISS_1488826725_NMore examples are available in thisJupyter Notebook.NoteIMPORTANT:I have no current affiliation with NASA or SETI. The package is providedas is, use at your own risk.
Package: opusxml
OPUSXML is a Python library to read OPUSXML files produced by the Online Positioning User Service (OPUS) hosted by the National Geodetic Survey. It prints information from OPUSXML files and converts them to formats supported by GDAL.InstallationTo install from the Python Package Index:$pipinstallopusxmlTo 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 opusxml.$condaconfig--appendchannelsconda-forge$condainstallopusxml-cmrahnisTo install from the source distribution execute the setup script in the opusxml directory:$python setup.py installExamplesTODOLicenseBSDDocumentationLatesthtml
Package: opvia-scripts
Opvia ScriptsThis repo is used to build custom cards on the Opvia platform.DevelopingThis project requires Poetry version 1.2.2 or newer and Python 3.9.x.InstallPoetryandpyenv:curl-sSLhttps://install.python-poetry.org|python3-
brewinstallpyenvand then follow instructions frompyenv initto setup your shell. Once that's done, install the correct version of python and set up poetry:pyenvinstall3.9&&pyenvlocal3.9&&poetryenvusepython3.9You can then use poetry as usual to install your dependencies:poetryinstallIf you are using VSCode, it will notice that poetry has created a new virtualenv and prompt you to use it. If it doesn't, you cancmd+shift+p->Python: Select Interpreter->Python 3.9.15 ('.venv': poetry) ./venv/bin/pythonat any point. If you then open up a new shell, vscode will automatically activate this venv for you.PRs made to this repo require approval from another developer. There should be reasonable tests for all functionality. Tests should protect backwards-compatibility of all of our changes.New changes should be accompanied by appropriate updates to thedocs, covering:Relevant class and function definitions for custom card writersSimple examples covering installed script functionalityIndependently readable in-app scripting versions of the same examplesUseful CommandsNote: if you are not inside the virtual environment created by poetry, you may need to usepoetry run poeinstead ofpoepoe autoformat- Autoformat codepoe lint- Lintingpoe test- Run Testspoe docs- Build docsReleaseRelease a new version by manually running the release action on GitHub with a 'major', 'minor', or 'patch' version bump selected.
This will create an push a new semver tag of the formatv1.2.3.Pushing this tag will trigger an action to release a new version of your library to PyPI.Optionally create a release from this new tag to let users know what changed.
Package: opvious
Opvious Python SDKDefine and deploy optimization models in minutes withOpvious.Try it out!HighlightsDeclarative modeling API withextensive static checks and automatic LaTeX generationRemote solves withreal-time progress notificationsFlexible data import/exportviapandasAdvanced multi-objective support: weighted sums, epsilon constraints, ...Smart debugging capabilities: semantic constraint relaxations, annotated LP formatting, ...DocumentationGetting started guideSDK API referenceInteractive optimization notebooksLicensingThe SDK is licensed under Apache 2.0. The Opvious platform is available both as a managed cloud service (free on small datasets) and self-hosted (free for non-commercial projects). See ourplans pagefor more information.
Package: opx
Installation$pip3installopxRequirementsDockerGitRepoGetting Started# initialize your workspace$opxinit# build all packages$opxbuild# assemble an installer$opxassemble# remove persistent container$opxremoveNew Features (Overopx-build)Opinionated defaultsRemembers to pull Docker image regularly so you don’t have toSort packages intopkg/$repo/after buildingPersistent container (if inside a workspace)One container allowed per workspacePublish packages to testing$opxpublishopx-loggingCommands are aliased# all run opx build$opxbopx-logging$opxbuiopx-logging$opxbuildopx-loggingCommand Line CompletionRun the command corresponding with your shell. Add to your shell startup file for persistent autocomplete.# bash$eval"$(_OPX_COMPLETE=source-bashopx)"# zsh$eval"$(_OPX_COMPLETE=source-zshopx)"# fish$eval(env_OPX_COMPLETE=source-fishopx)RoadmapPortopx_rel_pkgasmfrom python script to modulePortopx_get_packagesfrom python script to modulePortopx_bld_basicsfrom python script to moduleLicenseOpenSwitch Development Tool is distributed under the terms of theMIT License.