Saravanan666/pypi-org huggingface dataset:
Package: phonetics-py
The phonetics module computes the phonetic key of a string using different algorithms.SoundexNYSISSMetaphoneDouble MetaphoneTable of contentsInstallationLatest PyPI stable releaseLatest development release on githubRunning testsUsageModule ContentsContributionsLICENCEAuthorsInstallationLatest PyPI stable releasepipinstallphoneticsLatest development release on githubPull and install in the current directory:pipinstall-egit+https://github.com/Zack--/phonetics.git@master#egg=phoneticsRunning testsByDuncan McGreggor$python-munittestdiscoverphonetics/tests/-vOrnosetests--with-coverage--cover-package=phoneticsUsage>>>importphonetics>>>phonetics.dmetaphone('Danger')('TNJR','TNKR')Module ContentsThephoneticsmodule defines the following function:phonetics.soundex(source[,size=4])Use the soundex algorithm to create the phonetic key of thesourcestring.phonetics.nysiis(source)Use the New York State Identification and Intelligence System to create the phonetic key of thesourcestring.phonetics.metaphone(source)Use the metaphone algorithm to create the phonetic key of thesourcestring.Based onLawrence Philips’ Metaphone Algorithm.phonetics.dmetaphone(source)Use the double methaphone algorithm to create the phonetic key of thesourcestring.Based onLawrence Philips’ Metaphone Algorithm.ContributionsAll source code is hosted onGitHub.
Contributions are welcome.See theCONTRIBUTINGfile for more information.LICENCEOpen Source :AuthorsRanked by contributions.Zack Dibe (Zack–) **Original author
Package: phonetisaurus
Phonetisaurus for PythonPython wrapper for the excellentphonetisaurusgrapheme to phoneme tool (license).Includes pre-built binaries for:x86_64- desktop/laptop/server (64-bit)armv6l- Raspberry Pi 0/1armv7l- Raspberry Pi 2/3/4 (32-bit)aarch64- Raspberry Pi 3/4 (64-bit)RequirementsPython 3.7+LinuxTested with Debian BusterInstallingForx86_64systems:$pipinstallphonetisaurusFor Raspberry Pi, seeReleasesfor compatible wheels:Raspberry Pi 0/1phonetisaurus-<VERSION>-py3-none-linux_armv6l.whlRaspberry Pi 2/3/4 (32-bit)phonetisaurus-<VERSION>-py3-none-linux_armv7l.whlRaspberry Pi 3/4 (64-bit)phonetisaurus-<VERSION>-py3-none-linux_aarch64.whlTrainingAssuming you have a lexicon formatted likethe CMU pronouncing dictionary:word1 phoneme1 phoneme2 ...
word2 phoneme1 phoneme2 phoneme3 ...saved tolexicon.dictrun:$phonetisaurustrain--model/path/to/write/g2p.fst/path/to/lexicon.dictYou may supply more than one lexicon.Seephonetisaurus train --helpfor more options.Predicting$phonetisauruspredict--model/path/to/g2p.fstword1word2...If no words are provided on the command line, they will be read line-by-line from standard in.You may optionally supply one or more--lexicon /path/to/lexicon.dictarguments to avoid guessing pronunciations for known words.Seephonetisaurus predict --helpfor more options.
Package: phonetisch
# phonetisch[![Build Status](https://travis-ci.org/muhammad-ahsan/phonetisch.svg?branch=master)](https://travis-ci.org/muhammad-ahsan/phonetisch) [![PyPI version](https://badge.fury.io/py/phonetisch.svg)](https://badge.fury.io/py/phonetisch)Phonetic algorithms library in python focusing of multiple languages.## Key features* Implementation of Soundex and Caverphone.* Simple to use.* Support multiple languages.* Supports Python 3.4+.## InstallationUse pip to install the lastest version:```bashpip install phonetisch```## Usage Examples```pythonfrom phonetisch import soundex, caverphonefirst_code = soundex.encode_word('Example')second_code = soundex.encode_word('Ekzampul')if first_code == second_code:print('Both words are homophones')print(caverphone.encode_word("Thompson"))```## Referencehttps://en.wikipedia.org/wiki/Soundex## Links* Project: https://github.com/muhammad-ahsan/phonetisch## LicenseMIT License## Contributers* Muhammad Ahsan [@muhammad-ahsan](https://github.com/muhammad-ahsan)* Dounia Sediame [@sediame](https://github.com/sediame)
Package: phonetizer-fr-dan
Phonetizer - FrenchUtils library that converts French word or text into phonems.
Provides python functions and CLI.UsageInstall as pip package, then use command line:$ sentence_to_phonem maison
-> mEz§GCP APIIn Process...Under the cogsCuts sentence into wordsChecks if word is in dictionaryIf so returns phonemic translationElse returns WordNotFoundErrorDevTo dev in local while retaining access to GCP:export GOOGLE_APPLICATION_CREDENTIALS=/path/to/gcp/jsons/phonetizer-dev-key.jsonTodoLib for nn inference of unknown words is up. Needs to be faster (preload model before inference). Use it to guess new words.Parse Wiktionaire for more comprehensive dictionaryCreate POS-Tagging to resolve non-homophonic homograms
Package: phoneutria
phoneutriaDescriptionPython 3 library providing security testing capabilities for webservers, enabling GET and POST requests, and incorporating checks against common vulnerabilities such as XSS, SQL Injection, and CSRF.install:pip install phoneutriainstall in ubuntu:pip install phoneutria --break-system-packagesCommand line usage:Google Hacking:phoneutria -gh access.logsOccurrence of the word in website:phoneutria -t https://api.example.com -w wordTo make a GET request of the all links in website:phoneutria -t https://api.example.com --links
Package: phonevalidator
phonevalidatorCustomcerberus.Validatorfor phone numbersFree software: MIT licenseFeaturesCustom validation mixin forCerberusor anEveAPI.
Uses thephonenumberspackage for validation’s and formatting.
Tested under Python 2.7, Python 3.3, Python 3.4, and Python 3.5.CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.This package also use thephonenumberspackage which is licensed under
theApache2license. TheCerberuspackage which is an open-source project.Eveis licensed under theBSDlicense.History0.0.1 (2016-07-22)Initial dev package.1.0.0 (2016-07-23)Only support’s python-3.51.1.0 (2016-07-24)Adds support and tests for python-2.7
Package: phonex
phonexAlgorithmephonexpourpython3porté parOphir LOJKINEécrit parFrédéric BROUARDpackagé pourpipparDamien CORPATAUXInstallationpip install phonexUsageLa fonctionphonexretourne un nombre qui correspond à la prononciation d'un mot en français.>>> from phonex import phonex
>>> phonex('Dupont')
0.7638993238166792
>>> phonex('Dupond')
0.7638993238166792
>>> phonex('Clairac')
0.47921338864425217
>>> phonex('Clairaque')
0.47921339555074816CréditsPhonex est un algorithme de Soundex plus perfectionné [...] que la version francisée de Soundex2.
Sachez que Phonex est optimisée pour le langage français, sait reconnaître différents types de sons
comme les sons ‘on’, ‘ai’, ‘ein’, etc... et place son résultat sous la forme d’un réel de type double précision
(5.0 x 10-324 .. 1.7 x 10308 sur 15 à 16 chiffres significatifs).
Son temps de calcul est double de Soundex et 30% supérieure seulement à Soundex2.Voir la version originale.Algorithme Phonex
Copyright Frédéric BROUARD (31/3/99)
Package: phonexia-grpc
Phonexia microservice communication via grpc libraryThis library contains defined interfaces for all microservices developed byPhonexia.To use this library you will first need a running instance of any Phonexia microservice. If you don't yet have any running instance, don't hesitate tocontact our sales department.Onthis page, you may find a gRPC API reference for all microservices.ExampleExamples require microservice running on local machine at port 8080.Health checkYou can invokehealth checkmethod of any microservice like this:importgrpcfromphonexia.grpc.common.health_check_pb2importHealthCheckRequestfromphonexia.grpc.common.health_check_pb2_grpcimportHealthStubdefhealth_check(stub:HealthStub):"""Create request and call the service.Invoke Info method of the health stub.Args:stub (LicensingStub): Created stub for communication with service."""request=HealthCheckRequest()response=stub.Check(request)print(response)defmain():"""Create a gRPC channel and connect to the service."""withgrpc.insecure_channel(target="localhost:8080")aschannel:"""Create channel to the service.The target parameter is the service address and port.insecure channel is used for connection without TLS.To use SSl/TLS see the grpc_secure_channel function."""stub=HealthStub(channel)health_check(stub)if__name__=="__main__":main()If the microservice is running, it should return:status: SERVING.Check licenseEach microservice has licensed model which is required to run the service. You can fetch information about licensed models like this:importgrpcfromphonexia.grpc.common.licensing_pb2importLicensingInfoRequestfromphonexia.grpc.common.licensing_pb2_grpcimportLicensingStubdeflicensing_check(stub:LicensingStub):"""Create request and call the service.Invoke Info method of the Licensing stub.Args:stub (LicensingStub): Created stub for communication with service."""request=LicensingInfoRequest()response=stub.Info(request)print(f"The license for technology '{response.technology_name}' with model"f" '{response.model_info.name}:{response.model_info.version}'"f"{'is'ifresponse.is_validelse'was'}valid until{response.valid_until}.")defmain():"""Create a gRPC channel and connect to the service."""withgrpc.insecure_channel(target="localhost:8080")aschannel:"""Create channel to the service.The target parameter is the service address and port.insecure channel is used for connection without TLS.To use SSl/TLS see the grpc_secure_channel function."""stub=LicensingStub(channel=channel)licensing_check(stub)if__name__=="__main__":main()Returned message should contain information about technology name, model name with version and time validity of license.
Package: phonexia-speaker-diarization-client
Phonexia speaker diarization clientThis module contains client for communication withvoiceprint diarization microservicedeveloped byPhonexia.To use this client you will first need a running instance of anyPhonexia speaker diarization microservice. If you don't yet have any running instance, don't hesitate tocontact our sales department.You can learn more about the speaker diarization technologyhere.Onthis page, you will find agRPC APIreference forvoiceprint diarization microservice.
Package: phonexia-speech-to-text-whisper-enhanced-client
Phonexia speech to text whisper enhanced clientThis module contains client for communication withspeech to text whisper enhanceddeveloped byPhonexia.To use this client you will first need a running instance of anyPhonexia speech to text whisper enhanced microservice. If you don't yet have any running instance, don't hesitate tocontact our sales department.You can learn more about the speech to text whisper enhanced technologyhere.Onthis page, you will find agRPC APIreference forspeech to text whisper enhanced microservice.
Package: phonexia-voiceprint-comparison-client
Phonexia voiceprint comparison clientThis module contains client for communication withvoiceprint comparison microservicedeveloped byPhonexia.To use this client you will first need a running instance of anyPhonexia voiceprint comparison microservice. If you don't yet have any running instance, don't hesitate tocontact our sales department.You can learn more about the speaker identification technologyhere.Onthis page, you will find agRPC APIreference forvoiceprint comparison microservice.
Package: phonexia-voiceprint-extraction-client
Phonexia voiceprint extraction clientThis module contains client for communication withvoiceprint extraction microservicedeveloped byPhonexia.To use this client you will first need a running instance of anyPhonexia voiceprint extraction microservice. If you don't yet have any running instance, don't hesitate tocontact our sales department.You can learn more about the speaker identification technologyhere.Onthis page, you will find agRPC APIreference forvoiceprint extraction microservice.
Package: phoning-home
phoning-homePhoning home provides out of the box capabilities
to phone home for security, analytics, gaming and reporting
with in-built consent mechanism.
No server setups needed, onlyTursoatm.Demofromphoning_homeimportph# url, tokenph.connect('http://url.turso.io','t0k3nfh734tr673gqi78rytg3q34786')# use env vars# Increment counters@ph.counter('ZIP_DWNLDS')defdownload_zipfile():# code for downloading zip file...count=ph.fetch('counter','ZIP_DWNLDS')# Leaderboardph.leaderboard('scrabble-123','yus',100)leaderboard=ph.fetch('leaderboard','scrabble-123')# Send a deluge of kv valuesph.info({'version':'1.2.3','os':'linux'})info=ph.fetch('info')# Or namespace itdata={'name':'Miaw Spoogle','username':'purr678'}ph.namedinfo('USER_INFO',data)namedinfo=ph.fetch('namedinfo','USER_INFO')
Package: phonoLAMMPS
phonoLAMMPSCalculate the harmonic interatomic force constants using phonopy and LAMMPS.Online manual:https://phonolammps.readthedocs.ioMain featuresCommand line interface (phonopy like style)Python API fully compatible with phonopyUse of official LAMMPS python interfaceSimple and easy to useFinite temperature force constants using DynaPhoPyRequirementspython 2.7.x/3.xnumpyphonopy (https://atztogo.github.io/phonopy/)LAMMPS python interface (https://lammps.sandia.gov/doc/Python_library.html)Optional requirements for phonon band structure previewmatplotlibseekpath (https://github.com/giovannipizzi/seekpath)Optional requirements for finite temperature FC calculationsDynaPhoPy (https://github.com/abelcarreras/DynaPhoPy)Optional requirements for tinkerTinker testgrad (https://dasher.wustl.edu/tinker/)Installation instructionsFrom source code# python setup.py install --user --prefix=From PyPI repository# pip install phonoLAMMPS --userFor convenience, you may want to copy (or link) the files inside scripts
folder to a location included in $PATH environment variableCommand line interfacephonoLAMMPS has a similar interface to phonopy to allow to easily
calculate the 2nd order force constants and generate the crystal unitcell
from a LAMMPS input file in VASP/POSCAR format. All outputs
are fully compatible and ready to use in phonopy calculations.
Also features a quick preview of the phonon
band structure (requires seekpath).# phonolammps in.lammps --dim 2 2 2 -c POSCAR_unitcell -pAdditionally phonoLAMMPS allows to easily calculate finite temperature force constants
from molecular dynamics by quasiparticle theory (requires dynaphopy).# phonolammps in.lammps --dim 2 2 2  -c POSCAR_unitcell -p -t 300       (at 300 K)The obtainedFORCE_CONSTANTSandPOSCAR_unitcellcan be used in phonopy using--readfcoption for more advanced calculations.# phonopy --dim="2 2 2" --readfc -c POSCAR_unitcell band.confPython APISimple python API fully compatible with phonopy.from phonolammps import Phonolammps
from phonopy import Phonopy

phlammps = Phonolammps('in.lammps',
                       supercell_matrix=[[3, 0, 0],
                                         [0, 3, 0],
                                         [0, 0, 3]])

unitcell = phlammps.get_unitcell()
force_constants = phlammps.get_force_constants()
supercell_matrix = phlammps.get_supercell_matrix()

phonon = Phonopy(unitcell,
                 supercell_matrix)

phonon.set_force_constants(force_constants)
phonon.set_mesh([20, 20, 20])

phonon.set_total_DOS()
phonon.plot_total_DOS().show()

phonon.set_thermal_properties()
phonon.plot_thermal_properties().show()Contact infoAbel Carrerasabelcarreras83@gmail.comDonostia International Physics Center (DIPC)Donostia-San Sebastian (Spain)
Package: phonon
When your users are sending 1000s, or even 10s of 1000s of events per second, it becomes hard to keep up with realtime user behavior.Aggregating writes, and writing them out in a smart way allows the most efficient batching possible.With phonon, you can join events across a cluster of worker/consumer nodes by totally abstracting away reference counting.You can decide to collect events and aggregate across your cluster, and then write to a data backend at the time the user’s session ends. You can also decide to write out based on how many events have been aggregated up to that point, for the user.This allows your ingestion pipeline to scale to 10s of 1000s of client-facing events per second with a single redis backend. Oh, and phonon provides sharding with linear scaling.
Package: phonon-gas-model
pgm: A Python package for free energy calculations within the phonon gas modelCalculate thermodynamic properties of matter using phonon gas model(PGM)ContributorsThis repository is authored and maintained byHongjin WangandJingyi Zhuang.How to citeThe associated paper is publishedonline here.Please cite this article as:Hongjin Wang, Jingyi Zhuang, Zhen Zhang, Qi Zhang, Renata M. Wentzcovitch, pgm: A Python package for free energy calculations within the phonon gas model, Computer Physics Communications (2023), Volume 291, 2023, 108845,https://doi.org/10.1016/j.cpc.2023.108845.If you are unable to access the full text of this article, please contact the authors.InstallationInstall from PyPIYou can install the package directly from PyPI:$pipinstallphonon-gas-modelManual installTo install thepgmpackage, first clone the code repository usinggit:$gitclonehttps://github.com/MineralsCloud/pgm.gitAfter cloning the code repository, change to the code directory usingcd:$cdpgmAfter changing to the code directory, install the required Python packages usingpip:$pipinstall-rrequirements.txtFinally, install the pgm package usingpip:$pipinstall.See details inInstallation of pgm.How to useHere we provide two examples inside the example folder. One is CaSiO₃, and one is B8-FeO.For the case of CaSiO₃, simply run the following commands from the root path of the package:$cdexamples/casio3$pgmruncasio3.yamland for another case, B8-FeO,run the following commands from the root path of the package:$cdexamples/feo$pgmrunfeo.yamlSee detailsCommand Line Tool of pgm.Use your own exampleFirst, you need to prepare a set of phonon calculations calculated at different temperatures.Convert them as standard qha input files(for now use input converter in qha pkg), and put the input files like in the case of CaSiO₃ or B8-FeOCompose your ownsettings.yamlfile, enjoy.Details will be provide shortly.DocumentationSeeGitHub pages of pgm.
Package: phontext
PhonTextA python package for phonology analysis from text filesInstallationUse the package managerpipto install phontext.pipinstallphontextUsageWorking with wordsfromphontextimportWordconfig={'vowels':['a','e','i','o','u'],'consonants':['p','t','k','ch','ts','rr','r']}# Parse words into segmentsword=Word('chincha',**config)len(word)>>5word.cv>>CVCCVword.word_str>>chinchaword.word>>["ch","i","n","ch","a"]# Find minimal pairsword1=Word('tasa',**config)word2=Word('kasa',**config)word3=Word('tasl',**config)word1.is_minimal_pair(word2)>>Trueword1.is_minimal_pair(word3)>>False# and much more...Working with wordlistfromphontextimportCorpuswords=['perro','pero','piso','peso']config={'vowels':['a','e','i','o','u'],'consonants':['p','t','k','ch','ts','rr','r']}corpus=Corpus(**config)forword_strinwords:corpus.append(word_str)segment_stat=corpus.get_segment_frequency()segment_stat>>{'vowels':{'e':3,'i':1}'consonants':{'p':4,'rr':1}'others':'s':2,'r':1}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.LicenseGPLv3
Package: phoopy
Full stack framework for python based on bundlesFull DocumentationInstall:curlhttps://raw.githubusercontent.com/phoopy/phoopy-installer/master/phoopy-installer-ophoopy-installerchmod+xphoopy-installer./phoopy-installermy-projectcdmy-projectpipinstall-rrequeriments.txtRun:bin/consoleRun Tests:pipinstall-rrequeriments-dev.txtphulpytest
Package: phope
patientThis is under review.Patients need to know effects of medication and exercise for alleviating diseases.
Biomarkers are used to monitor the status of individual diseases.phope.py (Patient for Hospital Observation and Predicting Effects of medication and exercise)
with five determinants such as "day" (tested date), "hgb" of hbA1c value (biomarker for diabetes), "ntbnp" of NT-proBNP value (biomarker for heart failure), "degree1" (polynomial regression for hbA1c), and "degree2" (polynomial regression for NT-proBNP) is a universal biomarker prediction tool that can be used for evaluating the performance and predicting values of biomarkers in the next hospital visit.To run phope.py after creating a data.csv, type python phope.py in the terminal.In phope.py, you can change it for your use.phope is a PyPI application. phope allows users to run on Windows, MacOS, and Linux operating systems as long as Python is installed on the system. phope can set left vertical axis and right vertical axis of two biomakers with data.csv.data.csv is a data file composed of seven determinants such as "day" (tested date), "hgb" of hbA1c value (biomarker for diabetes), "ntbnp" of NT-proBNP value (biomarker for heart failure), "degree1" (polynomial regression for hbA1c), "degree2" (polynomial regression for NT-proBNP), the first vertical-axis range on left side (low and high), and the second vertical-axis range on right side (low and high).The data.csv file must be created by the patient or physician before running the program.phope allows users to modify two biomarker's names such as hbA1c and NT-proBNP in data.csv.Five determinant names such as "day", degree1, degree2, y1 and y2 in data.csv should not be changed.phope is a universal biomarker prediction tool with the past data. This example shows two biomarkers such as hbA1c and NT-proBNP.phope can predict any two biomakers simultaneously using the data in the second and third columns.Columns 4 and 5 show the degree of polynomial regression for the first and second biomarkers, respectively.Columns 6 and 7 set the range of vertical axis for the first and second biomarkers, respectively.Based on data.csv with state-of-the-art technology, phope or phope.py can calculate and predict values of biomarkers for the next visit.Predicting biomarker values allows patients to know the progress and trends of improvement in their diseases.Predictive values are hopes of patients.How to install phope$ pip install phopeHow to run phope$ phope
Package: phos
phosPhos is a user-friendly Python library for dealing with the parsing of spectrometry data
and retrieve the spectral data and the metadata. Currently support only raw8 files.InstallationUse the package managerpipto install Phos.pipinstallphosBasic UsageTo parse a raw8 file, initialize a Raw8Spectra instance
passing the file directory.fromphosimportRaw8Spectraspectra=Raw8Spectra('input.raw8')The Raw8Spectra instance has all the attributes of the raw8 file.print(f'integration time:{spectra.integration_time}')print(f'integration delay:{spectra.integration_delay}')print(f'number of averages:{spectra.number_of_averages}')print(f'start pixel:{spectra.start_pixel}')print(f'stop pixel:{spectra.stop_pixel}')You can plot the spectra using the list of wavelenghts and counts.plt.plot(spectra.wavelenghts,spectra.counts)plt.show()You can get the spectra scan on a csv file or all the parameters of the experiment
in a json file.spectra.to_csv('test.csv')spectra.to_json('test.json')