Saravanan666/pypi-org huggingface dataset:
Package: barmuscomp
BarMusComp: Encoding songs with linear and nonlinear compression methods to reveal structureHello, and welcome on this repository!This project aims at compressing all bars in a song, and studies the compressed representations of every bar to infer its structure. It is related to my PhD thesis [1].This repository contains code for the NTD, PCA, NMF, and Autoencoders (developed in PyTorch), as presented in [2].This project is an extension of the toolbox as_seg [3], which computes the segmentation of an autosimilarity matrix.It can be installed with pip usingpip install barmuscomp.This is a first release, and may contain bug. Comments are welcomed!Software versionThis code was developed with Python 3.8.5, and some external libraries detailed in dependencies.txt. They should be installed automatically if this project is downloaded using pip.Tutorial Notebook3 tutorial notebooks are available in the folder "Notebooks", and present the different compression methods on the song 'Come Together'.They are only present if you downloaded the project from git (e.g.https://gitlab.inria.fr/amarmore/barmuscomp), and are not available in the pip version (which is in general not accessible easily in the file tree).How to citeYou should cite the packageBarMusComp, available on HAL (https://hal.archives-ouvertes.fr/hal-03782914).Here are two styles of citations:As a bibtex format, this should be cited as: @softwareversion{marmoret2022barmuscomp, title={BarMusComp: module for computing barwise compressed representations of music}, author={Marmoret, Axel and Cohen, J{'e}r{'e}my and Bimbot, Fr{'e}d{'e}ric}, URL={https://gitlab.inria.fr/amarmore/barmuscomp}, LICENSE = {BSD 3-Clause ''New'' or ''Revised'' License}, year={2022}}In the IEEE style, this should be cited as: A. Marmoret, J.E. Cohen, and F. Bimbot, BarMusComp: module for computing barwise compressed representations of music, 2022, url:https://gitlab.inria.fr/amarmore/barmuscomp.CreditsCode was created by Axel Marmoret (axel.marmoret@gmail.com), and strongly supported by Jeremy E. Cohen (jeremy.cohen@cnrs.fr).The technique in itself was also developed by FrÃ©dÃ©ric Bimbot (bimbot@irisa.fr).References[1] A. Marmoret, "Unsupervised Machine Learning Paradigms for the Representation of Music Similarity and Structure", Ph.D. dissertation, UniversitÃ© de Rennes 1, 2022.
(not uploaded yet but will be soon! You should check the website hal.archives-ouvertes.fr/ in case this README is not updated with the reference.)[2] A. Marmoret, J.E. Cohen, and F. Bimbot, "Barwise Compression Schemes for Audio-Based Music Structure Analysis"", in: 19th Sound and Music Computing Conference, SMC 2022, Sound and music Computing network, 2022.[3] A. Marmoret, J.E. Cohen, and F. Bimbot, "as_seg: module for computing and segmenting autosimilarity matrices", 2022, url:https://gitlab.inria.fr/amarmore/autosimilarity_segmentation.
Package: barn
Simple local/remote dataset store for Python.frombarnimportDatasettwitter_usa=Dataset(name='twitter_usa',task='NER')# download from an azure block blob storage and load into a dataframetwitter_usa.download(tags=['preprocessed'],version='20180305')df=twitter_usa.df(tags=['preprocessed'],version='20180305')Contents1Installation2Features3Use4Contributing4.1Installing for development4.2Running the tests4.3Adding documentation5Credits1Installationpipinstallbarn2FeaturesPure python.Supports Python 3.5+.3UseTBA4ContributingPackage author and current maintainer is Shay Palachy (shay.palachy@gmail.com); You are more than welcome to approach him for help. Contributions are very welcomed.4.1Installing for developmentClone:gitclonegit@github.com:shaypal5/barn.gitInstall in development mode, including test dependencies:cdbarnpipinstall-e'.[test]'4.2Running the testsTo run the tests use:cdbarnpytest4.3Adding documentationThe project is documented using thenumpy docstring conventions, which were chosen as they are perhaps the most widely-spread conventions that are both supported by common tools such as Sphinx and result in human-readable docstrings. When documenting code you add to this project, followthese conventions.Additionally, if you update thisREADME.rstfile,  usepython setup.py checkdocsto validate it compiles.5CreditsCreated byShay Palachy(shay.palachy@gmail.com).
Package: barneySA
barneySAA general-purpose library for sensitivity analysis using fractional factorial design and analysis of variance. The library conducts sensitivity analysis on a given model based on the ranges provided for the parameters. Basically, barneySA does the followings:Sample from the n-dimensional space of the parameters using fractional factorial designCreate a parameter set for each of sample setsRun the given model for each parameter set and collect distance valueConduct the analysis of variance to determine the relative importance of parameters with respect to one anotherGetting startedQuick startpip install --upgrade barneySA# inside your script, e.g. test.pyfrombarneySAimporttoolsfree_params={# define the parameters and their range'P1'=[2,3],'P2'=[1.2,4.3]}settings={# define settings"MPI_flag":True,"replica_n":2,"output_path":"outputs/SA","model":MODEL# this is your model}obj=tools.SA(free_params=free_params,settings=settings)obj.sample()obj.run()obj.postprocess()# in terminalmpiexec-n'cpu_numbers'pythontest.pybarneySA receives two inputs from users. First, the free parameters' list that is a python dictionary that contains the names and bounds (min and max) of each free parameter. Second, the settings that is another python dictionary that contains specifications of SA. Inside the specification, the model which is an object of the fomulated problem needs to be provided. The model object should have a function named 'run' that receives a parameter set (a sample of the given free parameters) and results in a distance value based on the goodness of fit considered for the problem in hand.OutputsThe library results in a value for each free parameters that shows the importance of that parameter with respect to the rest of the parameters.AuthorsJalil NourisaAcknowledgmentsNo one yet. Give some feedback so your name would appear here :-)
Package: baro
Easy and simple loading bar for python.CLASSES:
    baro.thin(total, color_start=fore.GREEN, color_end=fore.BLUE)
    baro.line(total, color_start=fore.GREEN, color_end=fore.BLUE)
    baro.bar(total, color_start=fore.GREEN, color_end=fore.BLUE)
    baro.spin(total, color_start=fore.GREEN, color_end=fore.BLUE)
    baro.spin2(total, color_start=fore.GREEN, color_end=fore.BLUE)
    baro.customspin(total, chars, color_start=fore.GREEN, color_end=fore.BLUE)
    baro.timed(total, desc='', color_start=fore.GREEN, color_end=fore.BLUE)

FORE, STYLE, BACK:
    fore.BLACK, fore.RED, fore.GREEN, fore.YELLOW, fore.BLUE, fore.MAGENTA, fore.CYAN, fore.WHITE, fore.RESET

    style.BOLD, style.DIM, style.NORMAL, style.RESET_ALL

    back.BLACK, back.RED, back.GREEN, back.YELLOW, back.BLUE, back.MAGENTA, back.CYAN, back.WHITE, back.RESETHow to use baro!importbarobaro.thin(100).start().close()bar=baro.line(100)bar.start()bar.close()bar2=baro.bar(100)withbar2asbar_2:foriterableinbar2:# do somethingbar_2.update(iterable)bar_2.sleep(0.1)bar3=baro.spin(100).start().close()bar4=baro.spin2(100).start().close()bar5=baro.custom(100,['a','b','c','d','e','f','g','h','i']).start().close()bar6=baro.timed(100,'This is a timed bar').start().close()
Package: baroness
Toolkit for easy searching and manipulation of python source code using
redbaron.Installationpip install baronessSeehttps://pypi.python.org/pypi/baronessUsageSearchingYou can search through python code using the redbaron API on the
commandline. By default baroness will search through all python files
from the current directory down recursively. The search pattern is just
regular python code that would work with redbaron. The top level node is
called root.For example to search for allnamenodes with a value ofbar:baroness search 'root("name", value="bar")'searchis the default subcommand so you can write the same with:baroness 'root("name", value="bar")'For full usage look atbaroness search--help:usage: baroness search [-h] [--no-cache] [--parents PARENTS] [--no-color]
                       [--no-linenos]
                       pattern [files [files ...]]

positional arguments:
  pattern            Python redbaron code to search where `root` is the
                     variable holding the tree
  files              File names and/or glob pattern. Default to recursive
                     search of python all files.

optional arguments:
  -h, --help         show this help message and exit
  --no-cache         Do no use the cache in `.baroness` even if it exists
  --parents PARENTS  Number of parents to go up on matched nodes.
  --no-color         Do not color the output.
  --no-linenos       Do not output the linenumbers.CachingParsing python files to a baron fst can be time consuming for large code
bases. Baroness can cache the baron fst as json files to save time when
searching. By default caching isn’t enabled, but will be used if
baroness finds a.baronessdirectory.Saving/Initialising CacheTo enable caching (and initially create cache) you can use:baroness cache saveFor full usage look atbaroness cache save--help:usage: baroness cache save [-h] [--force] [FILE [FILE ...]]

Save given files (all tree) to disk

positional arguments:
  FILE        Files to save to cache.

optional arguments:
  -h, --help  show this help message and exit
  --force     Save over already existing cache files.Clearing the CacheTo delete all.baronessdirectories recursively use:baroness cache delete
Package: bar-protonmail
New message notifications and unread messages count from ProtonMail (Waybar/Polybar module)Dependenciesproton-client >= 0.7.1 (not available on pypi.org)ttf-font-awesome (default badge: )libnotify (new email notifications, can be disabled with-dnflag)libcanberra (optional, notification sound)To display notifications you must have anotification daemonrunning on your system.InstallArchLinux and derivativesAUR packageOther distrosgitclonehttps://github.com/crabvk/bar-protonmail.git# WARN: Checkout to the latest tag, don't use master branch.pipinstall-e.And now you can execute~/.local/bin/bar-protonmailUseFirst, you need to authenticate the client:bar-protonmailauththen just runbar-protonmailorbar-protonmail -f polybar.
Session, cache and log are stored in ~/.cache/bar-protonmail.Waybar config example~/.config/waybar/config"modules-right":{"custom/protonmail"}"custom/protonmail":{"exec":"bar-protonmail","return-type":"json","interval":10,"tooltip":false,"on-click":"xdg-open https://mail.proton.me/u/0/inbox"}~/.config/waybar/style.css#custom-protonmail.unread{color:white;}#custom-protonmail.inaccurate{color:darkorange;}#custom-protonmail.error{color:darkred;}Polybar config examplemodules-right=protonmail...[module/protonmail]type=custom/scriptexec=bar-protonmail -f polybarinterval=10click-left=xdg-open https://mail.proton.me/u/0/inboxScript argumentsSeebar-protonmail -hfor the list of arguments with descriptions.Possible values for-s,--soundcan be found with:ls/usr/share/sounds/freedesktop/stereo/|cut-d.-f1for example-s message-new-instant.
Package: barpy
# barpy #This is Python a port of [barby][] library written in Ruby. I couldn’t find
lightweight Python barcode generation library of the same caliber asbarby([elaphe][] is broken and others don’t support GS1-128andQRCode at the same
time, so I portedbarby.[barby]:http://toreto.re/barby/[elaphe]:http://code.google.com/p/elaphe/API is basicly the same as ofbarby, but in Python style.The port is very quick and not complete at the moment (I ported only parts
I really need for my project), I will port the rest eventually.Also the port is quite direct, in a sense there are a lot of places in Python
code which have more Rubyish flavour instead of Pythonian (e.g. a lot of@propertydecorators to call methods without parenthesis). I did it to avoid
logic errors during porting process, I will make code more Pythonian in the
future.
Package: barracks_sdk
Barracks SDK for Python #The Python SDK to interact with the [Barracks](https://barracks.io/) API## Set up ##* Summary of set up* Configuration* Dependencies* Deployment instructions## Usage ##### BarracksHelper ###First you need to init a BarracksHelper with you API key```#!pythonbarracksHelper = BarracksHelper.BarracksHelper("YOUR_API_KEY")```### Check for Updates ###Check for new available updates with the UpdateCheckerHelper```#!python# Perform a simple checkrequest = UpdateDetailRequest.UpdateDetailRequest("v1", "MyDevice", "{\"AnyCustomData\":\"any_value\"}")checkHelper = barracksHelper.updateCheckerHelpercheckHelper.check_update(request, check_update_callback)```### Download Update ###Download the package linked to an UpdateDetail with the PackageDownloadHelper```#!pythonpackageDownloadHelper = PackageDownloadHelper.PackageDownloadHelper(bh.apiKey)packageDownloadHelper.download_package("./myUpdate", updateDetail, download_package_callback)```### Full example using Callbacks ###Check & download update using callbacks```#!pythondef download_package_callback(*args):"""Callback to handle the downloaded file from PackageDownloadHelper.download_package"""if args:# We've got an ApiError"if isinstance(args[0], ApiError.ApiError):print "Message : " + args[0].get_message()# We've got the downloaded file pathelse:file_path = args[0].__str__()if os.path.isfile(file_path):print "File downloaded at " + file_path.__str__()else:print "File Error"def check_update_callback(*args):"""My callback to handle new update from UpdateCheckerHelper.check_update"""if args:  # If args is not empty.# We've got an UpdateDetailif isinstance(args[0], UpdateDetail.UpdateDetail):# Download the file linked to this UpdateDetailph = PackageDownloadHelper.PackageDownloadHelper(bh.apiKey)ph.download_package("./myUpdate", args[0], download_package_callback)# We've got an ApiErrorelif isinstance(args[0], ApiError.ApiError):print "Error message : " + args[0].get_message()else:print args[0].__str__()# Call Helpers to check & download for new updatebarracksHelper = BarracksHelper.BarracksHelper("YOUR_API_KEY")request = UpdateDetailRequest.UpdateDetailRequest("v1", "MyDevice", "{\"AnyCustomData\":\"any_value\"}")checkHelper = barracksHelper.updateCheckerHelpercheckHelper.check_update(request, check_update_callback)```
Package: barrett
=======barrett=======barrett is a software package meant to process and visualise the output of the nested samplingalgorithm MultiNest. There are several packages already on the market for this, but barrett'smain differential feature is out-of-core processing so the code can handle very large datasets.Specific technologies: HDF5, and Python (h5py, scipy, numpy, matplotlib).Usage-----barrett is split into four submodules:+ barrett.data implements methods for modifying data (e.g. log, change units) or calculatedepended variables (e.g. mean squark mass)+ barrett.posterior is for calculating and plot the one or two dimensional marginalposterior distribution.+ barrett.profilelikelihood is for calculating and plot the one or two dimensional profilelikelihood.+ barrett.util contain various utility functions most notable convert_chain() which convertsthe plain text MultiNest output to the HDF5 format used by barrett.As for parallelisation; writing to the same hdf5 file is strongly discouraged. Reading the fileis however perfectly fine. So posterior/profilelikelihood module is perfectly parallelisable.The code itself is not parallelised, instead I recommend using Python's multiprocessing module toproducing several plots in parallell. In most system tested the plotting is CPU bound, yourmileage may vary.Installation------------Barrett is available on PyPI and can be installed using pippip install barrettCite----If you use barrett in your research please cite arXiv:1608.00990:@article{2016arXiv160800990L,author = {Liem, Sebastian},title = "{Barrett: out-of-core processing of MultiNest output}",archivePrefix = "arXiv",eprint = {1608.00990},primaryClass = "stat.CO",year = 2016}Example-------Please check the example directory for plot.py for an, you guessed it, example.
Package: barrier3d
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4730988.svg)](https://doi.org/10.5281/zenodo.4730988)# Barrier3D
A spatially explicit exploratory model of coastal barrier evolution.### Full documentation for Barrier3D is available at: <https://unc-cecl.github.io/Barrier3D/>There are two primary branches for this repository:
-Barrier3D-v1.0– Created by Ian Reeves and used for all simulations in Reeves et al., 2021 (GRL)
-master– Contains a basical model interface, written by Eric Hutton and Katherine Anarde and used in Anarde et al., (in prep). This branch contains an abbreviated copy ofBarrier3D-v1.0for testing purposes.# Credits## Contributors[Katherine Anarde](https://github.com/anardek)[Ian Reeves](https://github.com/irbreeves)[Eric Hutton](https://github.com/mcflugen)
Package: barrins-codex
Barrin's CodexA website about MtG Duel Commander StrategySpecial ThanksI started working withlionel-panhaleuxon a project during first lockdown (around April 2020). We worked on hisCodex of the Damned(repo) to support
internationalisation. The whole structure of this project is derived from his
Codex, hence the name as a small tribute.ContributingContributions are welcome.Pull Requestswill be merged if they respect the general style.Issueswill be dealt with as quickly as possible.This site usesFlaskto generate pages
dynamically .InstallationTo install a working developpment version of the site, usepip:python3-mvenvvenvsourcevenv/bin/activate
pipinstall-e".[dev]"Run the CodexYou can run the development version of the site using thecodexentrypoint:$codex
*ServingFlaskapp"barrins_codex"(lazyloading)*Environment:productionWARNING:Thisisadevelopmentserver.Donotuseitinaproductiondeployment.UseaproductionWSGIserverinstead.
*Debugmode:off
*Runningonhttp://127.0.0.1:5000/(PressCTRL+Ctoquit)The Makefile has a command to start codex in debug :make codexVersioningThe version number take the form X.Y.Z where X, Y, and Z are non-negative
integers, and do not contain leading zeroes. X is the major version, Y is the
minor version, and Z is the patch version. Each element MUST increase
numerically. For instance:1.9.0->1.10.0->1.11.0.Given a version number MAJOR.MINOR.PATCH, I increment the:MAJOR version when I make a backend evolution or a design evolution,MINOR version when I add content (most likely a match), andPATCH version when I make bug and typo fixes.Additional labels for pre-release and build metadata are available as
extensions to the MAJOR.MINOR.PATCH format.
Package: barry-energy-api
Welcome to Barry Energy API Client 👋Simple python package to work with the API of Barry Energy.
The API documentation can be foundhere.Please be aware that this project is NOT offical.Installpip3installbarry-energy-apiUsageGet your API TokenGetfrommobileappunder"Add-ons"->"Barry API"Import the packagefrombarry_energy_apiimportPriceZone,BarryEnergyAPIInitialize the APIapi=BarryEnergyAPI('api-token',5,PriceZone.DK_EAST)Get aggregated consumption for the last 5 days as defined when API was initialized.api.consumption()Get prices from the last two days.Notice that methode has overloadingapi.spotprices(2)Author👤Emil Elkjær NielsenWebsite:https://evsn.dkGithub:@eelkjaerLinkedIn:@emil-elkjærShow your supportGive a ⭐️ if this project helped you!📝 LicenseCopyright © 2021Emil Elkjær NielsenThis project isMITlicensed.This README was generated with ❤️ byreadme-md-generator
Package: bars
A small command-line utility to take a CSV file and print a bar chart in
your terminal. Especially useful in combination with tools likeCSVKit,q, andjq.$ curl -s http://www.census.gov/popest/data/national/totals/2015/files/NST-EST2015-alldata.csv | head -n 6 | bars --label NAME --value POPESTIMATE2015 --width 72 -
NAME             POPESTIMATE2015
United States        321,418,820 ▓░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
Northeast Region      56,283,891 ▓░░░░░
Midwest Region        67,907,403 ▓░░░░░░
South Region         121,182,847 ▓░░░░░░░░░░░░
West Region           76,044,679 ▓░░░░░░░
                                 +---------+---------------------------+
                                 0    100,000,000            400,000,000Repository:https://github.com/flother/barsIssues:https://github.com/flother/bars/issuesInstallationpip install -e git+https://github.com/flother/bars#egg=barsRequirementsPython 3ClickAgateUsageUsage: bars [OPTIONS] CSV

  Load a CSV file and output a bar chart.

Options:
  --label TEXT        Name or index of the column containing the label values.
                      Defaults to the first text column.
  --value TEXT        Name or index of the column containing the bar values.
                      Defaults to the first numeric column.
  --domain NUMBER...  Minimum and maximum values for the chart's x-axis.
  --width INTEGER     Width, in characters, to use to print the chart.
                      [default: 80]
  --skip INTEGER      Number of rows to skip.  [default: 0]
  --encoding TEXT     Character encoding of the CSV file.  [default: UTF-8]
  --no-header         Indicates the CSV file contains no header row.
  --printable         Only use printable characters to draw the bar chart.
  --help              Show this message and exit.
Package: barseq
barseqPython package for analyzing barseq data.Installationpipinstallgit+https://github.com/mjmlab/barseq.git@masterUsagebarseq-i<directoryofsequencingreads>-b<barcodefile>-e<experimentname>-i/--inputDirectory with Illumina reads in either fastq or fastq.gz.-b/--barcodesCSV file with barcode and correspondent gene names.-e/--experimentName of experiment, it is used for creating results folder.Files NeededDirectory of Illumina reads [-i]for analyzing. Can be either fastq or fastq.gz format@M06026:87:000000000-D69HY:1:1102:15909:1336 1:N:0:TGACCA
CTCTAGAAAGTATAGGAACTTCAGGGCCATTTATATACCTTCCACTCTTCAACCGTGTCTTGACTTGACCTGGATGTCTCTACTGCTGTCATGCTACGTAGCTCATGCTACGTCGATCTAGTCGATGCATGCTAGCTGATCGACTCTCTTC
+
A#>>>3AA2DD>FBFGBFBFBFDDFGGAAEEEHDHFFFDDDBDGDFDDDDDADFGFFDDBFFEBFD5DFEEBBADABFGFGBBFGDD5BF3F43B3F1/11B144BGEBF@BBFB0B0BBFBBBBBBBB?E/FGFBB?/???B???/?FGGBarcode file [-b]with gene names. Needs to be in CSV format.Barcode,Gene
ATGAAGACTGTTGCCGTA,WT
CACGACGCCCTCCGCGGA,gene1
ACTATTACGCAAAATAAT,gene2
ATGGAAGATATTATTATT,gene3
CCTCTCCAACCGGGTCTG,gene4
CCCGGTCGCCTAGCCCCG,gene5
GGCCCCCCGCCCGTCCCC,gene6
GGATCACTGCTAGCGTAT,gene7
CCTGCAGCAGCGGCCCGC,gene8
ACACATGCAGACATAGAG,gene9
CGCGCCATCCGCCGCCCA,gene10
AATATTCAGATGGGACGT,gene11Outputresults/directory_results.csv: barcode counts found in each sequence file.GeneBarcodeSample 1Sample 2Sample 3...gene1ATGAAGACTGTTGCCGTA50057...gene2CACGACGCCCTCCGCGGA121319...gene3ACTATTACGCAAAATAAT131110..._other_other284029...Barseq Workflow
Package: barseqcount
barseqcountAnalysis of DNA barcode sequencing experimentsIt is recommended to use barseqcount in acondaenvironment (can be Linux, Mac or Windows).Install from Bioconda:conda install -c bioconda barseqcountInstall from PyPI:pip install barseqcountRun:barseqcount [-h] [-v] {count,analyze} ...orpython -m barseqcount [-h] [-v] {count,analyze} ...Full documentation:https://barseqcount.readthedocs.io/GitHub issues (bug reports, feature requests):https://github.com/damienmarsic/barseqcount/issues/new/choose
Package: barsup-core
WTFbarsup-core- представляет собой базовые серверные реализации различных
уровней rest-приложения, с возможностью декларативного описания функционала
на базеIoC.Возможностистрогая зависимость между уровнями приложения с отслеживанием утечек абстракциивозможности расширять конфигурацию своими реализациямизапуск контейнера как в режимевебсокетов, так и в стандартном режимеwsgiвозможности создания business-middleware и initwareвстроенные механизмы аутентификации и авторизацииУстановкаПоследнюю версию можно установить изPYPIкомандой:$ pip install barsup-coreВ качестве примера использования рекомендуется посмотретьdemo(с возможностьюочень быстрого запуска средствами Vagrant’a),
а так же примеры использования изтестовПодробная документация