Saravanan666/pypi-org huggingface dataset:
Package: branch-statement-analyzer
Python Branch Statement AnalyzerThe purpose of this library is two-fold:Detect independent paths through a function and represent all paths as a
fully-connectedKripke Structure.Instrument a function to preserve the states of the conditional variables for
an execution of the function and augment the return value of the function
with the conditional variable states.Path detectionTODOInstrumentationTODOUsageDecomposition of a function into a condition tree is accomplished by calling
theBranchTree.from_functionstatic method like so:defmyfunc(x):ifx<=10:returnx**2else:returnx*2tree=BranchTree.from_function(myfunc)Conversion of the BranchTree into a Kripke Structure can be accomplished by
calling theBranchTree.into_kripkemethod once the function has been analyzed.A function can be instrumented using theinstrument_functiondecorator, which
will return another function that accepts the same inputs and returns a tuple
containing the return value of the function and the states of the conditional
variables.@instrument_functiondefmyfunc(x):ifx<=10:returnx**2else:returnx*2states,retval=myfunc(8)DocumentationDocumentation for this project can be found onRead the Docs
Package: branch-time
Time BranchTime Branch is a command-line interface tool that allows you to track the time you spend working on different branches in your repository. With Time Branch, you can easily monitor how much time you spend in each branch, helping you stay on top of your activities and improve productivity. Additionally, Time Branch offers features to export collected data to an output file, making it easy to analyze and share information with your team. With the help of Time Branch, you can optimize your software development activities and improve your efficiencyInstallpipinstallbranch-timeHow to usetime values ​​in minutesbranchtime'your\repository.git'--time20--output'output\directory'branchtime'your\repository.git'-t20-o'output\directory'branchtime'your\repository.git'--time20--output'output\directory'or
branch-time'your\repository.git'--time20--output'output\directory'default values:repository = your current directory--time = 5 minutes--output = your current directoryHelpOutput2023-04-24.txtBranch: master - Time: 20:57:17
FINISHED... 21:44:11

Branch: main - Time: 21:58:19

Branch: AUTO-29975 - Time: 22:10:29

Branch: AUTO-32659 - Time: 22:34:10

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Branch: main - Time: 23:55:32
FINISHED... 23:055:33
Package: brand
brandFinding available domain namesTo install:pip install brandHow to useExample scriptsearch_names.pyshows an example of how to assemblebrandfunctionalities to write a script that will search
names of the formCVCVCV(Cfor consonant,Vfor vowel)
with no more than4unique letters and where either the
consonants or the vowels are all the same....
(10)12:49:07 - 2255: nesebe
(10)12:49:08 - 2256: nesede
(10)12:49:09 - 2257: nesefe
---> Found available name: nesefe
(10)12:49:09 - 2258: nesege
---> Found available name: nesege
(10)12:49:09 - 2259: nesele
---> Found available name: nesele
(10)12:49:11 - 2260: neseme
---> Found available name: neseme
(10)12:49:11 - 2261: neseneThe functions available to youname_is_availablename_is_availablechecks if a name is available using the system'swhoiscommand.frombrandimportname_is_availableassertname_is_available('google.com')isFalseassertname_is_available('asdfaksdjhfsd2384udifyiwue.org')isTrueThe storeFirst, you'll need to provide a "store".
That is, a dict-like object that will hold the names you've checked so far,
under keysavailable_names.pandnot_available.p(which contains the names
that were checked, but not available).The functions use this both to not check what you've already checked,
and to store its results as they check names.A store can be an actualdict, or a dict-like interface to files or a DB.We advise to usepy2store(which is installed withbrand) to make dict-like
interfaces to your storage system of choice.When you askbrandto make a store with no further specifications,
it makes a directory and places files in there for you.importbrands=brand.get_store()Now you can use that store to see what's already available from
past work (if anything).available=brand.available_names(s)not_available=brand.not_available_names(s)len(available),len(not_available)process_namesprocess_nameswill take somenames(specified as an iterable,
generator function, or pickle file) and check if each is available,
saving the results in the given store.try_these=['google.com','gaggle.com','giggle.org','asdfiou3t.org']process_names(try_these)
Package: brand-alert
OverviewThe client library forBrand Alert APIin Python language.The minimum Python version is 3.6.Installationpipinstallbrand-alertExamplesFull API documentation availablehereCreate a new clientfrombrandalertimport*client=Client('Your API key')Make basic requests# Get the number of domains.result=client.preview(['google'])print(result.domains_count)# Get raw API responseraw_result=client.raw_data(['google'],response_format=Client.XML_FORMAT,mode=Client.PREVIEW_MODE)# Get list of recently registered/dropped domains (up to 10,000)result=client.purchase(['google'])Advanced usageExtra request parameterstoday=datetime.date.today()delta=datetime.timedelta(days=10)result=client.purchase(['google'],exclude_terms=['blog'],since_date=today-delta,with_typos=True,punycode=False)raw_result=client.raw_data(['google'],exclude_terms=['blog'],since_date=today-delta,with_typos=True,punycode=False,mode=Client.PURCHASE_MODE,response_format=Client.JSON_FORMAT)Changelog1.0.0 (2021-05-04)First release
Package: brandeis-acs
Acoustic Classification & SegmentationSimple audio segmenter to isolate speech portion out of audio streams. Uses a simple feedforward neural network for classification (implemented usingtensorflow) and heuristic smoothing methods to increase the recall of speech segments.Requirements and installationSystem packages:ffmpegInstallation: installbrandeis-acsfrom PyPIpip install brandeis-acsTrainingPretrained modelWe provide apretrained model. The model is trained onMUSAN corpus, using binary labels (speechvs.nonspeech). The model is, then, serialized usingtensorflow::SavedModelformat. Because of the distribution bias in the corpus (a lot more of speech recordings in the training data), we randomly resampled from frames (size of 10ms) from speech examples to match its size to negative examples. In doing so, the language distribution among the resampled speech examples was NOT deliberately balanced.Training pipelineTo train your own model, invokebacswith-tflag and pass the directory name where training data is stored. You might also want to take a look atextract_allfunction infeature.pyto change how the labels are read in, if using corpora other than the MUSAN.SegmentationTo run the segmenter over audio files, invokebacswith-sflag, and pass the directory where audio files are stored. Optionally, you can pass the model path with-mflag. If the model path is not given, the default pretrained model will be used. Currently, it will process allmp3andwavfiles in the target directory.If you want to process other types of audio file, you need to edit source code for now. Clone this repository and add to or change thefile_extlist near the bottom ofrun.pyfiles. When running from source code, runrun.pyfile.The processed results are stored assegmented.tsv, a tab-separated file, in the target directory. Each row of the file represents a result from a single audio file, and columns represents as follows;first column shows the file pathlast column shows the ratio of speech portion of the filecolumns between are paired into start and end points (in seconds) of speech segments.Using dockerWe also provideDockerfile. If you want to run the segmenter as a docker container (not worrying about dependencies), first build an image from this project directory using theDockerfile. Note that the image will not use the PyPI package version, but copy the code as of the build-time.
Then run the image with the target directory with audio files to process mounted at/segmenter/data. Just MAKE SURE that target directory is writable by others (chmod o+w $TARGET_DIR) because a non-root user will be running the processor in the container. For example,gitclonehttps://github.com/keighrim/audio-segmentation.gitcdaudio-segmentation
chmod-Ro+w$HOME/audio-files&&dockerbuild.-taudioseg&&dockerrun--rm-v$HOME/audio-files:/segmenter/data-itaudiosegOnce the process is done, you'll find asegmented.tsvfile in the local target directory.
Package: brandelion
===============================Brandelion===============================.. image:: https://badge.fury.io/py/brandelion.png:target: http://badge.fury.io/py/brandelion.. image:: https://travis-ci.org/aronwc/brandelion.png?branch=master:target: https://travis-ci.org/aronwc/brandelion.. image:: https://pypip.in/d/brandelion/badge.png:target: https://pypi.python.org/pypi/brandelionSocial media brand analytics* Free software: BSD license* Documentation: https://brandelion.readthedocs.org.Features--------* TODOHistory---------------------0.1.7 (2017-01-23)* bugfixes0.1.4 (2015-10-06)* require scikit-learn-------0.1.4 (2015-10-06)---------------------* require sklearn0.1.3 (2015-10-06)---------------------* Correctly specify requirements in setup.py0.1.2 (2015-10-06)---------------------* Fix packaging bug0.1.1 (2015-10-06)---------------------* Python 2->3* Support continuous collection of followers.0.1.0 (2015-01-01)---------------------* First release on PyPI.
Package: brandub
BrandubA python package to play brandub.InstallationpipinstallbrandubPlay a gameTo play via the command line, simply run thebrandubcommand.To play a game in a python terminal or ipython terminal,
instantiate aBrandubGameobject and use therun()method.>frombrandubimportBrandubGame>game=BrandubGame()>game.run()To exit either version, simply ctrl+c and enter 'y'.RulesWe use the rules onthis  website.
But here's a rundown:Brandub is played on a 7x7 board. The monarch sits in the center surrounded
to the left, right, above, and below by defensive pawns. There are eight
attacking pawns, two each placed side by side next to the defensive pawsn
such that all pieces form a plus sign.
The goal for the defending team is to escort the monarch to any of the
corners. The goal for the attacking team is to capture the monarch.All pieces can move horizontally or vertically any number of spaces,
except that no piece can land on another piece nor can a piece move
past a piece in its way. Only the monarch can land in the corners of
the board -- the "forests" --
and no piece may land in the central square -- the "castle" -- once it
has been abandoned by the monarch, although any piece may continue moving
past it.The pawns are captured if they are trapped by two opposing pieces
either to the left and right or above and below. Additionaly, pawns
can be trapped by the empty castle or by the forests. (Attacking
pawns can be trapped by the occupied castle since the only possible
occupant is the monarch.)If inside the castle, the Monarch is only captured if surrounded by
four attacking pawns, one above, one below, one right, one left. If
the monarch is immediately next to the castle (not diagonally) then
the monarch is trapped by three attacking pawns and the empty castle.
Elsewhere, the monarch is trapped just like pawns, including being
trapped by a forest and attacking pawn.The attackers move first. The game ends in a draw if a board position
is repeated.
Package: brange
Better RangeA range which automatically deals with either direction.Installationpip install brangeUsageStart is always inclusive and end is always exclusive. Step must be a positive integer, as it always steps toward the end. A negative value will result in an empty range.Regularfrombrangeimportbrange# This will create a list between 10 (inclusive) and -40 (exclusive)# [10, 11, 12, ... -37, -38, -39][iforiinbrange(10,-40)]N-dimensionalfrombrangeimportnbrangedimensions=[(1,10,2),# X(3,-2,1),# Y(-2,5,1),# Z][xyzforxyzinnbrange(*dimensions)]# This will result in a list as below:# [#     (1, 3, -2),#     (1, 3, -1),#     ...#     (9, -1, 2),#     (9, -1, 3),#     (9, -1, 4),# ]
Package: brasilapi
brasilapi-pythonUm cliente Python assíncrono para oBrasil  APIMotivaçãoFornecer um cliente HTTP assíncrono de alto nível para acessar e desserializar recursos do BrasilAPI.InstalaçãoCom pip:pip install brasilapiOu com Poetry:poetry add brasilapiUsoEste cliente fornece chamadas à API do BrasilAPI dentro de um gerenciador de contexto assíncrono para uma melhor performance.Por exemplo, o seguinte programa:importasynciofrombrasilapiimportBrasilAPIasyncdefrun():asyncwithBrasilAPI()asclient:result=awaitclient.ceps.get("89010025")print(repr(result))if__name__=="__main__":asyncio.run(run())Fornece uma saída igual ou semelhante a:CEP(cep='89010025',state='SC',city='Blumenau',neighborhood='Centro',street='Rua Doutor Luiz de Freitas Melro',service='correios',location=CEPLocation(type='Point',coordinates={'longitude':'-49.0641133','latitude':'-26.9239862'}))Chamadas dentro do gerenciador de contexto utilizam uma mesma sessão que só é fechada ao sair do bloco. Você pode optar por compartilhar o mesmo cliente e sessão durante o tratamento de uma solicitação no seu aplicativo (por exemplo, funciona muito bem retornar uma instância do BrasilAPI como uma dependência do FastAPI) ou enquanto fizer sentido para seu cenário.Modelos PydanticOs resultados das consultas são instâncias de modelosPydantic v2. Você pode aproveitar a consistência e todas as dicas de tipo.Os modelos Pydantic foram construídos com base nadocumentação oficial do BrasilAPIe os nomes dos serviços e atributos são iguais aos
da documentação; portanto, alguns estão em inglês e outros em português. Excetuam-se mudanças decamelCaseparasnake_case. Mas você pode usar seu próprio modelo Pydantic:importasynciofrompydanticimportBaseModel,FieldfrombrasilapiimportBrasilAPIclassCustomDDD(BaseModel):estado:str=Field(alias="state")cidades:list[str]=Field(alias="cities")asyncdefrun():asyncwithBrasilAPI()asclient:ddd=awaitclient.ddd.get("83").with_deserializer_class(CustomDDD)print(repr(ddd))if__name__=="__main__":asyncio.run(run())
Package: brasilapy
BrasilApyUm cliente daBrasil  APIem python3. Link dorepositóriooficial.Nesta versão1.0.0esse cliente possui suporte a autocomplete por meio de Typed Hints. Todos as respostas são traduzidas para objetos do Pydantic, que trazem previsibilidade ao explorar a API  através da sua IDE favorita.InstalaçãoRode o comandopip install brasilapye estará tudo pronto.
A versão do python que é compativel com essa biblioteca é a3.10+.DocumentaçãoDocumentação oficial da API com todas as chamadas poderão se encontradasneste link.Código de exemploPara efetuar as consultas na API, basta instanciar a classe e fazer as consultas.frombrasilapyimportBrasilAPIclient=BrasilAPI()estado=client.get_ibge_estado(state_uf="pb")print(estado.id)print(estado.regiao)print(estado.sigla)#### para um caso mais complexo, temos###frombrasilapy.constantsimportIBGEProvidermunicipios=client.get_ibge_municipios(state_uf="pb",providers=(IBGEProvider.DADOS_ABERTOS_BR,))formunicipioinmunicipios:print(municipio.nome)print(municipio.codigo_ibge)Métodos disponíveis doBrasilAPIMétodoDetalhesget_banks()get_bank(code: str)get_cep(test_cep: str, api_version: APIVersion)get_cnpj(test_cnpj: str)get_ddd(test_ddd: str)get_feriados(year: int)get_fipe_veiculos(tipo_veiculos: FipeTipoVeiculo, tabela_referencia: int)get_fipe_precos(codigo_fipe: str, tabela_referencia: int)get_fipe_tabelas()get_ibge_municipios(state_uf: str, providers: tuple[IBGEProvider]get_ibge_estados()get_registro_br_domain(fqdn: str)get_taxas_juros()get_taxa_juros(taxa: TaxaJurosType)Os tipos de dadosAPIVersion,FipeTipoVeiculo,IBGEProvidereTaxaJurosTypesão classes de constants que podem ser importadas através do seguinte comando:frombrasilapy.constantsimportAPIVersion,FipeTipoVeiculo,IBGEProvider,TaxaJurosTypeAutoresFilipe SoaresJonhnatha TrigueiroGostaria de contribuir?Escrevemos um guia que pode ser encontrado emCONTRIBUTE.md.
Package: brasil.gov.newfieldcomplement
ConteúdoIntroduçãoInstalaçãoDocumentaçãoIntroduçãoComplementa a inclusão de novos campos nos tipos de conteúdo Dexterity,
provida pelo pacote plone.app.contenttypes.Engloba:Formulário de criação de novo índice e metadado no portal_catalog.
Esse índice poderá ser utilizado nos filtros da pesquisa facetada
(eea.facetednavigation) e na exibição do resultado da pesquisa.Formulário de gerenciamento de quinze listas de valores/opções, convertidas
em quinze vocabulários dinâmicos que podem ser utilizados tanto pelos novos
campos (seleção/checkbox) criados nos tipos de conteúdo Dexterity, quanto nos
filtros da pesquisa facetada.Nova visão de pasta Facetada Tabular para exibição do resultado da pesquisa
facetada no formato tabular de até cinco colunas.Novo formulário de configuração da visão Facetada Tabular, que permite a
seleção do campo, vocabulário (caso necessário) e do título de cada uma das
cinco colunas que podem ser exibidas no resultado da pesquisa.Vocabulário fixo de Estados e caminho das pastas, úteis em novos campos ou
filtros da pesquisa facetada.InstalaçãoPara habilitar a instalação deste produto em um ambiente que utilize o
buildout:Editar o arquivo buildout.cfg (ou outro arquivo de configuração) e
adicionar o pacotebrasil.gov.newfieldcomplementà lista de eggs da instalação:[buildout]
...
eggs =
    brasil.gov.newfieldcomplementApós alterar o arquivo de configuração é necessário executar
‘’bin/buildout’’, que atualizará sua instalação.Reinicie o Plone4. Acesse o painel de controle e instale o produtoSuporte a novos campos dexterity na busca multifacetada (brasil.gov.newfieldcomplement).Obs.: Os sites que utilizam o pacote IDG já vem com os pacotesTipos de conteúdo Dexterity (plone.app.dexterity)eContent-Types (plone.app.contenttypes)instalados. Para os sites que não utilizam o pacote IDG, é necessário que os mesmos sejam instalados.
Caso não estejam disponíveis para instalação, devem ser adicionados ao buildout:[buildout]eggs =plone.app.dexterityplone.app.contenttypesbrasil.gov.newfieldcomplementDocumentaçãoA documentação encontra-se na pastadocs.
Package: brasil.gov.vlibrasnews
ConteúdoIntroduçãoEstado deste pacoteInstalaçãoUsoComo funcionaColaboradoresChangelog1.0b1 (2016-09-07)1.0a1 (2016-08-01)IntroduçãoO VLibras News API é um serviço desenvolvido peloLaboratório de Aplicações de Video Digitalpara gerar traduções paraLIBRASem forma de vídeos armazenados no YouTube.Este pacote é uma integração do VLibras News API no Plone,
atraves de um behavior para tipos de conteúdo Dexterity.Estado deste pacoteInstalaçãoPara habilitar a instalação deste produto em um ambiente que utilize o buildout:Editar o arquivo buildout.cfg (ou outro arquivo de configuração) e
adicionar o pacotebrasil.gov.vlibrasnewsà lista de eggs da instalação:[buildout]...eggs=brasil.gov.vlibrasnewsApós alterar o arquivo de configuração é necessário executar ‘’bin/buildout’’, que atualizará sua instalação.Reinicie o PloneAcesse o painel de controle e instale o produto.gov.br: Tradução de Português para LIBRAS.UsoApós instalar o pacote é preciso ir na ‘Configuração do Site’,
selecionar ‘VLibras News API’ nas ‘Configurações de Complementos’,
e informar o token de acesso.Para ativar o behavior é necessário ir em ‘Tipos de conteúdo Dexterity’,
selecionar o tipo de conteúdo que será processado,
e habilitar o behavior ‘VLibras News’.Um novo campo de só leitura será disponibilizado para armazenar o endereço do vídeo com a tradução a LIBRAS do conteúdo processado.Como funcionaQuando um usuário publicar um objeto de um tipo de conteúdo com o behavior habilitado,
uma requisição é feita na API para criar um vídeo com a tradução do conteúdo para LIBRAS.A partir desse momento a API é consultada periodicamente para conhecer o estado do processamento do vídeo.
Quando o vídeo ficar pronto para visualização, um viewlet disponibiliza um player para assistir o video.Caso o conteúdo for modificado,
o vídeo anterior é retirado e uma nova requisição é feita para criar um novo vídeo com a tradução do conteúdo atualizado para LIBRAS.Caso o conteúdo for excluido,
uma requisição é feita para excluir também o vídeo com a tradução do conteúdo para LIBRAS.ColaboradoresRodrigo Ferreira de SouzaHéctor VelardeChangelog1.0b1 (2016-09-07)Fix control panel configlet icon.
[hvelarde]The implementation was rewritten as a behavior.
No upgrade step is available, you must uninstall the previous version and install the new one.
[rodfersou, hvelarde]Fix button translation.
[rodfersou]1.0a1 (2016-08-01)Initial release.
Package: brasil.vocab
Table of ContentsOverviewVocabularies availableGeographic informationTelecom informationRequirementsInstallationBasic usageSponsoringCreditsChangelog0.8 (2011-12-20)0.7 (2011-05-26)0.6 (2011-05-25)0.5 (2011-05-24)OverviewThis package aims to provide basic vocabularies related to Brazil for Python
developers.It’s written in Brazilian Portuguese.Bug tracker and code repository can be found atGitHubVocabularies availableGeographic informationCountries (ISO 3166 in Brazilian Portuguese)States (Brazilian states)Cities (Brazilian cities, organized by state)Cities (Brazilian cities)Telecom informationArea codes (Geographic Codes a.k.a DDD)Non Geographic Codes (0x00 prefixes)Codes (Geographic + Non Geographic Codes)RequirementsPython 2.4InstallationInstalling on your Python packages:easy_install brasil.vocabAdding it to install_requires in another Python package (in setup.py):install_requires=[
    'setuptools',
    # -*- Extra requirements: -*-
    'brasil.vocab'
],Basic usageAfter installing it we just need to import it and use:>>> from brasil.vocab.geo import uf
>>> len(uf)
27
>>> print uf[0]
('AC', u'Acre')SponsoringDevelopment of this product was sponsored by :TRT13.Simples Consultoria.APyB.CreditsSimples Consultoria (products at simplesconsultoria dot com dot br) -
ImplementationChangelog0.8 (2011-12-20)Added tests [ericof]Added codes vocabulary to telecom  (cng + ddd)[ericof]Added cng vocabulary to telecom [ericof]DDD vocabulary now do not provide cng prefixes (0x00) [ericof]0.7 (2011-05-26)Fixing typo in Cities vocabulary [erico_andrei]0.6 (2011-05-25)Fixing Cities vocabularies [erico_andrei]0.5 (2011-05-24)Countries [erico_andrei]Brazilian States and Cities [lepri]Initial implementation [erico_andrei]Area Codes [erico_andrei]
Package: braspag
# Braspag[![Build Status](https://secure.travis-ci.org/TracyWebTech/braspag.png?branch=master)](https://travis-ci.org/TracyWebTech/braspag)## Getting Started### DependenciesThe following dependencies are automaticatly installed by the setup.py:Jinja2### InstallationClone the repository to your machine.Runpython setup.py installfrom the root of your local clone.# Documentationhttps://braspag.readthedocs.org/# LICENSEAll source code here is available under the [LGPL Version 3][] license, unless
otherwise indicated.[LGPL Version 3]:http://www.gnu.org/licenses/lgpl.txt
Package: brasser
brasser.pyA Python library for generating cryptographically random UUIDs.Installation$ pip install brasserBrief"Brasser" is a Python library that provides a function for generating cryptographically random UUIDs (Universally Unique Identifiers). UUIDs are used to uniquely identify resources, and are often used as keys in databases or as part of URLs to identify web resources. The UUIDs generated by thegenerate_uuidfunction in the "brasser" library are randomly generated using theos.urandomfunction, which generates random bytes using the operating system's secure random number generator. This makes the UUIDs generated by "brasser" suitable for use in security-sensitive applications where uniqueness and unpredictability are important.Example Usagefrombrasserimportgenerate_uuiduuid=generate_uuid()print(uuid)# Prints a new random UUID each time