Saravanan666/pypi-org huggingface dataset:
Package: cepcenv
CEPC software management toolkitInstall cepcenvInstallcepcenvwithcurlorwgetcurl -sSL http://cepcsoft.ihep.ac.cn/package/cepcenv/script/install.sh | sh -s [CEPCENV_DIR]orwget -qO- http://cepcsoft.ihep.ac.cn/package/cepcenv/script/install.sh | sh -s [CEPCENV_DIR]IfCEPCENV_DIRis omitted,cepcenvwill be installed in the
current directory.Install cepcsoft with cepcenvSetupcepcenv:. <CEPCENV_DIR>/setup.shList available CEPC software version:cepcenv ls-remoteSpecify CEPC software version and where to install:cepcenv [-r <SOFTWARE_ROOT>] install <version>If-r<SOFTWARE_ROOT>is not specified, everything will be
installed in the current directory.Multiple versions could be installed under the same software root
directory.ConfigurationCreate the configuration file if it does not exist:[ -e ~/.cepcenv.conf ] || cepcenv config -e > ~/.cepcenv.confEdit~/.cepcenv.confand uncommentsoftware_root:software_root: <SOFTWARE_ROOT>Select cepcsoft VersionList local installed CEPC software version:cepcenv -r <SOFTWARE_ROOT> lsSelect local CEPC software version you would like to use:cepcenv -r <SOFTWARE_ROOT> use <version>
Package: cepclient
Users can use this command line tool to generate a “history” of openration events performed on Chameleon Testbed corresponding to a user session in json format.
An experiment precis is defined as a series of real-time events a user performed under a lease of a project. Corresponding hardware and metric information is also included.InstallpipinstallcepclientRunBefore requesting the experiment precis using CEP client, user needs to provide Chameleon authentication information.
You can eithersourcethe OpenStack RC fileor pass the authentication information as command line arguments.
Usecep--helpfor authentication options and usage details.To list all experiment precis, use command:ceplist# use help for more informationceplist--helpTo get an experiment precis, use command:You can apply different filters to print experiment precis. For example, use--exclude-hardwareto hide hardware information
or use--exclude-metricto screen out metrics from the printed experiment precis.
In addition, you can prettyprint the experiment precis by passing--prettyargument.
To save the experiment precis to a file, specify output location using--outputargument.
For more options of printing an experiment precis, usecep print--help.To rename an experiment precis, use command:ceprename--name<newname><epnameorid># use help for more informationceprename--help
Package: ceph-command-api
ceph-command-api. An automatically generated API for accessing the Ceph CLI.It provides proper auto completion in your IDE, an automatically
[generated documentation](https://ceph-command-api.readthedocs.io/en/latest/mon_command_api.html)
, and static type checking.UsageInstall [ceph-command-api](https://pypi.org/project/ceph-command-api/) from PyPi:` pip installceph-command-api`And then:`python import rados from ceph_command_api import MonCommandApi cluster =rados.Rados(conffile='/etc/ceph/ceph.conf')cluster.connect()print(MonCommandApi(cluster).version())`Rebuild the APISee./rebuild.shReferenceSee [cholcombe973/ceph_command_parser](https://github.com/cholcombe973/ceph_command_parser) for a
similar project.
Package: cephes4py
cephes4pycephes4py is a Python interface to the HCephes library, which is a reformatted version of Netlib Cephes. It provides a convenient way to access the functionality of the HCephes library within Python. cephes4py has been updated to ensure compatibility with modern Numba releases (specifically tested on version 0.57.0).MotivationThe motivation behind developing cephes4py was the need to use SciPy special functions within Numba functions running in nopython mode. Unfortunately, this was not possible due to compatibility issues. Since many of SciPy's special functions are actually wrappers of Cephes functions, I decided to create my own bindings to Cephes that were compatible with Numba.Although cephes4py is much less "batteries included", I have conducted a preliminary experiment that suggests some performance improvements as well. You can refer tothis notebookfor more details.No Argument ValidationIt is important to note that cephes4py does not perform validation of the arguments passed to the underlying C-functions. This decision was made because validating even a single argument in Python could potentially double the execution time. Additionally, it would require wrapping the functions with the validation code, which makes them uncompatible with Numba. Therefore, I have chosen to leave the responsibility and freedom of argument validation to you. Please refer toFUNCTIONS.txtorinterface.hto see the expected parameter and return types.In the event that you provide invalid arguments, Hcephes will display an error message and return a fallback value. Please keep in mind that an argument can be considered invalid even if the data type is correct. For example, the binomial distribution function requires arguments to be positive, with the parameterpranging from 0 to 1 andkbeing smaller thann. Once again, please consultFUNCTIONS.txtfor more information.Cephes Function BindingsFor a list of available Cephes functions and their descriptions, please refer toFUNCTIONS.txt. Please note that I have not tested all of the functions extensively, but as long as the parameters and return types are scalar-valued, they should work properly. If you intend to pass Numpy arrays as arguments, things get a little more involved as you'll have to get the pointer to its buffer:a=np.zeros(10,dtype=np.float64)pointer=cephes4py.from_buffer("double[]",a)function_you_want_to_use(pointer)InstallationTo install cephes4py, please follow these steps:Install thehcephesbinary. It is recommended to compile it from source, but you will need Cmake to do so. You can use the following command to install it:curl-fsSLhttps://git.io/JerYI|GITHUB_USER=limixGITHUB_PROJECT=hcephesbashNavigate to the root directory of this repository.Install the cephes4py package by running the following command:pipinstall.You're all set! You can now use cephes4py in your Python code:importcephes4py# Example usagebdtr=cephes4py.bdtr(4,6,0.3)# You can even use the function in Numba-jitted functions running in nopython mode:@nb.njitdefnb_bdtr(k,n,p):returncephes4py.bdtr(k,n,p)bdtr=nb_bdtr(4,6,0.3)
Package: ceph-workbench
ceph-workbenchceph-workbench is a command-line toolbox forCephDocumentation :http://ceph-workbench.readthedocs.org/Home page :https://pypi.python.org/pypi/ceph-workbenchInstallationInstall Dockerhttp://docs.docker.com/engine/installation/Copy the following to~/.bashrc:eval "$(docker run dachary/ceph-workbench install)"Verify that it works:ceph-workbench --helpOptionally copy your OpenStack$PROJECT-openrc.shfile to~/.ceph-workbench/openrc.sh: theceph-qa-suitesubcommand will
use it.HackingFor best results, develop in Ubuntu 14.04 as a normal user (not root).Get the code:git clone --recursive http://ceph-workbench.dachary.org/root/ceph-workbench.gitSet up the development environment:deactivate || true ; source bootstrapThis creates a virtualenv containing theceph-workbenchexecutable and everything it needs to work.Activate the development environment and runceph-workbench:source virtualenv/bin/activate
PYTHONPATH=teuthology ceph-workbench --helpRun the tests (requires OpenStack credentials to get 100% coverage):deactivate || true ; bash run-tests.shSync the teuthology submodule:git submodule update --remote teuthologyRun a single test:tox -e py27 -- -s -k test_run tests/test_ceph_qa_suite.pyRun ceph-workbench using the dev environment of the current working
directory in the docker container instead of the installed version:eval "$(docker/entrypoint.sh install)"
ceph-workbench --help # use what is installed in the container
ceph-workbench-debug --help # use ceph-workbench from the working directory
ceph-workbench-shell bash # login the container and debugCheck the documentation : rst2html < README.rst > /tmp/a.htmlRelease managementPrepare a new versionversion=1.3.0 ; perl -pi -e “s/^version.*/version = $version/” setup.cfg ; for i in 1 2 ; do python setup.py sdist ; amend=$(git log -1 –oneline | grep –quiet “version $version” && echo –amend) ; git commit $amend -m “version $version” ChangeLog setup.cfg ; git tag -a -f -m “version $version” $version ; donePublish a new versionpython setup.py sdist upload –signgit push ; git push –tagsdocker rmi dachary/ceph-workbenchdocker build –no-cache –tag dachary/ceph-workbench dockerdocker build –tag dachary/ceph-workbench:1.5.9 dockerdocker logindocker push dachary/ceph-workbenchdocker push dachary/ceph-workbench:1.5.9pypi maintenancepython setup.py register # if the project does not yet existtrim old versions athttps://pypi.python.org/pypi/ceph-workbench
Package: cepimose
cepimoseSmall library to parse raw data from NIJZ's PowerBI dashboards embedded inNIJZ stats page:vaccination stats for Slovenialatest epidemic dataExamplesPrepare environmentpython -mvenv env
. ./env/bin/activate
pip install cepimoseExamplesimport pandas as pd
import cepimose

data = cepimose.vaccinations_by_day()
df = pd.DataFrame.from_dict(data)
print(df)

data = cepimose.vaccinations_by_age()
df = pd.DataFrame.from_dict(data)
print(df)

data = cepimose.vaccines_supplied_and_used()
df = pd.DataFrame.from_dict(data)
print(df)Changelog0.0.4Addedvaccines_supplied_by_manufacturer()0.0.3Addedvaccinations_by_region()0.0.2Initial releaseDevgit clone https://github.com/sledilnik/py-cepimose
cd py-cepimose
pipenv install -d # install dependencies (including dev)
pipenv run test # run all tests
pipenv run testForSledilnik # run just tests for sledilnik.org
pipenv shell # run virtualenv shell
pipenv run fmt # format the code (also available as VS Code task)
Package: cepko
Cepko implements easy-to-use communication with CloudSigma’s VMs through a virtual
serial port without bothering with formatting the messages properly nor parsing the
output with the specific and sometimes confusing shell tools for that purpose.Having the server definition accessible by the VM can ve useful in various ways.
For example it is possible to easily determine from within the VM, which network
interfaces are connected to public and which to private network. Another use is
to pass some data to initial VM setup scripts, like setting the hostname to the
VM name or passing ssh public keys through server meta.For more information take a look at the Server Context section of CloudSigma
API Docs:http://cloudsigma-docs.readthedocs.org/en/latest/server_context.htmlUsageImports and definitions>>> from cepko import Cepko
>>> client = Cepko()Fetch the whole server context>>> server_context = client.all()
>>> server_context['name']Fetch the server’s meta>>> meta = client.meta()
>>> meta['ssh_public_key']
'ssh-rsa AAAAB3NzaC1yc2EAAAAD...'Fetch conrete key from the server context>>> drives = client.get('drives')
>>> [key for key in drives[0]['drive']]
['uuid', 'tags', 'media', 'name', 'meta', 'allow_multimount', 'licenses', 'affinities', 'size']
>>> drives[0]['drive']['size']
10737418240Fetch nested key from the server context>>> first_drive = client.get('drives/0/drive')
>>> first_drive['size']
10737418240
Package: ceplib
CepLibUma lib feita em python para consultar cep em diversos serviçosInstalando a Libpip install ceplib
poetry add ceplibServiços disponíveisAwesomeApiCep.laCorreiosViaCepWidenetComo utilizarNo mesmo diretório onde está o example.py execute o código abaixo:from ceplib import Cep

cep = Cep()
print(cep(21351050))Quando o cep é encontrado# {'cep': '21351050', 'state': 'RJ', 'city': 'Rio de Janeiro', 'district': 'Madureira', 
# 'address': 'Estrada do Portela - até 279 - lado ímpar', 'provider': 'CorreiosService'}Consultando todos os serviçosfrom ceplib import Cep

cep = Cep()
print(cep(21351050, get_all=True))#[{'cep': '01513000', 'state': 'SP', 'city': 'São Paulo', 'district': 'Liberdade', 'address': 'Rua São Paulo', 
#'provider': 'CepLaService'}, {'cep': '01513000', #'state': 'SP', 'city': 'São Paulo', 'district': 'Liberdade', 
#'address': 'Rua São Paulo', 'provider': 'AwesomeApiService'}, {'cep': '01513000', 'state': 'SP', #'city': 'São Paulo', 
#'district': 'Liberdade', 'address': 'Rua São Paulo', 'provider': 'ViaCEPService'}, {'cep': '01513000', 'state': 'SP', 
#'city': 'São Paulo', #'district': 'Liberdade', 'address': 'Rua São Paulo', 'provider': 'WideNetService'}, 
#{'cep': '01513000', 'state': 'SP', 'city': 'São Paulo', 'district': #'Liberdade', 'address': 'Rua São Paulo', 
#'provider': 'CorreiosService'}]Quando o cep não é encontrado# {'response': 'Cep não encontrado'}
Package: cepmex
CEPPython client library for CEP (http://www.banxico.org.mx/cep/)InstalaciónpipinstallcepmexUsofromdatetimeimportdatefromcepimportTransferenciatr=Transferencia.validar(fecha=date(2019,4,12),clave_rastreo='CUENCA1555093850',emisor='90646',# STPreceptor='40012',# BBVAcuenta='012180004643051249',monto=8.17,)pdf=tr.descargar()
Package: cepmex-bp
CEPPython client library for CEP (http://www.banxico.org.mx/cep/)InstalaciónpipinstallcepmexUsofromdatetimeimportdatefromcepimportTransferenciatr=Transferencia.validar(fecha=date(2019,4,12),clave_rastreo='CUENCA1555093850',emisor='90646',# STPreceptor='40012',# BBVAcuenta='012180004643051249',monto=8.17,)pdf=tr.descargar()
Package: ceppy
CeppyConsulta CEPs em vários serviços (Correios, ViaCep, OpenCep) de maneira totalmente assíncronaComece por aquiNesta seção você encontrará instruções de como instalar o pacote e também encontrará exemplos de usoRequerimentosEsse projeto é compatível com as versões3.10e3.11do python no momento. A compatibilização com versões anteriores está prevista, e qualquer contribuição é bem vinda.InstalaçãoPIPpip install pycepPoetrypoetry add pycepFazendo uma consultaTenha em mente que a lib vai retornar o serviço que responder mais rápidofrompycepimportCepcep=Cep("75140070")Acessando os dados da consultaVocê pode usar os atributos listados abaixo para acessar os dados do Cep:frompycepimportCepcep=Cep("75140070")print(cep.number)# 75140070print(cep.state)# GOprint(cep.city)# Anápolisprint(cep.street)# Rua Senador Mardocheu Dinizprint(cep.district)# Dom Pedro IIprint(cep.query_service)#CorreiosServiceprint(cep.status)# query_doneVocê também pode converter os dados para dictfrompycepimportCepcep=Cep("75140070")print(dict(cep)){'street':'Rua Senador Mardocheu Diniz','district':'Dom Pedro II','city':'Anápolis','state':'GO','cep':'75140070','provider':'CorreiosService'}Este projeto utilizaAioHTTP- Requisições HTTPPoetry- Gerenciamento de dependências e publicaçãoPytest- Testes automatizadosAutorErick Duarte-Implementação inicial-erickodLicençaO projeto está disponível através da licença MIT - Consulte o arquivoLICENSE.mdpara mais detalhes.Menções importantesEste projeto foi inspirado na libcep-promise, criada pelo Felipe Deschamps.
Package: cep-range
cep_rangeA bibliotecacep_rangefornece funcoes relacionadas a obtencao de coordenadas geograficas, calculo de distancia entre dois pontos, obtencao de CEP a partir de coordenadas, busca de CEPs dentro de um raio especifico, outros.Funcoes:validate_cep(cep): Funcao para validar um CEP que retornar um formato padrao "XXXXX-XXX".get_coordinates(cep): Funcao para obter as coordenadas geograficas (latitudeelongitude) a partir de um CEP. Utiliza o Selenium para abrir o Google Maps, inserir o CEP na barra de pesquisa, aguardar o carregamento da pagina e extrair as coordenadas da URL. Retorna as coordenadas como uma tupla(latitude, longitude). Se as coordenadas nÃ£o forem encontradas, gera uma mensagem de erro.calculate_distance(cep_1, cep_2, unit): Funcao para calcular a distancia entre dois pontos geogrÃ¡ficos. ObtÃ©m as coordenadas dos CEPs fornecidos usando a funcaoget_coordinates(), converte as coordenadas para radianos e calcula a distancia. O resultado e retornado em quilometros (unit='KM') ou metros (unit='M'). Se as coordenadas nao forem encontradas para algum dos CEPs gera uma excecaoCoordinatesNotFoundError.get_cep(latitude, longitude): Funcao para obter o CEP correspondente a um par de coordenadas geograficas (latitudeelongitude). Utiliza Nominatim do Geopy para reverter a geocodificacao e obter o CEP. Retorna o CEP se encontrado. Caso contrario, lanÃ§a uma excecao indicando que nao foi possivel converter as coordenadas em CEP. Infelizmente o Nominatim pode retorna dados imprecisos.ceps_range(raio_m, cep_c): Funcao para gerar uma lista de CEPs unicos dentro de um determinado raio (em metros) a partir de um CEP central.Bibliotecas Necessarias:geopy.geocoders.Nominatim: Biblioteca que fornece uma interface para o servico de geocodificacao do Nominatim, usado para converter coordenadas em CEP.selenium.webdriver: MÃ³dulo utilizado para automatizar a interacao com um navegador web, usado para capturar dados de (latitudeelongitude) de forma precisa.selenium.webdriver.common.by: 'By' Utilizada para localizar elementos em uma pagina.selenium.webdriver.support.ui.WebDriverWait: Classe utilizada para aguardar condicoes especificas de elementos da pagina.selenium.webdriver.support.expected_conditionsmathreInstalacao:pip install cep-rangeExemplos:importcep_rangeceps_raio_500m=cep_range.ceps_range(500,'01153-000')# output = ['01155-020', '01154-020', '01234-001', '01150-000', '01151-000', '01156-001', '01155-010', '01152-000', '01155-040', '01232-010', '01155-030', '01154-030', '01155-060', '01156-030', '01233-060', '01154-000', '01150-001', '01231-010', '01155-000', '01235-000', '01154-010']distancia=cep_range.calculate_distance('01150-000','01154-010','m')# output = 829.704coordenadas=cep_range.get_coordinates('01154-010')# output = (-23.5290645, -46.6634956)
Package: cep-scraper
cep-scraperCEP scraper library for consulting transactions in CEP (COMPROBANTE ELECTRÓNICO DE PAGO)RequirementsPython 3.7+Installationpipinstallcep_scraperTestsmaketestBasic usageConsult a transactionfromcep_scraperimportget_transactiontransaction=dict(fecha_proceso='31-03-2019',clave_rastreo='CUENCA1554068382',institucion_ordenante='90646',institucion_beneficiaria='40012',cuenta_beneficiario='4152313324202675',)get_transaction(transaction)Release to PyPipipinstall-Usetuptoolswheeltwine
makerelease# PyPi will prompt you to log in
Package: ceptacle
Object-Oriented Peer-to-Peer RPC access library and server application framework.:Author: `Thetaplane <cbanis@gmail.com>`__:Requires: Python 2.6+:Version: 0.4.0:Group Application: application, config, debugging, security, storage:Group Core: architecture, encoding, packaging, runtime:Group Networking: network, client, server:Group Service Partner Bus: bus, bus.partners, bus.services, bus.spline:Bug: Some synchronization issues cause intermittant network failures:Todo: Optimize the package format to eliminate unnecessary marks:Copyright: |copyright| 2011-2023 Thetaplane.. |copyright| unicode:: 0xA9 .. copyright sign
Package: cep-to-coords
Pacote Python para converter CEP em latitude e longitudeComo usar:Instale:gitclonehttps://github.com/millengustavo/cep-to-coords.gitcdcep-to-coords
gitcheckoutmaster
pipinstall-e.Converta um CEP para latitude e longitude:fromcep_to_coords.convertimportcep_to_coordscoordenadas=cep_to_coords('22070-900')print(coordenadas)# {'latitude': -22.9864082, 'longitude': -43.189592}Opcional - Usando ohttps://cepaberto.com/Para usar esse conversor você precisa se cadastrar no site e exportar seu token como variável de ambienteCEP_ABERTO_TOKENexportCEP_ABERTO_TOKEN='seu_token'fromcep_to_coords.convertimportcep_to_coordsfromcep_to_coords.strategiesimportCEPAbertoConvertercoordenadas=cep_to_coords('22070-900',factory=CEPAbertoConverter)print(coordenadas)# {'latitude': -22.9864082, 'longitude': -43.189592}Testandopython-munittestdiscover
Package: cepy
cepyImplementation of the connectome embedding (CE) framework.Embedding of brain graph or connectome embedding (CE) involves finding a compact vectorized
representation of nodes that captures their higher-order topological attributes. CE are
obtained using the node2vec algorithm fitted on random walk on a brain graph. The current
framework includes a novel approach to align separately learned embeddings to the same
latent space. Cepy is tested on Python 3.6, 3.7 and 3.8.Documentation:https://cepy.readthedocs.io/en/latest/Installationpip install cepyUsageimportcepyasceimportnumpyasnp# Load an adjacency matrix (structural connectivity matrix)sc_group=ce.get_example('sc_group_matrix')# Initiate and fit the connectome embedding modelce_group=ce.CE(permutations=1,seed=1)ce_group.fit(sc_group)# Extract the cosine similarity matrix among all pairwise nodescosine_sim=ce_group.similarity()# Save and load the modelce_group.save_model('group_ce.json')ce_loaded=ce.load_model('group_ce.json')# load it# Load two existing CE modelsce_subject1=ce.get_example('ce_subject1')ce_subject2=ce.get_example('ce_subject2')# Align the two to the space of the [ce_group]:ce_subject1_aligned=ce.align(ce_group,ce_subject1)ce_subject2_aligned=ce.align(ce_group,ce_subject2)# Extract the node vectorized representations (normalized) for subsequent use - prediction, for examplew_sbject1=ce_subject1_aligned.weights.get_w_mean(norm=True)w_sbject2=ce_subject2_aligned.weights.get_w_mean(norm=True)A set of example interactive Jupyter notebooks are also availablehere.CitingIf you findcepyuseful for your research, please consider citing the following paper:Levakov, G., Faskowitz, J., Avidan, G. & Sporns, O. (2021). Mapping structure to function
 and behavior with individual-level connectome embedding. bioRxiv. doi: https://doi.org/10.1101/2021.01.13.426513ContributingCepy is an open-source software project, and we welcome contributions from anyone.
We suggestraisingan issue prior to
working on a new feature.ReferenceThe node2vec implementation is modeified from thenode2vecpackage by Elior Cohen and theconnectome_embeddingcode by Gideon Rosenthal.Rosenthal, G., Váša, F., Griffa, A., Hagmann, P., Amico, E., Goñi, J., ... & Sporns, O. (2018). Mapping higher-order relations between brain structure and function with embedded vector representations of connectomes. Nature communications, 9(1), 1-12.
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