Saravanan666/pypi-org huggingface dataset:
Package: cuid2
cuid2CUID2 for Python 3. Next generation GUIDs. Collision-resistant ids optimized for
horizontal scaling and performance.A port of theCUID2 reference implementationbyParallel Driveto Python 3.:memo: Note: Originally taken fromhttps://github.com/overflowdigitalbefore it
was unpublished. Thank you to @joshuathompsonlindley for your original contribution!What is CUID2?Secure: It's not possible to guess the next ID.Collision resistant: It's extremely unlikely to generate the same ID twice.Horizontally scalable: Generate IDs on multiple machines without coordination.Offline-compatible: Generate IDs without a network connection.URL and name-friendly: No special characters.Why?For more information on the theory and usage of CUID2, see thefollowing.Improvements Over CUIDFor more information on the improvements of CUID2 over CUID, see thefollowing.Installpip install cuid2UsageYou can generate CUIDs directly in the terminal with the following:$cuid2Or you can rely on a CUID wrapper if you don't need any customizations:fromtypingimportCallablefromcuid2importcuid_wrappercuid_generator:Callable[[],str]=cuid_wrapper()defmain():my_cuid:str=cuid_generator()next_cuid:str=cuid_generator()Finally, for more explicit control of the CUID generator, you can instantiate the class directly:fromcuid2importCuidCUID_GENERATOR:Cuid=Cuid(length=10)defmain():my_cuid:str=CUID_GENERATOR.generate()next_cuid:str=CUID_GENERATOR.generate()
Package: cuimage
A CUDA-accerlated image processing libraryFree software: Apache Software License 2.0Installationpip install cuimageYou can also install the in-development version with:pip install https://github.com/gigony/cuimage/archive/master.zipDocumentationhttps://cuimage.readthedocs.io/DevelopmentTo run all the tests run:toxNote, to combine the coverage data from all the tox environments run:Windowsset PYTEST_ADDOPTS=--cov-append
toxOtherPYTEST_ADDOPTS=--cov-append toxChangelog0.0.0 (2020-09-17)First release on PyPI.
Package: cuinixam-app-dev
Cuinixam App DevelopmentMy application development modules.InstallationInstall this via pip (or your favourite package manager):pip install cuinixam_app_devStart developingThe project uses Poetry for dependencies management and packaging.
If you do not have Poetry installed, you can run theboostrap.ps1script.
This will install Python and Poetry as configured inscoopfile.json.Set-ExecutionPolicy-ExecutionPolicyBypass-ScopeCurrentUser-Force.\bootstrap.ps1To install the development dependencies in a virtual environment, type:poetryinstallThis will also generate apoetry.lockfile, you should track this file in version control. To execute the test suite, call pytest inside Poetry's virtual environment viapoetry run:poetryrunpytestCheck out the Poetry documentation for more information on the available commands.For those usingVS Codethere are tasks defined for the most common commands:install development dependenciesrun testsrun all checks configured for pre-commitgenerate documentationSee the.vscode/tasks.jsonfor more details.Committing changesThis repository usescommitlintfor checking if the commit message meets theconventional commit format.Contributors ✨Thanks goes to these wonderful people (emoji key):This project follows theall-contributorsspecification. Contributions of any kind welcome!CreditsThis package was created withCopierand thebrowniebroke/pypackage-templateproject template.
Package: cuisine-postgresql
ImportantThis project is no longer being maintained!cuisine-postgresqlprovides cuisine-style PostgreSQL management commands.Installationpip install cuisine-postgresqlUsagefrom cuisine_postgresql import (postgresql_role_ensure,
                                postgresql_database_ensure)


@task
def configure_database():
        postgresql_role_ensure('user', 'pass', createdb=True)
        postgresql_database_ensure('database',
                                   owner='user',
                                   template='template0',
                                   encoding='UTF8')
Package: cuisine_sweet
Sugar-coated declarative deployment recipes built on top ofFabricandCuisine.With Fabric’s low-level remote ssh orchestration and Cuisine’s generic recipes; the goal
is to build a collection of wrappers capturing various, usually opinionated, system deployment
styles.At the heart ofcuisine_sweetis the collection ofensuremodules. These modules encapsulate
what is being checked/deployed (declarative), without specifying the how and the where parts
(imperative). An ensure is both an assertion check + action-if-needed in the form:ensure.object.state(params).Sample Usagecuisine_sweetis to be used in tandem withfabric.To illustrate usage, see the samplefabfile.pybelow:from fabric.api import task, env
from cuisine_sweet import ensure

env.hosts = [ 'myproject@server1.example.com', 'myproject@server2.example.com' ]

@task
def initial():
    ensure.yum.package_installed('gcc')
    ensure.yum.package_installed('make')
    ensure.yum.package_installed('git')
    ensure.yum.package_installed('python')
    ensure.yum.package_installed('python-devel')
    ensure.supervisord.installed()

@task
def deploy():
    ensure.local_git.up_to_date(against='origin/master')
    ensure.local_git.clean()
    ensure.git.rsync('git@ourgit.example.com:myproject.git', 'myproject', refspec='master', base_dir='git')
    ensure.user_crontab.loaded('git/myproject/user.cron')
    ensure.supervisord.running('git/myproject/supervisord.conf', '/tmp/myproject.supervisord.pid')
    ensure.supervisord.updated_with_latest_config('git/myproject/supervisord.conf')ReferencesSource CodeDocumentationFeedback / Patches -Create an issueCopyright © 2012, Dexter B. Tad-y
Package: cujirax
cujiraxCucumberJira andXraySetup environment variablesexportJIRA_DOMAIN="urdomain.atlassian.net"exportJIRA_EMAIL="youremail@yourcompany.com"exportJIRA_SECRET="xxxxx",exportXRAY_CLIENT_ID="xxxxx"exportXRAY_CLIENT_SECRET="xxxxx"Maintaining cucumber result json fileMake sure it is alway updated fromhttps://raw.githubusercontent.com/cucumber/cucumber-json-schema/main/schema.jsonGenerating model fromdatamodel-codegen --input schema.json --output cujirax/cucumber.py
Package: cukcuk
Cukcuk SDKExamples:Get all invoices in a date rangeimportcukcukfromdatetimeimportdatetime,timedeltasession=cukcuk.LoginSession.from_json("login.json")last_sync_date=datetime(2023,5,1)before_date=datetime(2023,5,5)invoices=session.get_invoices(last_sync_date=last_sync_date,before_date=before_date)df=invoices.to_df()# Convert to pandas DataFrameprint(df)Using asynchronous session to speed up requestsimportasyncioimportcukcukfromdatetimeimportdatetime,timedeltasession=cukcuk.AsyncLoginSession.from_json("login.json")last_sync_date=datetime(2023,5,1)before_date=datetime(2023,5,5)invoices=asyncio.run(session.get_invoices(last_sync_date=last_sync_date,before_date=before_date))df=invoices.to_df()# Convert to pandas DataFrameprint(df)
Package: cuke4behave
cuke4behaveWhat is this.There is a popular bdd library in python, Behave.
Cucumber Expressions are areplacement for regexs in Gherkin codebases. in large swaths of Behave implementations.
Cucumber also has a good language server and vscode extension.
To support both, this library allows you to inject a new step matcher into Behave, for use with more modern Gherkin paradigms.InstallationPip:pip install cuke4behavePoetry:poetry install cuke4behaveUsagefromcuke4behaveimportbuild_step_matcherfrombehaveimportgiven,then,whenfrombehave.matchersimportmatcher_mapping,use_step_matcherfromcucumber_expressions.parameter_typeimportParameterTypefromcucumber_expressions.parameter_type_registryimportParameterTypeRegistryfromcuke4behave.step_matcherimportbuild_step_matcherfromfeatures.steps.helpersimportColor,full_add# Build a ParameterType and ParameterTypeRegistrycolor_ptr=ParameterType("color","red|blue|orange|purple|brown",Color,lambdas:Color(s),use_for_snippets="",prefer_for_regexp_match=False,)ptr=ParameterTypeRegistry()# do this as many times as necessaryptr.define_parameter_type(color_ptr)# step matcher to pass to behavestep_matcher=build_step_matcher(ptr)# THIS IS IMPORTANT. Patch in the step matcher to behavematcher_mapping["cucumber_expressions"]=step_matcheruse_step_matcher("cucumber_expressions")`
Package: cukuramoto
Installgitclonehttps://github.com/stdogpkg/cukuramoto/&&cdcukuramoto&&pythonsetup.pyinstallRunningimportigraphasigimportnumpyasnpfromstdog.utils.miscimportig2sparseblock_size=1024# gpu parameternum_couplings=40N=10000G=ig.Graph.Erdos_Renyi(N,3/N)adj=ig2sparse(G)adj=adj.tocsr()ptr,indices=adj.indptr,adj.indicescouplings=np.linspace(0,4,num_couplings).astype("float32")omegas=np.tan((np.arange(1,N+1)*np.pi)/N-((N+1.)*np.pi)/(2.0*N)).astype("float32")phases=np.random.uniform(-np.pi,np.pi,int(num_couplings*N)).astype("float32")importcukuramotodt=0.1num_temps=100simulation=cukuramoto.Heuns(N,block_size,omegas,phases,couplings,indices,ptr)simulation.heuns(num_temps,dt)order_parameter_list=simulation.get_order_parameter(num_temps,dt)order_parameter_list=order_parameter_list.reshape(num_couplings,num_temps)r=np.mean(order_parameter_list,axis=1)stdr=np.std(order_parameter_list,axis=1)importmatplotlib.pyplotaspltplt.ion()fig,ax1=plt.subplots()ax1.plot(couplings,r,'.-')ax2=ax1.twinx()ax2.plot(couplings,stdr,'r.-')plt.show()
Package: culebratester-client
## Snaky Android Test — If you want to be able to try out the API using theExecuteorTRYbutton from this page - an android device should be connected using &#x60;adb&#x60; - the server should have been started using &#x60;./culebratester2 start-server&#x60;  then you will be able to invoke the API and see the responses.   # noqa: E501
Package: culebrONT
Table of ContentsAbout CulebrONTCitationAuthorsUseful notesThanksLicenseAbout CulebrONTHomepage:https://culebront-pipeline.readthedocs.io/en/latest/Using data from long reads obtained by Oxford Nanopore Technologies
sequencing makes genome assembly easier, in particular to solve repeats
and structural variants, in prokaryotic as well as in eukaryotic
genomes, resulting in increased contiguity and accuracy.Bunch of softwares and tools are released or updated every week, and a
lot of species see their genome assembled using those.That’s right.“But which assembly tool could give the best results for my favorite
organism?”CulebrONT can help you!CulebrONT is an open-source, scalable,
modulable and traceable snakemake pipeline, able to launch multiple
assembly tools in parallel and providing help for choosing the best
possible assembly between all possibilities.Citationhttps://doi.org/10.1101/2021.07.19.452922AuthorsJulie Orjuela (IRD)Aurore Comte(IRD)Sébastien Ravel(CIRAD),Florian Charriat(INRAE)Sébastien Cunnac(IRD).Tram Vi (IRD, AGI)Francois Sabot(IRD)Useful notesBefore launching CulebrONT, you could base-calling of arbitrarily
multiplexed libraries across several Minion runs with sequencing quality
control and gather the output files by genome for subsequent steps. For
that usehttps://github.com/vibaotram/baseDmux.ThanksThanks to Ndomassi Tando (i-Trop IRD) by administration support.The authors acknowledge theIRD i-Trop HPC(South Green Platform) at IRD
Montpellier for providing HPC resources that have contributed to this work.Thanks toYann Delormefor this beautiful logoLicenseLicencied underCeCill-Cand GPLv3.Intellectual property belongs toIRD,CIRADand authors.
Package: culendar
CulendarCulendar is afree/librecalendar application in python and
curses.FeaturesDisplays your events on a week, hour by hourDisplays a TODO listAdds, deletes, edits, categorizes eventsColour themes for your categorized eventsImports from ICalendar format or fromcalcursefilesCustomizableDisplays webcalsDeals with caldavsHow to installpip install culendarorgit clonehttps://framagit.org/mit/culendarcd culendarpoetry installpoetry run culendar to run itHow to useRun it. Default key "h" to get help, "c" to configure.No warrantiesCulendar has been tested on Debian stable and old-stable,
rxvt-unicode as a terminal and UTF-8 encoding only.
It needs much more testing to be officially reliable.Don't hesitate toreport bugsorrequest features.ScreenshotsChat:IRC: #culendar on irc.geeknode.org/6697
Package: culingam
CULiNGAM - CUDA Accelerated LiNGAM AnalysisIntroductionCULiNGAM is a high-performance library that accelerates Linear Non-Gaussian Acyclic Model (LiNGAM) analysis on GPUs. It leverages the computing power of NVIDIA GPUs to provide fast and efficient computations for LiNGAM applications, making it ideal for large-scale data analysis in fields such as bioinformatics, economics, and machine learning.InstallationTo install CULiNGAM, you need a system with NVIDIA CUDA installed and a compatible GPU. This library is tested with CUDA 12.2 and designed for GPUs with the architecturesm_86, although it may work with other versions and architectures with appropriate adjustments.PrerequisitesNVIDIA GPU with CUDA Compute Capability 8.6 or higherCUDA Toolkit 12.2 or compatible versionPython 3.6 or newerNumpyA C++17 compatible compilerInstalling from PyPICULiNGAM is available on PyPI and can be easily installed with pip:pipinstallculingamInstalling CULiNGAM manuallyClone the repository to your local machine:gitclonehttps://github.com/Viktour19/culingamEnsure that CUDA_HOME environment variable is set to your CUDA Toolkit installation path. If not, you can set it as follows (example for default CUDA installation path):exportCUDA_HOME=/usr/local/cuda-12.2Optionally, set the GPU_ARCH environment variable to match your GPU architecture if it differs from the default sm_86:exportGPU_ARCH=sm_xx# Replace xx with your GPU's compute capabilityInstall the library using pip:pipinstall.UsageAfter installation, you can use CULiNGAM in your Python projects to accelerate LiNGAM analysis. Here's a simple example to get started:https://github.com/Viktour19/culingam/blob/main/examples/basic.pySupportFor bugs, issues, and feature requests, please submit a report to the repository's issue tracker. Contributions are also welcome.AuthorVictor AkinwandeLicense and AcknowledgmentThis project is licensed under the MIT License - see the LICENSE file for details.
A good amount of the code is adapted from sequential implementations of the LiNGAM algorithms present in CULiNGAM:https://github.com/cdt15/lingam.
Package: cull
Cull provides a very specific cli tool to parse boto3 output. Usage can viewed by
running the tool via cli:cullEC2Instance Name Tags are expected to use the following
naming convention:<cloud>_<service>_*How toTo parse EC2 instances with Name tags likeproduction_app_*:cull ec2 production appS3A list tool to list or delete root level S3 bucketsListTo list all root level buckets with a specific string in the name:cull s3list productionDeleteTo delete a root level bucketAND ALL CONTENTS WITHIN:cull s3delete bucketnameYou will be prompted before delete function is executed
Package: culligan
CulliganA discovery for Culligan smart water productsWater SoftenerThe Excel sheet contains a listing of endpoints and what is needed for interaction with the Aylanetworks API. This data was gathered from proxy traffic.The powershell module is a way to interact with the endpoints via Powershell.The python code is for packageability and publishing to PyPi as a module.The softener does have an http webpage for wifi status and connect/disconnect.
Local control of the device does not seem possible without understanding how Ayla sends commands to the device.Ayla ReferencesThis device is integrated by/with Ayla Networks and (generally) uses their documentation.SeeAyla-iot-unofficialLocal Wifi Module DocDirect doc linked from the reference above:salesforce docInstallationFrom PyPipipinstallculliganBuild from sourcepipinstallbuild
pipbuild
pipinstallculliganLibrary RequirementsRequires typical http interaction and datatype packages like requests, aiohttp, ujson, and the ayla-iot-unofficial module to handle devices and communication.User RequirementsReqiures a username and password (typically a smart device's app login credentials).
The Culligan specific app_id is included in the package (obtained from the Culligan app).UsageClass ObjectInstantiate a new class object through new_culligan_api() or Culligan() directly.Access TokensThe Culligan() object will call sign_in() automatically to obtain Culligan IoT and Ayla access_tokens.
Then, it will instantiate an AylaApi() object with the Ayla access_token (no sign_in() required).Use Culligan for communication with the Culligan IoT domain.
Use the Ayla property of the Culligan object for direct communication with Ayla Networks.DevicesGather devices by calling the Ayla.get_devices().By default, calling get_devices() will return a list of class specific device objects with updated properties for use.See ayla-iot-unofficial/device.py for implemented device classes.Typical Operationpython3-mpipinstallCulliganimportCulliganUSERNAME='me@email.com'PASSWORD='$7r0nkP@s$w0rD'CulliganApi=new_culligan_api(username,password)CulliganApi.sign_in()CulliganApi.Ayla=CulliganApi.get_ayla_api()device_list=CulliganApi.Ayla.list_devices()devices=CulliganApi.Ayla.get_devices()# Example Water Softener Devicessoftener=devices[0]softener.capacity_remaining_gallonssoftener.set_vacation_mode()LicenseMIT
Package: cullinan
_____      _ _ _                      
  / ____|    | | (_)                     
 | |    _   _| | |_ _ __   __ _ _ __     
 | |   | | | | | | | '_ \ / _` | '_ \    
 | |___| |_| | | | | | | | (_| | | | |   
 \_____\__, _|_|_|_|_| |_|\__,_|_| |_|CullinanCullinan is written based on tornado and Sqlalchemy to help the project quickly build web applicationHow to useinstallpip install cullinandemoFile controller:fromcullinan.controllerimportcontroller,get_api@controller()classTestController:@get_api(uri='/get',query_params=['id','name'])defget(self,query_params):returnself.TestService.test(query_params['id'],query_params['name'])File service:fromcullinan.serviceimportService,service@serviceclassTestService(Service):deftest(self,id,name):self.response.set_body({'id':id,'name':name})returnself.responseFile application:fromcullinanimportapplicationdefmain():application.run()if__name__=='__main__':main()Now, A web application demo is completed!File structure:project
   |----application.py                               # Web Application main entrance
   |----controller                                   # Controller package
   |  |----TestController.py                            
   |----service                                      # Service package
   |  |----TestService.pyWikiwiki and other related references:https://github.com/plumeink/Cullinan/wikiMaintainer
Package: culqi
Culqi PythonBiblioteca de CULQI para el lenguaje Python, pagos simples en tu sitio web.RequisitosPython 2.7, 3.5, 3.6, 3.7, 3.8-devCredenciales de comercio enCulqi.InstalaciónpipinstallculqiCada metodo retona un diccionario con la estructura{"status":status_code,"data":data}Elstatus_codees el estatus HTTP numérico devuelto por la solicitud HTTP que se
realiza al API de Culqi, ydatacontiene el cuerpo de la respuesta obtenida.DocumentaciónReferencia de APIEjemplosWikiChangelogTodos los cambios en las versiones de esta biblioteca están listados enCHANGELOG.md.DesarrolloRevisa nuestra guia de contribuciónContribuidores
Package: culqi2
Culqi PythonNuestra Biblioteca PYTHON oficial de CULQI, es compatible con la v2.0 del Culqi API, con el cual tendrás la posibilidad de realizar cobros con tarjetas de débito y crédito, Yape, PagoEfectivo, billeteras móviles y Cuotéalo con solo unos simples pasos de configuración.RequisitosPython 2.7+Afiliateaquí.Si vas a realizar pruebas obtén tus llaves desdeaquí, si vas a realizar transacciones reales obtén tus llaves desdeaquí(1).Recuerda que para obtener tus llaves debes ingresar a tu CulqiPanel > Desarrollo >API Keys.Recuerda que las credenciales son enviadas al correo que registraste en el proceso de afiliación.InstalaciónEjecuta los siguientes comandos:py-mpipinstallpytest
py-mpipinstallpython-dotenv
py-mpipinstallculqi2
py-mpipinstalljsonschema
py-mpipinstallpycryptodomeElstatus_codees el estatus HTTP numérico devuelto por la solicitud HTTP que se
realiza al API de Culqi, ydatacontiene el cuerpo de la respuesta obtenida.DocumentaciónReferencia de APIDemo Checkout V4 + Culqi 3DSWikiPruebasEn la caperta/testecontraras ejemplo para crear un token, charge,plan, órdenes, card, suscupciones, etc.Recuerda que si quieres probar tu integración, puedes utilizar nuestrastarjetas de prueba.ChangelogTodos los cambios en las versiones de esta biblioteca están listados enCHANGELOG.md.DesarrolloRevisa nuestra guia de contribuciónContribuidores
Package: culqi3
Culqi PythonNuestra Biblioteca PYTHON oficial de CULQI, es compatible con la v2.0 del Culqi API, con el cual tendrás la posibilidad de realizar cobros con tarjetas de débito y crédito, Yape, PagoEfectivo, billeteras móviles y Cuotéalo con solo unos simples pasos de configuración.RequisitosPython 2.7+Afiliateaquí.Si vas a realizar pruebas obtén tus llaves desdeaquí, si vas a realizar transacciones reales obtén tus llaves desdeaquí(1).Recuerda que para obtener tus llaves debes ingresar a tu CulqiPanel > Desarrollo >API Keys.Recuerda que las credenciales son enviadas al correo que registraste en el proceso de afiliación.InstalaciónEjecuta los siguientes comandos:py-mpipinstallpytest
py-mpipinstallpython-dotenv
py-mpipinstallculqi2
py-mpipinstalljsonschema
py-mpipinstallpycryptodomeElstatus_codees el estatus HTTP numérico devuelto por la solicitud HTTP que se
realiza al API de Culqi, ydatacontiene el cuerpo de la respuesta obtenida.DocumentaciónReferencia de APIDemo Checkout V4 + Culqi 3DSWikiPruebasEn la caperta/testecontraras ejemplo para crear un token, charge,plan, órdenes, card, suscupciones, etc.Recuerda que si quieres probar tu integración, puedes utilizar nuestrastarjetas de prueba.ChangelogTodos los cambios en las versiones de esta biblioteca están listados enCHANGELOG.md.DesarrolloRevisa nuestra guia de contribuciónContribuidores
Package: culqi-api-python
Culqi API PythonBiblioteca de CULQI para el lenguaje Python, pagos simples en tu sitio web.RequisitosPython 3.6, 3.7, 3.8, 3.9Credenciales de comercio enCulqi.Instalaciónpipinstallculqi-api-pythonCada metodo retona un diccionario con la estructura{"status":status_code,"data":data}Elstatus_codees el estatus HTTP numérico devuelto por la solicitud HTTP que se
realiza al API de Culqi, ydatacontiene el cuerpo de la respuesta obtenida.DocumentaciónReferencia de APIEjemplosWikiChangelogTodos los cambios en las versiones de esta biblioteca están listados en
elhistorial de cambios.DesarrolloRevisa nuestraguia de contribuciónContribuidoresMira la lista de contribuidoresaquí.Historia...La libreria de Culqi para Python inicio su desarrollo en enero del 2017, d ela mano de@william-muro-culqiy@marti1125, posteriorme@brayancruces,@KhanMaytoky@oskargicastcomplementaron el trabajo incial y mantiuvieron la libreria estable hasta mediados de 2019. En enero del 2020@zodiacfireworkshace una refactorizacion completa de la libreria, estos cambios son aprobados y mejorados por@joelibaceta. Con estos cambios se publicaron las versiones 1.0.0, 1.0.1, 1.0.2 y 1.0.3 de la libreria.@zodiacfireworksenvió más cambios para corregir algunos errores de empaquetamiento, lamentablemente, tras mas de un año de haber sido enviados, no se publicaron a traves del canal oficial, por este motivo es que en@SoftButterflyhemos tomado la iniciativa publicar esta libreria, compatible con la original, con los cambios que no llegaron a publicarse y otras mejoras que se pueden ver en elhistorial de cambios. Con el fin de respetar el trabajo de quienes participaron del desarrollo de esta libreria en el repositorio focial de Culqi, el historial original de contribuciones se ha mantenido en este repositorio.