Saravanan666/pypi-org huggingface dataset:
Package: proctoring
AI Based Smart Exam Proctoring PackageIt takes image (base64) as input:
Provide Output as:Detection of Mobile phone.Detection of More than 1 person in the exam.Gaze Estimation: Estimating the position of student body & eyes movements.DOWNLOAD LINK OF YOLO V3 MODEL:https://pjreddie.com/media/files/yolov3.weightsDOWNLOAD LINK OF shape_predictor_68_face_landmarks.dat MODEL:https://github.com/italojs/facial-landmarks-recognition/blob/master/shape_predictor_68_face_landmarks.dat?raw=trueCode Sample Workingfromproctoring.proctoringimportget_analysis,yolov3_model_v3_path# insert the path of yolov3 model [mandatory]yolov3_model_v3_path("yolov3.weights_model_path")# insert the image of base64 formatimgData="base64_image_format"proctorData=get_analysis(imgData,"shape_predictor_68_face_landmarks.dat_model_path")print(proctorData)Code Sample Output{'mob_status': 'Not Mobile Phone detected', 'person_status': 'Normal', 'user_move1': 'Head up', 'user_move2': 'Head right', 'eye_movements': 'Blinking'}
Package: proctracer
/proc TracerThis is the developer/maintainer documentation. For user documentation, go tohttps://github.com/david-kracht/proctracerSetupYou can run proctracer from source in Windows, MacOS, and Linux:Install pip followingpip docs.Clone proctracer repository:$gitclonehttps://github.com/david-kracht/proctracer.gitInstall in editable mode$cdproctracer&&sudopipinstall-e.You are ready, try to run proctracer:$proctracer--help
usage:/procTracer(Daemon)[-h][-cCONFIG][-oOUTPUT_PATH][-nREPORT_NAME][-f]{start,stop,restart,message}...

positionalarguments:{start,stop,restart,message}startStartTracerstopStopTracerrestartRestartTracermessageMessagetoRunningTracer

optionalarguments:-h,--helpshowthishelpmessageandexit-cCONFIG,--configCONFIGPathto/procTracerconfigyaml.-oOUTPUT_PATH,--output_pathOUTPUT_PATHOutputpathforreport.-nREPORT_NAME,--report_nameREPORT_NAMENameofthereportfile.-f,--foregroundStartTracerinforeground,notdaemonized.Examplary usage and result:$proctracer-o~/1/2-nproc_reportstart
Start/procTracer(Daemon)...
Outputwillbewrittento:/root/1/2

$proctracermessagefirst
Messagetorunning/procTracer(Daemon)...
$proctracermessage2nd
Messagetorunning/procTracer(Daemon)...
$proctracermessage2nd
Messagetorunning/procTracer(Daemon)...
$proctracermessage3rd
Messagetorunning/procTracer(Daemon)...

$stress-c1-t5stress:info:[514601]dispatchinghogs:1cpu,0io,0vm,0hdd
stress:info:[514601]successfulruncompletedin5s

$proctracerstop
Stop/procTracer(Daemon).

$tree~/1
/home/user/1
└──2└──proc_report.pdfPackage and Upload
Place token in~/.pypirc, i.e[pypi]
username =tokenpassword = pypi-AgEIcHlwa0A5vasXU4w$chmod600~/.pypirc

$sudopipinstalltwine

$python3setup.pysdistbdist_wheel
$twineuploaddist/*
Package: procurement-tools
procurement-toolsA handy collection of python utilities and tools to navigate federal contracting.FeaturesUEI validationGet a URL for an entity from USASpendingGet recent award data for an entity from USASpendingLookup a FAR provision by citationGet entity information from the SAM entityAccess innovations from the Periodic Table of Acquisition InnovationsUsageFor full documentation, head tothe docs.fromprocurement_toolsimportFAR,UEI,USASpending,PeriodicTableprint(UEI.is_valid("J7M9HPTGJ1S9"))# Trueprint(USASpending.get_usaspending_URL("J7M9HPTGJ1S9"))# 'https://www.usaspending.gov/recipient/bf1220c1-2373-042a-e8e1-33d5a29639d0-P/latest'print(FAR.get_section("17.502-2"))# Returns a pydantic model with the title, section number, url, and text of the sectionprint(PeriodicTable.get_random_innovation())# Returns a dict with an innovation from the FAI Periodic Table of Acquisition InnovationsAdditionally, we have the beginning of a SAM API client:fromprocurement_toolsimportSAMres=SAM.get_entity({"ueiSAM":"XRVFU3YRA2U5"})print(res)# Returns a pydantic model with the latest SAM data for a given EntityCLI UsageOut of the box, there is a simple CLI, calledfargo. You can use it to do things like:fargosamentity[UEI]# Dumps a json of an entity's informationfargosamopportunities--q"machine"# Dumps a json of active opportunities that match the keyword "machine"fargousaspending[UEI]--awards# Dumps a json of an entity's 10 most recent awards (in the last 90 days)Check outthe docsfor all of the CLI optionsInstallationpipinstallprocurement-toolsLicenseApache 2.0
Package: procurve
ProCurveWhat is ProCurve?It is a robust principal curve package focused on fitting data that lies in a sphere.
Splines are the estimators used for the principal curves.How to installThe package can be installed via pip using:pipinstallprocurveExample:Run the load base case as:fromsrc.procurve.principal_curveimportPrincipalCurvefromsrc.procurve.utilsimportcreate_datasetfromsrc.procurve.plottingimportplot_3d,segmentsimportnumpyasnpfrommpl_toolkits.mplot3d.art3dimportLine3DCollectionX=create_dataset(source="snake")spline_params={"degree":4,"low_angle_deg":-40,"high_angle_deg":180,"radius":1.0}pc=PrincipalCurve()X,s,f_spline=pc.fit(X,init_fn="curve",param_fun=spline_params)s_high_res=np.linspace(0,1,1000)f_s=f_spline(s_high_res)#%% Plot dataax=plot_3d(X,plot_wireframe=True)ax.plot(f_s[:,0],f_s[:,1],f_s[:,2],color="C3",linewidth=0.5,label="Principal curve")line_collections_fit=segments(pc.last_iteration_log["data_sorted"],pc.last_iteration_log["p_orthogonal"])lc_fit=Line3DCollection(line_collections_fit,colors="C1",linewidths=0.4,label="Orthogonal projection")ax.add_collection(lc_fit)ax.legend(fontsize="small")Reading and citations:The pseudo-algorithm and mathematical formulation can be foundhere.How to contact usAny questions, suggestions or collaborations contact Mauricio Salazar at <e.m.salazar.duque@tue.nl>
Package: procustodibus-agent
Pro Custodibus AgentPro Custodibusis a service that makesWireGuardnetworks easy to deploy and manage. You run the Pro Custodibus agent on each WireGuard host you want to manage, and the agent monitors and synchronizes the hosts' WireGuard settings with the remote Pro Custodibus service.InstallingRequires python 3.7 or newer and libsodium. Installer script can install requirements, plus the agent itself, on most linuxes. Install from source like the following:./install.sh --installOr run it like the following to see more options:./install.sh --helpSee theInstaller Documentationfor full details.DockerThedocker/wireguard.dockerfileis built weekly and pushed to thedocker.io/procustodibus/wireguardrepository. It produces a base WireGuard image without the agent.Thedocker/agent.dockerfileis built weekly and pushed to thedocker.io/procustodibus/agentrepository. It produces a Docker image with WireGuard and the latest agent installed together.Run either image by placing your WireGuard or Pro Custodibus configuration files in a host directory like/srv/containers/wireguard/conf, and then running the image like the following:docker run \
    --cap-add NET_ADMIN \
    --publish 51820:51820/udp \
    --name wireguard \
    --rm \
    --volume /srv/containers/wireguard/conf:/etc/wireguard \
    procustodibus/agentSee theContainer Documentationfor full details.DevelopmentSet up dev envCreate a virtualenv withpyenv:pyenv virtualenv 3.10.4 procustodibus-agentActivate the virtualenv:pyenv local procustodibus-agent 3.7.17 3.8.18 3.9.18 3.10.13 3.11.7 3.12.1Install tox:pip install toxInstall pre-commit and pre-push hooks:tox -e pre-commit -- install
tox -e pre-commit -- install -t pre-pushDev tasksList all tox tasks you can run:tox -avRun unit tests in watch mode:tox -e watchBuild and run docker dev image (with*.conffiles in/srv/containers/wireguard/conf):tox -e build
docker/dev.sh dev
docker run \
    --cap-add NET_ADMIN \
    --publish 51820:51820/udp \
    --name wireguard \
    --rm \
    --volume /srv/containers/wireguard/conf:/etc/wireguard \
    procustodibus-agent:devRun all (docker-based) installer tests:docker-compose -f test_install/docker-compose.yml build --pull
tox -e py310 test_installManually run pre-push hook on all version-controlled files:tox -e pre-commit -- run -a --hook-stage pushContributingCode of ConductFile a BugReport a VulnerabilitySubmit a PatchResourcesHome page:https://www.procustodibus.com/Documentation:https://docs.procustodibus.com/guide/agents/run/Changelog:https://docs.procustodibus.com/guide/agents/download/#changelogIssue tracker:https://todo.sr.ht/~arx10/procustodibusMailing list:https://lists.sr.ht/~arx10/procustodibusSource code:https://git.sr.ht/~arx10/procustodibus-agentLicenseThe MIT License
Package: procustodibus-broker
Pro Custodibus BrokerPro Custodibusis a service that makesWireGuardnetworks easy to deploy and manage.To integrate Pro Custodibus with your own SIEM or other log tools, you can run the Pro Custodibus broker on one of your own internal hosts, and the broker will pull alerts and other events from Pro Custodibus and push them to your own security management systems.InstallingRequires python 3.8 or newer and libsodium. Installer script can install requirements, plus the broker itself, on most linuxes. Install from source like the following:./install.sh --installOr run it like the following to see more options:./install.sh --helpSee theInstaller Documentationfor full details.DevelopmentSet up dev envCreate a virtualenv withpyenv:pyenv virtualenv 3.8.18 procustodibus-brokerActivate the virtualenv:pyenv local procustodibus-broker 3.8.18 3.9.18 3.10.13 3.11.7 3.12.1Install tox:pip install toxInstall pre-commit and pre-push hooks:tox -e pre-commit -- install
tox -e pre-commit -- install -t pre-pushDev tasksList all tox tasks you can run:tox -avRun unit tests in watch mode:tox -e watchRun all (docker-based) installer tests:docker-compose -f test_install/docker-compose.yml build --pull
tox -e py38 -- test_installManually run pre-push hook on all version-controlled files:tox -e pre-commit -- run -a --hook-stage pushContributingCode of ConductFile a BugReport a VulnerabilitySubmit a PatchResourcesHome page:https://www.procustodibus.com/Documentation:https://docs.procustodibus.com/guide/integrations/brokers/Changelog:https://docs.procustodibus.com/guide/integrations/brokers/#changelogIssue tracker:https://todo.sr.ht/~arx10/procustodibusMailing list:https://lists.sr.ht/~arx10/procustodibusSource code:https://git.sr.ht/~arx10/procustodibus-brokerLicenseThe MIT License
Package: procxx
procxxSimple C++ builder toolsAboutprocxx is a c++ builder tools for building c++ project.If you want something with more features, you can use CMake.procxx target is to make building c++ easier.Supported Compilersgcc (g++)clang (clang++)other compilers that support gcc and clang flagsExamplefromprocxximportCXXProjectmyproject=CXXProject("g++")# you can remove the g++ if you want it auto-detect compilermyproject.add_include("include")# add include pathmyproject.add_raw("src/*.cpp")# add raw argument. Usually for adding source filemyproject.autorun("main.cpp")# you can also use run method but autorun will automatically run the compiled executeableLicenseMIT
Package: procyclingstats
Procyclingstats is a Python package for scrapingprocyclingstats.com,
which is a website with cycling stats. It’s recommended to get familiar with
the website before using this package.InstallationUsing pip:$ pip install procyclingstatsManual (for development):$ git clone https://github.com/themm1/procyclingstats.git
$ pip install -r procyclingstats/requirements_dev.txtBasic usageBasic Rider class usage:>>> from procyclingstats import Rider
>>> rider = Rider("rider/tadej-pogacar")
>>> rider.birthdate()
"1998-9-21"
>>> rider.parse()
{
    'birthdate': '1998-9-21',
    'height': 1.76,
    'name': 'Tadej  Pogačar',
    'nationality': 'SI',
    ...
}Interface consists from scraping classes which are currentlyRace,RaceStartlist,RaceClimbs,Ranking,Rider,RiderResults,StageandTeam. Usage of all scraping classes is almost the same and
the only difference among them are parsing methods as is for examplebirthdatein Rider class usage example.Unexpected behaviour and parsing errorsSince the project is a web scraper which parses HTML, it’s difficult to make
it reliable and it’s common to encounter some HTML parsing problems. After
getting some kind of unexpected behaviour or parsing errors, it’s recommended
to update the package on your system usingpip install procyclingstats--upgrade. If the problem proceeds, see the
GitHubissuespage and if the issue hasn’t been opened yet, don’t hesitate to
open one!LinksGitHubPyPIDocumentation
Package: prodamuspy
Prodamus hash verifier (HMAC)Generate and verify Prodamus hash.https://help.prodamus.ru/payform/integracii/rest-api/instrukcii-dlya-samostoyatelnaya-integracii-servisov#kak-prinyat-uvedomlenie-ob-uspeshnoi-oplateInstallationpip install prodamuspyUsageInit object:prodamus = prodamuspy.PyProdamus(API_TOKEN)Parse query string to a dictionary:bodyDict = prodamus.parse(body)Create signature:checkSign = prodamus.sign(bodyDict)Verify signature:signIsGood = prodamus.verify(bodyDict, receivedSign)
if signIsGood:
    print("Signature is awesome")
else:
    print("Signature is incorrect")CopyrightCopyright 2023 [Max Arnold, Daniil Nagikh], all rights reserved.This software is released under the MIT License.A huge thank tohttps://github.com/max-arnold
Package: prodapi
prodapiA thin layer on top ofFastAPIwith the following features:Integrates withFastAPI-Securityto add a custom route/users/me(path is overridable)Easily add CORS to your app by callingapp.with_basic_cors()Add health routes to the app viaapp.with_health_routes(). Adds a liveness route at/__is-aliveand a readiness route at/__is-ready(both paths can be overridden). Useful together withKubernetes liveness and readiness probesfor example.And, thanks to FastAPI, all routes are automatically added to the API documentationInstallationpip install prodapiExamplefromprodapiimportProdAPI,ApiRouter,FastAPISecurity# First let's set up security, via FastAPI-Securitysecurity=FastAPISecurity()# Set up HTTP Basic Authsecurity.init_basic_auth([{"username":"johndoe","password":"123"},{"username":"janedoe","password":"abc123"},])# Set up OAuth2 and OIDC# NOTE: There is also `init_oauth2_through_jwks` in case OIDC is not availablesecurity.init_oauth2_through_oidc("https://my-auth0-tenant.eu.auth0.com/.well-known/openid-configuration",)# Make sure that basic auth user `jane` and OAuth2 user# `p56OnzZb8KrWC9paxCyv8ylyB2flTIky@clients` gets all permissions automatically.# NOTE: For basic auth you have to set up permissions this way, for OAuth2 permissions#       will be automatically extracted from the incoming JWT token (via the key#       `permissions`, which might only be implemented for Auth0)security.add_permission_overrides({"jane":["*"],"p56OnzZb8KrWC9paxCyv8ylyB2flTIky@clients":["*"],)# Now we're ready to create the app# NOTE: ProdAPI is just a thin layer on top of `fastapi.FastAPI`app=ProdAPI()# CORS - Allow any origins, methods and headers. Don't expose any headers.app.with_basic_cors()# Add routes `/__is-alive` and `/__is-ready`. Useful together with Kubernetes or similar# URL paths are configurable.app.with_health_routes()# Enable `/users/me` route to get info about the user. URL path is configurable.app.with_user_routes(security)# Create our app specific API router and our routesproducts_router=ApiRouter()@products_router.get("/products")deflist_products():return[]app.include_router(products_router)# And we're done! Now just use uvicorn or similar to deploy.TODOCreate cli utility (usingtiangolo typer?), which can generate:A stub project usingprodapiFrontend (React?)docker-compose.yml and DockerfileKubernetes deployment files
Package: prodapp
ProdAppDemo- click aboveFeaturesSelf-scoring+5:poor productivity-- didn't get much done+10:fair productivity-- normal work+15:excellent productivity-- laser-focused shredding of workloadCountdown timerBleeps at 0 -> give youreslf a scoreChange values with click + typingPausableDefaults to 10 minute intervals, configurableSaved progress: imagesSwap between daily progress pics with a button press for easy comparisonSaved progress: csvRecover/edit data for reference or further processingInstallationUse.exe installer. For the Python package (not needed for.exe),pip install prodappUsageExeDouble-click shortcutCommand Linecd path/to/prodapp
python app.pyOpenhttp://127.0.0.1:8050/in browserConfigsEditprodapp/config.iniMiscEdit data: opendata/<current_date>.csv, edit, save. Make sure the app is closed in the meantime.Edit images: can't. Must make new save.Save data/image: add productivity (+5/10/15), saves automatically.Change timer reset value: either via configs (requires app restart), or: first click reset, then change time value (e.g. to 12:00); that'll be the new reset.To-doThe app is "finished"; I don't intend to do much further, but I welcome contributors. A list that I might sometime work on, or invite others to:prodapp.exeTo-do list under the red orb (example; this is original ProdApp written in electron.js)Edit values forother(non-current) hours straight from application, including subtracting valuesMake the orb functional; change color, size, rotation rate depending on total "productivity" for the day
Package: prodb
Prodb.csv database for prosðŸŒ DemoðŸ”—https://share.streamlit.io/lukexyz/prodb/app.pyðŸ“ DocumentationðŸ”—https://lukexyz.github.io/prodb/(github pages)Setup environment andnbdevFirst time only:Ubuntu / WSLconda create -n prodb python=3.9 jupyter pip nbdev twine
conda activate prodb  
git clone https://github.com/lukexyz/prodb.git  
pip install -r requirements.txtInstall githooks from project foldernbdev_install_git_hooksPackage auto-managermake releaseWSL error work around for: [Errno 16] Device or resource busyubuntu $ make release
windows > python setup.py sdist bdist_wheel
 ubuntu $ twine upload --repository pypi dist/*Frequently during develoment:1. ðŸ—ï¸Build libfrom notebooksnbdev_build_lib2. ðŸ“Build docsfrom notebooksnbdev_build_docsInstallpip install prodb
Package: prodclass
Meu Projeto de ModeloDescriÃ§Ã£o do projeto: Este projeto visa desenvolver, testar e implantar modelos de machine learning para classificaÃ§Ã£o de descriÃ§Ãµes de produtos. Utiliza tÃ©cnicas avanÃ§adas de vetorizaÃ§Ã£o de texto e algoritmos de classificaÃ§Ã£o para prever categorias de produtos baseadas em suas descriÃ§Ãµes.Estrutura do ProjetoO projeto estÃ¡ organizado da seguinte forma:data/: ContÃ©m os datasets usados pelo modelo, incluindo dados brutos (raw/) e dados processados (processed/).notebooks/: Jupyter notebooks para exploraÃ§Ã£o de dados, anÃ¡lises preliminares e prototipagem de modelos.src/: CÃ³digo-fonte do projeto, incluindo scripts de manipulaÃ§Ã£o de banco de dados, gestÃ£o de experimentos, modelos de machine learning e funÃ§Ãµes utilitÃ¡rias.tests/: Testes automatizados para garantir a qualidade e a confiabilidade do cÃ³digo.requirements.txt: Lista de dependÃªncias necessÃ¡rias para executar o projeto.README.md: Este arquivo, contendo a documentaÃ§Ã£o do projeto.Como usarInstalaÃ§Ã£o das DependÃªnciasPara instalar as dependÃªncias necessÃ¡rias, execute:pip install -r requirements.txtPreparaÃ§Ã£o dos DadosColoque seus dados brutos emdata/raw/e processe-os conforme necessÃ¡rio. O resultado deve ser salvo emdata/processed/para uso posterior pelo modelo.ExploraÃ§Ã£o de Dados e PrototipagemUse os notebooks emnotebooks/para explorar os dados e criar protÃ³tipos de modelos.ExecuÃ§Ã£o do ModeloO cÃ³digo-fonte para treinar e avaliar modelos estÃ¡ localizado emsrc/. Veja os scripts especÃ­ficos para instruÃ§Ãµes detalhadas sobre como executar cada modelo.TestesExecute os testes emtests/para garantir que as alteraÃ§Ãµes no cÃ³digo nÃ£o quebrem funcionalidades existentes.ContribuindoSinta-se livre para contribuir com o projeto. Por favor, envie um pull request ou abra uma issue para discutir o que vocÃª gostaria de mudar.LicenÃ§a[Inserir tipo de licenÃ§a aqui] - Veja o arquivo LICENSE para mais detalhes.
Package: prodcon
prodconAn easy to use implementation of the producer consumer pattern with threadingInstallationpipinstallprodconExample usageimportrandomimporttimefromqueueimportQueuefromprodconimportProducer,Consumerdefgenerate_items(start,end):foriinrange(start,end+1):ifi==end:# Add poison pill to stop producer and consumersyieldNone# Simulate producing timetime.sleep(random.random())print(f'Produced item #{i}')yieldf'Item #{i}'defprocess_item(item):# Simulate processing timetime.sleep(random.random()+1)print(f'Processed{item}')q=Queue()p=Producer(q,generate_items,args=(1,100))c=Consumer(q,process_item)p.start()c.start()Example usage with decoratorsimportrandomimporttimefromprodconimportproduces,consumes@producesdefgenerate_items(start,end):foriinrange(start,end+1):ifi==end:# Add poison pill to stop producer and consumersyieldNone# Simulate producing timetime.sleep(random.random())print(f'Produced item #{i}')yieldf'Item #{i}'@consumesdefprocess_item(item):# Simulate processing timetime.sleep(random.random()+1)print(f'Processed{item}')generate_items(1,100)# Use multiple consumersfor_inrange(5):process_item()
Package: prodconpattern
ProducerConsumerPattern通过装饰器方式实现生产者消费者模式。
可以作用于函数、类的方法上，使其变为异步调用，同时，转变为逐次调用，批量执行。方便将零碎的调用转变为批量形势进行统一执行。Github 地址：ProducerConsumerPattern安装pip install prodconpattern示例代码函数调用：逐次调用 -> 异步逐次调用fromprodconpatternimportProducerConsumer@ProducerConsumer(threshold=3)defmethod_single_invoke(n):"""函数调用：逐次调用 -> 异步逐次调用"""print('method_single_invoke ->',n)importtime# 函数调用：逐次调用 -> 异步逐次调用forninrange(10):print("call -> method_single_invoke(%d)"%n)method_single_invoke(n)time.sleep(6)函数调用：逐次调用 -> 异步批量调用fromprodconpatternimportProducerConsumer@ProducerConsumer(threshold=3,pass_arg_list=True)defmethod_list_invoke(n):"""函数调用：逐次调用 -> 异步批量调用"""print('method_list_invoke ->',n)importtime# 函数调用：逐次调用 -> 异步批量调用forninrange(10):# time.sleep(1)print("call -> method_list_invoke(%d)"%n)method_list_invoke(n)time.sleep(6)对象方法调用：逐次调用 -> 异步批量调用fromprodconpatternimportProducerConsumerclassAClass:@ProducerConsumer(threshold=3,pass_arg_list=True,is_class_method=True)defclass_method_list_invoke(self,n):"""对象方法调用：逐次调用 -> 异步批量调用"""print(self.__class__.__name__,"print_method",n)importtime# 对象方法调用：逐次调用 -> 异步批量调用aaa=AClass()forninrange(10):print("call -> class_method_list_invoke(%d)"%n)aaa.class_method_list_invoke(n)time.sleep(6)更多例子参考example.py 文件
Package: prodglob
prodglobosandglobextensions with advanced path joining.InstallpipinstallprodglobUsagefromprodglobimportprodglob,pathprod,prodmakeprint('pathprod: creating a product of path items.')forfinpathprod('base',('a','b'),'something',('c','d')):print(f)print()print('prodglob: globbing over the product of path items.')forfinprodglob('base',('a','b'),'something',('c','d')):print(f)fs=pathprod('base',('a','b'),'something',('c','d'))print('how many files exist?',sum(os.path.exists(f)forfinfs))print()print('prodmake: making directories from the product of path items.')fs=prodmake('base',('a','b'),'something',('c','d'))print('how many files exist?',sum(os.path.exists(f)forfinfs))print()print('prodglob: globbing over the product of path items.')forfinprodglob('base',('a','b'),'something',('c','d')):print(f)Outputs:pathprod: creating a product of path items.
base/a/something/c
base/a/something/d
base/b/something/c
base/b/something/d

prodglob: globbing over the product of path items.
how many files exist? 0

prodmake: making directories from the product of path items.
how many files exist? 4

prodglob: globbing over the product of path items.
base/a/something/c
base/a/something/d
base/b/something/c
base/b/something/d
Package: prodiapy
Descriptionprodiapy is an unofficial lightweight Python package forProdia Stable Diffusion APIPre-requirementsThe minimal ver. of Python supported by this package is 3.8.10Installationpip install prodiapy==5.0a1text2img examplefromprodiapyimportProdiaprodia=Prodia(api_key="YOUR_PRODIA_KEY")job=prodia.sd.generate(prompt="cat")result=prodia.wait(job)print(result.image_url)ContactJoin our discord to get help with package -https://discord.gg/7NbzdD6qg8