Saravanan666/pypi-org huggingface dataset:
Package: ktoolbox-pure-py
KToolBoxKToolBox is a useful CLI tool for downloading posts content inKemono.party / Kemono.suEnglish|中文FeaturesSupport formulti-threaddownloads (technically, coroutine)Retryafter download failedAbility to download individual post as well asall postby a specified creator/artistUpdate downloadedcreator/artist directories to the latest statusCustomize thestructureof downloaded post/creatordirectoriesSearch for creators/artists and posts, andexport the resultsCross-platformsupport &iOS shortcutsavailableFor Coomer.su / Coomer.party support, check documentCoomerfor more.Dev PlanAdd a Fluent Design style GUIAdd uvloop support for Unix platformTutorialSeedocumentationfor more details.InstallationNormalpip3installktoolboxFora-Shellpip3installktoolbox-pure-pyCommandFor more information, use the help command or gotoCommandpage.❓ Get general helpktoolbox-h❓ Get help of a commandktoolboxdownload-post-h⬇️🖼️ Download a specific postktoolboxdownload-posthttps://kemono.su/fanbox/user/49494721/post/6608808If some files failed to download, you can try to execute the command line again,
the downloaded files will beskipped.⬇️🖌️ Download all posts from a creatorktoolboxsync-creatorhttps://kemono.su/fanbox/user/9016By default, you will get acreator-indices.ktoolboxfile in the creator directory,
you can use it to update the directory anytime.🔄️ Update a downloaded creator directoryktoolboxsync-creatorhttps://kemono.su/fanbox/user/641955--update-with=./xxx/creator-indices.ktoolboxThecreator-indices.ktoolboxfile contains the information and filepath of posts inside the directory.iOS ShortcutsGotoShortcuts for iOSpage for more details.ConfigurationGotoConfiguration-Guidepage for more details.Other BranchesPure Python branch:🔗pure-pyUse pydantic v1 so that cargo is not needed for installationFor example, you can use it on iOS terminal Appa-Shell🔗PyPIDevelopment branch:🔗develAbout KemonoDescription fromhttps://kemono.su:Kemono is a public archiver for:PatreonPixiv FanboxDiscordFantiaAfdianBoostyDLsiteGumroadSubscribeStarContributors here upload content and share it here for easy searching and organization.To get started viewing content, either search for creators on the artists page, or search for content on the posts page.Code CoverageLicenseKToolBox is licensed under MIT.Copyright © 2023 by Ljzd-PRO.
Package: ktorrent
A Python module to fetch and parse data from Kickass Torrents.Installpip install ktorrentUsage# Import Library>>> import ktorrent# Basic Search>>> search = ktorrent.search(search='Linux')# Complex Search>>> search = ktorrent.search(search='Linux Shell script', strict=1, category='books', field='age', sorder='desc', page=2)# Top movies>>> top_movies = ktorrent.top(category='movies', page=2)Know MorekTorrent Docs:https://github.com/codenirvana/kTorrent#readme
Package: ktpanda-modules
ktpanda_modulesA collection of helper modules by PinkPandaKatie (https://ktpanda.org)threadpoolMaintains a pool of threads which can execute jobs.object_poolMaintains a pool of objects which can be checked out as needed by different threads.hotloadA class which can reload its methods from a module when it detects changes.sqlite_helperA wrapper class for an SQLite database that includes schema versioning and
various helper methods.textcolorA module for coloring text using VT100 codesttyutilUtilities for controlling Posix TTY devices and reading raw input.dateutilsSimple utilities for dealing with date / time, extending the built-in datetime.fileutilsSimple utilities for dealing with files / directories.vt100Defines constants for VT100 control codes.cliDefines decorators which make it easy to create dispatch-style CLI interfaces.
Package: ktpl
# ktplUtility to template Kubernetes Resource Definitions using the jinja2 templating engine, then apply or delete the templated resources[![Build Status](https://travis-ci.org/whereismyjetpack/ktpl.svg?branch=master)](https://travis-ci.org/whereismyjetpack/ktpl)## Getting Started`pip install git+https://github.com/whereismyjetpack/ktpl.git@master`### Prerequisites`kubectl`### Usage```Usage:ktpl [options] [<folder>...]ktpl [options] [--input-file=<file>]...ktpl [options] [--template-file=<file>]...Options:--delete -d                      Delete, instead of apply templated manifests--template -t                    Template manifests, and print to screen--environment -e                 Consider environment when processing variables--input-file=<file> -i           Path to input file(s) to process instead of the defaults--template-file=<file> -t        Path to template file(s) to process instead of the defaults```### Directory Structure:```.├── folder-1│   ├── template.yml.tpl│   └── values.yml <- "defaulty" variables for resources in this folder├── folder-2│   ├── template.yml.tpl│   └── values.yml <- "defaulty" variables for resources in this folder├── values.yml <--- global variables used in all resources├── folder-2.yml <--- values that get added only for resources in folder-2├── folder-2-customer-b.yml <--- a second set of values, that will get appied to resources in folder-2├── folder-1.yml <---values that get added only for resources in folder-1└── values.yml.secret <--- global variables, that will be merged with values.yml. good for using `git-crypt` to encrypt only secret portions of your variables```### Variable precidence:{{folder_name}}.ymlvalues.yml{{folder_name}}/values.yml### Examples:```1.) ktpl- processes folder-1/template.yml.tpl, and folder-2/template.yml.tpl. processes folder-2/template.yml.tpl twice. once with values from folder-2.yml, and once with values from folder-2-customer-b.yml.2.) ktpl folder-1- processes folder-1/template.yml.tpl with values from values.yml, values.yml.secret, and folder-1.yml. variables from folder-1.yml will override defaulty variables set in values.yml3.) ktpl --template- processes the same as example 1, but prints the template to screen instead of sending to kubectl```
Package: ktplotspy
ktplots-pyWelcome! This is a super light-weight python library for plottingCellphoneDBresults. Ported fromktplotsR package. For more options,
please check out the original Rpackage.The documentation ishere.InstallationpipinstallktplotspySupportSupport is provided on a voluntary basis, as time permits.If there are any ideas, comments, suggestions, thing you would like to
know more etc., please feel free to email me atz.tuong@uq.edu.auor
post in the issue tracker and I will get back to you.CitationIf you find this useful, please cite the following preprint:[Troule2023]Troulé K, Petryszak R, Prete M, Cranley J, Harasty A, Tuong ZK, Teichmann SA, Garcia-Alonso L, Vento-Tormo R. (2023)CellPhoneDB v5: inferring cell-cell communication from single-cell multiomics data.,arXiv. preprint arXiv:2311.04567. 2023 Nov 8.as well, as github repositories. Also leave a star at thektplotspyand the originalktplotsrepositories!
Package: kts
An interactive environment for modular feature engineering, experiment tracking, feature selection and stacking.Install KTS withpip install kts. Compatible with Python 3.6+.Modular Feature EngineeringDefine features as independent blocks to organize your projects.Source Code TrackingTrack source code of every feature and experiment to make each of them reproducible.Parallel Computing and CachingCompute independent features in parallel. Cache them to avoid repeated computations.Experiment TrackingTrack your progress with local leaderboards.Feature SelectionCompute feature importances and select features from any experimentwithexperiment.feature_importances()andexperiment.select().Interactivity and Rich ReportsMonitor the progress of everything going on in KTS with our interactive reports.From model fitting to computing feature importances.Getting StartedTitanic TutorialStart exploring KTS with tutorial based onTitanic dataset. Run notebooks interactively in Binder or just read them in NBViewer.1. Feature EngineeringModular Feature Engineering in 30 secondsDecorators referenceFeature TypesRegular FeaturesFeatures Using External FramesStateful FeaturesGeneric FeaturesStandard LibraryFeature Set2. ModellingModelsValidationLeaderboardMultiple LeaderboardsExperimentsInferenceFeature ImportancesCustom Models3. Stackingstl.stackAnti-overfittingNoiseRefinerDeep StackingDocumentationCheck outdocs.kts.aifor a more detailed description of KTS features and interfacesInline DocsMost of our functions and classes have rich docstrings. Read them right in your notebook, without interruption.AcknowledgementsMVP of the project was designed and implemented by the team ofMikhail Andronov,Roman GorbandNikita Konodyukunder the mentorship ofAlexander Avdyushenkoduring a project practice held by Yandex and Higher School of Economics on 1-14 February 2019 at Educational Center «Sirius».
Package: kttool
Kattis unofficial command line helperInspired by (and works well with) xalanq'scodeforce toolSample usage1. Config your template typeFirst and foremost,download your kattisrc fileand put it in your$HOMEdirectory (ie~/.kattisrc). After that, runktconfigto configure your code template. This will allow the tool to quickly generate code template for your problem.2. Generate folder for problem statement and sample intputs and outputsktgen<problem_id>For example, if you want to attempt problemDistinctive Character, the problem ID isdistinctivecharacter. From your kattis working folder, type inktgendistinctivecharacterYou should be able to see 2 set of sample inputs/outputs generated in a folder calleddistinctivecharacterAfter that, you cancdinto the folder and start working on the problem.3. Test your codeIf you've set up your config properly, you should be ready to test whether your code pass sample input and output. Simply runkttestAnd observe the difference ..Submit file and check result on the terminalFrom your current problem folderktsubmitYou should be able to see how many test cases your code has passed so far$ kt open -h
Usage: kt open [problem_id]

    Open the default browser with the link to the full problem statement on Kattis. If no problem id is provided, the problem id wil be deduced using the
    current directionary name

    Options
    --------
    problem_id: Kattis problem idUpdate version of kttoolCheck current version of kttoolktversionIf there is a newer version, you can runktupdateto check.Installationpipinstall--upgradekttoolReferencehttps://github.com/Kattis/kattis-clihttps://github.com/xalanq/cf-toolLicenseMIT LicenseRemaining features yet to be implementedMultiple profiles. Ability to switch between Kattis open domain and competition domain with ease
Package: kttools
kttoolsKelvin’s miscellaneous python toolsInstallpipinstallkttools# orpipinstallgit+https://github.com/tuonglab/kttools.git# orgitclonehttps://github.com/tuonglab/kttools.gitcdkttools;pipinstall-e.UsageimporttoolsPlease checkout the documentationapifor details about the
functions you can use to make your life easier.jupyterhub issueOn jupyterhub, If you find yourself trying to import from local
directory, i.e.git clone, and finding that you can’t import it, you
will need to edit your yourkernel.jsonfile like so:vi/home/jovyan/.local/share/jupyter/kernels/<condaenvironmentname>/kernel.jsonadd in the$PATHand$PYTHONPATHbits:{"argv":["/home/jovyan/my-conda-envs/<condaenvironmentname>/bin/python","-m","ipykernel_launcher","-f","{connection_file}"],"env":{"PATH":"/home/jovyan/scripts/kttools:$PATH","PYTHONPATH":"/home/jovyan/scripts/kttools:$PYTHONPATH"},"display_name":"Python (<condaenvironmentname>)","language":"python"}
Package: kt-toposis
UCS633 Project SubmissionName-Kartikey TiwariRoll no.-101703282kt-toposiskt-toposis is a Python package for displaying ranking of all criteria using Topsis technique to get good computational efficiency and ability to measure the relative performance for each alternative in a simple mathematical form.Topsis DescriptionTechnique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is one of the multi-criteria models in making decision which is known for its  simplicity, rationality, comprehensibility and good computational efficiency. Multi-criteria decision making (MCDM) refers to making choice of the best alternative from among a finite set of decision alternatives in terms of multiple, usually conflicting criteria.Getting StartedThese instructions will help you to install and use this package for general use.PrerequisitesYour csv file should not have categorical dataInstallationUse the package managerpipto install foobar.pipinstallkt-toposisUsageYou can import it either in Python IDLE or run directly through command promptFor Command PromptIf you want to use this package on "data.csv" file with 4 columns. You need to change the directory where "data.csv" is stored then. Here -w represents weights which signifies weight of each feature or column in our dataset and -i represents impacts which signifies impact of each column or feature in our data. If a feature is good we will use + to denote else we will use -kt-toposisdata.csv-w1111-i++-+You can use the following command for helpkt-toposis-hFor Python IDLEfromkt_toposis.topsisimporttoptop(X,weights,impacts)#X should be a matrix#impacts should be a list of string + for positive impact - for negative impact#weights should be a list of int or floatSample datasetSinger IDSurTaalLaayePitchPaceS10.790.621.2560.8911S20.660.442.893.0720S30.560.311.5762.8716S40.820.672.6870.1916S50.750.561.380.3920kt-toposisBook1.csv-w11111-i+++++ResultTopsisSelectionModels|Rank-----------------------1|32|53|44|15|2SuccessfullyexecutedContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.LicenseMIT
Package: ktug-hanyang-pua
ktug-hanyang-puaKTUG Hanyang PUA table reader/writerThis package provides reader/writer utility for files fromKTUG Hanyang PUA table project.Note that this package does not handle HanyangPUA-to-UnicodeJamo conversion itself.Documentation:https://ktug-hanyang-pua.readthedocs.orgDevelopment environmentTo setup development environment:virtualenv -p python3.4 .
bin/pip install -U setuptools pip pip-tools
make
make test test-reportChanges0.1.2 (2019-03-19)Change table binary format.0.1.1 (2019-03-17)Fix dump_mappings_as_text_table().0.1.0 (2019-03-17)Initial release.
Package: ktuhope
HopeChange Log0.0.1 (01/04/2022)First ReleasePrograms added. Matrix Operations
. SVD
. K-NN
. Naive Bayes
. Linear Regression
. Chunking
. Speech Tagging
. ngrams Built-in
. ngrams
. scrapping
. k-Means
. Linear Regression Built-in
. Web CrawlerOther details
Package: ktuvit-api
Unofficial python client to ktuvit.me APIUsage is pretty straight forward:importktuvitapi=ktuvit.KtuvitApi()api.find_series("Subtitle","Prodigal.Son.S01E07.720p.HDTV.x264-KILLERS",1,1)# Possible search_types are FilmName, Subtitle, ImdbID (case sensetive)api.find_film('ImdbID','tt5463162')# Deadpool 2"""Should return something like this:{'ErrorMessage': None,'IsSuccess': True,'Results': [{'Identifier': 'B01A861744343E9201D4ED1C73378559','SubtitleName': 'Deadpool.2.2018.NEW.720p.HD-TC.X264-CPG'}}"""subtitle=api.get_subtitle('B01A861744343E9201D4ED1C73378559')# get the specified subtitles# Save the subtitles to a filewithopen("out.srt","wb")asout:out.write(subtitle)see documentation for more information.
Package: ktypes
KTypes or KnownTypes is a an open-source library which provides a framework to
formally define complex data types and functions between data types inside a
formal type theoretic framework.The type-specified universe coexists with the standard Python type system,
allowing for seamless switching between formally typed functions and traditional
pythonic methods. Runtime type-checking and library recursors serve as tools
that ensure type correctness. A library parser is provided to facilitate the
pipeline of ad-hoc data into the formal typed setting of KTypes.
Package: ktz
KTZ - Python ToolsKantholtz' personal Python toolbox. Check out thedocumentation here.InstallationPython 3.9 is required.$condacreate-nktzpython=3.9$condaactivatektz$pipinstallktzFor a local installation with all dev dependencies:$gitclonehttps://github.com/kantholtz/ktz.git$cdktz$condacreate-nktzpython=3.9$condaactivatektz$pipinstall.[dev]#runtests$pytest#tocontinuallyruntests$ptw-c#tocheckcodecoverage$coveragerun-mpytest$coveragereport$coveragehtml
Package: kuai-log
1 kuai_log安装 pip install kuai_logkuai_log 是最快的python日志,比loguru和logging快30倍.kuai_log的控制台日志自动彩色.kuai_log的文件日志多进程切割安全.kuai_log的文件日志支持更友好的json文件写入,更适合elk采集.(例如logger.info直接记录一个字典,会自动转换)kuai_log KuaiLogger 对象的方法名和入参在logging.Logger对象中一定存在,且参数相同,虽然不是基于logging开发,但保持了良好的兼容性1.2 为什么用 kuai_log用户怕了logging包的创建logger, 创建handler, handler设置formatter, logger添加handler 的方式,感觉logging复杂,导致用户想用loguru

loguru对logging包的不兼容和复杂.比如loguru记录flask框架的已有日志内容,就比较麻烦,说的是在已有logging命名空间添加handler,loguru困难.
例如loguru记录flask werkzeug 请求记录的日志 ,记录 tornado.access的 日志,麻烦.2 性能比较在 win11 + r7 4800h上,单进程for for循环写入10万次控制台和文件，（具体的测试代码可以直接用 tests/compare_spped 中的代码验证）loguru 写入文件和打印控制台,10万次日志耗费48秒

logging 写入文件和打印控制台,10万次日志耗费45秒

nb_log 写入文件和打印控制台,10万次日志耗费7秒

kuai_log 写入文件和打印控制台,10万次日志耗费1.7秒3 kuai_log 写入 10万次文件和打印控制台代码:importloggingimporttimefromkuai_logimportget_loggerlogger=get_logger(name='test',level=logging.DEBUG,log_filename='t5.log',log_path='/pythonlogs',is_add_file_handler=True,)t_start=time.time()foriinrange(10):logger.debug(i)print(time.time()-t_start)3.2 kuai_log的日志级别和常用的日志是一样的.debug info warning error criticalimportloggingimporttimefromkuai_logimportget_loggerlogger=get_logger(name='test77',level=logging.DEBUG,log_filename='t777.log',log_path='/pythonlogs',is_add_file_handler=True,json_log_path='/python_logs_json',is_add_json_file_handler=True,)t_start=time.time()foriinrange(1):logger.debug(i)logger.info(i)logger.warning(i)logger.error(i)logger.critical(i)print(time.time()-t_start)4 kuai_log 用法比logging和loguru简单.4.1 有些人问需要实例化生成logger,没有 from loguru import logger直接用爽?因为是每个name的日志行为是独立的,用户在大项目中有很多个日志,不同的表现行为不同,
例如有的函数里面日志界别高才输出,有的模块需要日志级别低就输出,
例如有的模块的日志需要写入文件,有的模块的日志不需要写入文件,
所以用不同的name来区分日志是最好的4.2 用户想偷懒,学习loguru直接导入就使用,想不需要手动实例化生成loggerkuai_log 自带一个已经实例化好的 k_logger 对象,你还嫌麻烦?fromkuai_logimportk_loggerk_logger.debug('hello')5 kuai_log为什么快?因为logging日志系统功能非常丰富强大,扩展性好,代码较为复杂,kuai_log没有基于logging包来封装,是完全从0写的,代码简单自然就性能好了.kuai_log实现的文件日志多进程rotate切割安全,使用了特殊的方式,所以技能保证切割不报错又能保证性能.nb_log是基于logging封装的,kuai_log是手写的.6 kuai_log 日志截图
Package: kuanghl
build and install.# envpipinstall--upgradebuildtwine# 编译安装包python-mbuildcddist&&pipinstallxxx.tar.gz# 本地编译安装pythonsetup.pybdist_wheel
pipinstall-e.# 导入环境变量/home/hongliangkuang/.local/lib/python3.8/site-packages# mkdocsmkdocsserve--dev-addr=0.0.0.0:8000
Package: kube
Opinionated Python interface for the Kubernetes APIThis package provides a Pythonic interface to use theKubernetesAPI
from within Python code.  It is hand-crafted and opinionated in an
attempt to hide the edge cases and cumbersome parts of the raw API
which would be exposed by a client using theswaggerdefinitions.This package is far from finished, the current major features are:Major resources wrapped:NodesNamespacesPodsReplicaSets/ReplicationControllersServicesSecretsGood labelling supportBoth blocking and non-blocking support for the WATCH API.Query, create and delete resources.Low-level API to use Kubernetes API more directly.Write tests without needing a real clusterWe are working on these features:Modifying ReplicaSets: i.e. changing number of replicas, changing selectors.Modifying resources in general.Creating new resource items.Deleting resource items.Installationpip install kubeUsageTo use the API one has to authenticate to the Kubernetes apiserver.
Currently only the recommendedapproachof using kubectl in proxy
mode is supported.  Simply runkubectl proxyon the localhost and
the connection will work.  When running in a cluster itself this can
be easily achieved by running the kubectl proxy in anothercontainerin the same pod.The central object to work with the Kubernetes cluster is theClusterobject:import kube

cluster = kube.Cluster()
rs = cluster.replicasets.fetch('proxy', namespace='default')
pods = cluster.pods.filter(labels=rs.meta.labels,
                           filter={'metadata.namespace': 'default'})
for pod in pods:
   assert pod.phase is pod.PodPhase.RunningDocumentationThe kube library is fully documented athttp://python-kube.readthedocs.io.ContributingThe project is still in it’s early stages, feel free to submit
suggestions, issues or pull requests to the project.https://bitbucket.org/cobeio/kubeAll feedback is welcome.Development DependenciesWhen developing kube you will need some extra dependencies:pytestpytest-covpylintinvokeTesting KubeThe tests can be run in two ways: Using a stubbed-out API server (default),
or against a real Kubernetes cluster.  The former runs very fast and will
not mess around with a real cluster.  The latter is a bit slower but can be
used to verify that the code behaves correctly against a real Kubernetes
cluster.  To reiterate, by default the tests will use the stubbed-out
apiserver.  To execute the tests against a real cluster, invoke them
withpy.test--verify<kubectl-context>.  There is no need to run akubectl proxy, this is done automatically.  The tests will try not to
break your cluster or leave any artefacts around after the test run, however
we’d recommend that<kubectl-context>refers to a test cluster.LicenseKube is available under theLGPLv3which allows you to use it in your
own projects regardless of the license you choose, be it proprietary
or open source, while keeping kube itself free software.
Package: kubeagi-cli
kubeagi-cliThis package implements the CLI for Kubeagi Core.Quick StartThere are several ways to use thekubeagi-clilibrary:Install the libraryInstall from PyPIInstalling the libraryUse the following instructions to get up and running withkubeagi-cliand test your
installation.Install the Python SDKpip install kubeagi-cliAt this point, you should be able to run the following code:convert-v
Package: kubeagi-core
Kubeagi CoreKubeagi Core including some common functions, these functions are designed to be as modular and simple as possible.Quick StartThere are several ways to use thekubeagi_corelibrary:Install the libraryInstall from PyPIInstalling the libraryUse the following instructions to get up and running withkubeagi_coreand test your
installation.Install the Python SDKpip install kubeagi_coreAt this point, you should be able to run the following code:fromkubeagi_core.qa_provider.openaiimportQAProviderOpenAIqa_provider=QAProviderOpenAI(api_key="fake",base_url="http://fastchat-api.172.22.95.167.nip.io/v1",model="f8e35823-3841-4253-ae79-0fff47917ae3",)data=qa_provider.generate_qa_list(text="大语言模型（LLM）是指使用大量文本数据训练的深度学习模型，可以生成自然语言文本或理解语言文本的含义。大语言模型可以处理多种自然语言任务，如文本分类、问答、对话等，是通向人工智能的一条重要途径。")print(data)
Package: kube-api
Kubernetes Python APIThis repository contains a simple Kubernetes Python API (Kube API). This API is built using theOfficial Python client library(Official API) forkubernetesLoading the ConfigurationsA configuration file is required for calling the APIs. There are two ways for loading configurations:Set the "KUBERNETES_CONFIG" environment variable to the path of the configuration file. The configurations will be loaded automatically.Explicitly callconfig.load_configuration(config_file_path).Handling ExceptionsThe official API raises exceptions when there is an error. Kube API will catch the ApiException and return an error message instead. This is implemented by wrapping the function calls to the official API using theapi_request()function inutils.py.When there is an error calling the official API, Kube API will return a JSON response containing the body of the ApiException (which is a dictionary-like object), plus three (3) additional fields:status, the status returned in the ApiExceptionerror, the reason of the errorheaders, the header of the ApiException