Saravanan666/pypi-org huggingface dataset:
Package: kpredict
KpredictKpredict is a ptyhon library that can predict the size of the compiled vmlinux file given only a .config file using machine learning.UsageKpredict is available on pip :pip install kpredictThe straightest way to use it is to run the built-in script :kpredict .configNote : this module requires at elast Python 3.8 to work.Supported versionsWith the help of transfer learning, multiple versions are supported :4.134.154.205.05.45.75.8For now, the models are noly available for Linux/x86 version, using the compiler ggc version 6.3.0.AccuracyOn version 5.8, the error rate is on average 5.2% of the real size, using Mean Absolute Percentage error, with a standard deviation of 5.63. The median is at 3.67%, meaning half the predictions are below this error rate. 97% of the predictions are below 20% error.
Package: kProcessor
@DIB-LAB/kProcessor📖 Table of Contents➤ Table of Contents➤ Table of Contents➤ Introduction➤ Quick Installation (pip)➤ Build from sourceCloneInstall dependenciesBuildCMake optionsBuild The kProcessor LibraryBuild Everything➤ Manually build the Python bindingsGenerate bindings➤ Contributors➤ License➤ IntroductionkProcessoris a C++ API with a handy Python interface that enables easy handling of sequence kmer content. kProcessor stores kmers with their associated metadata in a virtual data structure called kDataframe. By default, kDataFrame stores the kmers with their counts in the input dataset. However, kDataFrame supports adding multiple other columns to store more information about these kmers in different data types. Users can easily merge multiple kDataFrames or apply different set functions (e.g. union, intersect and difference) on a group of kDataFrames. Colored kDataFrame is another core virtual data structure in kProcessor that allows the indexing of the kmers in a multi-sequence reference input. It is composed of a kDataFrame that replaces the kmer count with a key (aka color). This key connects the kmer to all sequences associated with this kmer.➤ Quick Installation (pip)python-mpipinstallkProcessor➤ Build from sourceClonegitclonehttps://github.com/dib-lab/kProcessor.gitcdkProcessor/
gitsubmoduleupdate--init--recursiveInstall dependenciessudoapt-getinstallg++swigcmakepython3-devzlib1g-devlibghc-bzlib-devpython3-distutilslibboost-all-devBuildCMake optionsDescriptionOptionDefaultBuild testsBUILD_TESTSOFFBuild documentationBUILD_DOCSOFFBuild everything!BUILD_ALLOFFBuild The kProcessor Library# Run CMake configure
cmake -Bbuild

# Run make with parallel execution.
cmake --build build -j4 # -j4 = execute 4 recipes simultaneously.Build Everythingcmake -Bbuild -DBUILD_ALL=1

cmake --build build -j4 # -j4 = execute 4 recipes simultaneously.Build Docs OnlyOutput directory:build/doxygen/htmlcmake-Bbuild-DBUILD_DOCS=1cmake--buildbuild--targetGenerateDocsBuild Tests Onlycmake-Bbuild-DBUILD_TESTS=1cmake--buildbuild-j4# Run testscdbuild/tests/kProcessorLibTests
./testKprocessorLib➤ Manually build the Python bindingsPython bindings are generated usingSWIG. It'srecommendedto installswig=4.0.2usingConda.You can build the python bindings by executingbuild_wrapper.sh, or you can follow the next steps.Generate bindingsFirst, you need to follow the instructions in theBuild from source.Whilepwd=kProcessorrun:python setup.py bdist_wheel.Install the generated wheel package using:cd dist && python -m pip install kProcessor*.whl.➤ ContributorsMostafa ShokrofMohamed AbuelaninTamer Manosur➤ LicenseLicensed underBSD-3-Clause.
Package: kpsh
kpshkpsh, or KeePass Shell, is a password manager and an interactive shell for
working directly with KeePass password database files.Featurescreate, open, lock and unlock databasesadd, edit and delete database entrieslist contents of databaseshow contents of database entries and filter them by fieldsautotype usernames and passwords or any sequences of entry fields (by
xdotool on X11 and ydotool on Wayland)access all commands non-interactively via-cswitch or by piping commands
directly to kpshtab-completion in interactive modedaemon mode: open and unlock your database once and then quickly access
its contents from kpsh-client.several built-in ways to obtain a password, which can be passed by argument,
typed directly to kpsh or through pinentry program program or fetched from a
provided command outputships with highly customizable kpsh-menu script which performs any kpsh
command on entries selected by dmenu/rofi/fzf (e.g. autotype passwords
selected in dmenu/rofi)Online Documentationhttps://pages.goral.net.pl/keepass-shellUsage examplesTypical session:$ kpsh passwords.kdbx

passwords.kdbx> ls
Password: ********
personal/bank
personal/login
personal/website
work/login

passwords.kdbx> show work/login
path: work/login
username: John Doe
password: jsdf7y8h8349yhj3h42
notes[1]: this is my work password
notes[2]: it's the bestGet a password from gpg-encrypted file (trailing newline, which isn't a part
of password is trimmed):$ gpg --encrypt -o masterpass.gpg -r mymail@example.com
<type type type>
^D
$ kpsh passwords.kdbx --password-command "gpg --decrypt masterpass.gpg | tr -d '\n'"... or from a keyring:$ secret-tool store --label='keepass' database passwords.kdbx
$ kpsh passwords.kdbx --password-command "secret-tool lookup database passwords.kdbx"Autotype a user/password sequence:$ kpsh passwords.kdbx --password-command "secret-tool lookup database passwords.kdbx"
                      -c autotype entry1... or just a password, but a little faster:$ kpsh passwords.kdbx --password-command "secret-tool lookup database passwords.kdbx"
                      -c "autotype -s {PASSWORD} -D 12 entry1"Run as daemon (-d):$ kpsh passwords.kdbx -d --password-command "secret-tool lookup database passwords.kdbx" &
$ kpsh-client ls
entry1
entry2
$ kpsh-client autotype entry1Use pinentry to get a password to unlock database:$ kpsh passwords.kdbx --pinentry /usr/bin/pinentryInstallationUsepipx:$ pipx install kpshOr directly pip:$ pip install --user kpshInstall fetched git repository (for example to test yet unreleased code):$ cd keepass-shell
$ rm -rf dist
$ pipx install poetry>=1.2.0a
$ poetry build
$ pipx install dist/kpsh-*.whlTest kpsh without installation (e.g. for development purposes)One time setup:$ pipx install poetry>=1.2.0a
$ poetry lock
$ poetry installThe last command installs kpsh ineditablemode, meaning that it will
automatically reflect changes in source code. You can safely use it to change
kpsh to your liking.Once kpsh is installed in poetry-managed virtualenv, you can run it like
this:$ poetry run kpsh
Package: kpsv2-client
KPSv2 ClientBu proje, Türkiye Cumhuriyeti Kimlik Paylaşımı Sistemi'nin (KPS) v2 sürümüne erişmek için bir istemci sağlar. Bu istemci, KPS API'sine HTTP istekleri gönderir ve yanıtları alır.GereksinimlerKPS V2 Test HesabıPython 3VenvÖrnek Kullanımfromkpsv2_clientimportKpsServicekps_service=KpsService()kps_service.set_auth("username","password")resp=kps_service.bilesik_kutuk_sorgula(identity_number="01234567890",birth_date="01.07.1891")Katkıda BulunmaLütfen katkıda bulunmak için pull request açın. Her türlü katkıya açığız.LisansBu proje MIT lisansı altında lisanslanmıştır. Daha fazla bilgi için LICENSE dosyasına bakın.İletişimEğer bir sorunuz veya geri bildiriminiz varsa, lütfenissuessayfasında bir konu açın.
Package: kptool
What’s thisKeePass version 1 database file access tool that includes access
module.Currently, support search the entries or groups as the command line
tool.How to UseExample:% python kptool.py <kdbfilepath>
password required
kptool> Ent
Entry2:
pass    : entry
modified: 2010-10-01 22:01:02
Entry1:
url     : URL
pass    : testtest
modified: 2010-09-26 13:18:13
kptool> ^DBuilding and installation% python setup.py installTesting% python setup.py testRequirementPython 2.6 or laterpyCryptoargparseKeePassdb module APIConstructor(kdbfilepath, masterpassword)Create DB from KeePass DB file path and Master password.>>> from kptool.keepassdb import keepassdb
>>> password = "Hogehoge"
>>> k = keepassdb.KeepassDBv1("tests/keepass-test.kdb", password)get_groups()Get groups.>>> for g in k.get_groups():
...   if ('groups' in g):
...     "%s %s in %s" % (g['title'], g['group_id'], g['groups'])
...   else:
...     "%s %s" % (g['title'], g['group_id'])
'Group1 2877859699'
'SubGroup1 1203768070 in 2877859699'
'Group2 2251441873'get_entries()Get entries.
Note: KeepassDB has a history. get_entries() get all entries include
history. Since that, entries that have same title may be acquired.>>> for e in k.get_entries():
...   print "%s %s %s" % (e['title'], e['username'], e['created'])
Entry2 entry2 2010-10-01 22:00:51
SubGroup1 gr 2010-10-01 22:00:29
Entry1 test 2010-09-26 13:17:55
日本語です sub 2010-10-01 21:59:33
Meta-Info SYSTEM 2010-10-01 22:01:04get_entries_from_groupid(groupid)Get entries from groupid. Groupid should be Integer.>>> for e in k.get_entries_from_groupid(2877859699):
...   e['title']
'Entry1'
'Meta-Info'find_groups(searchword)Find groups that has <searchword> in title or id.>>> for g in k.find_groups("up1"):
...   g['title']
'Group1'
'SubGroup1'find_entries(searchword)Find entries that has <searchword> in title, url, comment or username.>>> for e in k.find_entries("Ent"):
...   e['title']
'Entry2'
'Entry1'clear()Clears any currently loaded groups and entries in the database.>>> k.clear()
>>> k.get_entries()
[]
>>> k.get_groups()
[]Entry Field Listsid:entry id. String.group_id:group id. Integer.icon:icon Integer.title:title. ASCII or UTF-8url:urlusername:usernamepassword:passwordcomment:comment. ASCII or UTF-8.created:created date. Datetime object.modifed:modified date. Datetime object.accessed:accessed date. Datetime object.expires:expires date. Datetime object.
if “never”, shows 2999-12-28 23:59:59.bin_desc:binary:Group Field Listsgroup_id:group id. Integer.title:titleicon:iconlevel:level. start from 0.comment:comment.BUGSOnly Rijndael is supported.Only passkeys are supported (no key files).Only read methods is supported.TODOWrite methods.KeePass db version 2 support.LicenseGPL version2AcknowledgementKnowledge about the KeePass DB v1 format was gleaned from the source
code of keepassx-0.4.3 andFile::KeePassin the CPAN.KeePassX 0.4.3 bears the copyright ofCopyright (C) 2005-2008 Tarek Saidi <tarek.saidi@arcor.de>
Copyright (C) 2007-2009 Felix Geyer <debfx-keepassx {at} fobos.de>File::KeePassbears the copyright ofPaul Seamons <paul at seamons dot com>
Package: kpwrapper
Smart-M3 Python knowledge processor wrapper libraryUsage:- See the Smart-M3 documentation about how to set up and run a Smart-M3 SIB.- See examples/kpwrapper_sample.py for sample usage.Links:- http://smart-m3.sourceforge.net- http://public.futurice.com/~ekan/thesis.pdfChangelog=========1.0.4 - Released 2010-04-19----------------* Nicer looking log output from preconfigured discovery, with a timestamp1.0.3 - Released 2010-02-13----------------* Applied Janne Vanhala's patch that fixes handling of booleans in SIB tuple return values1.0.2 - Released 2009-12-23----------------* Packaging improvements for releasing in PyPi1.0.1 - Released 2009-12-17----------------* Moved code to SourceForge1.0.0 - Released 2009-12-10----------------* First stable release.* Use the eggified smart-m3_pythonKP instead of a custom wrapper egg.
Package: kpx
Install# Install or update it from pippipinstall-Ukpx# Install or update it from gitlabpipinstall-Ukpx--index-urlhttps://gitlab.com/api/v4/projects/24038501/packages/pypi/simpleUsage# Configure profile region and output typekpxconf[profile-name][aws-zone][output-type]# Configure profile credentialskpxcred[profile-name][access-key-id][secret-access-key]# List route53 hosted zoneskpxr53# List records in a hosted zonekpxr53[zone-id]# List ec2 instances (without pagination)kpxec2
Package: kpy
kpyKpy stands for Keitai (Japanese mobile phone) model name extractor on Python.This module extracts model name of mobile phone/tablet from user agent string.Currently, This module supports 1007 Japanese mobile phones/tablets.Docomo: 561 models (F501i, 1999. - SO-03H, 2015)au: 91 models (IS01, 2010 - SOV32, 2015; currently supporting only Android models)SoftBank (J-PHONE, Vodafone, Disney mobile, EMOBILE, WILLCOM, Y!mobile): 357 models (J-SH02, 1999. - Nexus 6P, 2015)INSTALATION$ pip install kpyUSAGEimportkpyua=('Mozilla/5.0 (Linux; U; Android 4.1.1; ja-jp; HTL21 Build/JRO03C) ''AppleWebKit/534.30 (KHTML, like Gecko) Version/4.0 Mobile Safari/534.30')kpy.extract(ua)# => 'HTL21'TODOSupports other countries’ mobilephoneOutput model series name of mobilephoneContributions are welcome.LicenseMIT LicenseCHANGES0.2.1 (2016-03-12)Resolved installation problem.0.2 (2015-11-22)Support 2014’s winter model to 2015’s winter model
(docomo, au, softbank)Support Python 3.50.1 (2014-12-02)Initial release.
Package: kq
KQ: Kafka Job Queue for PythonKQ (Kafka Queue)is a lightweight Python library which lets you enqueue and
execute jobs asynchronously usingApache Kafka. It useskafka-pythonunder the hood.AnnouncementsSupport for Python 3.5 will be dropped from KQ version 3.0.0.Seereleasesfor latest updates.RequirementsApache Kafka0.9+Python 3.6+InstallationInstall usingpip:pipinstallkqGetting StartedStart your Kafka instance.
Example usingDocker:dockerrun-p9092:9092-eADV_HOST=127.0.0.1lensesio/fast-data-devDefine your KQworker.pymodule:importloggingfromkafkaimportKafkaConsumerfromkqimportWorker# Set up logging.formatter=logging.Formatter("[%(levelname)s]%(message)s")stream_handler=logging.StreamHandler()stream_handler.setFormatter(formatter)logger=logging.getLogger("kq.worker")logger.setLevel(logging.DEBUG)logger.addHandler(stream_handler)# Set up a Kafka consumer.consumer=KafkaConsumer(bootstrap_servers="127.0.0.1:9092",group_id="group",auto_offset_reset="latest")# Set up a worker.worker=Worker(topic="topic",consumer=consumer)worker.start()Start your worker:pythonmy_worker.py[INFO]StartingWorker(hosts=127.0.0.1:9092topic=topic,group=group)...Enqueue a function call:importrequestsfromkafkaimportKafkaProducerfromkqimportQueue# Set up a Kafka producer.producer=KafkaProducer(bootstrap_servers="127.0.0.1:9092")# Set up a queue.queue=Queue(topic="topic",producer=producer)# Enqueue a function call.job=queue.enqueue(requests.get,"https://google.com")# You can also specify the job timeout, Kafka message key and partition.job=queue.using(timeout=5,key=b"foo",partition=0).enqueue(requests.get,"https://google.com")The worker executes the job in the background:pythonmy_worker.py[INFO]StartingWorker(hosts=127.0.0.1:9092,topic=topic,group=group)...[INFO]ProcessingMessage(topic=topic,partition=0,offset=0)...[INFO]Executingjobc7bf2359:requests.api.get("https://www.google.com")[INFO]Jobc7bf2359returned:<Response[200]>See thedocumentationfor more information.
Package: kqlmagic-kernel
PrerequisitesJupyter NotebookandKqlmagicInstallationTo install using pip:pip install kqlmagic_kernelAdd--userto install in the user-level environment instead of the system environment.To install using conda:conda config --add channels conda-forge
conda install kqlmagic_kernel
conda install texinfo # For the inline documentation (shift-tab) to appear.
python -m kqlmagic_kernel.installKqlmagic Jupyter kernelspec is automatically installed as part of the
python package.  This location can be found usingjupyter kernelspec list.
If the default location is not desired, remove the directory for thekqlmagickernel, and install usingpython-mkqlmagic_kernel install.  Seepython-mkqlmagic_kernel install--helpfor available options.UsageTo use the kernel, run one of:jupyternotebook# In the notebook interface, select Kqlmagic from the 'New' menujupyterqtconsole--kernelkqlmagicjupyterconsole--kernelkqlmagicThis kernel is based onipykernel,
which means it features a standard set of magics (such as%%html).  For a full list of magics,
run%lsmagicin a cell.A sample notebook is availableonline.ConfigurationThe kernel can be configured by adding ankqlmagic_kernel_config.pyfile to thejupyterconfig path.The path to the Kqlmagic kernel JSON file can also be specified by creating anKQLMAGIC_KERNEL_JSONenvironment variable.TroubleshootingKernel Times Out While StartingIf the kernel does not start, run the following command from a terminal:python-mkqlmagic_kernel.checkThis can help diagnose problems with setting up integration with Octave.  If in doubt,
create an issue with the output of that command.Kernel is Not ListedIf the kernel is not listed as an available kernel, first try the following command:python-mkqlmagic_kernelinstall--userIf the kernel is still not listed, verify that the following point to the same
version of python:whichpython# use "where" if using cmd.exewhichjupyterFor details of how this works, see the Jupyter docs onwrapper kernels
Package: kquant
kquantkquant패키지는 코스콤에서 개발한 금융데이터 분석용 파이썬 패키지로 코스콤 CHECK-API 서비스를 통해 금융데이터를 불러오고 분석하는 기능을 제공합니다.kquant사용법에 대해서는 CHECK-API 활용 웹사이트를 참조하시기 바랍니다.https://koscom.github.io/checkapi/index.htmlkquant의 함수 목록은 kquant API 웹사이트를 참조하시기 바랍니다.https://koscom.github.io/kquant/index.html패키지 설치kquant패키지는 pip install 명령으로 설치할 수 있습니다.pipinstallkquant준비 사항kquant패키지를 사용하기 위해서는 실시간 금융 데이터를 REST-API 및 WebSocket 기반으로 제공하는 서비스인
코스콤 CHECK-API 서비스를 신청하여 API ID 및 API KEY를 발급받으셔야 합니다.코스콤 CHECK-API 서비스에 대해서는 다음 홈페이지를 참조해 주세요.https://checkapi.koscom.co.kr/배포 기록v0.3.6지수/업종period_index함수 추가상장 펀드symbol_fund함수 추가info_basic_fund함수 추가daily_fund함수 추가trade_fund함수 추가intra_fund함수 추가period_fund함수 추가API 키 정보 저장 위치 옵션 추가Linux/Mac 서버에서/.kquant/credential디렉토리에서 API 정보를 읽는 기능 추가v0.3.5trade_index함수 추가daily_investor_index함수 추가basic_info_index함수명 변경 ->info_basic_indexrank_broker_stocks함수명 변경 ->sum_broker_stocksrank_block_stocks함수명 변경 ->sum_block_stocksrank_short_stocks함수명 변경 ->sum_short_stocksrank_investor_stocks함수명 변경 ->sum_investor_stocksv0.3.4daily_index,intra_index추가v0.3.3basic_info_index추가v0.3.2pandas 2.2 버전 대응v0.3.1intra_investor_stocks함수 삭제 ->rank_investor_stocks함수에 기능 통합v0.3.0주식 CHECK API 추가모듈명 변경kquant.data.market->kquant.data.stock일중 데이터 함수 추가quote_stock: 주식 종목의 호가 정보를 반환하는 함수trade_stock: 주식 종목의 체결 틱데이터 정보를 반환하는 함수intra_investor_stocks: 전종목 당일 당일 투자자 정보를 반환하는 함수일간 데이터 함수 추가daily_block_stock: 주식 종목의 일자별 대량매매 정보를 반환하는 함수daily_short_stock: 주식 종목의 일자별 공매도 정보를 반환하는 함수daily_lend_stock: 주식 종목의 일자별 대차잔고 정보를 반환하는 함수daily_margin_stock: 주식 종목의 일자별 신용잔고 및 대주 정보를 반환하는 함수순위 데이터 함수 추가rank_broker_stocks: 회원사별 기간 매매집계 정보를 반환하는 함수rank_block_stocks: 종목별 기간 대량매매 정보를 반환하는 함수rank_short_stocks: 종목별 기간 공매도 정보를 반환하는 함수rank_investor_stocks: 종목별 기간 투자자 정보를 반환하는 함수주기 데이터 함수 추가period_stock: 주식 종목의 주/월/분기/연도별 주기 정보를 반환하는 함수v0.2.9단일 및 복수 주식 종목에 대한 정보를 반환하는info_basic_stock,info_basic_stocks함수 추가v0.2.8백테스트시 상한가 매수 및 하한가 매도 금지v0.2.7백테스트용 액면 분할/합병 처리 추가포트폴리오 백테스트 버그 수정v0.2.6intra_stock함수에서date인수를 추가하여 과거 분봉 데이터 조회 가능.v0.2.5KRX 주식 투자 알고리즘 경진대회용 최초 배포 버전.
Package: kquery
kqueryDamn light QT-based database clientThis postgresql client is intended to satisfy KDE Plasma users who has really low-spec hardware (Yepo laptops, Raspberry PI, etc), those who already runs Plasma or QT desktop and don't want fancy resources, wich full database IDEs available like DBeaver already provides.The goal is to keep a light, quick-starting, tiny usable interface with basic database features for software developers.If you need complex database management features, have a decent modern workstation or if you don't use a Plasma/QT desktop, this is not the tool for you, there are plenty of other wonderful clients out there.Bonus feature: funny dialogs for user interaction.Install steps:This step is rather complicated, but I'm counting on you!$ pip install kqueryAnd then, to run:$ kqueryAnd that's it!FAQ:Q - Why did you choose PyQt5, a 100+MB framework for a "light" database client? You must be stupid to load that much dependency for such a small application.A - Because this amount of space isn't a problem for me. Hard Disk space is plentiful and cheap nowadays, not as much as battery/memmory/processing in low-powered devices.Q - Do you plan to provide other database connectors? Or improved postgresql connecion features?A - Yes! If I have enough time and application load time and performance is not compromised, why not?
Package: kr8s
A simple, extensible Python client library for Kubernetes that feels familiar for folks who already know how to usekubectl.HighlightsAPI inspired bykubectlfor a shallow learning curve.Sensible defaultsto reduce boiler plate.No swagger generated code, human readable code only.Has both a standard and anasync APIthat can be used withasyncioandtrio.Client cachingto reduce passing API objects around.Batteries included by providinguseful utilities and methodsinspired bykubectl.QuickstartInstallation$pipinstallkr8sExamples[!TIP]
See theExamples Documentationfor a full set of examples includingasyncioexamples.List NodesPrint out all of the node names in the cluster.importkr8sfornodeinkr8s.get("nodes"):print(node.name)Create a PodCreate a new Pod.fromkr8s.objectsimportPodpod=Pod({"apiVersion":"v1","kind":"Pod","metadata":{"name":"my-pod",},"spec":{"containers":[{"name":"pause","image":"gcr.io/google_containers/pause",}]},})pod.create()Scale a DeploymentScale the Deploymentmetrics-serverin the Namespacekube-systemto1replica.fromkr8s.objectsimportDeploymentdeploy=Deployment.get("metrics-server",namespace="kube-system")deploy.scale(1)List Pods by label selectorGet all Pods from all Namespaces matching a label selector.importkr8sselector={'component':'kube-scheduler'}forpodinkr8s.get("pods",namespace=kr8s.ALL,label_selector=selector):print(pod.namespace,pod.name)Add a label to a PodAdd the labelfoowith the valuebarto an existing Pod.fromkr8s.objectsimportPodpod=Pod("kube-apiserver",namespace="kube-system")pod.label({"foo":"bar"})Generate a PodGenerate a simple Pod with a couple of keyword arguments.fromkr8s.objectsimportPodpod=Pod.gen(name="example-1",image="nginx:latest")pod.create()Cordon a NodeCordon a Node to mark it as unschedulable.fromkr8s.objectsimportNodenode=Node("k8s-node-1")node.cordon()Pod ExecExec a command in a Pod.fromkr8s.objectsimportPodpod=Pod.get("my-pod")command=pod.exec(["uptime"])print(command.stdout.decode())# 13:49:05 up 23:03,  0 users,  load average: 0.66, 0.87, 0.85Port forward a PodOpen a port forward to a Pod as a background task/thread.fromkr8s.objectsimportPodpod=Pod.get("my-pod")pf=pod.portforward(remote_port=1234,local_port=5678)# Starts the port forward in a background threadpf.start()# Your other code goes here# Optionally stop the port forward thread (it will exit with Python anyway)pf.stop()[!TIP]
See theExamples Documentationfor a full set of examples includingasyncioexamples.
Package: kraconvert
# kraconvert
Converts Krita .kra files into common used filesConvert a kra to a bunch of jpeg files:kraconvert $HOME/pictures/pepper_n_carrot.kra -p -w -s 1000 2000 40 -j 95 -i-p: extract the mergedimage.png, you need this exception if you want just the icc profile-w: webready, converts the jpeg files to sRGB-s: different sizes, maintains aspect ratio-j: jpeg quality, in that case 95-i: extract the icc profile, if you use -w (webready) you need that switch# TL;DR
If you don’t need anything fancy just runkraconvert pepper_n_carrot.kra -i -p -wYou can even omit the ‘-w’ if you don’t need a sRGB version.
Package: krait
Krait – CLI for setting up new python projectsWelcome to Krait!Krait is a python-built CLI for new python projects! Working on new code usually means setting up linters, type checkers, testing frameworks, and/or automations, but how often do those things get worked on?I made Krait to solve the issue of starting up new python projects rapidly while ensuring that code quality is high. By baking these tools into the project creation process, you can find mistakes and issues early on and save time debugging.Krait is currently in Beta, and new features are still being worked on. A few of the features coming soon:Pre-commit hooksSupport for creating projects with FlaskDocumentation is also being worked on to explain the process of extending Krait by writing your own plugins. This would allow external packages to enhance the number of options permitted for each of the tools that we supportInstallationSimplest installation is through pip.$pipinstallkrait