Saravanan666/pypi-org huggingface dataset:
Package: kkScript
kkScriptdatabaseУстановкаКоманда pippip install kkscriptПрименениеРабота с NoSQL базами данных kkdb через .kks файл..py файлfrom kkScript import script

script("code").kks файл$kkdb=create.DB."db"."db1".db1

$kkdb.setData."age".89.db1
$kkdb.updateData.db1

printLn=db1.getData("age", "int")Вывод89Файл базы данных .kkdbage=\data/=89Работа с NoSQL базами данных kkdb через .py файл.py файлfrom kkScript import kkdb

db1 = kkdb.DB("db", "db1")

db1.setData("age",89)
db1.updateData()

print(db1.getData("age", "int"))Вывод89Файл базы данных .kkdbage=\data/=89АвторНикнеймНикнейм 1OmnyНикнейм 2xDreyКонтактыЭл. почтаomenplay325@gmail.comСоц сетиTelegramEasyOmnyYouTubeOmnyxDreyДокументацияСсылкаПока нет!
Package: kkssh
kksshKkssh is a user-friendly SSH client that simplifies the process of connecting to remote servers. With a built-in hostname prompt, you no longer need to memorize or search for the correct hostname.InstallPython 3.10.10pipinstall--upgradekksshUsagekkssh-c~/.ssh/configHOSTDeveloppythonsetup.pysdist
twineuploaddist/*
Package: kktool
ktool介绍储存一些我常用的自己写的工具软件架构软件架构说明
twine upload dist/*
在setup.py目录终端执行命令python3 -m pip install --upgrade setuptools wheel，安装setuptools和wheel
在setup.py目录终端执行命令python3 setup.py sdist bdist_wheel，会在setup.py同一级目录下生成dist文件夹，里面有两个文件，一个***.tar.gz，一个****.whl文件
在setup.py目录终端执行命令python3 -m pip install --upgrade twine，安装twine
在setup.py目录终端执行命令python3 -m twine upload --repository-urlhttps://upload.pypi.org/legacy/dist/*，就上传了自己的python库。安装教程xxxxxxxxxxxx使用说明xxxxxxxxxxxx参与贡献Fork 本仓库新建 Feat_xxx 分支提交代码新建 Pull Request码云特技使用 Readme_XXX.md 来支持不同的语言，例如 Readme_en.md, Readme_zh.md码云官方博客blog.gitee.com你可以https://gitee.com/explore这个地址来了解码云上的优秀开源项目GVP全称是码云最有价值开源项目，是码云综合评定出的优秀开源项目码云官方提供的使用手册https://gitee.com/help码云封面人物是一档用来展示码云会员风采的栏目https://gitee.com/gitee-stars/
Package: kktools
kktools========This library provides python tools for finance and treasury specialists.Installationpip install kktoolsRealized Functionalityget_ecb_rates("CUR", "YYYY-MM-DD")- returns pandas dataframe with historical values for a given currency ("CUR") starting from the given date.get_last_ecb_rates()- returns pandas dataframe with the latest valid ECB exchange rates for all published currencies.df_to_excel("file_name.xlsx", dataframe)- exports pandas dataframe to an excel file with pretty formatting.dfs_to_excel("file_name.xlsx", list_of_dataframes)- exports list of pandas dataframes to an excel file with pretty formatting.Camt053- class for parsing CAMT053 files (EOD bank statements, ISO20022 standard).Pain001- class for parsing PAIN001 files (payment initiation, ISO20022 standard).Basic UsageImporting history of EUR/GBP exchange rates since 2000-01-01 and exporting it to an excel file with pretty formattingimport kktools as kkt

df = kkt.get_ecb_rates("GBP", "2000-01-01")
kkt.df_to_excel("Historical_Rates.xlsx", df)Parsing CAMT053 file and getting list of balances and list of all transactions:from kktools import Camt053

camt = Camt053(file_name) # creates an object of Camt class you need to pass path+file_name of the CAMT053 file to be processed
camt.camt.statements_info # returns list of dictionaries for each statement with the following information: account id and owner name, all available balances (OPBD/CLBD/CLAV/PRCD/FWAV/etc.), 
camt.transactions # returns list of all transactions in the file.LicenseMIT licensed. Check theLICENSEfile for full details.
Package: kkwebapi
KoikatuWebAPIA Web API wrapper for Koikatu / EmotionCreators official uploader.InstallationThis module is available onPyPI.$ pip install kkwebapi$ python -m pip install kkwebapiBasic Usage>>>fromkkwebapiimportKoikatuWebAPI>>>df=KoikatuWebAPI.get_ranking()>>>print(df)idsexheightbusthairpersonalityblood_type...namenicknamehandle_namecommentdownload_numuidweekly_download_num01112203...高岡結香ユイILLUSIONILLUSIONサンプル1256gOuAD02g92pX05r3Sj2aJJeJ01FdWqh01pe5PM1284vK01...6...
Package: klab
klab - The Kortemme Lab Tools Repository========================A collection of utilities used by our lab for computational biophysics, including PDB parsing, SGE cluster submission scripts, and interfaces with the Rosetta macromolecular software suite.Coding convention=================Besides the whitespace convention (spaces, not tabs), contributors can / generally do use their own preferences. However, code within a module should follow a consistent convention. Finally, please do not reformat modules created by other developers to your preferences.Here are some semi-standard guidelines:- General rules      : The PEP 8 conventions (https://www.python.org/dev/peps/pep-0008/) are mostly sensible.- Blank lines        : See "Blank Lines" in PEP 8. Particularly, surround top-level function and class definitions with two blank lines.- Line length        : Up to the module creator programmer.- Whitespace         : Use spaces instead of tabs, with indents set to 4 spaces. Feel free to nuke any tabbed indents with prejudice.- Import order       : Import standard Python packages first (sys, os) then higher-level/add-on packages (sqlalchemy, numpy), then our other packages (klab), then this package (kddg). Put a line break between each section of imports.- Natural language   : Please do not introduce contractions into alien modules unless that is the usual for that module.Installation============This package can be installed via:::pip install klabTo install via pip and allow git push/pulling, use:In a virtualenv:::pip install -e git+ssh://git@github.com/Kortemme-Lab/klab.git#egg=klabIn your user-directory:::pip install --user -e git+ssh://git@github.com/Kortemme-Lab/klab.git#egg=klabIn your user-directory, without using SSH:::pip install --user -e git+https://github.com/Kortemme-Lab/klab.git#egg=klab
Package: klab-autotime
# klab-autotimeTime everything in IPython## Installation:use pip## Examples```pythonInstalled autotime.py. To use it, type:%load_ext klab-autotimeIn [2]: %load_ext klab-autotimetime: 1433692.87 sIn [3]: x = 1time: 730.99 usIn [4]: x + 2Out[4]: 3time: 2.50 msIn [5]: x + ''---------------------------------------------------------------------------TypeError                                 Traceback (most recent call last)<ipython-input-5-bde712cacec5> in <module>()----> 1 x + ''TypeError: unsupported operand type(s) for +: 'int' and 'str'time: 156.05 ms```## Want to turn it off?```pythonIn [5]: %unload_ext klab-autotime```# klab-autotime
Package: klab-client-py
k.LAB CLient PythonA Python client library to interact with a running (local or remote) k.LAB Engine.This package is a python client fork.LAB. It allows registered users of k.LAB to make observations on the k.LAB semantic web from a Python program using the REST API. After creating a spatial/temporal context root observation as a context, you can submit concepts to be observed in it and the relative observations will be made at the server side and returned. Depending on the semantics submitted, the results will consists of different scientific artifacts that can be exported or inspected as needed through the API.While the API (both k.LAB's public REST API and the interfaces in this package) should be stable, this code is young - features are still missing and bugs certainly remain. Please submit Github issues as needed.This README assumes knowledge of k.LAB and semantic modeling. An introduction to both is available as atechnical notewhile more extensive documentation is developed.InstallationThe module can be installed through pip as:pip install klab-client-pyUsageUsage example: observe elevation on a given regionNote that asyncio is used to handle async elaborations.add necessary imports and create a new client instancefrom klab.klab import Klab
from klab.geometry import GeometryBuilder
from klab.observable import Observable
from klab.observation import Observation
from klab.utils import Export, ExportFormat
import asyncio

klab = Klab.create()define a geometry to use as context through its WKT definitionruaha = "EPSG:4326 POLYGON((33.796 -7.086, 35.946 -7.086, 35.946 -9.41, 33.796 -9.41, 33.796 -7.086))"create a semantic type and a geometryobs = Observable.create("earth:Region")
grid = GeometryBuilder().grid(urn= ruaha, resolution= "1 km").years(2010).build()submit them to the engine and obtain the contextticketHandler = self.klab.submit(obs, grid)
context = await ticketHandler.get()create the elevation observable and submit it to the contextobsElev = Observable.create("geography:Elevation")
ticketHandler = context.submit(obsElev)
elevation = await ticketHandler.get()export the observation to a geotiffpath = "your path here"
elevation.exportToFile(Export.DATA, ExportFormat.BYTESTREAM, path)For more examples have a look atthe testcases in the repository.
Package: klak
KlakKlak provides the ergonoics of a project Makefile with the ease of Python and power ofClick.Table of ContentsBackgroundInstallUsageMaintainersContributingLicenseBackgroundMakefiles provide a simple interface,make <command>, that is great for automating repetitive project tasks. Makefile syntax, however, is archaic, error-prone, and ill-suited for constructing modern, useful command-line interfaces.Python, on the other hand, has wonderful syntax and isgreatfor scripting. When Python is paired withClickconstructing modern, useful command-line interfaces is easy!Is there a way we can combine the power of Python and Click into a "Makefile like" experience?Enter Klak.Klak exposes a single entry-point—klak—which auto-loads a100%, vanilla Python file called aClickfile. All CLI is built using standard Python and Click, and all commands are available via:klak <command>(seeUsage).What is it good for?Klak's purpose is to provide a convenient, single-file experince for automating repetitive project tasks. It does not, nor will it ever, intend to replace Make or Makefiles.InstallStable Release# NOTE: This is the recommended method of installation.pipinstallklakFrom SourceKlak usesPoetryto manage depdencies and distribution (in lieu of setuptools).# NOTE: Clone the public repositorygitclonegit://github.com/aubricus/klak# NOTE: or download the tarballcurl-OLhttps://github.com/aubricus/klak/tarball/master# NOTE: Once the source is downloadedpoetryinstallUsageTo get started with Klak create aClickfile. Here's a simpleClickfileto get started:"""Example Clickfile.NOTE: Set your editor's language mode to Python toenable syntax highlighting! :^)"""importloggingimportclickfromklak.cliimportclilog=logging.getLogger("Clickfile")# -------------------------------------# Examples# -------------------------------------# Example: Add a command.@cli.command()@click.argument("name")defgreet(name):"""Greet someone."""click.secho(f"Hello,{name}")# Example: Add a group and sub-command.@cli.group()defhumans():"""Humans command group."""pass@humans.command(name="count")defhumans_count():"""Count all the humans."""click.secho("Over 9000!!!")NOTE: You can also organize commands into a python package in the same directory. SeeKlak/Pull/229.Once yourClickfileis ready, access commands throughklak.$klak--helpSupportThis project is a hobby/passion project which I maintain in my own time.PythonPython 3.5+OSLinux ✓MacOS ✓Windows ✘ (any volunteers?)Maintainers@aubricusContributingSeethe contributing file!PRs accepted!Please note, if editing the README, please conform to thestandard-readmespecification.LicenseMIT © 2018, 2019 aubricus@gmail.com
Package: klampt-jupyter
Klampt-jupyter-extensionA Jupyter Widget for KlamptInstallationYou can install usingpip:pipinstallklampt_jupyterIf you are using Jupyter Notebook 5.2 or earlier, you may also need to enable
the nbextension:jupyternbextensionenable--py[--sys-prefix|--user|--system]klampt_jupyterDevelopment InstallationCreate a dev environment:condacreate-nklampt_jupyter-dev-cconda-forgenodejsyarnpythonjupyterlab
condaactivateklampt_jupyter-devInstall the python. This will also build the TS package.pipinstall-e".[test, examples]"When developing your extensions, you need to manually enable your extensions with the
notebook / lab frontend. For lab, this is done by the command:jupyter labextension develop --overwrite .
yarn run buildFor classic notebook, you need to run:jupyter nbextension install --sys-prefix --symlink --overwrite --py klampt_jupyter
jupyter nbextension enable --sys-prefix --py klampt_jupyterNote that the--symlinkflag doesn't work on Windows, so you will here have to run
theinstallcommand every time that you rebuild your extension. For certain installations
you might also need another flag instead of--sys-prefix, but we won't cover the meaning
of those flags here.How to see your changesTypescript:If you use JupyterLab to develop then you can watch the source directory and run JupyterLab at the same time in different
terminals to watch for changes in the extension's source and automatically rebuild the widget.# Watch the source directory in one terminal, automatically rebuilding when neededyarnrunwatch# Run JupyterLab in another terminaljupyterlabAfter a change wait for the build to finish and then refresh your browser and the changes should take effect.Python:If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.
Package: klang-globconf
globconfCreates a global configparser object, regardless of the project and module in need of itGetting StartedIn project:from globconf import config
# config will attempt to read local config.ini file if present - otherwise:

if 'important section' not in config.sections():
    config.read_string("""
    [important section]
    host = critical-system.com
    user = REST_USER
    pwd = REST_PASSWORD
    verify_ssl = false
    """)
# or config.read('some_other_config.ini')

# load class using globconf.configIn modules:from globconf import config, verify_required_options
class module(object):
    def __init__(self):
        sec = 'service now'
        self.cfg = verify_required_options(sec, ['host', 'user', 'pwd'])
        if not self.cfg.getboolean('verify_ssl', fallback=True):
            import urllib3
            urllib3.disable_warnings(InsecureRequestWarning)And your module is happy as long as someone has initialised the needed section in the global config.PrerequisitesconfigparserInstallingA step by step series of examples that tell you how to get a development env runningGive the exampleAnd repeatuntil finishedEnd with an example of getting some data out of the system or using it for a little demopackagepython setup.py sdisttestpytestorpyton -m unittestAuthorsSteffen Schumacher-Initial work-steffenschumacherLicenseThis project is licensed under the MIT License - see theLICENSE.mdfile for detailsAcknowledgmentsHat tip to anyone whose code was usedInspirationetc
Package: klarenz
Klarenz(current release:v1.2.3) is a highly minimalist Python package (the entire API consists of a single classPartand a main processor functionproc!) for compiling Lilypond sheet music.For more information and examples please check theDocumentation.ContributingIf you wish to contribute your code to this repository, please consider the following points:PackagingEnsure to update thesrc/klarenz/version.pyfile and runpython prebuild.py(and push the changes!) before initiating the build-upload process for each release with:python -m build && twine upload dist/*This README is generated byprebuild.py. Never edit it directly by hand! Instead, modify thereadmevariable in the
pre-build file.
Package: klarfio
klarfioMinimalist python library to read and write Klarf v1.8 files.This module is a pure python module, there are no dependencies.The idea is that once the data is loaded, you can copy the defects data into a numpy array or a pandas dataframe.The data of the klarf file is held in a nested dictionnary that follows closely the structure of the klarf file itself.I plan on adding a few helper functions to simplify the access to the defect data.Note : This code is based on the one klarf v1.8 I had on hand. I don't have more files to test with.
Package: klarf-reader
The klarf-reader library is a python 3 lib that allow to parse and get klarf content as dataclass.Installing Karf-ReaderTo install klarf-reader, if you already have Python, you can install with:pip install klarf-readerHow to import Karf-ReaderTo access klarf-reader and its functions import it in your Python code like this:from klarf_reader.klarf import KlarfReading the example codeTo reader a klarf file you just have to give the klarf path and klarf-reader will return you an instance of KlarfContent that contains information from klarf file.path = Path('wd') / 'my_klarf_file'

content = Klarf.load_from_file(filepath=path)You can also get raw contents from file.path = Path('wd') / 'my_klarf_file'

content, raw_content = Klarf.load_from_file_with_raw_content(filepath=path)
Package: klarg
KlargAKommandLineARGument parsing library.Klarg is a small and simple command line argument parsing library built with no 3rd party dependencies.Why use klarg?Simple syntaxIt abstracts all the complexities away so that you can focus on developing the appication itself.# example.pyimportklargname=klarg.get_str("name")print(f"Your name is:{name}")# python example.py --name klarg# Your name is: klargEasy configuringIt makes use of the powerful dictionary data type to make configuring klarg a breeze.# example.pyimportklarg# Replace -- with +CONFIG["long_prefix"]="+"name=klarg.get_str("name")print(f"Your name is:{name}")# python example.py +name klarg# Your name is klargSimple data typesKlarg only returns basic data types such asint,float,strandbool. This means no converting from strings to integers, or to booleans, klarg already does that.# example.pyimportklargis_there=klarg.get_bool("is-there")ifis_there:print("I am here")else:print("I am not here")# python example.py --is-there# I am hereNo 3rd party dependenciesKlarg was specifically designed not to include any external dependencies, helping to keep the size small.InstallationInstalling klarg is incredibly simple, just type inpipinstallklargHow to use?# example.pyimportklargklarg_is_cool=klargs.get_bool(long="klarg-cool",short="k")klargs.on_help(do_something)if(klarg_is_cool):print("Oh, my, klarg is cool.")# python example.py --klarg-cool# Oh, my, klarg is cool.# python example.py -k# Oh, my, klarg is cool.Check out theDocumentationfor more.
Package: klarify
klarifyEasy but extendable command line interface for splitting large, multi-part .yaml files for kubernetes configuration into more easily managed and readable chunks, tied together with kustomization files.Quick notes:helm template aws-cloudwatch-metrics --namespace amazon-cloudwatch eks/aws-cloudwatch-metrics --set clusterName=my-eks-cluster > amazon-cloudwatch.yamlAbove command generates the amazon-cloudwatch.yaml file in the tests folder. Actual tests coming in future releases, along with documentation. I just wanted to get this initial working version available.
Package: klarity-connector
Klarity ConnectorPython connector for Klarity APIInstallationpipinstallklarity-connectorUsagefromklarity_connectorimportKlarityConnector# Create a connectorconnector=KlarityConnector(region='eu'api_key='YOUR_API_KEY',billing_period='current'|'previous'# Current is a default billing period)# Sending GraphQL queryquery="""query applications{applicationsPaginated(limit: 100, page: 0){results{name,cost{currentMonth}}}}"""response=connector.graphql_request(query)# Sending GraphQL mutationmutation="""mutation createApplication($name: String!, $description: String){createApplication(name: $name, description: $description){name}}"""variables={'name':'My new application','description':'My new application description'}response=connector.graphql_request(mutation,variables)Official product documentationdocs
Package: klasifikasi-py
Klasifikasi for PythonOfficialKlasifikasiAPI Client LibraryInstallationpip install klasifikasi-pyQuick startYou will need validclientId&clientSecretof your model. You can get those
from credential section at your model page, which is both unique per modelfromklasifikasiimportKlasifikasiklasifikasi_instance=Klasifikasi(creds=[{'client_id':'client_id','client_secret':'client_secret'}])You can pass multipleclientId&clientSecrettoofromklasifikasiimportKlasifikasiklasifikasi_instance=Klasifikasi(creds=[{'client_id':'client_id_1','client_secret':'client_secret_1'},{'client_id':'client_id_2','client_secret':'client_secret_2'}])ClassifyYou need your modelpublicIdto start classifying. You can get those from your
model page, or you get get it from here :models=klasifikasi_instance.get_models()forpublicIdinmodels:print(publicId)Classifying example :result=klasifikasi_instance.classify('publicId','query')LogsYou can get your classifying logs based on your modelpublicIdlogs=klasifikasi_instance.classify('publicId',{'started_at':'1 December 2020','ended_at':'2 December 2020','skip':0'take':10})ended_at&started_atparameter is mandatory, the rest is optionalErrorAll the function above will throw an Exception if something bad happen. Always
run each function insidetry&exceptblock
Package: klassez
KLASSEZTheklassezpackage is a collection of classes and functions to handle NMR data.It is organized in modules, each of which contains functions dedicated to specific tasks.Full documentation is available, after installation of the package, through the functionopen_doc, which displays the fileklassez.pdflocated in the "docs" subfolder of your install dir.Some of the functions employed byklassezare taken from the NMRGLUE package and modified to suit the needs of theklassezpackage itself.klassezis developed and tested onUbuntu 22.04 LTS. Other OS should encounter no issues; however, if it raises any errors, please notify.
Package: klassify
### KlassifyRedis based text classification service with real-time web interface.### Demo![klassify](http://i.imgur.com/iG4atNg.gif)### Installingpip install klassify#### Usage```python -m klassify```Command line options:```--port                           run on the given port (default 8888)--prefix                         prefix that will be used in redis keys(default klassify)--redis-db                       redis database (default 0)--redis-host                     redis host (default localhost)--redis-port                     redis port (default 6379)```