Saravanan666/pypi-org huggingface dataset:
Package: kylie
KylieKylie provides mappings between JSON data structures and Python objects. It
provides a reasonable amount of power with only a tiny bit of magic, and it has
100% code coverage.FeaturesFree software: BSD licenseDocumentation:https://kylie.readthedocs.org/Allowsname mappingbetween Models and python dictionary keys.Allowstype conversionwhen serializing and de-serializing objects.Automatic serialization/deserialization ofnested models.Not bound to JSON in any way, and should also be useful forMessagePackSupports Python 2.6+ & 3.3+ExampleclassSpanishInquisitionModel(Model):inquisition_id=Attribute('id')expected=Attribute(python_type=bool,serialized_type=int)Then:>>>surprise=SpanishInquisitionModel(inquisition_id=1234,expected=False)>>>surprise.inquisition_id1234>>>surprise.serialize(){'id':1234,expected=0}Note that the attributeinquisition_idbecomes the dict key"id", and
expected is mapped to0instead ofFalse.We can now take this dict,dumpsit to JSON, and somewhere else call
the following on the json_data (which is a dict returned fromloads):>>>my_surprise=SpanishInquisitionModel.deserialize(json_data)>>>my_surprise.inquisition_id1234>>>my_surprise.expectedFalseKylie supportsnested models, so you can embed
other Model instances inside the data, and Kylie will manage serialization and
deserialization of them for you.Non-FeaturesSo what doesn’t Kylie do yet? Well, there are a few things, because it’s
very new:Doesn’t have any mechanism for validation. I plan to add this once I
decide the best way to do it.Ideas welcome!No post-deserialize option, unless you do it yourself.
This would allow wiring up of objects that are referred to byidand
provided elsewhere in the serialized data-structure, for example.So, still some important things to do, but I think Kylie is already useful.Why is it called Kylie?Back in the late 80’s (I’m old!) Kylie and Jason were today’s Kim and Kanye.ThisKylie works well with JSON. Geddit?History0.3.0 (2015-06-05)MappedModelChoice & BaseModelChoice for determining Model to deserialize
at runtime.Change to internal Attribute interface (will lead to minor version bump)_apply_modelhas been replaced with a direct set ofattr_name.Minor code quality improvements.Documentation improvements.0.2.0 (2015-04-22)Added list support to Relation withsequence=Trueparameter.0.1.1 (2015-04-12)Removed print statement inside class constructor.0.1.0 (2015-04-12)First release on PyPI.
Package: kylin
This library is to readTeleinfoframesUsageimportkylinteleinfo=kylin.Kylin(timeout=2,verbose=True)teleinfo.open()teleinfo.readframe()teleinfo.close()DevelopmentUnit tests usingTox$tox-rCode coverage:$tox-r-ecoverageDocumentationDocumentation is available at:http://readthedocs.org/docs/kylin/en/latestContributeCheck for open issues or open a fresh issue to start a discussion around a feature idea or a bug.Forkthe repositoryon GitHub to start making your changes to thedevelopbranch (or branch off of it).Write a test which shows that the bug was fixed or that the feature works as expected.Send a pull request and bug the maintainer until it gets merged and published. :)ChangeLogA changelog is availableChangeLog.ContactNicolas Lamirault <nicolas.lamirault@gmail.com>
Package: kylinautosolve
The client library of Kylin Autosolveby Kylin Inc.This is a client library of Kylin Autosolve based on the WebSocket protocol.Installationpip install kylin-autosolve-client-pythonUsageInitialize a clientimportkylinautosolveclient=kylinautosolve.KylinAutosolveClient()Connect to the autosolve servicecliennt.access_token='ACCESS_TOKEN'client.cient_key='CLIENT_KEY'client.start()Add a listener to receive resultdefhandler(evt):notification=evt.notificationtask_result=notification.task_result()evt.handled+=1print('received task result:',task_result)client.on('notification:task_result',handler)NOTEThetokenfield is encoded in JSON format.Create a task to solve a challengeoptions={'site_key':'6Lfv-q0ZAAAAADy0U9JUaCPCZI15U-7jhbAiYa0U','version':'3','action':'login'}message=client.make_create_task_message({'google','https://recaptcha-test.kylinbot.io/',options.get('timeout',0'),options})awaitclient.when_ready()response=awaitclient.invoke(message)print('response:',response)Poll the result of a taskYou don't have to poll the result usually, the autosolve server will notify client when it got the result fromKylin One Click, install a notification handler to receive result instead.awaitclient.invoke(client.make_get_task_result_message(kylinautosolve.GetTaskResultRequest(task_id=create_task_response.create_task.task_id)))Cancel a requestawaitclient.invoke(client.make_cancel_task_message(kylinautosolve.CancelTaskRequest(task_id=create_task_response.create_task.task_id)))Cancel all requestsawaitclient.invoke(client.make_cancel_task_message())
Package: kylin_client
Summarykylin_client is a api client for kylin.
It currently supports the versions from2.6
to 3.6(users of Python 2.4 and 2.5 may use2.1.3version).PyPyis also known to work.Example usagesQUERY
===>>>fromkylin_client.kylin_clientimportKylinClientaskyclient>>>client=kyclient(host='127.0.0.1:7070',user='ADMIN',password='KYLIN')>>>client.query('select * from kylin_test',project='kylin_test',limit=500)
Package: kylink
Kylink-pyKylink-py, means the package for Python Toolkit for Kylink PlatformInstallationpip install kylinkUsageExample: fetch and parse a USDT Transfer Eventimportosimportweb3importkylinkfromkylink.evmimportSingleEventDecoder# for internetky=kylink.Kylink(api_token=YOUT_APIKEY)log=ky.eth.events("address = unhex('dac17f958d2ee523a2206206994597c13d831ec7')",limit=1)[0]w3=web3.Web3()abi={"anonymous":False,"inputs":[{"indexed":True,"name":"from","type":"address"},{"indexed":True,"name":"to","type":"address"},{"indexed":False,"name":"value","type":"uint256"},],"name":"Transfer","type":"event",}decoder=SingleEventDecoder(w3,event_abi=abi)result=decoder.decode(log)print(result)You can read detailed guide onour document site
Package: kylinpy
Apache Kylin Python Client LibraryApache Kylin Python Client Library is a python-based Apache Kylin client.Any application that uses SQLAlchemy can now query Apache Kylin with this Apache Kylin dialect installed.InstallationThe easiest way to install Apache Kylin Python Client Library is to use pip:pip install kylinpyalternative, install by offline tarball package:# download from https://pypi.org/project/kylinpy/#files
pip install kylinpy-<version>.tar.gzApache Kylin dialect for SQLAlchemyAny application that uses SQLAlchemy can now query Apache Kylin with this Apache Kylin dialect installed.You may use below template to build DSN to connect Apache Kylin:kylin://<username>:<password>@<hostname>:<port>/<project>?<param1>=<value1>&<param2>=<value2>DSN FieldsDefaultAllow omittedusernamenullfalsepasswordnullfalsehostnamenullfalseport7070trueprojectnullfalseDSN query string config is as followsFieldsDefault ValueOptional valueDescriptionis_ssl00|1Is the Kylin cluster enabled for httpsprefix/kylin/apistringKylin cluster API prefixtimeout30integer > 0HTTP timeout with Kylin clusterversionv1v1|v2|v4v1 == using Apache Kylin APIv2 == using Kyligence Enterprise 3 APIv4 == using Kyligence Enterprise 4 APIis_pushdown00|1If enabled, viewing a project table will use the hive source tableis_debug00|1Whether to enable debug modeFrom SQLAlchemy access Apache Kylin$ python
>>> import sqlalchemy as sa
>>> kylin_engine = sa.create_engine('kylin://ADMIN:KYLIN@sandbox/learn_kylin?timeout=60&is_debug=1')
>>> results = kylin_engine.execute('SELECT count(*) FROM KYLIN_SALES')
>>> [e for e in results]
[(4953,)]
>>> kylin_engine.table_names()
[u'KYLIN_ACCOUNT',
 u'KYLIN_CAL_DT',
 u'KYLIN_CATEGORY_GROUPINGS',
 u'KYLIN_COUNTRY',
 u'KYLIN_SALES',
 u'KYLIN_STREAMING_TABLE']From Pandas access Apache Kylin$ python
 >>> import sqlalchemy as sa
 >>> import pandas as pd
 >>> kylin_engine = sa.create_engine('kylin://ADMIN:KYLIN@sandbox/learn_kylin?timeout=60&is_debug=1')
 >>> sql = 'select * from kylin_sales limit 10'
 >>> pd.read_sql(sql, kylin_engine)From Superset access Apache KylinNow you can configure the DSN in your application to establish the connection with Apache Kylin.For example, you may install Apache Kylin Python Client Library in your Superset environment and configure connection to Apache Kylin in Supersetthen you may be able to query Apache Kylin one table at a time from Supersetyou may also be able to query detail dataAlternatively, you may also be able to query multiple tables from Apache Kylin by using SQL Lab in Superset.
Package: kylinpython
Apache Kylin Python Client LibraryApache Kylin Python Client Library is a python-based Apache Kylin client.Any application that uses SQLAlchemy can now query Apache Kylin with this Apache Kylin dialect installed.InstallationThe easiest way to install Apache Kylin Python Client Library is to use pip:pip install kylinpyalternative, install by offline tarball package:# download from https://pypi.org/project/kylinpy/#files
pip install kylinpy-<version>.tar.gzApache Kylin dialect for SQLAlchemyAny application that uses SQLAlchemy can now query Apache Kylin with this Apache Kylin dialect installed.You may use below template to build DSN to connect Apache Kylin:kylin://<username>:<password>@<hostname>:<port>/<project>?<param1>=<value1>&<param2>=<value2>DSN FieldsDefaultAllow omittedusernamenullfalsepasswordnullfalsehostnamenullfalseport7070trueprojectnullfalseDSN query string config is as followsFieldsDefault ValueOptional valueDescriptionis_ssl00|1Is the Kylin cluster enabled for httpsprefix/kylin/apistringKylin cluster API prefixtimeout30integer > 0HTTP timeout with Kylin clusterversionv1v1|v2|v4v1 == using Apache Kylin APIv2 == using Kyligence Enterprise 3 APIv4 == using Kyligence Enterprise 4 APIis_pushdown00|1If enabled, viewing a project table will use the hive source tableis_debug00|1Whether to enable debug modeFrom SQLAlchemy access Apache Kylin$ python
>>> import sqlalchemy as sa
>>> kylin_engine = sa.create_engine('kylin://ADMIN:KYLIN@sandbox/learn_kylin?timeout=60&is_debug=1')
>>> results = kylin_engine.execute('SELECT count(*) FROM KYLIN_SALES')
>>> [e for e in results]
[(4953,)]
>>> kylin_engine.table_names()
[u'KYLIN_ACCOUNT',
 u'KYLIN_CAL_DT',
 u'KYLIN_CATEGORY_GROUPINGS',
 u'KYLIN_COUNTRY',
 u'KYLIN_SALES',
 u'KYLIN_STREAMING_TABLE']From Pandas access Apache Kylin$ python
 >>> import sqlalchemy as sa
 >>> import pandas as pd
 >>> kylin_engine = sa.create_engine('kylin://ADMIN:KYLIN@sandbox/learn_kylin?timeout=60&is_debug=1')
 >>> sql = 'select * from kylin_sales limit 10'
 >>> pd.read_sql(sql, kylin_engine)From Superset access Apache KylinNow you can configure the DSN in your application to establish the connection with Apache Kylin.For example, you may install Apache Kylin Python Client Library in your Superset environment and configure connection to Apache Kylin in Supersetthen you may be able to query Apache Kylin one table at a time from Supersetyou may also be able to query detail dataAlternatively, you may also be able to query multiple tables from Apache Kylin by using SQL Lab in Superset.
Package: kyly
Kyly is a simple and basic API wrapper for Bitly.Installing using pypi:pip install kylyExample:First generate an access tokenhere.import kyly

#kyly = kyly.KyLy(token='your token here')

kyly = kyly.KyLy(token='')


#x = kyly.shorten("your link here")
#shorten a link
x = kyly.shorten("https://github.com/centipede000")

#print shortened URL
print(x)Output:>>> https://bit.ly/3gMqqnkThe Bitly API has ratelimits, keep those in mind while using.
Package: kyo
KyoQuestions :tada:What does kyo mean?Kyo is a library focused on the development of bots for theAminoAppsplatform, so we can refer to Kyō as secret.What are kyo's objectives and approach?We start from the fact that there are too many junk code repositories regarding the making of bots thanks to bad code made by users who wanted to misuse the AminoApps api so this time we will moderate in kyo a better way to bring such bots without affecting the platform, besides this we want to imply that we will try to bring a quality library out of the wrong hands by bad intentioned users.In short;kyo wants to give the platform an air of quality.Contact:To keep it simple and to keep people confident with the bot we will not communicate via discord so if you want to contact me you are free to do so via my email:standby@sstandby.com. Please be brief and direct with what you want (I am willing to answer questions and accept improvements to the code).Install kyo:Linux/MacOSpipinstall-UkyoWindowspy-3-mpipinstall-UkyoDocsThe api doc will be done through:https://sstandby.com/kyoLicenseThis work is published underMITLicense.
Package: kyops
KyOps python library[[TOC]]OverviewKyOps is a python library for performing operations on data structures in python. It provides a set of functions to manipulate structures such as adict.InstallationKyOps is a Python3 library that you can install viapippipinstallkyopsUsageTo date, the functionality it offers is the ability to update a nested dictionary from another dictionary. Example:my_dict_to_update={"client":{"zip":"3500","username":"toto","password":"secret","contacts":{"tel":"000000","email":"<default_email>"}}}new_values={"client":{"zip":{"Dep":"35","code":"0000"},"password":"confidenti@lP@ssword","contacts":{"email":"email@gmail.com"}}}fromkyopsimportNdictn_dict=Ndict(my_dict_to_update)n_dict.update(new_values)# Now my_dict.data contains updated datasIt possible to usemerge_nested_dictstatic method:kyops.merge_nested_dict(my_dict_to_update,new_values)print(my_dict_to_update)#Output# {#     "client": {#         "zip": {#             "Dep": "35",#             "code": "0000"#         },#         "username": "toto",#         "password": "confidenti@lP@ssword",#         "contacts": {#             "tel": "000000",#             "email": "email@gmail.com"#         }#     }# }ContributingYou want to contribute to the project? Too cool, you're welcome. Please submit a pull request. Or write all your questions by opening an issue.
Package: kyos
Tools for haploid variant calling with Deep Neural Networks.Kyos was developed by the United States Food
and Drug Administration, Center for Food Safety and Applied Nutrition.Free softwareDocumentation:https://kyos.readthedocs.ioSource Code:https://github.com/CFSAN-Biostatistics/kyosPyPI Distribution:https://pypi.python.org/pypi/kyosFeaturesExtract features from a BAM fileTrain and Test a neural networkCiting KyosTo cite Kyos, please reference the Kyos GitHub repository:https://github.com/CFSAN-Biostatistics/kyosLicenseSee the LICENSE file included in the Kyos distribution.History0.2.0 (2020-05-13)Changes for Tensorflow 2.0.1.0 (2018-12-07)Initial version.
Package: kyoslib_py
kyoslib_pyUsageExample code:fromkyoslib_py.simulationimportSimulationsimulation_set=Simulation()Installationpip install kyoslib_pyDependenciesPython 3.11+DevelopmentThis project is executing CI checks usingGitHub actions.It will runpytestandblack.Invoking development tasksInvokeis used for development tasks.Tasks are stored intasks.pyand are executable using theinv[oke]command line tool.To see the list of tasks, you can type:inv--listFor example, before your commits, you should runinvformatto format your code.DocumentationThe package documentation is generated by MkDocs. The correct version can be installed in the project's virtual environment by:poetryinstallThen the documentation can be built, and a server to view it started by:mkdocsserve
Package: kyoto-reader
kyoto-reader: A processor for KWDLC, KyotoCorpus, and AnnotatedFKCCorpus以下のコーパスから形態素・係り受け関係・述語項構造・共参照関係・固有表現情報を抽出し、Pythonから扱うためのインターフェースを提供します。京都大学ウェブ文書リードコーパス (KWDLC)京都大学テキストコーパス (KyotoCorpus)不満調査データセットタグ付きコーパス (AnnotatedFKCCorpus)RequirementsPython 3.7.2+pyknp0.4.6+KNP5.0+ (optional)JumanDIC(optional)Installation$pipinstallkyoto-readerDocumentshttps://kyoto-reader.readthedocs.io/en/latest/Authors/Contact京都大学 黒橋・褚・村脇研究室 (contactatnlp.ist.i.kyoto-u.ac.jp)Nobuhiro Ueda <uedaatnlp.ist.i.kyoto-u.ac.jp>
Package: kyoushi-simulation
AIT Cyber Range Kyoushi - SimulationThe Kyoushi Simulation package provides a development API and cli utilities for creating
and running state machines. Developed state machines can be executed to automate the simulation
of both attacker and normal user behavior in a Cyber Range. Thus facilitating Cyber Range
exercises, IDS data set generation and other Cyber Range related tasks.Check out theDocumentationof this package.
Package: kyra
kyrais a small logging library written in Python I made for my own
use. This library has been tested with Python 2.7.x and Python 3.6.x.Installation:From source use$ python setup.py installor install from PyPi$ pip install kyraUsage:#!/usr/bin/env python# -*- coding: utf-8 -*-fromkyraimportLoggerlog=Logger()# An absolute path can be passed to Logger() to log to a file.@log.decoratordefsum(a,b):returna+bsum(2,4)log.error('This tests the ERROR logging call.')License:Copyright 2014-2017 Martin Simon

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

   http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.Buy me a coffee?If you feel like buying me a coffee (or a beer?), donations are welcome:WDC : WbcWJzVD8yXt3yLnnkCZtwQo4YgSUdELkj
HBN : F2Zs4igv8r4oJJzh4sh4bGmeqoUxLQHPki
DOGE: DRBkryyau5CMxpBzVmrBAjK6dVdMZSBsuS
Package: ky.scrouter
ScrouterA tool that looks for relations between users.InstallingVia pip:pip install ky.scrouterYou can also update to the latest version:pip install ky.scrouter --upgradeMake sure you have Python 3.8 or above installed!Program launchVia terminal:python -m scrouterAfter that, program will try to find the shortest follower of follower path:Library>>>importscrouter>>>scrouter.route('user1','user2')...LicenseThis project follows MIT license (seeLICENSE).
Package: kyso-jupyterlab
# jupyterlab-kyso## PrerequisitesJupyterLab 0.35 or moreA Kyso account## InstallationCheck your version of Jupyterlab using the following command`bashjupyter-lab--version0.35.2 `### JupyterLab 0.35 or aboveTo install this extension into JupyterLab (requires node 5 or later), do the following:`bash jupyter labextension install @kyso/jupyterlab pip install kyso_jupyterlab jupyter serverextension enable--sys-prefixkyso_jupyterlab `## DevelopmentFor a development install, do the following in the repository directory:`bash yarn yarn run build jupyter labextension install .--no-buildyarn run watch ``bash # and in another shell jupyter lab--watch`## DeploymentTo publish the client side extension:` npm publish `To publish the server side extension:` python3 setup.py sdist twine upload dist/* `
Package: kyss
kyssKyss is a YAML-inspired configuration language that keeps it simple.This repository includes a parser, an API to define schemas for more advanced usage, and a commandline tool that converts kyss-format files to Python syntax or JSON.You don't have to be universal to be my choiceYou don't have to support cycles to rule my worldAin't no particular JSON I'm compatible withI just want your config files and your:kiss:Kyss:kiss:(With apologies to Prince)Table of ContentsInstallationLicenseInstallationpip install kyssLicensekyssis distributed under the terms of theMITlicense.
Package: kysy
KysyAsk or know (Finnish: kysy tai tiedä).Relating answers to files and folders (Finnish: Vastaukset tiedostoihin ja kansioihin).Prototyping names and concepts:ask or know (kysy tai tiedä)ellipse (ellipsi)file (tiedosto)folder (kansio)License: MIT|Country of origin: Switzerland|Export control classification number(ECCN): EAR99Third party dependencies are documented in the folderthird-party.DocumentationUser and developerdocumentation of kysy.Bug TrackerAny feature requests or bug reports shall go to thetodos of kysy.Primary Source repositoryThe main source ofkysyis on a mountain in central Switzerland.
We use distributed version control (git).
There is no central hub.
Every clone can become a new source for the benefit of all.
The preferred public clones ofkysyare:on codeberg- a democratic community-driven, non-profit software development platform operated by Codeberg e.V.at sourcehut- a collection of tools useful for software development.ContributionsPlease do not submit "pull requests" (I found no way to disable that "feature" on GitHub).
If you like to share small changes under the repositories license please kindly do so by sending a patchset.
You can either send such a patchset per email usinggit send-emailor
if you are a sourcehut user by selecting "Prepare a patchset" on the summary page of your fork atsourcehut.StatusExperimental.Note: The default branch isdefault.
Package: kytchen
KytchenThis is a simple Python utility for handling recipes and meal plans. These are the capabilities of the package in terms of recipes:Design recipes modularly, referencing other recipes and a common collection of ingredients that you can keep in a CSV file.Keep track of the caloric content of every recipe with the information that you provide on the energetic content of the ingredients that you use.Scale your recipes for different serving sizes.Help you estimate cooking times.Design your recipes interactively in Python and save them as JSON files for future use.In terms of meal plans, this is what Kytchen can achieve:Help you efficiently organise and plan your cooking.Keep track of your average daily caloric intake.Generate a shopping list for every meal plan.InstallationThis package is on PyPi askytchen, so you can install it withpip3 install kytchen.How to useThere is an in-depth tutorial in thedoc/directory of the project's repository. You can also use Python'shelpfunction.What's next?This is still an alpha version — there's plenty of things yet to be done! Among them, I am planning to support exporting recipes to several formats (PDF, LaTeX, HTML, etc.), but I have yet to decide what the best way of doing that is. Keep in mind that I only work on this project every now and then, so the development process is likely going to beveryslow.Nevertheless, I do use this package to handle my own recipes, so I should be quick to fix any bugs!If you find any bugs yourself or you have any suggestions on how to improve Kytchen, please,get in touch!
Package: kytea
KyTea wrapper for pythonMykytea-python is a python wrapper module for KyTea, a general text analysis toolkit.
KyTea is developed by KyTea Development Team.Detailed information of KyTea can be found athttp://www.phontron.com/kyteaInstall DependenciesYou need to install KyTea before build.To install Mykytea-python, runpip install kyteaTo build Mykytea-python, run (if you don't want to usepip)makeIf you want to install, runsudomakeinstallIf you fail to make, please try to install SWIG and runswig-c++-python-I/usr/local/includemykytea.iOr if you still fail on Max OS X, run with some variables$ARCHFLAGS="-arch x86_64"CC=gccCXX=g++makeIf you compiled kytea with clang, you need ARCHFLAGS only.Or, you can use brew to install kytea.brewinstallkyteaKYTEA_DIR=$(brew--prefix)makeallHow to use it?Here is the example code to use Mykytea-python.importMykyteadefshowTags(t):forwordint:out=word.surface+"\t"fort1inword.tag:fort2int1:fort3int2:out=out+"/"+str(t3)out+="\t"out+="\t"print(out)deflist_tags(t):defconvert(t2):return(t2[0],type(t2[1]))return[(word.surface,[[convert(t2)fort2int1]fort1inword.tag])forwordint]# Pass arguments for KyTea as the following:opt="-model /usr/local/share/kytea/model.bin"mk=Mykytea.Mykytea(opt)s="今日はいい天気です。"# Fetch segmented wordsforwordinmk.getWS(s):print(word)# Show analysis resultsprint(mk.getTagsToString(s))# Fetch first best tagt=mk.getTags(s)showTags(t)# Show all tagstt=mk.getAllTags(s)showTags(tt)LicenseMIT License