Saravanan666/pypi-org huggingface dataset:
Package: kairospay
kairospayPayments library for Monnify, BinancePay and NowPaymentsInstallationpipinstallkairospayUsageTODOContributingInterested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.Licensekairospaywas created by Solomon Olatunji. It is licensed under the terms of the MIT license.Creditskairospaywas created withSolomon Olatunji.
Package: kaisia
Welcome to Kaisiaeasy way to compare GBQ tables schemas right in your terminalUsagebash$ pip install kaisia
...
bash$ kaisia
usage: kaisia [-h] [-V] [-t1 TABLE1] [-t2 TABLE2] [-c CREDENTIALS]

options:
  -h, --help            show this help message and exit
  -V, --version         show program's version number and exit
  -t1 TABLE1, --table1 TABLE1
                        Table1 full GBQ id
  -t2 TABLE2, --table2 TABLE2
                        Table2 full GBQ id
  -c CREDENTIALS, --credentials CREDENTIALS
                        GCP Service Account key
Package: kaiso
A graph based queryable object persistance framework built on top of Neo4j.Build statusExampleIn addition to objects, Kaiso also stores the class information in the graph.
This allows us to use cypher to query instance information, but also to answer
questions about our types.Let’s define some basic classesfromkaiso.attributesimportInteger,Outgoing,String,Uuidfromkaiso.typesimportEntity,Relationship# define a simple type hierarchyclassKnows(Relationship):passclassAnimal(Entity):id=Uuid(unique=True)name=String()knows=Outgoing(Knows)classCarnivore(Animal):passclassHerbivore(Animal):passclassPenguin(Herbivore):favourite_ice_cream=String()classLion(Carnivore):n_siblings=Integer()As with any orm, we can make some instances and persist them in our graphfromkaiso.persistenceimportManagermanager=Manager("http://localhost:7474/db/data/")# create some instancesfred=Penguin(name="Fred")tom=Lion(name="Tom")relation=Knows(fred,tom)manager.save(fred)manager.save(tom)manager.save(relation)Using the Neo4j web interface to explore our graph, we find Tom and Fred:However, in addition, we can also see the type information in the graph:We can make use of the type information in our queries, e.g. to find all
herbivores who know a carnivoreMATCH(Herbivore:PersistableType{id:"Herbivore"}),(Carnivore:PersistableType{id:"Carnivore"}),Carnivore<-[:ISA*]-()<-[:INSTANCEOF]-(carnivore),Herbivore<-[:ISA*]-()<-[:INSTANCEOF]-(herbivore),(herbivore)-[:KNOWS]->(carnivore)RETURN"The herbivore",herbivore.name,"knows the carnivore",carnivore.name;==> +---------------------------------------------------------------------+
==> | "The herbivore" | "Fred"      | "knows the carnivore" | "Tom"       |
==> +---------------------------------------------------------------------+
Package: kait
Kait (Kubernetes AI Tool)kaitis an AI assisted kubernetes debugging tool which automatically troubleshoots, diagnoses, and fixes issues related to kubernetes.kaituses autonomous AI agents built using Microsoft'sAutoGenInstallation and setupYou can installkaitdirectly using pip:pipinstallkaitkaitrequires an OpenAI API key which is read via the environment variable KAIT_OPENAI_KEY. You can provide a list of models to use andkaitwill use the available model. It is recommended to use models with the capabilities of gpt-4. Larger contexts work better too e.g. 'gpt-4-1106-preview'. Your environment variable needs to point to a list of models in the following format:[
    {
        "model": "gpt-4",
        "api_key": "YOUR_OPENAI_API_KEY"
    }
]Usagekaitrequires kubectl to be installed and authenticated against the cluster you want to use.To runkaitsimply run:kaitdebug<DESCRIPTIONOFTHEISSUETODEBUG>For a full list of options, run:kaitdebug--helpExamplesA number ofexamples/are provided so you can see howkaitperforms.
Package: kaitaistruct
Kaitai Struct: runtime library for PythonThis library implements Kaitai Struct API for Python.Kaitai Structis a declarative language used for
describe various binary data structures, laid out in files or in memory:
i.e. binary file formats, network stream packet formats, etc.It is similar toPython's Construct 2.10but it is language-agnostic. The format description is done in YAML-based .ksy
format, which then can be compiled into a wide range of target languages.Further reading:About Kaitai StructAbout API implemented in this libraryPython-specific notesin KS
documentation discuss installation and usage of this runtime
Package: kaiten
KaitenPython Kaiten API client for convenient work with itAs this is an open-source project that is community maintained, do not be surprised if some bugs or features are not implemented quickly enoughQuickstartJust import client, authorize with a server and token.
After that you can get essences you need from the API.import kaiten
client = kaiten.KaitenClient(server =, token = )Get single resourceCardcard = client.get_card(card_id)Spacespace = client.get_space(space_id)Boardboard = client.get_board(board_id)Current usercurrent_user = client.get_current_user()Propertyproperty = client.get_property(property_id)Get list of resourceUse option: ids_only = True, if you need only id's to be represented in the list (list of Resource will be the default behavior)For example:spaces = client.list_of().spaces(ids_only=True) # will return list of space idsList of spacesspaces = client.list_of().spaces()List of usersusers = client.list_of().users()List of tagstags = client.list_of().tags()List of propertiesproperties = client.list_of().properties()
Package: kaiterra-async-client
Python 3 client for retrieving readings from your Laser Egg or Sensedge using theKaiterra REST API.To use it, you’ll first need to create an account at theKaiterra Dashboard, then create an API key under Settings -> Profile -> Developer.Getting StartedInstall the library using pip:pipinstallkaiterra-async-clientExampleHere’s some code to retrieve readings from a couple test devices, one Laser Egg and one Sensedge:importaiohttpfromkaiterra_async_clientimportKaiterraAPIClientasyncwithaiohttp.ClientSession()assession:client=KaiterraAPIClient(session,api_key='YOUR_API_KEY_HERE')r=awaitclient.get_latest_sensor_readings(['/devices/00000000-0001-0001-0000-00007e57c0de/top','/devices/00000000-0031-0001-0000-00007e57c0de/top',])print(r)DevelopmentSource code, issues, and pull requests are managed usingGithub.
Package: kaitorch
KaiTorchKaiTorch is a  deep learning library that dynamically builds a neural network as adecentralized acyclic graph(DAG) ofScalarvalues and implements backprop using reverse-mode autodiff. Heavily over-commented, highly impractical, but hopefully educational.It implements aKeras-like APIthat allows you to build models using aSequentialclass with Dense and Dropout layers, with implementations of several commonly used weight initializers, activation functions, optimizers, and loss functions.This project was inspired by and is an extension of Andrej Karpathy'smicrograd:)InstallationpipinstallkaitorchTutorial NotebooksFunctions and GradientsJupyter Notebook // Google Colabkeywords:functions, derivatives, gradientsFunctions as a Feed Forward Neural NetJupyter Notebook // Google Colabkeywords:directed acyclic graph, operator overloading, magic methods, recursionReverse-mode Autodiff and BackpropogationJupyter Notebook // Google Colabkeywords:chain rule, reverse-mode autodiff, topological sort, backpropActivation FunctionsJupyter Notebook // Google Colabkeywords:sigmoid, tanh, ReLU, LeakyReLU, ELU, swishMulti-layer Perceptron and Weight InitializationJupyter Notebook // Google Colabkeywords:dense layer, multi-layer perceptron, weight initialization, sequential classLoss FunctionsJupyter Notebook // Google Colabkeywords:mean squared error, binary crossentropy, categorical crossentropyGradient Descent and Optimizers(*personal favorite)Jupyter Notebook // Google Colabkeywords: gradient descent, learning rate, momentum, adagrad, rmsprop, adamInverted DropoutJupyter Notebook // Google Colabkeywords:dropout layer, inverted dropout, regularizationExample NotebooksRegressionJupyter Notebook // Google ColabBinary ClassificationJupyter Notebook // Google ColabMulti-class ClassificationJupyter Notebook // Google ColabKeras-esque APIBuilding a Neural Netfromkaitorch.modelsimportSequentialfromkaitorch.layersimportDense,Dropoutfromkaitorch.lossesimportCategoricalCrossentropyfromkaitorch.optimizersimportAdamfromkaitorch.activationsimportLeakyReLUfromkaitorch.initializersimportLecunNormalmodel=Sequential()model.add(Dense(12,activation='sigmoid',initializer='he_normal'))model.add(Dropout(0.25))model.add(Dense(12,activation=LeakyReLU(alpha=0.01),initializer=LecunNormal()))model.add(Dense(3,activation='softmax'))model.compile(optimizer=Adam(lr=0.025),loss=CategoricalCrossentropy())Training a Neural Nethistory=model.fit(X_train,y_train,epochs=32)y_pred=model.predict(X_test)Tracing/Visualizationmodel.plot_model(filename='trace')
Package: kaiyo
Welcome to Commander clickTo generate build and dest filespython3 setup.py sdist bdist_wheelTo use on localpip3 install -e .Commands1 kaiyo login
2 kaiyo create --workspace=“”
3 kaiyo build --servicename ="bifrost" --repository = “”

xyz-bifrost
userdid-servicename

kaiyo list builds -servicename=""


4 kaiyo deploy --servicename="" --values="file.json" --version="" --worskpace=""

kaiyo logout

kaiyo update -—service=“”

kaiyo status --workspace= “”
kaiyo status --service=“”

kaiyo delete --service=“”
kaiyo delete --workspace=“”

kaiyo show --workspace=“”
kaiyo show --service=“”
kaiyo show bill 

kaiyo list builds --repository = “”
kaiyo list workspaces
kaiyo list services
kaiyo list services —worksapce = “”

kaiyo logs --service=“”
Package: kaizen
kaizenA python client and cli to manage your projects on AgileZen Kanban
style.InstallationIf you want to addkaizento your python project:pip install kaizenoreasy_install kaizenTestingTo test everything is in order you can run the following after
downloading the sources:python setup.py nosetestsReferenceshttps://agilezen.comhttp://dev.agilezen.com/
Package: kaizen-mapping
KaizenA Library build with two propose, tomap matchroad elements either withprobe trace or road elements from different
sourceand help, tackle the problem ofroads and building intersecting or overlapping, which are results of
inaccurate digitizing, snapping, or resource mismatch.This Library, presents, my view on tackling the aforementioned problem, caused during map making, addressed
using obstacle avoidance and map matchingMapMatchConflict ResolverICTInstallationpip install kaizen-mappingRequirementsRtree -installationGeopandas -installationRasterio -installationGDAL -installationFiona -installationShapely -installationThe library usesRtreewhich has a dependency onlibspatialindex,
It is recommend to resolve the dependency throughcondaLibSpatialIndex For Linux:$ sudo apt-get update -y
$ sudo apt-get install -y libspatialindex-devLibSpatialIndex For Windows:Experience is pretty slim, for Windows Installation, I recommend using conda, for trouble free installation.MapMatchExamplesMap Matching Road Element with Line StringMap Matching Road Element with List of PointConflict ResolverExamplesSolving Conflict Between Building and Road without additional ReferenceComplex Solving Conflict Between Building and Road without additional ReferenceSolving Conflict Between Building and Road with matching the conflict with neighbouring data and finding
associated reference pointsICTExampleSpatial ICTReferencesFast Map MatchingST-Map MatchingGame ProgrammingRobot Navigation
Package: kakaimagededup
imagededup is a python package that provides functionality to find duplicates in a collection of images using a variety
of algorithms. Additionally, an evaluation and experimentation framework, is also provided. Following details the
functionality provided by the package:Finding duplicates in a directory using one of the following algorithms:Convolutional Neural NetworkPerceptual hashingDifference hashingWavelet hashingAverage hashingGeneration of features for images using one of the above stated algorithms.Framework to evaluate effectiveness of deduplication given a ground truth mapping.Plotting duplicates found for a given image file.Read the documentation at:https://idealo.github.io/imagededup/imagededup is compatible with Python 3.8+ and runs on Linux, MacOS X and Windows.
It is distributed under the Apache 2.0 license.
Package: kakakucom
kakaku_robotKakaku lobot is a scraping library forhttps://kakaku.com/InstallationUse the package managerpipto install foobar.pipinstallkakakucomUsagefromkakaku_robot.site.rankingimportRankingresult=Ranking().ranking.all_category_ranking(pandas=True)result.to_csv("kakau_rank.csv")kakakucom-fall_category_ranking-d[Youroutputfolder]ContributingPull 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.Spark installLicenseMIT
Package: kakao-json
카카오톡 챗봇 빌더 도우미Python언어 전용소개Python 언어로 카카오 챗봇 서버를 만들 때 좀 더 쉽게 JSON 메시지 응답을 만들 수 있게 도와줍니다.SimpleText, SimpleImage, ListCard, Carousel, BasicCard, CommerceCard, ItemCard 등의챗봇 JSON 데이터를 쉽게 만들 수 있도록 도와줍니다.설치pipinstallkakao-json사용법ListCard 예제fromkakao_jsonimportButton,Kakao,ListItemk=Kakao()k.add_qr("오늘","카톡 발화문1")k.add_qr("어제")# label becomes also messageTextlist_card=k.init_list_card().set_header("리스트 카드 제목")list_card.add_button(Button("그냥 텍스트 버튼","message"))list_card.add_button(k.init_button("link label").set_link("https://google.com"))list_card.add_button(k.init_button("share label").set_action_share().set_msg("카톡에 보이는 메시지"))list_card.add_button(k.init_button("call label").set_number("010-1234-5678"))list_card.add_item(ListItem("title").set_desc("description").set_link("https://naver.com"))k.add_output(list_card)print(k.to_json()){"template":{"outputs":[{"listCard":{"buttons":[{"label":"그냥 텍스트 버튼","action":"message"},{"label":"link label","action":"webLink","webLinkUrl":"https://google.com"},{"label":"share label","action":"share","messageText":"카톡에 보이는 메시지"},{"label":"call label","action":"phone","phoneNumber":"010-1234-5678"}],"header":{"title":"리스트 카드 제목!"},"items":[{"title":"title","description":"description","link":{"web":"https://naver.com"}}]}}],"quickReplies":[{"action":"message","label":"오늘","messageText":"오늘 공지 보여줘"},{"action":"message","label":"어제","messageText":"어제 공지 보여줘"}]},"version":"2.0"}
Package: kakao-map-pkg-tyim0
2021.08.25 - tyim0프로그램 설명서개발환경Python 3.9Chrome 92.0.4515.159동작 방법/kakao_map/main.py 실행 혹은/kakao_map/dist/main/main.exe 실행실행 후 화면에 "Type search keyword : " 문구가 나오면 검색하고자 하는 키워드를 입력프로그램 동작이 끝나면 /data.csv 파일을 열어 데이터 확인
Package: kakaopy
kakaopyInstallationinstall from PyPIpip install kakaopyinstall from cloned repositorygit clone https://github.com/SeoJeongYeop/kakaopy.git
cd kakaopy
pip install .However, this way occur warning 'DEPRECATION'
This way is removed from pip 21.3 versioninstall from GitHub repositorypip install git+https://github.com/SeoJeongYeop/kakaopy.gitUsagefrom kakaopy import kakaopyfromkakaopyimportkakaopyset your REST_API_KEYkakaopy.setHeader('YOUR_REST_API_KEY')make objecte.g. doc, video, image, book, blog, cafedoc1 = kakaopy.doc()(option) setting object option.e.g. size, page, sort, target(only book)doc1.setSort("recency")More information can be found through object.help() function.doc1.help()object.search(query): search query and return search results in the form of json.doc1.search("python")object.save(query, path): save file.json in path. The 'path' is the file name or path to the file.doc1.save(query="web crawling",path="web.json")is same asdoc1.save(query="web crawling",path="web")
Package: kakao.py
kakao.pykakao.py is a very simple kakaotalk LOCO/HTTP API protocol wrapper for python.IntroductionLoco protocol compatible python libraryThis is discord.py style rewritten version of KakaoBot.DO NOT USE IN ABUSING. ABUSING CAN CAUSE PERMANENT SERVICE RESTRICTION.Quick StartimportkakaoclassMyclass(kakao.Client):asyncdefon_ready(self):print("Logged on")asyncdefon_message(self,chat):ifchat.message=="ping":awaitchat.reply("pong!")kakao.check_reg("LoginId","LoginPw")client=Myclass("LoginId","LoginPw")client.run()Quick Start (Bot)importkakaofromkakao.extimportcommandsfromkakao.ext.commandsimportBot@commands.command()asyncdefping(ctx):awaitctx.reply("pong")returnkakao.check_reg("LoginId","LoginPw")bot=Bot("/",LoginId="LoginId",LoginPw="LoginPw")bot.add_command(ping)bot.run()Thanks to (Forked from)ksaidev/KakaoBot (Commit 8df8cf3)LicenseMIT Licence
Package: kakaosb
kakao-skill-template-builderkakao-skill-template-builder특징InstallationExamplekakao i openbuilder skill response template builder ⚒ for python 🐍파이썬에서 카카오 i 오픈빌더의 응답 타입별 JSON 포맷을 생성하는 도구 입니다.특징👌 오픈빌더 도움말의 모든응답 타입별 JSON 포맷을 만들 수 있습니다. 모두 다 테스트 해봤어요! 😊tests/test_builder.py를 참고!⚒SkillResponseBuilder를 이용해서 원하는대로 이것저것 섞인 대답을 만들 수 있습니다!🐍 파이썬의 local 변수를 이용해서 코드가 엄청 짧아요! 고치기 쉽다는 뜻이죠.Installation$pipinstallkakaosbExampleSimpleTextfromkakaosbimportSkillResponseBuilder,SimpleTextsb=SkillResponseBuilder([SimpleText('Hello Kakao!')])res_dict=sb.to_dict()# 사전 형식 변환res_json=sb.to_json(indent=4)# json 형식 변환베이직 카드fromkakaosbimportSkillResponseBuilder,BasicCard,Thumbnail,Profile,Social,MessageButton,WeblinkButtonsb=SkillResponseBuilder()basicCard=BasicCard(thumbnail=Thumbnail('http://k.kakaocdn.net/dn/83BvP/bl20duRC1Q1/lj3JUcmrzC53YIjNDkqbWK/i_6piz1p.jpg'),title='보물상자',description='보물상자 안에는 뭐가 있을까',profile=Profile('보물상자','https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcT4BJ9LU4Ikr_EvZLmijfcjzQKMRCJ2bO3A8SVKNuQ78zu2KOqM'),social=Social(1238,8,780),buttons=[MessageButton('열어보기','짜잔! 우리가 찾던 보물입니다'),WeblinkButton('구경하기','https://e.kakao.com/t/hello-ryan')])sb.append(basicCard)res_dict=sb.to_dict()# 사전 형식 변환res_json=sb.to_json(indent=4)# json 형식 변환mixfromkakaosbimportSkillResponseBuilder,SimpleText,SimpleImagesb=SkillResponseBuilder()sb.append(SimpleText('Hello Kakao!'))sb.append(SimpleImage('http://k.kakaocdn.net/dn/83BvP/bl20duRC1Q1/lj3JUcmrzC53YIjNDkqbWK/i_6piz1p.jpg','보물상자입니다'))sb.append(SimpleText('Bye Bye 🧤'))res_dict=sb.to_dict()# 사전 형식 변환res_json=sb.to_json(indent=4)# json 형식 변환
Package: kakaotalk-msg-preprocessor
kakaotalk_msg_preprocessor카카오톡 채팅방에서대화 내보내기를 통해 생성한 파일에 있는 메시지를 전처리해주는 라이브러리입니다.주요 기능은 다음과 같습니다.parse: 카카오톡에서 export한 txt파일을 여러 메시지 정보(dict)를 담고있는 list로 파싱합니다.각 메시지 정보는 메시지를 보낸 시간(datetime), 메시지를 보낸 사람(user_name), 메시지 본문(text)를 key로 가지는 dictionary입니다.[{'datetime': datetime.datetime(2020, 6, 28, 1, 1), 'user_name': '김한길', 'text': '사진'}, {'datetime': datetime.datetime(2020, 8, 11, 12, 3), 'user_name': '김한길', 'text': 'https://www.youtube.com'}]url_msg_extract: 파싱한 데이터에서 URL이 포함되어 있는 메시지만 추출하여, URL과 메시지 정보를 담고 있는 list로 반환해줍니다.[{'datetime': datetime.datetime(2020, 8, 11, 12, 3), 'user_name': '김한길', 'url': 'https://www.youtube.com'}]GuideInstallpipinstallkakaotalk_msg_tokenizerUsageimportkakaotalk_msg_preprocessor카카오톡 메시지 파싱하기# get the device type and language of kakaotalk_export_filefile_type=kakaotalk_msg_preprocessor.check_export_file_type(file_path)print(file_type)#  Parsing the text from a kaotalk_export_filemessages=kakaotalk_msg_preprocessor.parse(file_type,file_path)print(messages)예시 결과window_ko
[{'datetime': datetime.datetime(2020, 6, 28, 1, 1), 'user_name': '김한길', 'text': '사진'}, {'datetime': datetime.datetime(2020, 6, 28, 1, 3), 'user_name': '김한길', 'text': '공부하기'}, 
{'datetime': datetime.datetime(2020, 8, 11, 2, 41), 'user_name': '김한길', 'text': '화 19:30-22:30\n\n\n자유석권(선착순)\n오후 6시 녹화장 앞 번호표대로 줄서기, 6시 50분부터 입장\n- 번호표 배부 : 녹화일 9:00 ~ 18:20까지 (입장순서가 부여된 방청권 선착순 배부)\n- 입장시간: 18시까지 녹화장 앞에서 번호표대로 줄서기(번호표 지참), 18:50부터 입장\n- 번호표 배부는 오후 6시 20분에 마감. 마감 이후에 오신 분들은 별도로 통제합니다'}, 
{'datetime': datetime.datetime(2020, 8, 11, 12, 3), 'user_name': '김한길', 'text': 'https://www.youtube.com'}]카카오톡 메시지에서 URL만 추출하기url_messages=kakaotalk_msg_preprocessor.url_msg_extract(file_type,messages)print(url_messages)예시 결과[{'datetime': datetime.datetime(2020, 8, 11, 12, 3), 'user_name': '김한길', 'url': 'https://www.youtube.com'}]지원 export 파일 종류카카오톡은 카카오톡 앱 실행 환경에 따라 상이한 형식의 txt파일을 export합니다.현재 정상작동이 확인된 환경은 다음과 같습니다.윈도우(OS언어: 한글)안드로이드(OS언어: 한글)안드로이드(OS언어: 영어)
Package: kakaotalkparse
kakaotalkparseParse and Statistics from txt file exported from KakaoTalk.ScreenshotCheck outLive Preview!Installpip install kakaotalkparseUsagehere are how to usefromkakaotalkparseimportKakaoTalkParseif__name__=='__main__':"""Example Code"""ktparse=KakaoTalkParse()filename="KakaoTalk_20210108_0846_18_555_group.txt"# filename = "Talk_2021.1.10 08_15-1.txt"ktparse.open(filename)data=ktparse.parse()# print(data)ktparse.setSrcTZ("Asia/Saigon")ktparse.setReportTz("Asia/Seoul")ktparse.setReportRange(startTime='2020-1-1',endTime='2020-12-31')stats=ktparse.stats(data)report=ktparse.conv2chartJS(stats)withopen('report.json','w',encoding='utf-8')asfp:json.dump(report,fp,ensure_ascii=False,indent=0)print(json.dumps(report))Resultssample outputApeach:{'totalCount':3686,'characters':62119,'urls':141,'photos':172,'files':5,'videos':5,'emoticons':108,'deletes':0,'activeTime':{'00':12,'01':5,'02':1,'03':0,'04':5,'05':14,'06':153,'07':269,'08':247,'09':284,'10':247,'11':174,'12':397,'13':331,'14':328,'15':296,'16':219,'17':162,'18':136,'19':102,'20':65,'21':94,'22':112,'23':33},'activeWeek':{'0':668,'1':756,'2':697,'3':679,'4':529,'5':243,'6':114},'activeMonth':{'01':197,'02':331,'03':448,'04':246,'05':387,'06':245,'07':130,'08':189,'09':314,'10':496,'11':290,'12':413}}Frodo:{'totalCount':1981,'characters':32649,'urls':5,'photos':18,'files':0,'videos':0,'emoticons':18,'deletes':8,'activeTime':{'00':6,'01':0,'02':0,'03':0,'04':0,'05':0,'06':270,'07':172,'08':127,'09':191,'10':122,'11':81,'12':193,'13':203,'14':128,'15':204,'16':78,'17':17,'18':7,'19':18,'20':36,'21':32,'22':57,'23':39},'activeWeek':{'0':353,'1':320,'2':358,'3':488,'4':360,'5':65,'6':37},'activeMonth':{'01':69,'02':124,'03':300,'04':53,'05':460,'06':80,'07':121,'08':163,'09':111,'10':162,'11':208,'12':130}}
Package: kakaotrans
KakaotransUnofficial python API forKakao translate service.Installation$pipinstallkakaotransUsageBasic Usage>>>fromkakaotransimportTranslator>>>translator=Translator()>>>translator.translate("Try your best rather than be the best.")# '최고가 되기보다는 최선을 다하라.'>>>translator.translate("최고가 되기보다는 최선을 다하라.",src='kr',tgt='de')# 'Tun Sie Ihr Bestes, anstatt das Beste zu sein.'Separate the query into multiple sentencesTranslation query might include multiple sentences. If you set separate_lines=True, translator will automatically separate the query and return the list of multiple sentences.fromkakaotransimportTranslatortranslator=Translator()translator.translate("""지난해 3월 오픈한 카카오톡 주문하기는 현재까지 약 250만명의 회원을 확보했다.전 국민에게 친숙한 카카오톡 UI를 활용하기 때문에 별도의 앱을 설치할 필요 없이 카카오톡 내에서 모든 과정이 이뤄지는 것이 특징이다.""",src='kr',tgt='en',separate_lines=True)# ['The ordering of KakaoTalk, which opened in March last year, has secured about 2.5 million members to date.', 'Because it uses KakaoTalk UI, which is familiar to the whole nation, it is characterized by all the processes in KakaoTalk without having to install a separate app.']Save translated result as file>>>fromkakaotransimportTranslator>>>translator=Translator()>>>translator.translate("Try your best rather than be the best.",save_as_file=True,file_name='result.txt')Referencegoogletranspypapago