Saravanan666/pypi-org huggingface dataset:
Package: krome
KROME 1.3.1Python package created as a Research Associate at UAE University. The package contains modules that calculate magnetic activity indices from spectroscopic data of M dwarfs.It accepts file types of .s taken from the spectropolarimeterNARVALand ADP.fits/s1d_A.fits from the spectrographsHARPS/HARPS-N.UsageFollow theTutorialwhich explains each activity index method in detail.Code DependenciesnumpymatplotlibpandastqdmastropyPyAstronomyspecutilsuncertaintiesCitingIf you use this software in your research, please cite the article "A Study of the Magnetic Activity and Variability of GJ 436" in the MNRAS journal using the following BibTex entry:@ARTICLE{2022MNRAS.tmp.2704K,
       author = {{Kumar}, M. and {Fares}, R.},
        title = "{A study of the magnetic activity and variability of GJ 436}",
      journal = {\mnras},
     keywords = {Stars: Individual: GJ 436, Stars: activity, Stars: chromospheres, Planetary systems, Astrophysics - Solar and Stellar Astrophysics},
         year = 2022,
        month = oct,
          doi = {10.1093/mnras/stac2766},
archivePrefix = {arXiv},
       eprint = {2209.11258},
 primaryClass = {astro-ph.SR},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2022MNRAS.tmp.2704K},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
Package: kronecker
KroneckerA small library that provides a convenient syntax for creating boolean tensors / sparse matrices.Examplesi,j=kronecker.indices(4,4)arr=(i>=j*2-1).to_numpy()np.array_equal(arr,np.array([[1,0,0,0],[1,1,0,0],[1,1,0,0],[1,1,1,0]]).astype(bool))>Truei,j,k=kronecker.indices(2,2,3)arr=(i>=j+k-1).to_numpy()np.array_equal(arr,np.array([[[1,1,0],[1,0,0]],[[1,1,1],[1,1,0]]]).astype(bool))>True# would run out of memory if created as a numpy arrayi,j=kronecker.indices(1_000_000,1_000_000)x=(i*5==j).to_sparse()assertx.sum()==200000LimitationsWhen creating sparse matrices linear expressions in the indices are simplified and evaluated once per row, giving a complexity of O(n_rows * n_True_per_row). For non-linear expressions (including ones that contain integer division//) a slower, O(n_rows * n_cols), path is used. This is mostly useless, creating a numpy array and converting is much faster (but uses more memory).Only the operators {+,-,*,/,//,**} are supported.Multiple comparisons (i < j < 2 * i) are not supported.
Package: krong
KrongKRONG: KoRean language processing toolkit based On Non-neural methods for General purposeTasksKrong(task="tagging"): 형태소 분석Krong(task="tokenization"): 토큰화Krong(task="augmentation"): 어그먼테이션Krong(task="hangulize"): 한글라이즈Krong(task="romanize"): 로마나이즈Krong(task="josa"): 조사처리Krong(task="summary"): 문서요약Krong(task="keyword"): 키워드 추출Krong(task="hanja2hangul"): 한자 → 한글 변환Krong(task="is_hangul"): 한글 여부 판별Krong(task="is_hanja"): 한자 여부 판별Krong(task="split_hanja"): 한자,한글 분리기Krong(task="jamo"): 자모 분리/조합Krong(task="has_jongsung"): 종성 존재판별Krong(task="extract"): 각종 정규식 추출기Krong(task="spacing"): 띄어쓰기 교정기Krong(task="grammar"): 맞춤법 검사기Krong(task="sent_tokenization"): 문장 토큰화Krong(task="pronunciation"): 발음 표기
Package: krono
KronoKrono é um aplicativo de linha de comando para rastrear tempo e gerar relatórios em formato de fatura.InstalaçãoUtilize o package managerpippara instalar o krono.pipinstallkronoUtilizaçãoPara iniciar a contagem de horas é preciso rodar o comandotrackinformado o nome da atividade em que se está trabalhandokronotrack"Nome da atividade"Para gerar uma fatura, é preciso utilizar o comandoreportinformando a data de início do relatório
no formato%Y-%m-%dkronoreport-s"2021-11-01"Mais informações estão disponíveis ao rodar o comandokrono--helpUtilizando um arquivo de configuraçãoA fim de facilitar a utilização, é possível criar um arquivo de configuração na pasta raiz do projeto
chamadorastreador.json, com as variáveis de valor hora (hourly_rate), solicitante (requested_from) e
solicitado (bill_to){"hourly_rate":1000,"requested_from":"rafael.matsumoto@catolicasc.org.br","bill_to":"catolicasc@catolicasc.org.br"}LicençaMIT
Package: kronos-backtester
kronos_backtesterInstallation$ pip3 install kronos-backtesterRequirementsPython>= 3.7.1Pandas>= 1.3.0YFinanceQuick Startfromkronos_backtesterimportBacktester# Example strategy to be backtesteddefmomentumStrategy(df,short_window=50,long_window=200,entry_threshold=0.02,exit_threshold=0.01):# Strategy code here# Inputs: Pandas Dataframe of price data, any relevant parameters for the strategy# The Dataframe will have columns 'Close', 'Open', 'High', 'Low', and 'Volume'# Output: Pandas Series of signals which are integers -1, 0, 1# -1 : Sell, 0 : Hold, 1 : Buy# Index of Series should be dates# The wrapper should only take in a DataFrame and output a Series of signals# This is essentially one version of the strategy with a specific set of parameters.deftestWrapper(df):returnmomentumStrategy(df,long_window=100)bt=Backtester(testWrapper)# This backtests on a particular ticker with given start and end datebt.testTickerReport('AAPL','2010-01-01','2020-01-01')# You can also backtest on a custom DataFrame of price databt.testCustomReport(customDF)Backtesting report output (dictionary)Start 2010-01-01
End 2020-01-01
Duration 2516
Exposure Time 470.5
Net Worth [1000000, ... ,8166774.230371475]
Equity Final 8166774.230371475
Equity Peak 8166774.230371475
Return 7.166774230371475
Buy and Hold Return 10.038871419853216
Max Drawdown -0.1029208755830342
Avg Drawdown -0.09627259509420738
Max Drawdown Duration 19
Avg Drawdown Duration 8.857142857142858
# Trades 4
Win Rate 1.0
Best Trade 0.984095270845883
Worst Trade 0.48189821881601236
Max Trade Duration 669
Avg Trade Duration 470.5
Sharpe Ratio 33.99413578326285
Sortino Ratio nan
Calmar Ratio 69.11692296006356
Package: kronos-daterange
KronosKronos makes dateranges easier.GitHub repo:https://github.com/nat5142/kronos.gitDocumentation:https://nat5142-kronos.readthedocs.io/Free software: BSDQuickstartInstall from pip:pipinstallkronos-daterangeImport & basic init:fromkronosimportKronoskronos=Kronos(start_date='2022-01-01',end_date='2022-01-31')Feature Demo# importfromkronosimportKronos# init --> defaults to range of <yesterday, today> unless otherwise specified by `KRONOS_DATERANGE` environment variablekronos=Kronos()# manually set dateskronos=Kronos(start_date='2022-10-17',end_date='2022-10-23')# set timezonekronos=Kronos(timezone='America/New_York')# specify date formatkronos=Kronos(start_date='10/20/2022',end_date='10/31/2022',date_format='%m/%d/%Y')# access start, end dateskronos=Kronos()kronos.start_date# 2022-10-19kronos.end_date# 2022-10-20# `date_format` carries over to properties:kronos=Kronos(date_format='%m/%d/%Y')kronos.start_date# 10/19/2022kronos.end_date# 10/20/2022# format start and end date with new formatkronos.format_start('%Y-%m-%d%H:%M:%S')# 2022-10-20 00:00:00kronos.format_end('%Y-%m-%d%H:%M:%S')# 2022-10-21 23:59:59# get the current date in specified timezonekronos=Kronos('America/Los_Angeles')kronos.current_date# 2022-10-20kronos=Kronos('America/Los_Angeles',date_format='%m/%d/%Y')kronos.current_date# 10/20/2022# overwrite your object's timezone without altering the timekronos=Kronos(timezone='UTC')kronos.change_timezone(tz='America/New_York')# relative shift forward/backkronos=Kronos()kronos.shift_range(weeks=-1)# pipes kwargs into timedelta# Kronos(start_date='2022-10-12', end_date='2022-10-13', ... )# pass start and end dates as datetime objectsstart_dt=datetime(2023,3,8,12,0,0)end_dt=datetime(2023,3,9,12,0,0)kronos=Kronos(start_dt,end_dt)kronos.format_start('%Y-%m-%d%H:%M:%S')# 2023-03-08 12:00:00kronos.format_end('%Y-%m-%d%H:%M:%S')# 2023-03-09 12:00:00# bisect a daterangekronos=Kronos('2023-03-01','2023-03-09')k1,k2=kronos.splice('2023-03-04')print(k1)# Kronos(start_date='2023-03-01', end_date='2023-03-04', ...)print(k2)# Kronos(start_date='2023-03-04', end_date='2023-03-09', ...)Defaults/Environment VariablesKronos is prepared to accept the following environment variables:KRONOS_TIMEZONE, which defaults to UTC if not set. Can often be overridden at method-levels for one-off timezone conversions.KRONOS_FORMAT, the strptime date format string for your dates.KRONOS_DATERANGE(see below)Note that bothKRONOS_TIMEZONEandKRONOS_FORMATcan be set during init astimezone=anddate_format=arguments, respectively.KRONOS_TIMEZONE:Can be any valid timezone name (find them atpytz.all_timezones)KRONOS_DATERANGE:List of accepted values:LATEST: start/end dates of yesterady/todayYESTERDAY_TODAY: same asLATESTLAST_MONTH: previous calendar monthMTD: month-to-dateLAST_{X}_DAYS: relative range where end_date is today, start date is set X days behind.THIS_WEEK__{X}: week-to-date starting on previous day of week specified by X. Valid values for X:SUN, MON, TUES, WED, THURS, FRI, SATCreditsThis package was created withCookiecutterand thefedejaure/cookiecutter-modern-pypackageproject template.
Package: kronos-pipeliner
kronosis a software tool for automating reproducible, auditable and distributable bioinformatics workflow development.
It obviates explicit coding for workflow development to a great extent by compiling a text configuration file into an executable Python scripts.Dependenciesruffus == 2.4.1PyYaml >= 3.11Optional Python LibrariesFor running on a cluster using drmaa, i.e. using-b drmaa, you will need to install:drmaa-python == 0.7.6DocumentationPlease refer to kronosonline documentation.Contactemail:
Jafar Taghiyar <jafar.taghiyar@gmail.com>Please report issues in ourkronos google group.Change log2.3.0:added a mechanism to update the requirements of the implicit merge via GENERAL section.Note:you can switch off the implicit merge and use an explicit merge if you want to specify a particular requirement for only that merge task.previously, multiple identical implicit merge tasks could exist in a workflow. In the new version, they are combined into a single merge task that happens only once.added a switch calledmergethat defaults toTruein therunsubsection of each task. If it is set toFalse, the implicit merging mechanism is switched off for that task and the following warning message is shown when initializing the workflow:UserWarning: Implicit merge is off for task <the_task_name>.
You may have to use an explicit merge task.added support for tags in the interval file,i.e.an optional tag can be added for each chunk in each line of the interval file that will be used as the suffix for the name of the task corresponding to that chunk. The tags should be added to each line using tab as the separation character, e.g.:chunk1     tag1
chunk2     tag2
chunk3
chunk4     tag4bug fixes.2.2.0:each task in the configuration file now has its ownrequirementsentry in therunsubsection which takes precedence over the requirements listed in the GENERAL section. This enables users to have different versions of the same requirements for different tasks.interval file now takes precedence over the synchronization, i.e. if a task has an interval file, then it will not be synchronized with its predecessors.added support for floating point memory requests.made all the merged files to store in a directory calledmerge.username and version are automatically added to the config files when usingmake_configcommand.added a check to make sure that the input of the implicit merge node is always a list.bug fixes.2.1.0:Kronos now uses multithreading instead of multiprocessing.2.0.4:removed the limitation on the number of simultaneous jobs/pipelines.added--no_prefixback to the input options ofruncommand.minor bug fixes.2.0.3:First version released!
Package: kronus
kronusPython program with my own way of representing time as a int numberPrograma en python para representar as datasPrograma en python para representar las fechasExample:Exemplo:Ejemplo:2019/07/10 09:55:00:000000+20190710095500000000+ 2019 07 10 09 55 00 000000-(0)        → a.C                       → 1bitor/ou/o+(1)        → d.C                       → Same bit/Mesmo bit/Mismo bit2019        → year/ano/año              → 5bits07          → month/mes                 → 2bits10          → day/día                   → 2bits55          → minute/minuto             → 2bits00          → second/segundo            → 2bits000000      → microsecond/microsegundo  → 6bitsDonations 🙇🙇‍♀Bitcoinbc1q79vja8jzr27dxaf3ylu7e49ady8zq0jsm5qfk6Monero88Rezd6ZQzaCb1s7K1tRCiCaDzuHrfYsn4q348jJuePpLs84JNsWEghMAZZgzpDPrqD4PBxk7hwMkSdNQ4CLqFHyPVLdX1DWowneroWW2RheTNrq8goAi42Dz5AKUj1qLSaTSSgiH7sHR2qRqojg238EXP3MM3xuUgswriET7UrpkEoYaCkecBhnU49oxM1dZyYoSmm
Package: kross
krossA simple CLI to "multi-arch all the things"What is kross ?kross is a tool to automate the build of Docker images for multiple architectures without any changes required on your codeQuick startInstall via pippip install krossInitialize it (once)kross initUpdate your docker build commandsBeforedocker build -t me/myapp:vX.X.X ...args... path/to/docker/context
docker push me/myapp:vX.X.XAfterkross build -t me/myapp:vX.X.X ...args... path/to/docker/context
kross push me/myapp:vX.X.XWhy kross ?Kross is born from a Raspberry Pi passionnate developer.
Because Raspberry Pi are arm-based and 90% of images on Dockerhub are amd64-based, developers have to duplicate/tweak all Dockerfiles so the image will work on it and avoid the too much popularcannot execute binary file: Exec format error.To know more, read thefull article.How kross is working ?kross is based upon theqemu libraryto build multiple architectures images on a amd64-based host machine.
After all images are built and pushed to a docker registry, amanifest listis pushed too so that users can pull images based on their architectures in a seamless way.Supported architectureskross will try to build images for the following architectures:amd64arm32v6arm32v7arm64v8ppc64les390xi386Run the exampleInstall krosspip install krossCheck your machine configurationkross initRun the kross buildkross build -t kross-world:v0.1.0 https://raw.githubusercontent.com/pcorbel/kross/master/docs/example/DockerfileRun the kross pushkross push kross-world:v0.1.0Check images availability on yourDockerhub accountRun your image anywheredocker run --rm kross-world:v0.1.0Example image availablehereTips and tricksTo know exactly what is happening while kross is workingexport KROSS_VERBOSE=true
Package: krovak05
krovak05Geodetic package for transformation ETRS89 (ETRF2000) coordinates to S-JTSK (Czech national coordinate system)
and heights to Bpv system (Baltic vertical datum After Adjustment).InstallationRun the following to install:pipinstallkrovak05Methodsget_available_diff_tables()-> table_names - List[str]interpolate_dydx(Y,X)-> dy, dx - float,floatinterpolate_undulation(B,L)-> undulation - floatbicubic_dotr(Y,X)-> dy,dx - float, floatetrs_jtsk05(B,L,H)-> Y_jtsk05,X_jtsk05,H_bpv - float, float, floatetrs_jtsk(B,L,H)-> Y_jtsk,X_jtsk,H_bpv - float, float, floatjtsk05_jtsk(Y_jtsk05,X_jtsk05)-> Y_jtsk,X_jtsk - float, floatjtsk_jtsk05(Y_jtsk,X_jtsk)-> Y_jtsk05,X_jtsk05 - float, floatjtsk_etrs(self,Y,X,H)-> B,L,H - float, floatUsageimportkrovak05krovak=krovak05.Transformation()## Undulation of kvasigeoidundulation=krovak.interpolate_undulation(50,15)print(undulation)# --> 44.438## Differences between S-JTSK and S-JTSK/05dy,dx=krovak.interpolate_dydx(750000,1050000)print(dy,dx)# --> 0.072 -0.037## Get list of possible dydx grid datagrids=krovak.get_available_diff_tables()print(grids)# --> ['table_yx_3_v1710', 'table_yx_3_v1202', 'table_yx_3_v1005']## Transform ETRS89 (ETRF2000) coordinates to S-JTSK/05B_etrs_in=50L_etrs_in=15H_etrs_in=100Y_sjtsk05,X_sjtsk05,H_bpv=krovak.etrs_jtsk05(B_etrs_in,L_etrs_in,H_etrs_in)print(Y_sjtsk05,X_sjtsk05,H_bpv)# --> 5703011.866856858 6058147.235673166 55.562## Transform ETRS89 (ETRF2000) coordinates to S-JTSKY_sjtsk,X_sjtsk,H_bpv=krovak.etrs_jtsk(B_etrs_in,L_etrs_in,H_etrs_in)print(Y_sjtsk,X_sjtsk,H_bpv)# --> 703011.8997768582 1058147.294883166 55.562## Reverse transformation S-JTSK coordinate to ETRS89B_etrs_out,L_etrs_out,H_etrs_out=krovak.jtsk_etrs(Y_sjtsk,X_sjtsk,H_bpv)print(B_etrs_out,L_etrs_out,H_etrs_out)# --> 50.00000000579285 15.000000005855975 100.0print("Differences:")print(f"dB ={(B_etrs_in-B_etrs_out)*(math.pi/180)*6378000*1000}mm")print(f"dL ={(B_etrs_in-B_etrs_out)*(math.pi/180)*(6378000*math.cos(B_etrs_in*(math.pi/180)))*1000}mm")print(f"dH ={(H_etrs_in-H_etrs_out)*1000}mm")# --> dB = -0.64 mm# --> dL = -0.41 mm# --> dH = 0.0 mmSet different grid table:krovak=krovak05.Transformation("table_yx_3_v1005")TODOBetter documentationRewrite to more time efficient code - constants, less calculation of goniometric functionsData validationvalidation of data accuracy was performed using of theCUZK transformation serviceRepository
Package: krovetz
Py KrovetzThis is a Python wrapper forKrovetz Stemmer C++ library. It uses Cython to build a wrapper and allow access to the cpp object in python.Usageimportkrovetzks=krovetz.PyKrovetzStemmer()ks.stem('walked')InstallationRequirementsPythonAll the requirements are handled automatic. However, tests have been made on Linux GNU and OSX using Python 3.5-3.6. Notice that using python 3.5 and macos might not work as some compilation of python 3.5 are linked to older versions of OpenSSL. This affects the communication ofpipand PyPI website when retrieving libraries. If you plan to use this combination, make sure that Python is linked to an updated version of OpenSSL.python -c 'import ssl; print(ssl.OPENSSL_VERSION)'Version should be1.*.*C++ compilerThe original code of the stemmer is written inC++. Thus, aC++compiler is neededwhen building yourself. If this is your decision, make sure you have a C++ compiler installed. We have testedgccin Linux system andclangin MacOS. Regardless of this, other combinations and compilers might also work.SetupPyPIPyPI provides a ready-to-go version (wheel) for different systems and Python versions.pip install -i https://test.pypi.org/simple/ krovetzIf you want to force binary version:pip install -i https://test.pypi.org/simple/ --only-binary=krovetz krovetzCurrently, we support distributions for Python 3.5 - 3.7 in Linux and Python 3.6 in macOS >= 10.9.Compiling yourselfIf you prefer to compile your own package, you can do it using the following command.pip3 install -i https://test.pypi.org/simple/ --no-binary=krovetz krovetzUsing your own CythonYou can use your ownCythonto generate the c++ source. Our git repo only includes cython files (.pxd) and not the files generated byCython. Therefore, if you plan to install from here,you need to haveCythoninstalledin order to generateC++files.pip install cythonThen just do:pip install git+https://github.com/ptorrestr/py_krovetz.gitDevelopmentWe are usingpipenvto handle the development environment. This tool is very handy to manage different python versions and configurations.ImportFirst, import the project in your machinegit clone https://github.com/ptorrestr/py_krovetz.gitEnvironment setupYou can install the environment needed just using the following commandpipenv installHave a look on filesPipfileandPipfile.lockin order to check the versions of the dependencies used in our development machine.TestingTest can be run using the environment defined bypipenv.pienv run python setup.py test
Package: krozark-json-include
An extension for JSON to support file inclusionjson-include is an extended way for JSON to support file inclusion, it has two parts:A syntax definition calledinclude syntax.A Python implementation to parse and build JSON file that containsinclude syntax.Syntaxjson-include supports an extended syntax calledinclude syntaxin JSON,
formatted as:{"...":"include(<json file name>)"}or{"<any key>":"include_text(<text file name>)"}The include syntax means that this object (the whole{"...": "include(<json file name>")}) in JSON is a reference to the JSON file named in<json file name>notation, and should be included into its place.The included JSON should always be an object (dict) rather than an array (list), to prevent implicit meaning and make sure we can get a clear view of the structure without looking into the included JSON files.In case multiple include statements are used, passing key insidemakeUniqueadds a random string to each included value at the corresponding key:{"...":"include(<json file name>)","makeUnique":"<key>"}In a normal JSON when we want to include another JSON on an attribute, it should be written as follows:{"username":"alice","profile":{"...":"include(profile_model.json)"}}In this JSON aprofile_model.jsonis included to presentprofileattribute,
if the content ofprofile_model.jsonis like:{"age":18,"gender":"female"}then what we mean by the include syntax is that, when this JSON is being used
as a normal JSON, it should be seen as:{"username":"alice","profile":{"age":18,"gender":"female"}}To ture JSON with include syntax into a normal JSON, a build process is needed,
that's what the implementation does.Python ImplementationImplementation could be of any language as long as it can understand the include syntax
and output as expected, this repo contains a Python implementation for use.Installationpipinstallkrozark-json-includeUsageimportjson_includejson_include.build_json('example.json')json_include.build_json(ROOT_DIR,'example.json')json_include.build_str('example.json')json_include.build_str(ROOT_DIR,'example.json')json-buildtest/source/c.json
python-mjson_includetest/source/c.json
Package: krpc
Documentation:https://krpc.github.io/krpcForum release thread:http://forum.kerbalspaceprogram.com/index.php?/topic/130742-105-krpc-remote-control-your-ships-using-python-c-c-lua-v021-10th-feb-2016/Forum development thread:http://forum.kerbalspaceprogram.com/threads/69313
Package: krptn
We also have ahomepageanddocumentationfor you to check out.KrptnpipinstallkrptnWhat problem do we solve?We all love Django and other web frameworks!However, their primary focus is creating websites - not implementing secure storage for user data. Django makes it easy to store data. While it hashes the password, it does not encrypt user data for you. In case of a data breach, malicious actors could access any data from the DB. Encryption is left to the developer...Wouldn't it be nice if encryption would also be handled?Perhaps it could be handled in away that keys are derived from credentials, such that, without the user entering credentials, not even the database administrator can read it?! This is exactly what we do!We also handle user authentication, including MFA, and passwordless authentication.Krptn also runs in the same server instanceas your web app. So you don't have to host anything new. Just install the extension for Python.To prove that such is possible, we have aFlaskandDjangoexample on GitHub.What do we do exactly?We are building a user authentication and access management system (IAM) withdata encryption at rest derived from credentials. It is available as a python extension module. However we have certainlimitations.How we achieve this?All data is encrypted (any data can be requested by the developer to be secured)Only the appropriate users' credentials can unlock the cryptosystem (this protects you from server-side attacks)This gives yousecurity from encryptionwithout ever needing to even notice it! It protects you from server side attacks.Here is an example usage:fromkrypton.auth.usersimportuserModelmodel=userModel.standardUser(None)model.saveNewUser("Test_UserName","Test_Password")model.data.email="test@example.com"# The email will be encrypted, and securely storedTry it outQuickly install the package with pip for Python>3.9:pipinstallkrptnHave a look at ourUser Authentication documentation, and create some users.Ready to integrate it into your WebApp? Have a look at some of our integration's available withDjango and Flask!
Package: kr-school-meal
Korea School Meal대한민국 학교들의 급식 정보를 알려줍니다. 모든 정보는NEIS에서 얻어옵니다.How To Use> pip install kr_school_meal
> from kr_school_meal import meal, neis_codeneis_code.py- 각 학교의 NEIS 코드를 가져옵니다.> neis_code.get_code('이의고등학교')
> {'이의고등학교': {'코드': 'J100006813', '교육청': '경기', '종류': '04'}}meal.py- 지정일의 급식을 가져옵니다.> meal.get_meal('J100005882', '경기', '04', datetime.datetime(2019, 10, 10))
> ['[중식]', '우유', '차조밥', '오징어찌개', '새송이버섯불고기', '녹두빈대떡', '열무김치', '머루포도']Troubleshooting문제가 있다면 issue를 남겨주세요.made by moseoridev with <3