Saravanan666/pypi-org huggingface dataset:
Package: jogoel
Jogoel-langA Jogoel-lang encoding algorithm, a simple conversion of the popular slang in Jogja commonly known as "basa walikan". This is not
a programming language, yep, this is for cryptography purpose.Includes encoding functions that convert text to the logic used. It doesn't have
a specific encoding key like encoding in general, but only changes each group of
letters in the Javanese script (aksara Jawa).AlgorithmJavanese script consists of 20 characters, arranged in four lines, each consisting of five characters.Ha Na Ca Ra KaDa Ta Sa Wa LaPa Dha Ja Ya NyaMa Ga Ba Tha NgaTo usebasa walikan, substitute the characters in the first line to the characters
in the third line, and the characters in the second line to the characters in
the fourth line, and vice versa.NOTE:The differences betweenencodeanddecodefunction is just letterhawhich
becomehorvocal letterUsageBasically, import the module.fromjogoel.langimportencodefromjogoel.langimportdecodeNow, u can useencodeanddecodefunction that processed your plaintext into
ciphertext and vice versa.in example:print(encode('mas'))print(decode('dasuny'))NOTEThis is just a fun project and i'm not taking seriously developing it. But, u can
contributing by make PR or creating an issue.
Package: jogospybr
jogospythonDescription.
The package jogospython is used to:
- Import games from Brazil in your code
- jogos
- adivinhacao
- jokenpo
- parouimpar
- jogodedados
- megasenaInstallationUse the package managerpipto install package_namepipinstalljogospybrAuthorfelipeb_barretoLicenseMIT
Package: jogos-python
jogos_pythonPacote para facilitar a criação de jogos com Python, usando pygame por baixo dos panos.Instalaçãopip install jogos_pythonAjudaPara aprender como usar este pacote, veja a documentação, lá explicamos como funciona e damos exemplos.Documentação.Se você busca contribuir com o desenvolvimento deste pacote, você pode acessar o repositório oficial com o código-fonte, e ver a seção sobre Desenvolvimento.Código-fonte.DesenvolvimentoPara desenvolver é essencial ser capaz de rodar o programa e conferir as modificações em tempo real. Para isto, siga os passos abaixo, a partir da pasta raiz do reporitório. É necessário ter opipinstalado em seu sistema. Se necessário instale ovenvcompip install venv.Ambiente virtualCrie um ambiente virtual para desenvolvimento. Só é preciso fazer isto uma vez.python3 -m venv .venvSerá criada uma pasta oculta.venvna pasta do projeto.Ative o ambiente com o comando:source ./.venv/bin/activateQuando quiser desativar o ambiente use o comandodeactivate. Para rodas o programa em desenvolvimento é recomentado fazer no ambiente virtual, com um ambiente controlado para rodar o pacote.Instalação editável do pacotePara desenvolver faça uma instalação editável do pacote com o comandopip install -e .Instalando desta maneira o pacote sempre conterá o código atual em desenolvimento. Este passo precisa ser feito apenas uma vez no ambiente virtual e permitirá importar o pacote nos testes e exemplos da mesma forma que o usuário do pacote faria.Testes automáticosPara este projeto pretende-se usar o framework de testesPytest. Então para ainda rodar os testes (quando houver), instale o pacote de testes com comandopip install pyteste, depois, rode os testes unitários  (futuramente) pelo comandopytest.Atualização da distribuição do pacote no PyPIBuildpython3 setup.py sdist bdist_wheelPara os passos a seguir é preciso garantir que possui instalado o pacotetwine. Se necessário instale compip install twine.Checkagemtwine check dist/*UploadPara realizar o upload é preciso ser um desenvolvedor do pacote e possuir as credenciais para upload no PyPI.twine upload dist/*
Package: johann-plugin-example
Johann Plugin ExampleThis repository is an example "plugin" for Johann consisting of the following:Celery tasks which can be used in Johann Scores both inside and outside this pluginPlugin-specific Scores that encode new scenarios/experimentsPlugin-specific configuration variablesAdditions to Johann's core configuration variablesPlugin-specific pip dependenciesThis project does not contain, but the Johann plugin system also supports:Python modules that add new capabilities to Johann (e.g., an additional host control
mechanism such as SSH or the VMware API)Structure of a Johann pluginIn order to keep the Johann plugin ecosystem consistent and compatible:Plugin repositories should be namedjohann_extension_name, e.g.,johann_plugin_examplePlugins must provide a single package namedjohann_extension_name, e.g.,johann_plugin_examplePlugins must create pypi-style distributions that can be installed via pipAny Score files must be included in the distribution (e.g., via MANIFEST.in), and
should be contained in ascoressubfolder of the packageIt isstronglyrecommended that any publicly available plugins be BSD or MIT
licensedPlugins should support the same versions of Python as Johann, namely Python 3.6+Plugin repositories should utilize the Developer Certificate of Origin (DCO) for each
commitThis can be accomplished via the-sflag to git commit
Package: john-bumbo
Bumbo: Python Web Framework built for learning purposesBumbo is a Python web framework built for learning purposes.It's a WSGI framework and can be used with any WSGI application server such as Gunicorn.InstallationpipinstallbumboHow to use itBasic usage:frombumbo.apiimportAPIapp=API()@app.route("/home")defhome(request,response):response.text="Hello from the HOME page"@app.route("/hello/{name}")defgreeting(request,response,name):response.text=f"Hello,{name}"@app.route("/book")classBooksResource:defget(self,req,resp):resp.text="Books Page"defpost(self,req,resp):resp.text="Endpoint to create a book"@app.route("/template")deftemplate_handler(req,resp):resp.body=app.template("index.html",context={"name":"Bumbo","title":"Best Framework"}).encode()Unit TestsThe recommended way of writing unit tests is withpytest. There are two built in fixtures
that you may want to use when writing unit tests with Bumbo. The first one isappwhich is an instance of the mainAPIclass:deftest_route_overlap_throws_exception(app):@app.route("/")defhome(req,resp):resp.text="Welcome Home."withpytest.raises(AssertionError):@app.route("/")defhome2(req,resp):resp.text="Welcome Home2."The other one isclientthat you can use to send HTTP requests to your handlers. It is based on the famousrequestsand it should feel very familiar:deftest_parameterized_route(app,client):@app.route("/{name}")defhello(req,resp,name):resp.text=f"hey{name}"assertclient.get("http://testserver/matthew").text=="hey matthew"TemplatesThe default folder for templates istemplates. You can change it when initializing the mainAPI()class:app=API(templates_dir="templates_dir_name")Then you can use HTML files in that folder like so in a handler:@app.route("/show/template")defhandler_with_template(req,resp):resp.html=app.template("example.html",context={"title":"Awesome Framework","body":"welcome to the future!"})Static FilesJust like templates, the default folder for static files isstaticand you can override it:app=API(static_dir="static_dir_name")Then you can use the files inside this folder in HTML files:<!DOCTYPE html><htmllang="en"><head><metacharset="UTF-8"><title>{{title}}</title><linkhref="/static/main.css"rel="stylesheet"type="text/css"></head><body><h1>{{body}}</h1><p>This is a paragraph</p></body></html>MiddlewareYou can create custom middleware classes by inheriting from thebumbo.middleware.Middlewareclass and overriding its two methods
that are called before and after each request:frombumbo.apiimportAPIfrombumbo.middlewareimportMiddlewareapp=API()classSimpleCustomMiddleware(Middleware):defprocess_request(self,req):print("Before dispatch",req.url)defprocess_response(self,req,res):print("After dispatch",req.url)app.add_middleware(SimpleCustomMiddleware)
Package: johndoe
johndoeThe intention of this application is to test whether your environment will download any package from PyPi.
PyPi allows anybody (even John Doe) to upload packages to the internet, but a companies infrastructure
should have suitable measures in place so that only trusted packages are downloaded.The package tries to find some interesting data on your machine and prints them to the console.
If this was a genuinely malicious program, it could be sending the information to an unsavoury destination.Hopefully the app highlights some flaws in processes, or at least confirms their usefulness.Usagefrom johndoe import findinfo
from pprint import pprint

hostname = findinfo.findHostName()
domainname = findinfo.getDomainName()
cpu_percent = findinfo.getCpu()
user = findinfo.getUser()
gpinfo = findinfo.getGroupPolicyInfo()

print("hostname is {}".format(hostname))
print("domain name is {}".format(domainname))
print("cpu percentaage is {}".format(cpu_percent))
print("user is {}".format(user))
pprint("group policy info is {}".format(gpinfo))
Package: john-filler
john_fillerjohn_fillerは42の課題、fillerのPython実装です。開発者向け情報poetryインストール手順公式のインストール手順に従いインストール。pythonだと2系なので、python3に変更しています。curl-sSLhttps://raw.githubusercontent.com/python-poetry/poetry/master/install-poetry.py|python3-~/.zshrcを編集。poetryのPATHを追加するコマンドを追記します。exportPATH="/Users/{login}/Library/Python/3.9/bin:$PATH"~/.zshrcの変更を今のshellに反映します。source~/.zshrcvenvの保存場所の設定を変更venvはデフォルトで/Users/{login}/Library/Caches/pypoetry/virtualenvsにインストールされます。プロジェクトの中に置きたいので、設定を行います。poetryconfigvirtualenvs.in-projecttrue設定を行うと、poetry addなどで、{プロジェクトのディレクトリ}/.venvに仮想環境が作られます。poetry shellで仮想環境の中に入ることができます。PyPIへのパッケージアップロード手順参考[Python] poetryを使用したPyPIパッケージ公開手順 - QiitaPyPIorTestPyPIにユーザ登録します。API Tokenを発行、poetryに登録します。パッケージをビルドします。poetrybuildパッケージをアップロードします。# TestPyPIpoetrypublish-rtestpypi# PyPIpoetrypublishアップロードの際、バージョンが既にあるバージョンとは異なる必要があります（パッケージを削除してもNGなようです）。このため、TestPyPIにアップロードして確認後、PyPIにアップロードが安全かと思います。
Package: johnny
johnny - generic dep(p)endencies trackerTracking versions and alerting stale dependencies. Johnny is tool and language
independent and doesn't need central service.Currently supports: git, gitlab (gitlab.com and self-hosted), github, arch and aurFor git please prefer git:// is supported, but please prefer https://Note!: Most git URLs end in ".git" (github/gitlab), but API URLs do not.Runningpipinstalljohnny
johnnyexamples/deps.toml
Package: johnny-cache
Johnny Cache is a caching framework fordjangoapplications.  It works with
the django caching abstraction, but was developed specifically with the use ofmemcachedin mind.  Its main feature is a patch on Django’s ORM that
automatically caches all reads in a consistent manner.You can install johnny with pip:pip install johnny-cacheYou can fork johnny-cachefrom its git repository:git clone http://github.com/jmoiron/johnny-cache.gitOr if you prefer mercurial,from its hg mirror:hg clone http://bitbucket.org/jmoiron/johnny-cachePlease readThe full documentation to Johnny Cachebefore using it.
Package: johnnycanencrypt
Johnny can encryptJohnnycanencrypt akajceis a Python module written in Rust to do basic encryption and decryption, and detached signing operations.
It uses amazingsequoia-pgplibrary for the actual OpenPGP operations.You can also use Yubikeys for the private key operations using this module.How to build?First installRustup toolchainfor your user.Build dependencies in Fedorasudo dnf install nettle clang clang-devel nettle-devel python3-devel pcsc-lite-develBuild dependencies in Debian Bullseyesudo apt install -y python3-dev libnettle8 nettle-dev libhogweed6 python3-pip python3-venv clang libpcsclite-dev libpcsclite1 libclang-9-dev pkg-configpython3 -m venv .venv
source .venv/bin/activate
python -m pip install -U pip setuptools
python -m pip install -r requirements-dev.txt
python setup.py developFor a release build use the following command.python setup.py bdist_wheelIntroductionPlease read theIntroductiondocumentation.API documentationPlease go through thefull API documentationfor detailed
descriptions.LICENSE: LGPL-3.0-or-later
Package: johnnydep
JohnnydepPretty-print a dependency tree for a Python distribution. A simple example:$ johnnydep requests
name                       summary
-------------------------  ----------------------------------------------------------------------
requests                   Python HTTP for Humans.
├── certifi>=2017.4.17     Python package for providing Mozilla's CA Bundle.
├── chardet<3.1.0,>=3.0.2  Universal encoding detector for Python 2 and 3
├── idna<2.8,>=2.5         Internationalized Domain Names in Applications (IDNA)
└── urllib3<1.24,>=1.21.1  HTTP library with thread-safe connection pooling, file post, and more.A more complex tree:$ johnnydep boto3
name                                     summary
---------------------------------------  -------------------------------------------------
boto3                                    The AWS SDK for Python
├── botocore<1.11.0,>=1.10.77            Low-level, data-driven core of boto 3.
│   ├── docutils>=0.10                   Docutils -- Python Documentation Utilities
│   ├── jmespath<1.0.0,>=0.7.1           JSON Matching Expressions
│   └── python-dateutil<3.0.0,>=2.1      Extensions to the standard Python datetime module
│       └── six>=1.5                     Python 2 and 3 compatibility utilities
├── jmespath<1.0.0,>=0.7.1               JSON Matching Expressions
└── s3transfer<0.2.0,>=0.1.10            An Amazon S3 Transfer Manager
    └── botocore<2.0.0,>=1.3.0           Low-level, data-driven core of boto 3.
        ├── docutils>=0.10               Docutils -- Python Documentation Utilities
        ├── jmespath<1.0.0,>=0.7.1       JSON Matching Expressions
        └── python-dateutil<3.0.0,>=2.1  Extensions to the standard Python datetime module
            └── six>=1.5                 Python 2 and 3 compatibility utilitiesJohnnydep can also attempt to resolve the dependency tree:$ johnnydep ipython --output-format pinned
ipython==6.5.0
appnope==0.1.0
backcall==0.1.0
decorator==4.3.0
jedi==0.12.1
pexpect==4.6.0
pickleshare==0.7.4
prompt-toolkit==1.0.15
pygments==2.2.0
setuptools==40.0.0
simplegeneric==0.8.1
traitlets==4.3.2
parso==0.3.1
ptyprocess==0.6.0
six==1.11.0
wcwidth==0.1.7
ipython-genutils==0.2.0Note thatpip installlacked a working solverfor many years, butpip v20.3 has a new solver(December 2020) which has really improved matters!Checkjohnnydep --helpfor other features and options.Helpful linksCore metadata specificationsPEP 427 -- The Wheel Binary Package Format 1.0PEP 426 -- Metadata for Python Software Packages 2.0(nowrevokedbut still commonly seen in the wild)PEP 566 -- Metadata for Python Software Packages 2.1PEP 503 -- Simple Repository API
Package: john-resume
John's resume!I am currently making the most programmer'y resume that I can think of. That means I have to do stupid stuff like adding it to pip. Because why not? Wouldn't be much of a developer resume if it doesn't have:Version controlAutomated testsFull CI/CD pipelineAutomatic deploymentLegacy supportAnd more!This is totally dumb, but if you're interestedhead over to my websiteand let's be dumb together.Parameters to use this dumb script:-f : For fast printout
 --json : If you prefer getting the printout in a json format
 -h : for helpTo run the program just use the command "john-resume":john-resume //Prints the resume
john-resume -f //Prints the resume really fastNote that the script requires an interest connection, as this is an always online service.
Package: johnson
JohnsonPretty print .json data in your terminalInstallingInstall and update using pip:pipinstall-UjohnsonUsagePretty print your json filejohnson-fexample.json{"glossary":{"title":"example glossary","GlossDiv":{"title":"S","GlossList":{"GlossEntry":{"ID":"SGML","SortAs":"SGML","GlossTerm":"Standard Generalized Markup Language","Acronym":"SGML","Abbrev":"ISO 8879:1986","GlossDef":{"para":"A meta-markup language, used to create markup languages such as DocBook.","GlossSeeAlso":["GML","XML"]},"GlossSee":"markup"}}}}}See all commands availablejohnson--helpUsage:johnson[OPTIONS]╭─Options─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│*--file-fPATHpathtojsonfile[default:None][required]│
│--install-completionInstallcompletionforthecurrentshell.│
│--show-completionShowcompletionforthecurrentshell,tocopyitorcustomizetheinstallation.│
│--helpShowthismessageandexit.│
╰───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Package: johnstondechazal
johnstondechazalA method of optimising facial landmark selection from crowd sourced labels.Free software: GNU General Public License v3Documentation:https://johnstondechazal.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2020-03-02)First release on PyPI.
Package: john-toolbox
Welcome to john_toolbox 👋This is my own toolbox to handle preprocessing production ready based on scikit-learn Pipeline but with more flexibility.🏠HomepageInstallpipinstalljohn-toolboxAuthor👤Johnathan NguyenGitHub:@nguyenanhtHow to use ?If you want examples. please refer tonotebooks directory. It contains tutorials on how to use the package and other useful tutorials to handle end to end machine learning project.Show your supportGive a ⭐️ if this project helped you!Useful linkhow to publish new version in pypi with poetry ?https://johnfraney.ca/posts/2019/05/28/create-publish-python-package-poetry/how to create a new release ?https://www.atlassian.com/fr/git/tutorials/comparing-workflows/gitflow-workflowhow to generate docshttps://github.com/JamesALeedham/Sphinx-Autosummary-Recursionhow to deploy with github actionshttps://blog.flozz.fr/2020/09/21/deployer-automatiquement-sur-github-pages-avec-github-actions/This README was created with themarkdown-readme-generator
Package: joho
Description:HTML and SVG module to create lecture materials for 情報処理及び実習 TAC101
at the University of Yamanashi (山梨大学).Output file: html.Example:#!python
## -*- coding: utf-8 -*-
import joho as j
# create html output file and
# load the default web browser to open the file
j.title("Topic 12: Python: HTML SGV ")
j.insert_horizontal_line()
j.heading2("パイソンによる HTML")
j.write("Hello world")
j.heading2("パイソンによる図形、アニメションの作成")
Face =  j.line(0, 0, 100, 100) +\
        j.circle(100, 100, 50, fillcolor="none") + \
        j.polygon([200, 400, 400],[100,100,300])
j.draw(Face + j.grid(100))
j.MakeTableContent()
j.show()Installationpip install joho
Package: join
SQL-style joins for Python iterables.>>>fromjoinimportjoin,merge,tuple_join>>>dogs=[...Dog('gatsby','Rruff!',16),...Dog('ein','wruf!',9),...]>>>cats=[...Cat('pleo','mreeeoww',16),...Cat('xena','mreow',12),...Cat('gatsby','rowr',15),...]>>>catdogs=merge(cats,dogs,key='name')>>>catdogs[CatDog({'right':Dog(name='gatsby',woof='Rruff!',weight=16),'name':'gatsby','weight':15,'meow':'rowr','woof':'Rruff!','left':Cat(name='gatsby',meow='rowr',weight=15)})]>>>catdogs[0].meow'rowr'>>>catdogs[0].woof'Rruff!'InstallationInstall using pip:pip install joinUsejoindoes the work of associating iterable items together, but gives you all the power for customization, letting you supply your own join function, separate keys for left and right iterables, and even letting you use functions instead of attribute names.mergeused above, for example, isjoinusing an object union to join matched objects.  You can use a tuple join, which is default forjoin:>>>join(cats,dogs,key='name',join_fn=tuple_join)[(Cat(name='gatsby',meow='rowr',weight=15),Dog(name='gatsby',woof='Rruff!',weight=16))]Supplying your own join function is easy:>>>defweight_sum(left,right):...returnleft.weight+right.weight...>>>join(cats,dogs,key='name',join_fn=weight_sum)[31]Using separate key functions is easy too:>>>defcat_key(cat):...returncat.weight%3==0# weight divisible by 3...>>>defdog_key(dog):...returndog.weight%4==0# weight divisible by 4...>>>defname_join(left,right):...returnleft.name+'-'+right.name...>>>join(cats,dogs,left_key=cat_key,right_key=dog_key,join_fn=name_join)['pleo-ein','xena-gatsby','gatsby-gatsby']ContributingPull requests and issues welcome!  Run tests from project root withsh run_tests.sh.
Package: joinboost
JoinBoost: In-Database Tree-Models over Many TablesJoinBoost is a Python library to help you train tree-models (decision trees, gradient boosting, random forests).Note that many functionalities of JoinBoost are still under development. If you are interested in using JoinBoost, we are happy to provide direct supports. You can contact us through issues, or emailzh2408@columbia.eduWhy JoinBoost?JoinBoost algorithms follow LightGBM. However, JoinBoost trains modelsInside Database: JoinBoost translates ML algorithms into SQL queries, and directly executes these queries in your databases. This means:Safety: There is no data movement.Transformation: You can directly do OLAP and data transformation in SQL.Scalability: In-DB ML is natively out-of-core, and JoinBoost could be connected to distributed databases.Many tables: JoinBoost appliesFactorized Learningwith optimized algorithms. Therefore, JoinBoost trains a model over the join result of many tables but without materializing the join. This provides large performance improvement and is super convenient.Start JoinBoostThe easiest way to install JoinBoost is using pip:pip install joinboostJoinBoost APIs are similar to Sklearn, Xgboost and LightGBM. The main difference is that JoinBoost datasets are specified by database connector and join graph schema. Below, we specify a join graph of two tables sales and items:import duckdb
from joinboost.joingraph import JoinGraph
from joinboost.app import DecisionTree

# DuckDB connector
con = duckdb.connect(database='duckdb')

dataset = JoinGraph(con)
dataset.add_relation("sales", [], y = 'total_sales')
dataset.add_relation("items", ["family","class","perishable"])
dataset.add_join("sales", "items", ["item_nbr"], ["item_nbr"])

reg = DecisionTree(learning_rate=1, max_leaves=8)
reg.fit(dataset)Please Check out this notebook for DemoFor dev:https://gitpod.io/new#https://github.com/zachary62/JoinBoostDocsDocumentation is currently under development. To build docs locally, downloadSphinxand runmakehtmlin the folderdocs. The docs will be generated in the folderdocs/build/html.ReproducibilityThe technical report of JoinBoost could be found under /technical directory.We note that some optimizations discussed in the paper (e.g., inter-query parallelism, DP) are still under development in the main codes. To reproduce the experiment results from the paper, we include the prototype codes for JoinBoost under /proto folder, which includes all the optimizations. We also include Jupyter Notebook to help you use these codes to train models over Favorita.The Favorita dataset is too large to store in Github. Please download files fromhttps://www.dropbox.com/sh/ymwn98pvederw6x/AAC-z6R_rKvU40KZDCyitjsda?dl=0and uncompress the files.The modified DuckDB to support column swap is athttps://anonymous.4open.science/r/duckdb-D056.