Saravanan666/pypi-org huggingface dataset:
Package: shinylive
Shinylive Python packageDocumentation siteThis repository contains a Python package for exporting Shiny applications as Shinylive applications.This repository is not the same as thehttps://github.com/posit-dev/shinyliverepository. That repository is used to generate the Shinylive assets distribution, which is a bundle containing HTML, JavaScript, CSS, and wasm files. The Python package in this repository downloads the assets and uses them to create Shinylive applications.Installationpip install shinyliveUsage(Optional) Create a basic shiny application in a new directorymyapp/:shiny create myappOnce you have a Shiny application inmyapp/and would like turn it into a Shinylive app insite/:shinylive export myapp siteThen you can preview the application by running a web server and visiting it in a browser:python3 -m http.server --directory site --bind localhost 8008At this point, you can deploy thesite/directory to any static web hosting service.Multiple applicationsIf you have multiple applications that you want to put on the same site, you can export them to subdirectories of the site, so that they can all share the same Shinylive assets. You can do this with the--subdiroption:shinyliveexportmyapp1site--subdirapp1
shinyliveexportmyapp2site--subdirapp2Shinylive asset managementEach version of the Shinylive Python package is associated with a particular version of the Shinylive web assets. (See the releases here.)To see which version of this Python package you have, and which version of the web assets it is associated with, simply runshinyliveat the command prompt:$ shinylive
Usage: shinylive [OPTIONS] COMMAND [ARGS]...

  shinylive Python package version: 0.1.0
  shinylive web assets version:     0.2.1
...The web assets will be downloaded and cached the first time you runshinylive export. Or, you can runshinylive assets downloadto fetch them.$ shinylive assets download
Downloading https://github.com/posit-dev/shinylive/releases/download/v0.2.1/shinylive-0.2.1.tar.gz...
Unzipping to /Users/username/Library/Caches/shinylive/To see what versions you have installed, runshinylive assets info:$ shinylive assets info
    Local cached shinylive asset dir:
    /Users/username/Library/Caches/shinylive

    Installed versions:
    /Users/username/Library/Caches/shinylive/shinylive-0.2.1
    /Users/username/Library/Caches/shinylive/shinylive-0.0.6You can remove old versions withshinylive assets cleanup. This will remove all versions except the one that the Python package wants to use:$ shinylive assets cleanup
Keeping version 0.2.1
Removing /Users/username/Library/Caches/shinylive/shinylive-0.0.6If you want to force it to remove a specific version, use theshinylive assets remove xxx:$ shinylive assets remove 0.2.1
Removing /Users/username/Library/Caches/shinylive/shinylive-0.2.1
Package: shiny-multiprocessing
shiny_multiprocessingA small token piece of code meant to make multiprocessing a bit handier, when
it comes to executing functions, that need proper monitoring in terms of
idling, timing out or failing with errors.It makes use of Pebble to reliably enforce timeouts on the individual processes
while also providing comfortable retry capabilities for a range of exceptions
of your selection.More documentation to come. Maybe.Its home in Gitlabshiny_multiprocessing
Package: shinyobservable
shinyobservableEmbedObservable NotebooksinShiny for Python.Shinyobservable makes it a breeze to integrate libraries such asD3.Create any kind of JavaScript visualizations and let Shiny handle your data and interactivity.FeaturesEmbed entire notebooksEmbed selected cells onlyUpdate data cells to update visualizationsInstallationpipinstallshinyobservable# Devpipinstallgit+https://github.com/eodaGmbH/py-shiny-shinyobservableQuickstartfromhtmltoolsimportafromshiny.expressimportuifromshinyobservableimportObservable,ObservableRendererNOTEBOOK="https://observablehq.com/@d3/zoomable-sunburst"ui.h1("Observable Notebook in Shiny")ui.div(a(NOTEBOOK,href=NOTEBOOK,target="_blank"))ui.hr()# Render entire notebook@ObservableRendererdefrender_notebook():returnObservable(NOTEBOOK)# Render single cells only@ObservableRendererdefrender_cells():returnObservable(NOTEBOOK,cells=["chart"])Enjoy your Observable Notebook in Shiny!Seethis exampleon how to update the data of your notebook.Docshttps://eodagmbh.github.io/py-shiny-observable/
Package: shinyswatch
shinyswatchBootswatch+ Bootstrap 5 themes forShiny.Here are just three of the25 themesin shinyswatch:MintySketchySuperheroInstallationpipinstallshinyswatchTo install the latest development version from this repository:pipinstallhttps://github.com/rstudio/py-shinyswatch/tarball/mainUsageTo use a theme, call the theme function and add it to your App's UI definition.# Minty themeshinyswatch.theme.minty()# Sketchy themeshinyswatch.theme.sketchy()# Superhero themeshinyswatch.theme.superhero()Example Shiny application:File:app.pyScreenshotfromshinyimportApp,Inputs,Outputs,Session,render,uiimportshinyswatchapp_ui=ui.page_fluid(# Theme code - startshinyswatch.theme.darkly(),# Theme code - endui.input_slider("num","Number:",min=10,max=100,value=30),ui.output_text_verbatim("slider_val"),)defserver(input:Inputs,output:Outputs,session:Session):@output@render.textdefslider_val():returnf"{input.num()}"app=App(app_ui,server)Note: When writing shiny apps onshinylive.io, remember to addshinyswatchto yourrequirements.txtfile!Theme pickerTo add a theme picker to your app, add theshinyswatch.theme_picker_ui()in place of your theme object and addshinyswatch.theme_picker_server()into yourserverdefinition.Demo:shinylive.ioDevelopmentIf you want to do development on shinyswatch for Python:pipinstall-e".[dev,test,docs]"ExamplesThere are multiple examples in the shinyswatch repo.To run the demos locally, you can run the examples by calling:python3-mshinyrunexamples/basic-darkly/app.py
python3-mshinyrunexamples/big-sketchy/app.py
python3-mshinyrunexamples/components/app.py
python3-mshinyrunexamples/theme-picker/app.py
Package: shinytext
✨ Shiny TextThis package aims to be a one stop all package for all text processing tasks.
The package was developed using Python3.10.💻 Installationpipinstall-Ushinytext🚀 Usage# To clean textfromshinytext.cleantextimport<method># To clean dataframefromshinytext.cleandataimport<method># To download/fetch a spacy language modelfromshinytext.utils.spacy_loaderimportget_spacy_objectList of text cleaning methodsremove_punctuation: To remove punctuationsremove_stopwords: To remove stopwordsremove_frequent_words: To remove frequently occuring wordsremove_rare_words: To remove rarely occuring wordsstemmer: To perform stemminglemmatizer: To perform lemmatizingremove_emojis: To remove emoji'sconvert_emojis: To convert emoji's to textremove_emoticons: To remove emoticonsconvert_emoticons: To convert emoticons to textremove_urls: To remove URLsremove_html: To remove htmlconvert_chatwords: To convert chat words to textList of dataframe cleaning methodsfilter_english_records: To extract data with only english text✍ Contribution GuidelinesPlease ensure that you adhere to the following guidelines while making a pull request.Fork the project on to your repo. Create a branch under your name and create PR from your branch.USE proper commit messages and give detailed descriptions for your commit including the file name, function name and the changes made.Customize your commit titles according to below given instructions* "ADD: <your task title>" for new additions  
* "MOD: <your task title>" for modifications 
* "DEL: <your task title>" for deletions
* "FIX: <your task title>" for fixing bugsEnsure that your code adheres to PEP-8 guidelines.Click hereto know more about it.💼 Current RequirementsMore text processing techniquesTest cases for existing functions🙌 ContributorsRetin P Kumar❤ CreditsEmot librarybyNeel ShahGetting started with Text PreprocessingbySudalai Rajkumar⚙ DependanciesNLTKPandasPySpellcheckerSpaCy
Package: shiny-validate
shiny_validateOverviewThis is a python implementation ofshinyvalidate, which provides input validation forShiny for Pythonapplications.InstallationInstall from Pypi with:pip install shiny_validateOr, you can install the latest development version from GitHub using theremotespackage.pip install git+https://github.com/rstudio/shinyvalidate.gitBasic usageTo add validation to your Shiny app, you need to:Create an InputValidator object:iv <- InputValidatorAdd one or more validation rules to the InputValidator:iv.add_rule("title", check.required())Turn the validator on:iv$enable()That's all you need to do to get validation messages to show up.fromshinyimportApp,ui,render,reqfromshiny_validateimportInputValidator,checkapp_ui=ui.page_fluid(ui.input_text("name","Name"),ui.input_text("email","Email"),ui.output_text("greeting"),)defserver(input,output,session):iv=InputValidator()iv.add_rule("name",check.required())iv.add_rule("email",check.required())iv.add_rule("email",check.email())iv.enable()@render.textdefgreeting():req(iv.is_valid())returnf"Nice to meet you,{input.name()}<{input.email()}>!"app=App(app_ui,server)
Package: shinywidgets
shinywidgetsRenderipywidgetsinside aShiny(for Python) app.See theJupyter Widgetsarticle on the Shiny for Python website for more details.InstallationpipinstallshinywidgetsDevelopmentIf you want to do development on{shinywidgets}, run:pipinstall-e".[dev,test]"cdjs&&yarnwatch
Package: shio
Construct is a powerfuldeclarativeandsymmetricalparser and builder for binary data.Instead of writingimperative codeto parse a piece of data, you declaratively define adata structurethat describes your data. As this data structure is not code, you can use it in one direction toparsedata into Pythonic objects, and in the other direction, tobuildobjects into binary data.The library provides both simple, atomic constructs (such as integers of various sizes), as well as composite ones which allow you form hierarchical and sequential structures of increasing complexity. Construct featuresbit and byte granularity, easy debugging and testing, aneasy-to-extend subclass system, and lots of primitive constructs to make your work easier:Fields: raw bytes or numerical typesStructs and Sequences: combine simpler constructs into more complex onesBitwise: splitting bytes into bit-grained fieldsAdapters: change how data is representedArrays/Ranges: duplicate constructsMeta-constructs: use the context (history) to compute the size of dataIf/Switch: branch the computational path based on the contextOn-demand (lazy) parsing: read and parse only what you requirePointers: jump from here to there in the data streamTunneling: prefix data with a byte count or compress itExampleAStructis a collection of ordered, named fields:>>> format = Struct(
...     "signature" / Const(b"BMP"),
...     "width" / Int8ub,
...     "height" / Int8ub,
...     "pixels" / Array(this.width * this.height, Byte),
... )
>>> format.build(dict(width=3,height=2,pixels=[7,8,9,11,12,13]))
b'BMP\x03\x02\x07\x08\t\x0b\x0c\r'
>>> format.parse(b'BMP\x03\x02\x07\x08\t\x0b\x0c\r')
Container(signature=b'BMP')(width=3)(height=2)(pixels=[7, 8, 9, 11, 12, 13])ASequenceis a collection of ordered fields, and differs fromArrayandGreedyRangein that those two are homogenous:>>> format = Sequence(PascalString(Byte, "utf8"), GreedyRange(Byte))
>>> format.build([u"lalaland", [255,1,2]])
b'\nlalaland\xff\x01\x02'
>>> format.parse(b"\x004361789432197")
['', [52, 51, 54, 49, 55, 56, 57, 52, 51, 50, 49, 57, 55]]
Package: shioaji-position-management
Shioaji Realtime Kline ExtensionAn Extensions help you trading with Sinopac shioajiTable Of ContentsAbout the ProjectDescriptionGetting StartedUsageVersionRoadmapAuthorsAcknowledgementsAbout The ProjectWhen you use Shioaji Python API for technical analysis, you may need to place order. This package want to provide a convenient position management and place order.You won't deal with the callback anymore.DescriptionTo use the extension just initialize the objectimport shioaji_position_management
position = shioaji_position_management.shioaji_position_managements(api, "YOUR_ACCOUNT")Getting StartedThis is an example of how you may give instructions on setting up your project locally.pipinstallshioaji_position_managementUsageVersionv1.0.6 (2023/7/28) Adjust the log of callback messagev1.0.5 (2023/7/27) Fix some bugs about orderv1.0.4v1.0.3 (2023/7/24) Release & fix some bugsv1.0.2v1.0.1v1.0.0RoadmapSee theopen issuesfor a list of proposed features (and known issues).AuthorsYou-rui, Lin- ** -You-rui, Lin-Whole project
Package: shipami
CLI for simple AWS AMIs managementQuick StartInstall withpip:$pipinstallshipami$shipami--helpExample: Publish AMI for AWS MarketplaceList available AMIs in your default region (eg. eu-west-1)$shipamilistNAMERELEASEIDSTATECREATEDMANAGEDCOPIEDFROMCOPIEDTOfooami-00000000available5daysagonooriginCreate a release based on this image in us-east-1 region$shipami--regionus-east-1releaseami-000000001.0--source-regioneu-west-1ami-000000aa$shipami--regionus-east-1listNAMERELEASEIDSTATECREATEDMANAGEDCOPIEDFROMCOPIEDTOfoo-1.01.0ami-000000aapendingjustnowyeseu-west-1:ami-00000000Manually share with AWS Marketplace account$shipami--regionus-east-1shareami-000000aa$shipami--regionus-east-1showami-000000aaid:ami-000000aaname:foo-1.0state:availabletags:shipami:copied_from:eu-west-1:ami-00000000shipami:managed:Trueshipami:release:1.0devicesmappings:/dev/xvda8Gotype:gp2sharedwith:679593333241(AWSMARKETPLACE)OKCommandsYou can get further help and usage instructions on any command with the--helpoption.copy$shipamicopyami-00000000ami-000000aa$shipamilistNAMERELEASEIDSTATECREATEDMANAGEDCOPIEDFROMCOPIEDTOfooami-00000000available5daysagonoorigineu-west-1:ami-000000aafooami-000000aapendingjustnowyeseu-west-1:ami-00000000delete$shipamilistNAMERELEASEIDSTATECREATEDMANAGEDCOPIEDFROMCOPIEDTOfooami-00000000available5daysagonoorigineu-west-1:ami-000000aafooami-000000aaavailable1dayagoyeseu-west-1:ami-00000000$shipamideleteami-000000aaami-000000aa$shipamilistNAMERELEASEIDSTATECREATEDMANAGEDCOPIEDFROMCOPIEDTOfooami-00000000available5daysagonooriginlist$shipamilistNAMERELEASEIDSTATECREATEDMANAGEDCOPIEDFROMCOPIEDTOfooami-00000000available5daysagonooriginrelease$shipamireleaseami-000000001.0ami-000000aa$shipamilistNAMERELEASEIDSTATECREATEDMANAGEDCOPIEDFROMCOPIEDTOfooami-00000000available5daysagonoorigineu-west-1:ami-000000aafoo-1.01.0ami-000000aapendingjustnowyeseu-west-1:ami-00000000share$shipamishareami-000000aa012345678912show$shipamishowami-000000aaid:ami-000000aaname:foo-1.0state:availabletags:shipami:copied_from:eu-west-1:ami-00000000shipami:managed:Trueshipami:release:1.0devicesmappings:/dev/xvda8Gotype:gp2sharedwith:012345678912
Package: shipcal
SHIPcalSHIPcal is an open-source code to simulate solar heat applications for industrial process heat. SHIPcal is written in Python 3 and can be run from terminal or from a web based front-end. There are several propetary front-ends that call SHIPcal. As for example:STEORcal (Developed by Miguel Frasquet)ReSSSPI (Developed by SOLATOM)CIMAV (Developed by CIMAV)#Technical comments#Moved from bitbucket private repository to github (Eurosun 2018)
#Resuming commits and contributions begining October 2018#Improvements from 2019
-Juan Antonio Aramburo Pasapera (CIMAV) Changed demand creator function to improve the accuracy of the results
-Juan Antonio Aramburo Pasapera (CIMAV) Changed fixed raw water temperature function. Now it depends on the TMYMiguel Frasquet Herraiz (SOLATOM) Added new reg to allow external front-ends call ressspi (see an example of frontend athttps://github.com/mfrasquet/frontendRessspi#Bug fixing from 2019
-See slack channel for more informationhttps://shipcal.slack.com. If you want to contribute send an email tomfrasquetherraiz@gmail.com#All prev. contributors (from bitbucket) will received an email with instructionsInstallation instructions (Please check the pdf "SHIPcal Installation Manual" for further information)#From anaconda (on windows):create a new environment and install the following libraries:django, numpy, scipy, pandas, pillow and matplotlib.it is also necessary the iapws. Since it is not included in anaconda, install manually in the terminal:pip install iapwsNow create and navigate to the folder of your project, example /Desktop/SHIPcal:clone this repository in the folder: git clonehttps://github.com/mfrasquet/SHIPcal.gitclone the frontend repository in the same folder: git clonehttps://github.com/mfrasquet/SHIPcal_frontend.gitAccess the SHIPcal_frontend folder created after the clonning process (cd SHIPcal)Now type again:python manage.py runserver 0.0.0.0:8000and that's it!Finaly, open a browser and go tohttp://localhost:8000/DevelopersMiguel Frasquet HerraizJuan Antonio Aramburo PasaperaCarlos Santiago Rocha LeyvaFátima Monserrat Chávez PiedraJose Alfonso Romero RamosMercedes Ibarra MolláMihail PislaruCarlos José Felbol AcuñaFrancisco Ignacio Fuentes Herlitz
Package: shipchain-hydra
Hydra manages many heads of networksQuick-start GuideJust trying to use hydra? Follow ourValidator Setup GuideDeveloper InstructionsInstallmake virtualenv
source env/bin/activateConfigure client and run nodeNote: Replace network-name with your chosen network (e.g. shipchain-testnet-alpha)Join a networkhydra client join-network -n network-nameConfigure clienthydra client configure -n network-nameStart node and begin syncing with network - this will take a whilecd network-name && ./start_blockchain.shYour node is sync'd to the network whencurl localhost:46657/statusreturnssync_info.catching_up: falseShipchain validator node commands can be accessed from~/hydra/network-name/shipchainGeneral Installation and Development GuidelinesInstallation$ pip install -r requirements.txt

$ pip install setup.pyDevelopmentThis project includes a number of helpers in theMakefileto streamline common development tasks.Environment SetupThe following demonstrates setting up and working with a development environment:### create a virtualenv for development

$ make virtualenv

$ source env/bin/activate


### run hydra cli application

$ hydra --help


### run pytest / coverage

$ make testReleasing to PyPiBefore releasing to PyPi, you must configure your login credentials:~/.pypirc:[pypi]
username = YOUR_USERNAME
password = YOUR_PASSWORDThen use the included helper function via theMakefile:$ make dist

$ make dist-uploadDeploymentsDockerIncluded is a basicDockerfilefor building and distributingShipChain Network Hydra Manager,
and can be built with the includedmakehelper:$ make docker

$ docker run -it hydra --help
Package: shipdataprocess
# shipdataprocess (current latest version 0.8.2)shipdataprocess provides packages and modules that help users process raw ship data. The data may come from Automatic identification system (AIS) transmission or others. Ship data includes vessel’s name, callsign, shiptype, geartype information etc. You might find the packages here useful for normalizing ship names and IRCS (International Radio Call Sign) and for dealing with various types of ships and fishing gears. Typical usage often looks like this:#!/usr/bin/env pythonfrom shipdataprocess.normalize import normalize_shipname, normalize_callsignfrom shipdataprocess.shiptype import determine_shiptype, make_shiptype_dict, reduce_to_specifics, reduce_to_specifics_with_multiplesfrom shipdataprocess.standardize import standardize_imo, standardize_float, standardize_str, standardize_int_str, standardize_time, standardize_flag, standardize_geartypefrom shipdataprocess.collapse import non_zero_mean, non_zero_std, most_common_value, most_common_num, most_common_str, str_attached, min_time, max_time# Contributors
This work was done based on the previous work of the team of Global Fishing Watch (GFW).Jaeyoon Park,
David Kroodsma,
Andres Arana,
Enrique Tuya,
Bjorn Bergman,
Paul Woods# Development` virtualenv venv source venv/bin/activate pip install-e. py.test tests `# Changes/updates
See./CHANGES.md
Package: shipflowmotionshelpers
shipflowmotionshelpersPython helper function for ShipFlow MotionsFree software: MIT licenseDocumentation:https://shipflowmotionshelpers.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2020-12-09)First release on PyPI.
Package: shipfunk-python
ShipfunkPython module for Shipfunk APIFree software: MIT licenseDocumentation:https://shipfunk-python.readthedocs.io.FeaturesDeliveries handlingPickup point searchPackage card and tracking code creationUser accounts handlingCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.1 (2019-10-28)Updated requirements.txt. Newer “requests” module is needed.Updated test cases.0.1.0 (2018-01-08)First release on PyPI.
Package: ship-it-validate
Ship It ValidateThis package can be used to easily validate headers signed byShip It.Installpip install ship-it-validateUsageMake sure to set theSHIP_IT_PUBLIC_KEYenvironment variable to the base64 encoded public key provided in the Ship It site configuration page.Flaskfromship_it_validateimportvalidatefromflaskimportrequest@app.before_requestdefbefore_request():try:validate(request.headers.get('X-PROXY-SIGNATURE'),request.headers.get('X-USER-SUB'),request.headers.get('X-PROXY-TIMESTAMP'),)exceptValueErrorase:app.logger.warning('Invalid Ship It signature:%s',e)return"Unauthorized",401
Package: shipmmg
ShipMMG: Ship Maneuvering Simulation ModelWhat is it?ShipMMGis a unofficial Python package of ship maneuvering simulation with respect to the research committee on “standardization of mathematical model for ship maneuvering predictions” was organized by the JASNAOE.Where to get itThe source code is currently hosted on GitHub at:https://github.com/ShipMMG/shipmmgBinary installers for the latest released version will be available at the Python package index. Now, please install pDESy as following.pipinstallshipmmg# pip install git+ssh://git@github.com/ShipMMG/shipmmg.git # Install from GitHub# conda install -c conda-forge -c taiga4112 shipmmg # Install from AnacondaLicenseMITFor developersDeveloping shipmmg APIHere is an example of constructing a developing environment.dockerbuild-tshipmmg-dev-env.
dockerrun--rm--nameshipmmg-dev-v`pwd`:/code-w/code-itshipmmg-dev-env/bin/bashIn this docker container, we can runpytestfor checking this library.Checking shipmmg APIHere is an example of checking the shipmmg developing version using JupyterLab.docker-composebuild
docker-composeupAfter that, accesshttp://localhost:8888.Password isshipmmg.ContributionFork it (http://github.com/ShipMMG/shipmmg/fork)Create your feature branch (git checkout -b my-new-feature)Commit your changes (git commit -am 'Add some feature')Push to the branch (git push origin my-new-feature)Create new Pull RequestIf you want to join this project as a researcher, please contactme.
Package: shipnames
version number: 0.0.1
author: SignalOverviewGet random ship names from Ian Banks’ Culture novelsInstallation / UsageTo install use pip:$ pip install shipnamesOr clone the repo:$ git clonehttps://github.com/signalrock/shipnames.git$ python setup.py installUsageshipnames.py [-l | -s] [-a] [<amount>]Options:-h –help   Show this screen
-l          Lowercase
-s          Slugify (spaces and punctuation become hyphens and lowercase)
-a          Show all in alphabetical orderExample~: python shipnames.py 3Cargo Cult
Nervous Energy
Highpoint~: python shipnames.py 5 -ssubtle-shift-in-emphasis
unacceptable-behaviour
now-we-try-it-my-way
reasonable-excuse
its-character-forming