Saravanan666/pypi-org huggingface dataset:
Package: dash-chalice
dash-chaliceThis package integratesPlotly DashwithAWS Chalice. It provides aDashChaliceobject which is largely a slot-in replacement fordash.Dash, but with the underlying Flask server object replaced with a Chalice one. It aims to provide a more natural path for deployment using AWS Lambda thanZappa.A simple example is given below. Note that Chalice expects projects to have a particular structure. To run this example, save the code below asapp.pyand include an empty JSON object{}within.chalice/config.jsonin the same directory. The example can then be run locally withchalice local.importdash_html_componentsashtmlimportdash_core_componentsasdccfromdash.dependenciesimportInput,Outputfromdash_chaliceimportDashChalicedash_app=DashChalice(__name__,title="Example")dash_app.layout=html.Div([dcc.Input(id="input",placeholder="Please type a name"),html.Div(id="output"),])@dash_app.callback(Output("output","children"),Input("input","value"),)defset_output(input):return"Hello!"ifinputin(None,"")elsef"Hello{input}!"# this needs to be called after the dash app has been set updash_app.finalise()# nb: chalice expects an app variable to be exposed for running/deploymentapp=dash_app.serverFor more information on structuring and deploying apps with Chalice, see thedocumentation. In addition, you may findthese workshop notesuseful, as I have.
Package: dash-charlotte
Dash CharlotteA package of themes, tools and components for Plotly-Dash web dashboards.TL;DR:This is a personal project, so I'd suggest not taking this too seriously.Dash Charlotte is...... a package to speed up the creation of dashboards with standardized components;... a bunch of components that I often use on my personal projects.Dash Charlotte is NOT...... ready for production use. The structure, arguments or behavior of the components are not set in stone and change regularly depending on the ease of use observed in testing;... created in React (yet). Because of this, some components might not follow Dash rules and standards.SubmodulesClick on the following link to check each submodule documentation.Components: A set of standard Dash components for a fast and modular dashboard building.Themes: Tools for easy and consistent styling. Colors, fonts, icon packages and CSS stuff.Layouts: Some pre-built page layouts.Instatlationpip install dash-charlotteLicenseMITGetting StartedCheck theexample appor thelive demo.
Package: dash-chartist
dash-chartistMinimalDashwrapper forreact-chartistlibrary.Code Snippetfrom dash_chartist import DashChartist
import dash
from dash import  html

external_stylesheets = [
    "https://cdnjs.cloudflare.com/ajax/libs/chartist/0.3.1/chartist.min.css",
    ]

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)


data = {
    "labels": ['W1', 'W2', 'W3', 'W4', 'W5', 'W6', 'W7', 'W8', 'W9', 'W10'],
    "series": [ [1, 2, 4, 8, 6, -2, -1, -4, -6, -2] ]
}

options = {
    "high": 10,
    "low": -10,
}

chartType = 'Bar'

app.layout = html.Div([
    DashChartist(type=chartType, options=options, data=data)
])


if __name__ == '__main__':
    app.run_server(debug=False, host="0.0.0.0", port=5000)InstallationYou can installdash-chartistwithpip:pip install dash-chartistDocumentationHead over to theREADMEfor more details.ContributingThe source code fordash-chartistis availableon GitHub. If you find a bug or something is unclear, we encourage
you to raise an issue. We also welcome contributions, to contribute, fork the
repository and open apull request.
Package: dash-chartjs
Dash Chartjs ComponentChart.js is one the most popular javascript charting library.
Dash Chartjs Component is a Dash component library that rendersChartJs React componentinside Dash App.Installationpip install dash-chartjsProp Listid (str):The ID used to identify this component in Dash callbacks.type (str):Chart.js chart type.data (dict):The data object that is passed into the Chart.js chart.options (dict):The options object that is passed into the Chart.js chart.toolbox (boolean):Toolbox with reset and download buttons for chart.linearGradientList (list):List of colors for the Linear Gradient.linearGradientDirection (str):Set the direction of Linear Gradient. Either 'horizontal' or 'vertical'. Vertical is default.useGradient (str):Apply Linear Gradient on 'borderColor', 'backgroundColor' or on 'both'. Applies on both by default.customCanvasBackgroundColor (str):Set the Background color of Canvas.clickData (dict):clickData returns the datasetIndex and index of data point clicked.style (dict):Defines CSS styles which will override styles previously set.Additional Plugins Integratedchartjs-plugin-zoomBasic Configuration'options':{'plugins':{'zoom':{'zoom':{'wheel':{'enabled':True,},'pinch':{'enabled':True},'mode':'xy',}}}}chartjs-plugin-datalabelsBasic Configuration'options':{'plugins':{# Change options for ALL labels of THIS CHART'datalabels':{'color':'#36A2EB'}}},'data':{'datasets':[{# Change options only for labels of THIS DATASET'datalabels':{'color':'#FFCE56'}}]}Examplechartjs-plugin-annotationBasic Configuration'options':{'plugins':{'annotation':{'annotations':{'box1':{# Indicates the type of annotation'type':'box','xMin':1,'xMax':2,'yMin':50,'yMax':70,'backgroundColor':'rgba(255, 99, 132, 0.25)'}}}}}ExampleBasic Usagefromdashimportdash,htmlimportpandasaspdfromdash_chartjsimportChartJsapp=dash.Dash(__name__,meta_tags=[{"name":"viewport","content":"width=device-width, initial-scale=1"}])df=pd.read_csv('https://raw.githubusercontent.com/JetBlack101/visitors-to-georgia-ts-analysis/main/Data/VisitorsToGeorgia_2011-2019.csv')df['Date']=pd.to_datetime(df['Date'])x=df['Date']y=df['Visitors']data={'labels':x,'datasets':[{'label':'Visitors to Georgia','data':y,'fill':'false','borderColor':'rgb(75, 192, 192)','tension':0.1}]}options={'scales':{'x':{'type':'time'}},'plugins':{'zoom':{'zoom':{'wheel':{'enabled':True},'mode':'xy'}}}}app.layout=html.Div([ChartJs(type='line',data=data,options=options)])if__name__=='__main__':app.run_server(debug=False)Demohttps://user-images.githubusercontent.com/31138706/192035295-0a10eb80-0881-443b-8ea8-7dfd98eb77f3.mp4
Package: dash-chat-components
Dash Chat Componentsdash_chat_components is a library of chat components for Plotly Dash, that makes it easier to build conversational apps.Installationpipinstalldash_chat_componentsDevelopmentGetting StartedCreate a new python environment:python-mvenvvenv
.venv/bin/activateNote: venv\Scripts\activate for windowsInstall python dependencies:pipinstall-rrequirements.txtInstall npm packages:Optional: usenvmto manage node version:nvminstall
nvmuseInstall:npminstallBuild:npmrunbuildComponent CodePublishIf publish on npm:npmbuild
npmpublishJustfileAlternatively, use the providedjustcommands:Create a Python environment from previous step 1 and install:justinstallBuildjustbuildPublishjustpublishSee all commands withjust -l
Package: dash-cm
dash_cmInstallpipinstall--upgradedash_cmOptionally:sudotee/usr/local/bin/dashcm>/dev/null<<EOT#!/usr/bin/bashexec "python" -m dash_cm "\$@"EOTsudochmod+x/usr/local/bin/dashcmAnd then use as executabledashcmserve&To check used ports:netstat -tulpn | grep LISTEN |grep 3000Make '.model' file executableCreate the two following files:/usr/share/mime/packages/cardiac-model.xml<?xml version="1.0" encoding="UTF-8"?>
    <mime-info xmlns="https://www.freedesktop.org/standards/shared-mime-info">
    <mime-type type="application/zip">
        <comment xml:lang="en">Cardiac Model</comment>
        <glob pattern="*.model"/>
        <glob pattern="*.zip"/>
    </mime-type>
</mime-info>/usr/share/applications/cardiac-model.desktop[Desktop Entry]
Encoding=UTF-8
Version=1.0
Type=Application
Terminal=true
Exec=dashcm load %F
Name=CardiacModel
Icon=<path-to>/dash_cm/build/static/icons/logo_512.png
Package: dash-cognito-auth
Dash Cognito AuthDash Cognito Auth is a simple library using Cognito OAuth to authenticate and
view aDashapp.This Library usesFlask Danceand a modified version of Plotly's owndash authfor authentication.This Library is heavily inspired bydash-google-oauthcreated by Lucas ChapinBasic UseAuthentication can be added to your Dash application using theCognitoOAuthclass, i.e.fromdashimportDashfromflaskimportFlaskfromdash_cognito_authimportCognitoOAuthserver=Flask(__name__)server.config.update({'COGNITO_OAUTH_CLIENT_ID':...,'COGNITO_OAUTH_CLIENT_SECRET':...,})app=Dash(__name__,server=server,url_base_pathname='/',auth='auth')additional_scopes=[...]auth=CognitoOAuth(app,domain='mydomain',region='eu-west-1',authorized_emails,additional_scopes)# your Dash app here :)...ExampleSteps to try this out yourself:Install thedash-cognito-authlibrary usingpip:$pipinstalldash-cognito-authFollow theFlask Dance Guideto create an app on the cognito admin consoleMake a copy ofapp.pyand set the variables (or set the corresponding environment variables):server.config["COGNITO_OAUTH_CLIENT_ID"]=...server.config["COGNITO_OAUTH_CLIENT_SECRET"]=...with values from the Cognito OAuth 2 client you should have set up in step 1.
If you've set these up properly, you can find them atAPIs & Services > Credentialsunder the sectionOAuth 2.0 client IDs.Runpython app.pyand openlocalhostin a
browser window to try it out! If the app loads automatically without
prompting a Cognito login, that means you're already authenticated -- try
using an incognito window in this case if you want to see the login
experience for a new user.
Package: dash-component-editor
MLExchange Dash component editorThis script creates adaptive Dash GUI components from keyword pairs (JSON format).It currently supports 8 types of Dash GUI components: 3 types ofinput forms(int, float, str),slider,dropdown,radio items,boolean toggle switch, andimage. The corresponding keyword values are 'int', 'float', 'str', 'slider', 'dropdown', 'radio', 'bool', and 'img'.Legal keyword pairs: {'type': xxx, 'name': xxx, 'title': xxx, 'param_key': xxx, 'value': xxx} and all the other legal keyword pairs in the corresponding Dash components.Note: 'name' is the unique string identifier for each component.Dependencies:dash>=2.9.0
dash_bootstrap_components>=1.0.0
dash_daq>=0.1.0Code examplefromdashimportDash,html,Input,Outputfromdash_component_editorimportJSONParameterEditor# datacomponent_kwargs={"gui_parameters":[{"type":"int","name":"num-tree","title":"Number of Trees","param_key":"n_estimators","value":"30"},{"type":"dropdown","name":"dropdown-menu","title":"Choose a City","param_key":"city","options":[{'label':'New York City','value':'New York City'},{'label':'Montreal','value':'Montreal'},{'label':'San Francisco','value':'San Francisco'}],"value":"'Montreal"},{"type":"slider","name":"slider-id","title":"Fahrenheit Range","param_key":"f_temp","min":0,"max":10,"step":None,"marks":{0:'0°F',3:'3°F',5:'5°F',7.65:'7.65°F',10:'10°F'},"value":5},]}# set up Dash server and web layoutsapp=Dash(__name__)app.layout=html.Div([html.Button('Show GUI',id='button',n_clicks=0),html.Div(id='gui-layout',children=[])])# callback@app.callback(Output("gui-layout","children",allow_duplicate=True),Input("button","n_clicks"),prevent_initial_call=True)defshow_gui_layouts(n_clicks):item_list=JSONParameterEditor(_id={'type':'parameter_editor'},json_blob=component_kwargs["gui_parameters"],)item_list.init_callbacks(app)return[html.H5("GUI Layout",className="card-title"),item_list]app.run_server(host='0.0.0.0',port=8050,debug=True)
Package: dash-cool-components
Dash Cool ComponentsCool React components, wrapped for Plotly DashTable of contentsInstallationQuick StartInstallationpipinstalldash-cool-componentsComponentsDatetime PickerA date-time-timezone picker input. Implemented with theReact DatepickerandTimezone Picker Reactcomponents.Component Properties:ArgumentValueDescriptionidstringThe ID used to identify this component in Dash callbacks.valuestringThe input's current value, on ISO format with date, time and timezone.renderTimezonebooleanDefines if the timezone input should be rendered. Defaults to true.placeholderstringThe date input placeholder.timezonePlaceholderstringThe timezone input placeholder.styleobject or stringThe component container's style. Can be a style object or a css string.dateInputStyleobject or stringThe date input's style. Can be a style object or a css string.timezoneInputStyleobjectThe timezone container's style. Must be a style object.Example FileKeyed File BrowserFile and directory browser given a flat keyed list of objects. Implemented withReact Keyed File Browser.Component PropertiesArgumentValueDescriptionidstringThe ID used to identify this component in Dash callbacks.selectedPathstringThe current selected path in the file tree.filesarrayThe file tree to be displayed in the browser. Each entry in the array must be an object with thekeyproperty, which specifies it's location in the tree. Otherproperties aremodifiedandsize. To be able to receive the path selection feedback, you must enter keys for both files and folders.Example FileTag InputA tag input component. Implemented withReact Tag Input.Components PropertiesArgumentValueDescriptionidstringThe ID used to identify this component in Dash callbackswrapperStyleobject or stringThe component wrapper's style. Can be either a style object or a CSS string.tagStyleobject or stringThe tag's style. Can be either a style object or a CSS stringinputStyleobject or stringThe text input's style. Can be either a style object or a CSS string.tagDeleteStyleobject or stringThe tag delete button's style. Can be either a style object or a CSS string.placeholderstringPlaceholder for the text inputplaceholderstringPlaceholder for the text inputvaluearrayThe input's current tags array of objects. e.g [{"index": 0, "displayValue": "Tag"}]injectedTagsarrayTags to be inserted on the input. The input's atual tags are replaced.Example File
Package: dash-core-components
NoticeAs of Dash 2, the development of dash-core-components has been moved to themain Dash repoThis package exists for backward compatibilityDash Core ComponentsThis package provides the core React component suite forDash.DevelopmentThedashpackage contains some tools to build components and drive the bundles build process.
To avoid the circular dependency situation, we don't adddashas a required install in thedash-core-componentssetup.
But, in order to do development locally, you need to installdashbefore everything.Install the dependencies with:# it's recommended to install your python packages in a virtualenv# python 2$pipinstallvirtualenv--user&&virtualenvvenv&&.venv/bin/activate# python 3$python-mvenvvenv&&.venv/bin/activate# make sure dash is installed with dev and testing dependencies$pipinstalldash[dev,testing]# in some shells you need \ to escape []# run the build process$npmi--ignore-scripts&&npmrunbuild# install dcc in editable mode$pipinstall-e.Code quality and testsTo run integration tests (test_integration.py)You can run the Selenium integration tests with thenpmtestTesting your components in DashRun the build watcher by running
$ npm run build:watchRun the dash layout you want to test# Import dash_core_components to your layout, then run it:
 $ python my_dash_layout.pyUninstalling python package locally$npmrununinstall-localPublishingThere's an npm script that will handle publish, provided you have the right credentials. You can run it by running$npmrunpublish-allSee thePublishing New Components/Featuressection of the Contributing guide for step-by-step instructions on publishing new components.Dash Component BoilerplateSee thedash-component-boilerplaterepo for more information.Big ThanksCross-browser Testing Powered by
Package: dashcrypt
Dash Crypt adalah sebuah pustaka untuk enkrpsi sebuah text. Pustaka ini
terdapat beberapa macam mode enkripsi.Cara kerjaAlat ini menggunakan algoritma yang sangat mudah untuk di pelajari,
bahkan kalangan newbie atau pemula dapat memahami algoritma yang saya
buat sendiri. 1. Pertama kita ubah dahulu text atau string ke hash, Dash
Crypt telah mendukung beberapa hash yaitu - MD5 - SHA1 - SHA224 - SHA512
- BLAKE2BKedua, lalu kita ubah hash tersebut menggunakan algoritma yang sudah
dibuatKetiga, setelah itu kita tambahkan bilangan biner yang telah di acakContohfromdashcrypt.encryptimportEncrypts="Hello Indonesia".encode()e=Encrypt(s)e.setMode(False)result=e.crypt(mode=0)print(result)Lihat lain nya diSampleFungsiEncryptsetModemempunyai argumen bertipe boolean, berfungsi untuk
mengaktifkan automode (mendeteksi mode secara otomatis)cryptmempunyai argumen bertipe integer, berfungsi untuk
mengenkripsi text.generateHashtidak mempunyai argumen apapun, berfungsi untuk
mengubah text ke hash (md5, sha1, sha224, sha512, blake2b)
Package: dash-cute-charts
💡 Ideachart.xkcd-react📊 is an interesting visualization library written in React based on chart.xkcd, the chart style ofchart.xkcd-reactis so beautiful that I love it at first sight. 😍😍There is no doubt that Modern JavaScript has more advantages in interaction as well as visual effects. Besides that, as we all know, Python 🐍 is an expressive language and is loved by data science community. To build data sciecne products the community love to usedash. I tried to combine both dashplotly withchart.xkcd-reactended up building thedash_cute_chartscomponent for dash.Get started with demo example:git clone https://github.com/muntakim1/dash_cute_charts.gitInstall Dash and its dependencies:https://dash.plotly.com/installationRunpython usage.pyVisithttp://localhost:8050in your web browser, Click here for theLive DemoUsage 👨‍🏫What's new 🍭:1. Added new charts (stacked,scatter and radarcharts)
2. Fixed some bugs.InstallInstall the dash-cute-charts from pypip using below commandpip install dash-cute-chartsUsage with Dashimportdashimportdash_html_componentsashtmlfromdash.dependenciesimportInput,Outputimportdash_cute_chartsapp=dash.Dash(__name__)app.layout=html.Div([# Pie Chartdash_cute_charts.PieChart(id="pieChart",title="What Tim made of",dataset=[{"data":[500,200,80,90,100],}],labels=["a","b","e","f","g"],options=[{"innerRadius":0.5,}],),# Line Chartdash_cute_charts.LineChart(id="lineChart",title="Monthly income of an indie developer",xLabel="Month",yLabel="$ Dollors",labels=["1","2","3","4","5","6","7","8","9","10"],dataset=[{"label":"Plan","data":[30,70,200,300,500,800,1500,2900,5000,8000],},{"label":"Reality","data":[0,1,30,70,80,100,50,80,40,150],},],),# BarChartdash_cute_charts.BarChart(id="barchart",title="github stars VS patron number",dataset=[{"data":[100,2],}],labels=["github stars","patrons"],options=[{"yTickCount":2}],),])if__name__=="__main__":app.run_server(debug=True)Components 🧱SeeCOMPONENTS.mdContributingSeeCONTRIBUTING.mdInstall dependenciesIf you have selected install_dependencies during the prompt, you can skip this part.Install npm packages$ npm installCreate a virtual env and activate.$ virtualenv venv
$ . venv/bin/activateNote: venv\Scripts\activate for windowsInstall python packages required to build components.$ pip install -r requirements.txtInstall the python packages for testing (optional)$ pip install -r tests/requirements.txtRun code in a Python environment:Build your code$ npm run buildRun and modify theusage.pysample dash app:$ python usage.pyMaintainer 🤵Muntakimur RahamanIBM Certified Data Scientistwebsite:www.muntakim.xyzCredits 🙏chart.xkcd-reactchart.xkcd📃 LicenseMIT©muntakim
Package: dash-daq
dash_daqDAQ components for Dash.Docs:https://dash.plotly.com/dash-daqInstallationpip install dash_daq(Or for Python 3,pip3 install dash_daq)Getting started for contributors# Clone this repositorygitclonehttps://github.com/plotly/dash-daq.git# Install dependencies$yarn# Watch source for changes and build to `lib/`$yarnstartDocumentationComponent API documentation can be found athttps://dash.plotly.com/dash-daqDevelopmentDemo serverYou can start up a demo development server to see a demo of the rendered
components:$yarndemo
$openhttp://localhost:9000You have to maintain the list of components indemo/Demo.react.js.Code quality and testsTo run lint and unit tests:$yarntestTesting your components in DashBuild development bundle tolib/and watch for changes# Once this is started, you can just leave it running.
 $ yarn startInstall module locally (after every change)# Generate metadata, and build the JavaScript bundle
 $ yarn install-local

 # Now you're done. For subsequent changes, if you've got `yarn start`
 # running in a separate process, it's enough to just do:
 $ python setup.py installRun the Dash demo$ python demo.pyInstalling python package locallyBefore publishing to PyPi, you can test installing the module locally:# Install in `site-packages` on your machine$yarnruninstall-localUninstalling python package locally$yarnrununinstall-localProducing a new release as a tarballvimdash_daq/version.py# and increase it to X.X.Xrm-rfnode_modulesdistbuildlib
yarninstall
yarnbuild-tarball
lsdist/dash_daq-X.X.X.tar.gz# this is your tarballDemo applicationsDash Daq HP Multimeter -http://dash-gallery.plotly.host/dash-daq-hp-multimeterDash Daq IV Tracer -http://dash-gallery.plotly.host/dash-daq-iv-tracerDash Daq LED Control -http://dash-gallery.plotly.host/dash-daq-ledDash Daq Omega PID -http://dash-gallery.plotly.host/dash-daq-omega-pidDash Daq Pressure Gauge KJL -http://dash-gallery.plotly.host/dash-daq-pressure-gauge-kjlDash Daq Pressure Gauge Pfeiffer -https://dash-gallery.plotly.host/dash-daq-pressure-gauge-pvDash Daq Robotic Arm Edge -http://dash-gallery.plotly.host/dash-daq-robotic-armDash Daq Sparki -http://dash-gallery.plotly.host/dash-daq-sparkiDash Daq Stepper Motor -http://dash-gallery.plotly.host/dash-daq-stepper-motorDash Tektronix 350 -http://dash-gallery.plotly.host/dash-daq-tektronix350Dash Ocean Optics -http://dash-gallery.plotly.host/dash-ocean-optics
Package: dash-dashy
DashyA small framework built on top ofPlotly DashandDash Bootstrap Componentsintended to make it easy and quick to build dashboards without having to think about all the small details.How To Use|Key Features|Future|Credits|LicenseInstallpipinstalldash-dashyKey FeaturesSimpler callbacksDash callbacks usually looks like@app.callback(Output('container','children'),Input('btn-1','n_clicks'),Input('btn-2','n_clicks'),Input('btn-3','n_clicks'),State('dropdown','value'))defsome_callback_func(...):...In order to make callbacks less verbose Dashy apps has its own callback decorator using only list and tuples as arguments. The example above reduces to@app.cb(inputs=[('btn-1','n_clicks'),('btn-2','n_clicks'),('btn-3','n_clicks')],outputs=('container','children'),states=('dropdown','value'))defsome_callback_func(...):...Dashy also assume an implicit order of the decorator arguments which is, inputs -> outputs -> states. This is handy for simple callbacks like# callback taking buttons clicks as input and outputs 'children' to 'container'@app.cb(('btn-1','n_clicks'),('container','children'))defsome_callback_func(...):...Dashy callbacks also does not require an explicit output.# do something when the button is clicked@app.cb(('btn-1','n_clicks'))defsome_callback_func(...):...High level function componentsAll components in Dashy are functions, import what you need or everything# import individual componentsfromdashy.componentsimportnavbar,button,graph,dropdown# orimportdashy.componentsasdcLayoutDashy utilizes bootstrap's grid system and tries to handle as much of the layout as possible while still making the dashboards look good. Import thecontainerrowandcolcomponents and build your layout.fromdashy.componentsimportcontainer,row,collayout=container([row([# your components]),col([# more components])])Complete app exampleBuilding an app with a navbar, tabs and a callback to switch tabs becomesfromdashyimportcreate_appfromdashy.componentsimportnavbar,tabs,divapp=create_app(__name__,layout=[navbar('My App',dark=True),tabs(id='tabs',labels=['Tab1','Tab2','Tab3'],content_id='tab-content')])@app.cb(('tabs','active_tab'),('tab-content','children'))defswitch_tabs(tab_id:str):returndiv(f'Hello from{tab_id}')if__name__=="__main__":app.launch()FutureIntegrate all components with bootstrap themesDashboard templatesCreditsThis software uses the following awesome open source packages:Plotly DashDash Bootstrap ComponentsLicenseMIT