Saravanan666/pypi-org huggingface dataset:
Package: bokeh
Bokehis an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics and affords high-performance interactivity across large or streaming datasets. Bokeh can help anyone who wants to create interactive plots, dashboards, and data applications quickly and easily.PackageProjectDownloadsBuildCommunityConsidermaking a donationif you enjoy using Bokeh and want to support its development.InstallationTo install Bokeh and its required dependencies usingpip, enter the following command at a Bash or Windows command prompt:pip install bokehTo installconda, enter the following command at a Bash or Windows command prompt:conda install bokehRefer to theinstallation documentationfor more details.ResourcesOnce Bokeh is installed, check out thefirst steps guides.Visit thefull documentation siteto view theUser's Guideorlaunch the Bokeh tutorialto learn about Bokeh in live Jupyter Notebooks.Community support is available on theProject Discourse.If you would like to contribute to Bokeh, please review theContributor Guideandrequest an invitation to the Bokeh Dev Slack workspace.Note: Everyone who engages in the Bokeh project's discussion forums, codebases, and issue trackers is expected to follow theCode of Conduct.Follow usFollow us on Twitter@bokehSupportFiscal SupportThe Bokeh project is grateful forindividual contributions, as well as for monetary support from the organizations and companies listed below:If your company uses Bokeh and is able to sponsor the project, please contactinfo@bokeh.orgBokeh is a Sponsored Project of NumFOCUS, a 501(c)(3) nonprofit charity in the United States. NumFOCUS provides Bokeh with fiscal, legal, and administrative support to help ensure the health and sustainability of the project. Visitnumfocus.orgfor more information.Donations to Bokeh are managed by NumFOCUS. For donors in the United States, your gift is tax-deductible to the extent provided by law. As with any donation, you should consult with your tax adviser about your particular tax situation.In-kind SupportNon-monetary support can help with development, collaboration, infrastructure, security, and vulnerability management. The Bokeh project is grateful to the following companies for their donation of services:Amazon Web ServicesGitGuardianGitHubmakepathPingdomSlackQuestionScout1Password
Package: bokehgraph
bokeh-graphInteractive Graph visualization for networkX GraphsBasic UsagefrombokehgraphimportBokehGraphimportnetworkxasnxgraph=nx.karate_club_graph()plot=BokehGraph(graph)plot.draw()Jupyter NotebooksTo show graphs inlined in Jupyter Notebooks set theinlineparameterplot=BokehGraph(graph,width=300,height=300,inline=True)Draw parametersTheBokehGraph.draw()method has a couple of parameters to individualize the resulting plot:node_color="firebrick"
Set node color to any valid bokeh color (only respected if color_by is not set)

palette=None
Set palette to any valid bokeh color palette.
A list of palettes can be found under: https://docs.bokeh.org/en/latest/docs/reference/palettes.html

color_by=None
Set to a node attribute to color nodes by this attribute

edge_color="navy"
Set node color to any valid bokeh color

edge_alpha=0.17
Set edge alpha to a value between [0,1]

node_alpha=0.7
Set edge alpha to a value between [0,1]

node_size=9
Set node size

max_colors=-1
Set a maximum number of colors for color_by (or -1 to use as many colors as possible).
This must be < 256 and lower than the maximum number of colors of your selected palette.
It will divide the attribute space into evenly spaced to colors.
Package: bokehmol
bokehmol, gotta plot them mol! ⌬bokehmolprovides custom extensions that help plotting molecules with theBokehlibrary.It currently provides hover tools that can depict moleculeson-the-flyusing SMILES: no need to
pre-generate the depictions and store them in memory anymore! Everything is rendered client-side in
the browser so you don't even need to install rdkit in your Python environment.InstallationBokehmol only requires bokeh as a dependency. You can install it with:pip install bokehmolNotebooksSome examples on how to use the libraryhereDiscussionsFeature requests or questions on how to use should be postedhereIssuesBugtracker🐞
Package: bokeh-plot
bokeh-plotInstallation:pip install bokeh-plotUsage:To load this extension in jupyter notebook:%load_ext bokeh_plotThe following syntax is supported:plot([1,4,9])             # x is automatic 
plot([1,4,9], '.-')       # line and dots 
plot([1,2,3], [1,4,9])    # x and y 
plot([1,2,3], [1,4,9], '.-')    # x, y and line styleSeveral plots in one figure:Interactive controls:click and drag = pan
mouse wheel = zoom, 
wheel on x axis = scroll horizontally
wheel on y axis = scroll verticallyMultiple plot syntax (equivalent ways to draw it):x = [1,5,10]
y1 = [1,4,9]
y2 = [1,8,27]

- plot(x, y1, '.-')        # solid line with dots
  plot(x, y2, '.-g')       # the second plot is green

- plot([y1, y2])           # auto x, auto colors       

- plot(x, [y1, y2])

- plot([y1, y2], '.-bg')   # blue and green

- plot([y1, y2], style=['.', '.-'], color=['b', 'g'])

- plot(x, y1, '.-', x, y2, '.-g')The following markers are supported so far:'.' dots
'-' line
'.-' dots+lineThe following colors are supported so far:'b' blue
'g' green
'r' red
'O' orange  (capital O to avoid clashes with 'o' for open dots)NB The color specifier must go after the marker if both are present.Legend:- plot([1,2,3], [1,4,9], label='plot1')
  plot([1,2,3], [2,5,10], label='plot2')

- plot([y1, y2], label=['y1', 'y2'])Legend location:- plot([1,2,3], [1,4,9], label='plot1', legend_loc='top_left')
  plot([1,2,3], [2,5,10], label='plot2')Other legend locations:https://docs.bokeh.org/en/latest/docs/user_guide/styling.html#locationAxes labels:- plot([1,2,3], xlabel='time', ylabel='value')
- xlabel('time'); ylabel('value')
- xylabels('time', 'value')Several images side by side:(bp stands for bokeh.plot, bl is is a shortcut for bokeh.layouts)
There're three common layouts:bl.row,bl.columnandbl.gridplot(the former two accept list of figures,
the latter one accepts a list of lists of figures).Other uses:semilogx(),semilogy()andloglog()show (semi)logarithmic plots with the same syntax asplot().hist(x)displays a histogram of xplot(x, y, hover=True)displays point coordinates on mouse hover.plot(x, y, vline=1, hline=1.5, vline_color='red')in addition to the (x, y) plot displays an infinite vertical line with x=1 and custom red color and an infinite horizontal line with y=1.5 and the default pink color.plot(df)plots all columns of the dataframe as separate lines on the same figure with column names
displayed in the legend and with index taken as the x axis values. If the legend grows too long, it can
be hidden withlegend_loc='hide'(new in v0.1.13):show_df(df)displays pandas dataframe as a table (new in v0.1.14):imshow(a)displays an array as an image:Complete list of palettes:https://docs.bokeh.org/en/latest/docs/reference/palettes.htmlSee also a contour plot example in the bokeh gallerypageComparison to bokehbokeh-plot is a thin wrapper over the excellent bokeh library that cuts down the amount of boilerplate code.The following two cells are equivalent:
Package: bokeh-resources
bokeh-resourcesBokeh (https://bokeh.org/) Python plotting library has two main modes for serving static content: CDN and inline.'cdn' (=content distribution network) mode needs internet connection every time you open the notebook'inline' mode increases the size of ipynb files by 6Mbbokeh-resourcesis a jupyter extension that makes jupyter serve bokeh files locally.It keeps the size of ipynb files small and works offline as well.Installation:Install the nbextensions if you haven't already:pipinstalljupyter_contrib_nbextensions&&jupytercontribnbextensionsinstallThen eitherpipinstallbokeh-resources
python-mbokeh_resources.installOrgitclonehttps://github.com/axil/bokeh-resourcescdbokeh_resources/bokeh_resources
pythoninstall.pyThis will install the extension to jupyter and to create the symlink (see 'Updating' below)After this the package itself can be safely uninstalled (pip uninstall bokeh-resources).To uninstall the extension runjupyter nbextensions uninstall bokeh_resourcesUsage:In bokehlab:%bokehlablocalIn bokeh:frombokeh.ioimportoutput_notebookfrombokeh.resourcesimportResourcesoutput_notebook(Resources('server',root_url='/nbextensions/bokeh_resources'))Updating:Serving is performed through a symbolic link (or a directory junction on Windows).This means that it is resilient to bokeh updates.(= the extension does not need to be updated whenbokehis updated to the next version).The extension needs to be updated when switching to a different python version. Use
argument -f/--force to force overwriting of the symlink to the uptodate bokeh resources
directory witin the current python version:python-mbokeh_resources.install-f
Package: bokeh-root-cmd
bokeh-root-cmdCommand line wrapper to run one or more named Bokeh/Panel scripts/folders as root URL.This project is used inContainDS Dashboards, which is a user-friendly
way to launch Jupyter notebooks as shareable dashboards inside JupyterHub. Also works with Bokeh, Dash, Panel, Streamlit and other visualization frameworks.The published PyPI/Conda packages DO NOT bring in Bokeh or Panel as explicit dependencies, so you may
need to install those separately in your environment.Install and RunInstall using pip.pipinstallbokeh-root-cmdThe file to start is specified on the command line, for example:bokeh-root-cmd~/Dev/mybokehscript.pyBy default the server will listen on port 8888. To specify a differentport, use the --port flag.bokeh-root-cmd--port=8888~/Dev/mybokehscript.pyTo use the Panel server use the --server flag.bokeh-root-cmd--server=panel~/Dev/mybokehscript.pyTo run directly in python:python -m bokeh_root_cmd.main <rest of command line>Other command line args--allow-websocket-origin--debug--ipTestsIn order to be able to test manually you would need topip install panel pytest. This will also install bokeh.Automated Testspytesttests.pySingle File on Bokeh ServerRunbokeh-root-cmd test_apps/test_bokeh_hello.pyand verify the app is running athttp://localhost:8888.Single File on Panel ServerRunbokeh-root-cmd --server=panel test_apps/test_panel_hello.pyand verify the app is running athttp://localhost:8888.Multiple Files on Bokeh ServerRunbokeh-root-cmd test_apps/*.pyand verify the app index is running athttp://localhost:8888and test apps athttp://localhost:8888/test_bokeh_helloandhttp://localhost:8888/test_panel_hello.Multiple Files on Panel ServerRunbokeh-root-cmd --server=panel test_apps/*.pyand verify the app index is running athttp://localhost:8888and test apps athttp://localhost:8888/test_bokeh_helloandhttp://localhost:8888/test_panel_hello. Note that no `ready-check' app is included in the index list.You can also specify them individuallyRunbokeh-root-cmd --server=panel test_apps/test_bokeh_hello.py test_apps/test_panel_hello.pyand verify the app index is running athttp://localhost:8888and test apps athttp://localhost:8888/test_bokeh_helloandhttp://localhost:8888/test_panel_hello. Note that no `ready-check' app is included in the index list.Thank you toMarcSkovMadsenfor contributions.Changelog0.1.2 - Fix for Panel root dashboard when serving multiple apps. Previously caused problems in some browsers.
Package: bokeh-wordcloud2
bokeh_wordcloud2a (mostly complete) bokeh implementation ofwordcloud2-jsThis extension attempts to make wordcloud available inside the bokeh ecosystemThis was made as part of a learning project to make bokeh widgets, but it was too good not to share.Installationpip install git+https://github.com/joranbeasley/bokeh_wordcloud2.gitor you can clone this repo and runsetup.py installorpip install <git_checkout_directory>Documentation>>> |Read The Docs| <<<and try theinteractive jupyer notebookand check out theexamples
Package: bokkichat
bokkichatmasterdevelopBokkichat is a python library that offers unified interfaces for interacting
with different chat services.As an example, it could be used to write a bot for both Whatsapp and Telegram
without many service-specific alterations.A project that extends this idea iskudubot.Implemented Connection TypesCurrently the following connection types are supported out of the box:CLITelegram (Bot)InstallationInstalling bokkichat is as simple as runningpip install bokkichat, orpython setup.py installwhen installing from source.UsageFirst, you'll need to initialize the correct Settings object, which can then be
used to initialize the Connection.frombokkichat.settings.impl.TelegramBotSettingsimportTelegramBotSettingsfrombokkichat.connection.impl.TelegramBotConnectionimportTelegramBotConnectionsettings=TelegramBotSettings("APIKEY")connection=TelegramBotConnection(settings)Afterwards, you can send, receive and loop using the Connection object.Some examples:# Sending a messagefrombokkichat.settings.impl.TelegramBotSettingsimportTelegramBotSettingsfrombokkichat.connection.impl.TelegramBotConnectionimportTelegramBotConnectionfrombokkichat.entities.message.TextMessageimportTextMessagefrombokkichat.entities.AddressimportAddresssettings=TelegramBotSettings("APIKEY")connection=TelegramBotConnection(settings)receiver=Address("12345678")msg=TextMessage(connection.address,receiver,"BODY","TITLE")connection.send(msg)# Echo every received messagefrombokkichat.settings.impl.TelegramBotSettingsimportTelegramBotSettingsfrombokkichat.connection.impl.TelegramBotConnectionimportTelegramBotConnectionfrombokkichat.connection.ConnectionimportConnectionfrombokkichat.entities.message.MessageimportMessagesettings=TelegramBotSettings("APIKEY")connection=TelegramBotConnection(settings)defecho(con:Connection,msg:Message):reply=msg.make_reply()con.send(reply)connection.loop(echo)Implementing your own connection typeIf the connection type you want to use is not implemented by bokkichat itself,
you can always implement it yourself. To do so, you will need to implement two
classes.First off, you'll need to implement a subclass of theSettingsclass
and implement its abstract methods. Take a look at the implementation of
various Settings classesherefor some inspiration.The Settings class defines the authentication information required for the
bot to function.Afterwards, a subclass of theConnectionclass must be implemented.
Again, implement the abstract methods and let yourself be inspired byprevious implementationsThe Connection class defines how to communicate with the service itself.These two classes define everything that's needed for a bokkichat connection.Further InformationChangelogLicense (GPLv3)GitlabGithubProgstatsPyPi
Package: boklib
boklibusagefrom boklib import bok

api_key = 'example' # get an api key in this site: https://ecos.bok.or.kr/jsp/openapi/OpenApiController.jsp?t=main
lang = '' # 'kr'or 'en'
state_code = '' # get a state_code in table_list or get a state_code in item_list
cycle = '' # get a cycle in item_list
start_date = '' # get a start_date in item_list
end_date = '' # get a end_date in item_list
item_code = '' # get a item_code in item_list

bok = bok(api_key, lang)
result_key_list = bok.key_List()
result_table_list = bok.table_list()
result_item_list = bok.item_list(stat_code)
result_search = bok.search(stat_code, cycle, start_date, end_date, item_code)
result_meta = bok.meta(meta_search_word) # maybe korean language only - site: https://ecos.bok.or.kr/jsp/use/metadata/MetaData.jsp
result_word = bok.word(search_word) # maybe korean language only - site: https://ecos.bok.or.kr/jsp/use/metaword/MetaDataWordList.jsp

for result in result_key_list['row']:
  class_name =  result['CLASS_NAME']
  keystat_name = result['KEYSTAT_NAME']
  data_value = result['DATA_VALUE']
  cycle = result['CYCLE']
  unit_name = result['UNIT_NAME']
  print('class_name = %s, keystat_name = %s, data_value = %s, cycle = %s, unit_name = %s' % (class_name, keystat_name, data_value, cycle, unit_name))

#
# --- result example ---
# {'list_total_count': {}, 'row' : [] }
#
# print result_key_list
# {'list_total_count' : 1, 'row' : [{'CLASS_NAME' : '', 'KEYSTAT_NAME' : '', 'DATA_VALUE' : '', 'CYCLE' : '', 'UNIT_NAME' : ''}]}
#
# print result_table_list
# {'list_total_count': 1, 'row' : [{'P_STAT_CODE' : '', 'STAT_CODE' : '', 'STAT_NAME' : '', 'CYCLE' : '', 'SRCH_YN' : '', 'ORG_NAME' : ''}] }
#
# print result_item_list
# {'list_total_count' : 1, 'row' : [{'STAT_CODE' : '', 'STAT_NAME' : '', 'GRP_CODE' : '', 'GRP_NAME' : '', 'P_ITEM_CODE' : '', 'ITEM_CODE' : '', 'ITEM_NAME' : '', 'CYCLE' : '', 'START_TIME' : '', 'END_TIME' : '', 'DATA_CNT' : ''}]}
# print result_search
# {'list_total_count' : 1, 'row' : [{'STAT_CODE' : '', 'STAT_NAME' : '', 'ITEM_CODE1' : '', 'ITEM_CODE2' : '', 'ITEM_CODE3' : '', 'UNIT_NAME' : '', 'TIME' : '', 'DATA_VALUE' : ''}]}
#
# print result_meta
# {'list_total_count': 1, 'row' : [{'LVL' : '', 'P_CONT_CODE' : '', 'CONT_CODE' : '', 'CONT_NAME' : '', 'META_DATA' : ''}] }
#
# print result_word
# {'list_total_count': 1, 'row' : [{'WORD' : '', 'CONTENT' : ''}] }
#
Package: bol
Bol.com api connector in pythoninstallpipinstallbolLogin to the api from your projectimportbolBolShop=bol.Client(client_id='d75*****779',client_secret='AK6****quP')ExamplePython3.7.4(default,Oct42019,06:57:26)[GCC9.2.0]onlinuxType"help","copyright","credits"or"license"formoreinformation.>>>importbol>>>BolShop=bol.Client(client_id='d75*****779',client_secret='AK6****quP')loggingin>>>BolShop.BolShop.client_idBolShop.client_secretBolShop.sessionBolShop.token>>>BolShop._BolShop._get(BolShop._login(BolShop._orders(BolShop._post(>>>BolShop._orders(){'orders':[{'orderId':'26000000','dateTimeOrderPlaced':'2019-11-23T18:59:46+01:00','orderItems':[{'orderItemId':'2300004','ean':'5000000','cancelRequest':False,'quantity':1}]}]}>>>>>>Stability?It's pretty stable it has been running production for about a year on version0.1.4
Package: bola
Collection of sphere packing and meshing algorithms.Installationpip3installbolaThec++code requires the math libraryEigen3to be installed and a dependency of the pythongmshpackage islibglu. So, you may need to run (debian/ubuntu-based):sudoaptupdate
sudoapt-yinstalllibeigen3-devlibglu1Alternatively, you can follow the steps of theCI.ExamplesParticle size according tobola.psd.GradingCurve(sieve lines):gc=bola.psd.GradingCurves.fuller(d_min=4.,d_max=16)box=(32.0,32.0,32.0)radii=psd.sample_grading_curve(gc,V=0.5*np.prod(box))Initial packing usingbola.packing.rsa(random sequential addition)spheres=bola.packing.rsa(radii,box)Maximize particle distance usingbola.packing.edmd(event-driven molecular-dynamics)sim=bola.packing.edmd(box,spheres,growth_rate=0.1)whilesim.t()<10.0:sim.process(100*len(radii))sim.synchronize(True)print(packing.stats_string(sim))distant_spheres=sim.spheres()distant_spheres[:,3]=radii# new centers, old radiiMesh via gmsh usingbola.meshbola.mesh.create(box,new_spheres,bola.mesh.GmshOptions(mesh_size_matrix=2.0,mesh_size_aggregates=2.0,out="mesh.xdmf"))
Package: bolbcord
NextcordA modern, easy-to-use, feature-rich, and async-ready API wrapper for Discord written in Python.Fork noticeThis is a fork of discord.py, which unfortunately has beenofficially discontinuedon 28th August 2021.
Nextcord will try to replace discord.py, withcontinued support and features, to still offer former discord.py users a stable API wrapper for their bots.Key FeaturesModern Pythonic API usingasyncandawaitProper rate limit handlingOptimised in both speed and memoryInstallingPython 3.8 or higher is requiredTo install the library without full voice support, you can just run the following command:# Linux/macOSpython3-mpipinstall-Ubolbcord# Windowspy-3-mpipinstall-UbolbcordOtherwise to get voice support you should run the following command:# Linux/macOSpython3-mpipinstall-U"bolbcord[voice]"# Windowspy-3-mpipinstall-Ubolbcord[voice]To install additional packages for speedup, run the following command:# Linux/macOSpython3-mpipinstall-U"bolbcord[speed]"# Windowspy-3-mpipinstall-Ubolbcord[speed]To install the development version, do the following:$gitclonehttps://github.com/bolbcord/bolbcord/$cdbolbcord$python3-mpipinstall-U.[voice]Optional PackagesPyNaCl(for voice support)aiodns,Brotli,cchardet(for aiohttp speedup)orjson(for json speedup)Please note that on Linux installing voice you must install the following packages via your favourite package manager (e.g.apt,dnf, etc) before running the above commands:libffi-dev (orlibffi-develon some systems)python-dev (e.g.python3.8-devfor Python 3.8)Quick Examplefrombolbcord.extimportcommandsbot=commands.Bot(command_prefix='$')@bot.command()asyncdefping(ctx):awaitctx.reply('Pong!')bot.run('token')You can find more examples in the examples directory.NOTE:It is not advised to leave your token directly in your code, as it allows anyone with it to access your bot. If you intend to make your code public you shouldstore it securely.LinksDocumentationOfficial Discord ServerDiscord API
Package: bol-crawler
bolcom_crawlerThis is a really simple crawler that makes use of Scrapy to crawlbol.com.UsageTheCrawlerinstance has two functions you can use,crawl_productsandcrawl_category. See an example below.from bol_crawler.crawler import Crawler
crawler = Crawler()

# to crawl products
products = crawler.crawl_products(
    [
        'https://www.bol.com/nl/p/lg-34gl750-b-ultragear-gaming-monitor/9200000115819731',
    ]
)

# to crawl a category
products = crawler.crawl_category(
    [
        'https://www.bol.com/nl/l/gaming-toetsenborden/N/18214/', 0  # the 0 value is how often you want to go to the next page. 0 is just crawling the first page
    ]
)