Saravanan666/pypi-org huggingface dataset:
Package: vdk-trino
This plugin allows vdk-core to interface with and execute queries against a Trino database. Additionally, it can collect lineage data, assuming a lineage logger has been provided through the vdk-core configuration.UsageRunpipinstallvdk-trinoAfter this data jobs will have access to Trino database connection managed by Versatile Data Kit SDK.If it is the only database plugin installed , vdk would automatically use it.
Otherwise, users need to set VDK_DB_DEFAULT_TYPE=TRINO as an environment variable or set 'db_default_type' option in the data job config file (config.ini).For exampledefrun(job_input:IJobInput):job_input.execute_query("select 'Hi Trino!'")Templatesvdk-trino comes with pre-defined templates for SQL transformationsSCD1 -Slowly Changing Dimension type 1:See usage documentation hereSCD2 -Slowly Changing Dimension Type 2:See usage documentation hereLineageThe package gathers lineage data for all Trino SQL queries executed in a data jobOther plugins can read that lineage data log it.
They need to provide ILineageLogger implementation and hook this way:@hookimpldefvdk_initialize(context:CoreContext)->None:context.state.set(StoreKey[ILineageLogger]("trino-lineage-logger"),MyLogger())IngestionThis plugin allows users toingestdata to a Trino database, which can be preferable to inserting data manually as it automatically handles serializing, packaging and sending of the data asynchronously with configurable batching and throughput. To do so, you must set the expected variables to connect to Trino, plus the following environment variable:exportVDK_INGEST_METHOD_DEFAULT=TRINOThen, from inside the run function in a Python step, you can use thesend_object_for_ingestionorsend_tabular_data_for_ingestionmethods to ingest your data.ConfigurationRun vdk config-help - search for those prefixed with "TRINO_" to see what configuration options are available.TestingTesting this plugin locally requires installing the dependencies listed in vdk-plugins/vdk-trino/requirements.txtRunpipinstall-rrequirements.txt
Package: vdldraw
VDLdrawBatch plot the log files exported from VisualDL using Matplotlib.VisualDLVDLdrawHow to installIt can be installed throughpip:pipinstallvdldrawHow to useOnline experiences inAI Studio(Chinese).fromvdldrawimportget_tags,vdl_draw_folder## 1.View available tagsget_tags(log_folder)# Output like this:# ['Evaluate/F1', 'Train/loss', 'Evaluate/mIoU', 'Evaluate/Acc']## 2.Make up tags to be displayedtag_list=['Evaluate/mIoU','Evaluate/Acc']## 3.Save imagevdl_draw_folder(log_folder,tag_list,save_folder="output",mplstyle=None)# Args:# 	 log_folder (str): Folder path where logs are saved.# 	 tag_list (list): List of tags to be displayed.# 	 save_folder (str, option): Folder path to save pictures. Default: "output".# 	 mplstyle (str/path): Matplotlib style system. Default: None(Styles defined using VDLdraw).ColormapColormap referenceantv's contrasting orange, 20 colors in total.StyleIf you need use some styles, you could useSciencePlots. This repo has Matplotlib styles to format your figures for scientific papers, presentations and theses.
Package: vdocs
vDocsBusiness Ready Documents for Cisco SD-WAN vManageCurrent API CoverageARP InterfacesBFD SessionsBFD Sessions from DeviceBFD SummaryCEdge InterfacesControl ConnectionControl Local PropertyControl WAN InterfaceDevice CountersDevice StatusFabric DevicesHardware EnvironmentHardware InventoryInterfacesOMP PeersSystemSystem StatusTemplate Feature TypesTemplate FeaturesTemplate Policy ListvEdge DevicesInstallation$python3-mvenvsdwan$sourcesdwan/bin/activate(sdwan)$pipinstallvdocsUsage - Help(sdwan)$vdocs--helpUsage - In-line(sdwan)$vdocs--url<urltovManage>--username<vManageusername>--password<vManagepassword>Usage - Interactive(sdwan)$vdocsvManage URL: <URL to vManage>vManage Username: <vManage Username>vManage Password: <vManage Password>Usage - Environment Variables(sdwan)$exportURL=<URLtovManage>(sdwan)$exportUSERNAME=<vManageUsername>(sdwan)$exportPASSWORD=<vManagePassword>Recommended VS Code ExtensionsExcel Viewer - CSV FilesMarkdown Preview - Markdown FilesMarkmap - Mindmap FilesOpen in Default Browser - HTML FilesAlways On SandboxThis code works with the always on sandbox!https://devnetsandbox.cisco.com/RM/Diagram/Index/a4ab71bc-f7a0-4d63-bedb-05a051818569?diagramType=Topologyexport URL=https://sandbox-sdwan-2.cisco.comexport USERNAME=devnetuserexport PASSWORD='RG!_Yw919_83'(venv)$pipinstallvdocs(venv)$mkdirvdocs_output(venv)$cdvdocs_output(venv)/vdocs_output$ vdocs(venv)/vdocs_output$ code .(Launches VS Code and you can view the output with the recommended VS Code extensions)ContactPlease contact John Capobianco if you need any assistance
Package: vdom
VDOMWhy use VDOMWriteDeclarativePythonic layouts.Create headings, prose, images, and more common user interface items with user-friendly declarative statements.Render the layout inJupyterfrontends, such asnteractand JupyterLab.Serialize the layout for rehydration and later use in your web app.Check out the power of VDOMCreate layouts by writing and running Python code. Let's see an example
below to create and display a heading, styled prose, and a GIF:fromIPython.displayimportdisplayfromvdom.helpersimporth1,p,img,div,bdisplay(div(h1('Our Incredibly Declarative Example'),p('Can you believe we wrote this ',b('in Python'),'?'),img(src="https://media.giphy.com/media/xUPGcguWZHRC2HyBRS/giphy.gif"),p('What will ',b('you'),' create next?'),))Voila!Your example created a layout and served it below:Now Incredibly DeclarativeCan you believe we wrote thisin Python?What willyoucreate next?Getting startedInstall the Python packagepipinstallvdomUsageFirst, importvdom.helpersfor headings, text, and images:fromvdom.helpersimporth1,p,img,div,bCreate a layout using the VDOM helpers in Python code. Here's an example code
layout block:my_pretty_layout=div(h1('Our Incredibly Declarative Example'),p('Can you believe we wrote this ',b('in Python'),'?'),img(src="https://media.giphy.com/media/xUPGcguWZHRC2HyBRS/giphy.gif"),p('What will ',b('you'),' create next?'),)To display the layout, use IPython's display method:fromIPython.displayimportdisplaydisplay(my_pretty_layout)The full example, including rendered output, is foundabove.DocumentationDesign PatternsSpecification - VDOM Media TypeSpecification - VDOM Event SupportContribute to VDOMDeveloper install from source codegitclonehttps://github.com/nteract/vdomcdvdom
pipinstall-e.Contributing Guidelines and ReleasesWe follow theseContributing Guidelines.For contributors helping with creating releases, the [RELEASING.md] document
outlines the process.Find out more about nteractTake a look at thenteract websiteto see other projects
that we are working on.
Package: vdomify
# [vdomify](https://github.com/rgbkrk/vdomify)Convert plain ol' Python objects to VDOM ready objectsNote: the library isn't ready yet, this is README driven development## Why use vdomify?When you want a handy utility to convert python objects to vdom components.```pythonfrom vdomify import vdomifydisplay(vdomify({'test': True}))```## Install the Python package```bashpip install vdomify```## Developer install from source code```bashgit clone https://github.com/rgbkrk/vdomifycd vdomifypip install -e .```## We welcome feedback.Since this project and its API is still a work in progress, we would love tohear your thoughts on the API and suggestions for enhancements.
Package: vdot-calculator
VDOT CalculatorA compact VDOT calculator adhering to the original Daniels Running Formula book.Status: Work in Progress🚧Note: This project is currently under development.🚧DescriptionThe VDOT Calculator project aims to provide a compact tool for calculating VDOT, following the principles outlined in the original Daniels Running Formula book.Features (Coming Soon)Calculate VDOT based on your running performance.IssuesIf you encounter any issues or have suggestions, feel free toopen an issue.LicenseThis project is licensed under the MIT License - see theLICENSEfile for details.Installation$ python -m pip install vdot_calculatorHow to use>>> import datetime
>>> import vdot_calculator as vdot
>>> time = datetime.time(minute=27, second=00)
>>> distance = 5000 # meters
>>> vdot.vdot_from_time_and_distance(time, distance)
34.96321966414413>>> import datetime
>>> import vdot_calculator as vdot
>>> pace = datetime.time(minute=5, second=24)
>>> distance = 5000 # meters
>>> vdot.vdot_from_distance_and_pace(distance,pace)
34.96321966414413>>> import datetime
>>> import vdot_calculator as vdot
>>> pace = datetime.time(minute=5, second=24)
>>> time = datetime.time(minute=27, second=00)
>>> vdot.vdot_from_time_and_pace(time,pace)
34.96321966414413ContactFor questions or inquiries, you can contact the project maintainer:Cássio Maciel LemosEmail:cassio.lemos@petrobras.com.br
Package: vdownloader
VDownloaderExemplo de um programa simples para fazer downloads de vídeos ou áudios do YoutubeBiblioteca utilizada: pytube1º passo: Isolar dependências do projetopython -m venv .venv2º passo: Ativar o ambiente virtualWindows.\.venv\Scripts\activateLinuxsource .venv/bin/activate3º passo: Instalaçãopip install vdownloader4º passo: Executando o programa, comando:$ vdownloader
Package: vdr
VDRVDR is a Python library to simulate a VDR (Voyage Data Recorder).InstallationUse the package managerpipto install vdr.pipinstallvdrUsageYou first need to configure your VDR that will receive all the data.importvdrVDR=vdr.Vdr('/home/USER')# Create the VDR with its storage pathVDR.add_connection("localhost",12345,'ECDIS')# Create socket connection called 'ECDIS'VDR.add_connection("localhost",12346,'nmea')# Create socket connection called 'nmea'# Initialize threads with each data type that connections will receivedecdis=vdr.ReceivingFrame(VDR,"ECDIS")nmea=vdr.ReceivingNmea(VDR,"nmea")# Start threads, ready to receive and store dataecdis.start()nmea.start()Then, the library proposed different kind of agent to facilitate data emission.Frame Agentimportscreenagentagent=screenagent.ScreenAgent("localhost",12345)agent.send_screenshot()ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.LicenseMIT
Package: vdropbox
vdropboxUtilities to read/write objects to/from dropboxUsageThe first thing to do is to declare theVdropboxobject using a token with:fromvdropboximportVdropboxvdp=Vdropbox("my_secret")Unlike the officialdropboxpython package it is not needed to have a leading/in all names.Basic functions# Check if a file existsvdp.file_exists("my_file.txt")vdp.file_exists("folder/my_file.txt")# Check contents of a folervdp.ls("my_folder")# Delete a filevdp.delete("my_file.txt")Reading and writting text filesdata="Hello world"# Write a text filevdp.write_file(data,"my_file.txt")# Read a text filevdp.read_file("my_file.txt")Internally it is usingoyamlso all yamls are ordered.Reading and writting yamlsdata={"a":4,"b":2}# Write a yaml filevdp.write_yaml(data,"my_file.yaml")# Read a yaml filevdp.read_yaml("my_file.yaml")Internally it is usingoyamlso all yamls are ordered.Reading and writting excels with pandasimportpandasaspd# Dummy dataframedf=pd.DataFrame(list("ABCDE"),columns=["col"])# Write an excel filevdp.write_excel(df,"df.xlsx")# Read a parquet filevdp.read_excel("df.parquet")It is possible to pass keyworded arguments to the internalpd.read_excelordf.to_excelfunction.
For example:vdp.write_excel(df,"test.xlsx",index=False)Reading and writting parquets with pandasimportpandasaspd# Dummy dataframedf=pd.DataFrame(list("ABCDE"),columns=["col"])# Write a parquet filevdp.write_parquet(df,"df.parquet")# Read a parquet filevdp.read_parquet("df.parquet")It is possible to pass keyworded arguments to the internalpd.read_parquetordf.to_parquetfunction.AuthorsArnau VilloroLicenseThe content of this repository is licensed under aMIT.
Package: vdsql
vdsql:VisiDatafor DatabasesA VisiData interface for databasesPowered byIbis.Featuresquery data in VisiData from any supported backendoutput resulting query in SQL, Substrait, or PythonRequirementsPython 3.8VisiData 2.10.2Ibis 3.2Confirmed supported backendsSQLiteMySQLPostgreSQLDuckDBClickHouseGoogle BigQuerySnowflakeOther backends supported by IbisThese backends are supported by Ibis and should work, but haven't specifically been tested with vdsql.
If you have have problems connecting, pleasefile an issue.Apache ImpalaDatafusionDaskPySparkHeavyAIInstall latest releaseThis will install both:the usualvdwith the vdsql plugin available (use-f vdsqlto use Ibis instead of builtin loaders),thevdsqlscript that acts identically tovdbut will use Ibis instead of VisiData's builtin loader.pip install vdsqlOr install manually as a VisiData plugin (cutting edge development)pip install git+https://github.com/visidata/vdsql.gitInstall Ibis backendsTo minimize dependencies, only the sqlite backend is included by default.Install other backends for Ibisdirectly, and they will be supported automatically:pip install 'ibis-framework[postgres]'UsageOpen a databasevdsql foo.sqlite  # or .sqlite3
vdsql mysql://...
vdsql postgres://...
vdsql foo.duckdb  # or .ddb
vdsql clickhouse://explorer@play.clickhouse.com:9440/?secure=1
vdsql bigquery:///bigquery-public-data

vdsql <file_or_url>

vd -f ibis <file_or_url>wherefile_or_urlis any connection string supported byibis.connect()or any of the filetypes and options that VisiData itself supports.CommandsA decent amount of work has gone into makingvdsqlwork just like VisiData.You can learn about VisiData starting with theIntro to VisiData Tutorialand theVisiData documentation.There are a few differences, however:Use"(dup-sheet) to run a new base query, including added columns, filtering for the current selection, and applying the current sort order.By default vdsql will only get 10000 rows from a database source.  To get a different number, usez"to create a new sheet with a different limit.Some VisiData commands aren't implemented using the database engine.The base VisiData commands can only use the 10000 loaded rows, and this might be misleading, so most not-implemented commands should be disabled.But if you want to use the commands anyway, knowing the dataset is incomplete, you can useg'to freeze the current set of loaded rows into a new sheet.This sheet is a plain (non-database) VisiData sheet, so all VisiData commands can be used on it.Freezing the column typeUse'to cast the current column to its given type, which persists into future queries (with").Sidebarvdsqluses the VisiData sidebar (introduced in v2.9) to show the SQL query for the current view.To toggle the sidebar on/off, pressb.To choose a sidebar option, presszb.To open the sidebar as its own sheet, pressgb.In this way you can compose a SQL expression using VisiData commands, open the SQL sidebar, and save the resulting query to a file (or copy it into your system clipboard buffer).Licensevdsqlis licensed under the Apache 2.0 license.Share and enjoy!
Package: vdt.simpleaptrepo
Simple command line tool to create apt repositories. This will work on debian and ubuntu.Installation:First install from pypi:pip install vdt.simpleaptrepoThis tool is a wrapper for some debian specific packages, so you will need to install them first:apt-get install gnupg dpkg-sig apt-utilsTo show which commands are available:simpleapt --helpCreate a repository:First you need to create a gpg key to sign your packages with. This is not mandatory but highly recommended:simpleapt create-gpg-keyCopy and remember the key’s hash. The output looks something like this:gpg: key 10FB8BDC marked as ultimately trustedSo copy the10FB8BDChash, you will need it later.Now create a repository:simpleapt create-repo myrepo /www/ --gpgkey 10FB8BDC

Repository 'myrepo' created
Now add a component with the 'add-component' commandCreate a component:In one repository you have multiple components:simpleapt add-component myrepo testYou will see what you need to do now:Component 'test' created in repo 'myrepo'

Now add some unsigned debian packages in the directory
and run the 'update-repo' command (see the 'add packages' section below)

Configure your webservice to set the www-root to /www/
Add http://<hostname>/myrepo/test / to your sources.list

Add the key on the host where you want to install the packages.
(This is only needed once per repository)
wget -qO - http://<hostname>/myrepo/test/keyfile | sudo apt-key add -Add some more if you like:simpleapt add-component myrepo staging
simpleapt add-component myrepo productionSee that our repo is there:simpleapt list-repos

myrepo (gpgkey: 10FB8BDC)
   test
   staging
   mainAdd packages:Copy some debian package into a component’s directory and update the repo:simpleapt update-repo myrepo test

Exported key 10FB8BDC to /www/myrepo/test/keyfile

Signed package /www/myrepo/test/my-package_0.0.1_all.deb
Creates Packages
Creates Packages.gz
Create Release with key 10FB8BDC
Create InRelease with key 10FB8BDC
Create Releases.gpg with key 10FB8BDCWhen there a a lot packages you can skip resigning packages by using the--skip-signedoption:simpleapt update-repo myrepo test --skip-signed

Exported key 10FB8BDC to /www/myrepo/test/keyfile

Skipped signing /www/myrepo/test/my-package_0.0.1_all.deb

Creates Packages
Creates Packages.gz
Create Release with key 10FB8BDC
Create InRelease with key 10FB8BDC
Create Releases.gpg with key 10FB8BDCNow you can install these packages!Changelog:0.0.5 (2018-08-04):Checked for python 3.7 support0.0.4 (2017-11-20):Added a--skip-signedoption so we can skip already signed debian packagesAdded python 3 supportUseful URLS:http://blog.packagecloud.io/eng/2014/10/28/howto-gpg-sign-verify-deb-packages-apt-repositories/https://keyring.debian.org/creating-key.htmlhttps://wiki.debian.org/SecureApt#How_apt_uses_Release.gpghttps://help.ubuntu.com/community/CreateAuthenticatedRepositoryhttp://lists.gnupg.org/pipermail/gnupg-users/2004-May/022471.html
Package: vdt.versionplugin.buildout
Plugin forhttps://github.com/devopsconsulting/vdt.versionThis plugin uses [FPM](https://github.com/jordansissel/fpm/wiki) to build a Debian package out of
Python sources within the src folder of your [buildout](www.buildout.org). Additionally you will
get Debian packages for the whole dependency tree of your package. On doing so, all dependencies
are pinned to a minimum version in the control files of the resulting Debian packages. The versions
for the pinning are taken from the versions.cfg file of your buildout or any other file with the
same structure.Some maintainers of packages do not stick to the correct naming scheme between their Python and
Debian packages:
- pyyaml   <-> python-yaml
- pyzmq    <-> python-zmq
- pycrypto <-> python-cryptoIf you would build these packages with FPM you would end up with the following broken package names:
- pyyaml -> python-pyyaml
- pyzmq -> python-pyzmq
- pycrypto -> python-pycryptoThe vdt.versionplugin.buildout also takes care of this and fixes the affected names for you.You can use this plugin the following way in your buildout:` cdsrc/package-to-build../../bin/version--plugin=buildout--versions-file=versions.cfg-v`
Package: vdt.versionplugin.hotfix
When doing hotfixes, and try to automate versioning, we can envounter a couple of problems.The hotfix needs to fit in between 2 existing versions.
This is required, because production could be running on version 1.0.0 while test is
allready running on version 1.0.123.A hotfix should be merged back into the main branch, but not cause any disturbance of
The automatic version system.
What can happen is that we are doing a hotfix on 1.0.0, while HEAD has allready received
a tag for version 1.0.123. If we add a hotfix tag and merge it on top of 1.0.123, we
could reset the version counter.For this reason hotfixes are never tagged. We simply release a package as an iteration on
a previous package and release it without tagging the repository. The reasoning behind this
strategy is, that when the hotfix is merged back onto HEAD, it will get tagged and release
through the main branch anyway and it makes no sense at all to have multiple tags for the
same feature. (Enforcing this is a main feature of vdt.version).UsageThe hotfix plugin will look up the latest tag in your current branch and get it’s version.
If we started a branch from a tag somewhere in the middle of our version history, that
would work out fine:> version --plugin=hotfix --iteration=11 --maintainer=lars@permanentmarkers.nl -e -t deb setup.py
Skipping installation of /var/folders/46/j79zq70n21n5m54j30f1rwrh0000gp/T/package-python-staging20140618-19649-432fe4/usr/lib/python2.7/dist-packages/vdt/__init__.py (namespace package)
Skipping installation of /var/folders/46/j79zq70n21n5m54j30f1rwrh0000gp/T/package-python-staging20140618-19649-432fe4/usr/lib/python2.7/dist-packages/vdt/versionplugin/__init__.py (namespace package)
> ls
python-vdt.versionplugin.hotfix_0.0.1-11_all.debThe hotfix plugin can not create new versions and thus tags for you:> version --plugin=hotfix --minor --iteration=11 --maintainer=lars@permanentmarkers.nl -e -t deb setup.py
Skipping installation of /var/folders/46/j79zq70n21n5m54j30f1rwrh0000gp/T/package-python-staging20140618-19819-l5ti7o/usr/lib/python2.7/dist-packages/vdt/__init__.py (namespace package)
Skipping installation of /var/folders/46/j79zq70n21n5m54j30f1rwrh0000gp/T/package-python-staging20140618-19819-l5ti7o/usr/lib/python2.7/dist-packages/vdt/versionplugin/__init__.py (namespace package)
> ls
python-vdt.versionplugin.hotfix_0.0.1-11_all.debYou can see, that while we requested the minor version number to be incremented, that didn’t happen.These hotfix packages can be pushed to a separate ‘hotfix’ repository and because they received a higher iteration
number as the package it is based on, it will be installed on any environment running on that base version.Newer packages will have a higher version number and surpass the iteration.Plugin Arguments--iteration The iteration number for the hotfix
-s Fpm input type, one of 'dir', 'rpm', 'gem', 'python', 'empty', 'tar', 'deb'.
   The default is python, which has some default configuration.
Package: vdu-nlp-services
vdu-nlp-servicesFunction ReferenceReferenceanalyze_textPerform morphological analysisfromvdu_nlp_servicesimportanalyze_textres=analyze_text(u'Laba diena!',include_lemmas=True)print(res)([{u'lemma':u'laba diena',u'word':u'Laba diena',u'type':u'jst.'},{u'sep':u'!'},{u'p':None}],[{u'lemma':u'laba diena','span':(0,4),u'word':u'Laba',u'type':u'jst.'},{'other':u' ','span':(4,5)},{u'lemma':u'laba diena','span':(5,10),u'word':u'diena',u'type':u'jst.'},{'other':u'!','span':(10,11)}])stress_textAccentuate textfromvdu_nlp_servicesimportstress_textres=stress_text(u'Laba diena!')print(res)'Laba` diena`!'stress_wordAccentuate wordfromvdu_nlp_servicesimportstress_wordres=stress_word(u'Laba')forstressed_word,tagsinres:print(stressed_word,list(tags))Laba`['dktv.','mot.gim.','vnsk.','Įn.']La~ba['dktv.','mot.gim.','vnsk.','Š.']Laba`['bdvr.','mot.gim.','vnsk.','V.','neįvardž.']Laba`['bdvr.','mot.gim.','vnsk.','Įn.','neįvardž.']La~ba['bdvr.','mot.gim.','vnsk.','Š.','neįvardž.']La~ba['bdvr.','bevrd.gim.','neįvardž.']InstallPyPipipinstallvdu-nlp-servicesGitpipinstallgit+https://github.com/aleksas/vdu-nlp-services.git