Saravanan666/pypi-org huggingface dataset:
Package: vite
viteA simple and mnml static site generator that Just Works™Installation$pipinstallviteUsage$viteinitpath/to/project$vitenewblog/some-post.md# `pages/` is impliedThis createspages/blog/some-post.md.And then:$vitebuild# in project directoryRendered HTML will be in thebuilddirectory.Finally, run:$viteserve# also in the project directoryConfigurationNot very sophisticated, but basic configuration can be acheived usingconfig.pyfound in the project directory.
Example config:# config.pytitle=''author=''header=''footer=''template='index.html'# default is templates/index.htmlpost_build=[]# list of commands to run post-buildTemplatingVite uses Jinja2 templating, so template files must be placed in a separatetemplates/directory.A basic example would be:<linkrel="stylesheet"href="/static/sakura-earthy.css"><title>{{ title }}</title><body>{{ body }}</body><footer>{{ footer }}</footer>Specifying per-page templatesVite allows for specifying a unique template, per page. This is acheived by including YAML frontmatter at the top of the Markdown file, like so:---
template: foo.html
title: Some fancy buzzwords here
subtitle: Cool catch phrase heredate: 2019-08-09---## markdown here...Notes on templatingStylesheets, images and JS can be accessed from thestaticfolder.index.html, i.e. your website's homepage, should be_index.mdin thepages/directory.Directory treeexample
├── build
├── config.py
├── pages
│   └── test.md
├── static
└── templates
    └── index.htmlTODOTemplatingCSS supportImplement a simple HTTP server (later)Add example siteBasic config (config.py)Parsing frontmatter (JSON, YAML, TOML) for per-page optionsBetter support for home page (mainindex.htmlpage)More powerful frontmatter (title, date, draft status, etc.) (draft status is incomplete)Deeper directories underpages/(supports only one level now, breaks otherwise)(not happening)Tagging system(not happening)
Package: viterbi
Convolutional Encoder and Viterbi DecoderThis project is a fork ofhttps://github.com/xukmin/viterbithat introduces Python support, enabling effortless utilization of the Viterbi module within the Python environment.InstallpipinstallviterbiUsageThe following is a convolutional encoder with a constraint length of 7. The diagram indicates the binary values and polynomial form, indicating the left-most bit is the most-significant-bit (MSB). The generating polynomials are 1011011 and 1111001 can be alternatively expressed in octal as 133 and 171, respectively.Expressed in code as:fromviterbiimportViterbidot11a_codec=Viterbi(7,[0o133,0o171])You can use the viterbi decoder like this:fromviterbiimportViterbidot11a_codec=Viterbi(7,[0o133,0o171])bits=[0,1,0,1,0,0,0,0,1,1,1,0]output=dot11a_codec.encode(bits)# [0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0, 1]dot11a_codec.decode(output)# [0, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0]PuncturingThis library also allows you to puncture the original encoded data by specifying a puncture pattern or decode data that has already been punctured.fromviterbiimportViterbi# Puncture Pattern: [1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1]dot11a_codec=Viterbi(7,[0o133,0o171],[1,1,1,0,0,1,1,1,1,0,0,1,1,1,1,0,0,1])Using in C++You can find the way to use the Viterbi decoder in C++ in theREADMEof the original project.
Package: viterbi-trellis
Library to compute the best path through a trellis graph using the Viterbi algorithm.The source for this project is available here.This library provides the class ViterbiTrellis. At present it can only do one thing:
compute the best path through a trellis graph. The user must provide three inputs:Trellis layer structure, specified as a list of lists. Each inner list corresponds to a
single layer of the trellis. The first item in the outer list is the start layer, while the
final item is the end layer. Each innermost item is an object representing the state. This
could be a primitive type such as an int, or it could be a tuple or user-defined class.Acost functiongiving the cost for being in a given state.Atransition functiongiving the cost of transitioning between two particular states.The best path is chosen by globally minimizing the sum of the state costs and transitions via
the Viterbi algorithm.Example usage:from viterbi_trellis import ViterbiTrellis
v = ViterbiTrellis([[2, 6, 4], [4, 6], [0, 2, 6]], lambda x: x / 2.0, lambda x, y: abs(y - x))
best_path = v.viterbi_best_path()The return value in best_path is a list of indices of the states in the best path:>>> best_path
[2, 0, 1]This result corresponds to the states labeled[4, 4, 2]in the input trellis.
Package: vitess-helpers
# vitess-helpers
This library is intended to be a general library to help manage the lifecycle of a Vitess cluster.Visithttps://vitess.io/for more information on what Vitess is.## shard range library
Generate shard ranges using python. The library takes a single inputshardsand generates a list of shard range names.See Vitess documentation for further information:https://vitess.io/docs/reference/features/sharding/Example usage:`python >>> from vitess_helpers import shard_ranges >>> shard_ranges(3)['-55','55-aa','aa-']>>> `## to installpip install vitess-helpers
Package: vitex
An unholy conglomeration of vim, evince, and friends for writing LaTeXGoalDo you prefer to use vim to edit your LaTeX files, but wish there was better integration between the editor and your pdf viewer? Well this is the project for you! The goal of ViTeX is to bring together high quality tools in a convenient package to make editing LaTeX as painless(tm) as possible.StatusCurrently working on arch linux with the Gnome desktop environment.Features!Realneovim via VteCustominit.vimfor editing LaTeX (of course feel free to personalize)Embedded PDF view using Evince with auto reloadSynctex supportSupport for editing and viewing Markdown tooThat's pretty much it!RequirementsThis is likely a non-exhaustive list, so please feel free to create an issue if you found you needed something else.Python 3Gtk+EvinceneovimpandocControlsctrl -: Decrease editor font sizectrl +: Increase editor font sizectrl b: Start async build with latexmkctrl right: move divider to rightctrl left: move divider to leftctrl up: move divider to centerSetupThrough Gitgitclonegit@github.com:cfangmeier/vitex.gitcdvitex
pythonsetup.pyinstall--userVia pippipinstallvitex--user
Package: vitexpy
Python wrapper for vitex.net API v2vitex-py by `blacktygerInstallation:python -m pip install vitexpyDescription:Python wrapper for ViteX - Decentralized cryptocurrency exchange API.URL:https://x.vite.net/API DOCUMENTATION:https://vite.wiki/dex/api/dex-apis.html#overviewFeatures:Handling transaction signatures required by ViteX APIDecimal library to keep high precision with floating point numbersWell documented and readable for everyoneOOP approach withToken,TraidingPair,Order, andAPIobjectsHow to use:🔎PublicAPIcan be used out of the box without API keys,
enough to extract most of market data available for this platformAll PublicAPI endpointshttps://vite.wiki/dex/api/dex-apis.html#public-rest-apifrom vitexpy import PublicAPI

api = PublicAPI(print_response=True)  # Default: False

# Test connection with ViteX server
api.test_connection()
>>> Successfully connected to ViteX API with vitex-py module
>>> Server time: 2021-10-28 12:50:44.469000
>>> USD  /  CNY: 6.466199999999926

# Get list with Token object/s
api.get_token('EPIC-002')  
>>> [Token(EPIC-002)]

# Get list with all Token object/s
api.get_all_tokens()  
>>> [Token(AAVO-000), Token(ABC-000), Token(AGS-000), ...]

# Get list with TradingPair object/s
api.get_trading_pair('EPIC-002_BTC-000')  
>>> [TradingPair(EPIC-002/BTC-000)]📈TradingAPIrequires signature authentication by API Key and API Secret,
which you can apply for on ViteX platform.
Please note that API Key and API Secret are both case sensitive.
Also it is recommended to stake some VITE for QUOTA ('transactions fuel')
in order to execute multiple transactions.All TradingAPI endpointshttps://vite.wiki/dex/api/dex-apis.html#private-rest-apifrom vitexpy import TradingAPI, TradingPair

api_key = "YOUR VITEX API KEY"
api_secret = "YOUR VITEX API SECRET"

api = TradingAPI(api_key=user_key,
                 api_secret=user_secret,
                 print_response=True)

# Create dictionary with required values
order_params = {
    'test': True,  # Optional, when True transactions are not executed in network
    'symbol': 'EPIC-002_BTC-000',  # Market pair symbol ('BASE-XXX_QUOTA-XXX')
    'amount': 5,  # Amount to buy or sell in base token ('EPIC-002' in this case)
    'price': 0.00006000,  # Price for each base token ('EPIC-002') in quota token ('BTC-000')
    'side': 1,  # Buy(0) or Sell(1)
    }

# Create Order object with given params
order = api.prepare_order(**order_params)  

# Prepare, sign and execute Order object to Vitex network
api.execute_order(order)  

# Cancel all orders within given pair (TradingPair object or string with symbol)
api.cancel_all_orders(pair='EPIC-002_BTC-000')💌 DonationsProject isopen-sourceand free, if you like it please consider donation:Vite Chain: vite_15d3230e3c31c009c968beea7160ae98b491475236ae2cddbcEPIC Chain:https://fastepic.eu/keybaseid_blacktyg3rWAN  Chain: 0x37b056F68120a250D28C7de9650Fa02Ee740fec1BSC  Chain: 0xE6F431178cD7B44FBCb4381eBDb14Db213BDD866Contact:@blacktyg3r via TelegramThanks!
Package: vitime
VITimeCLI tool to view your timetable from terminal anytime!Table of contentsPreviewInstallationPyPISource codeUpdatesSetting upAdd timetableAdd courseUsageView today's timetableView a day's timetableView full timetableShow all coursesDelete courseDelete timetableChange logLicenseReferencesPreviewInstallationPyPIOpen terminal and install the package using python package installer.pipinstallvitime==0.2.1NOTE:This might require admin access, on windows run your terminal as administrator and for linux based systems use-sudopipinstallvitime==0.2.1Source codeDownload latest release viazip fileortar fileExtract the folder to your desired locationThen install it in your desired terminal using suitable commandLinux or Max OS Xuser@hostname:~$sudopython3setup.pyinstallWindowsRun command prompt as administrator andC:\users\username> python setup.py installUpdatesVITime has automatic update detection to notify user when a newer version is available! You can update usingvitime -uorvitime --update.Setting upCommandsvitime addtimetableCommand to add entire timetable.Note:This deletes any existing timetable.1. Copying timetable from vtop2. Adding timetable using VITimevitime addcourseCommand to add a course.UsageCommandsvitime todayShows all ongoing/left classes for the day.Note:This does not show all the classes during the day, to view all classes usevitable showdaycommand.vitime showdayShows all the classes on the day entered by the user.vitime fullShows the entire timetable.vitime showcoursesShows a lot of all the courses added to the timetable.vitime deletecourseDeletes the given course from timetable.vitime deletetimetableDeletes the entire timetable.Note:The confirmation message is case sensitive so 'YES', 'Yes' will not work.LicenseCopyright (c) 2021 Dhruv9449MIT licenseReferencesThis project is inspired byVITablemade by -CartelProjectVishesh BansalGagan MalviDeveloped byDhruv Shah
Package: vitis-quantizer
Vitis QuantizerTHIS IS NOT AN OFFICIAL XILINX PACKAGEA pip installable package to do the vitis model quantization for tensorflow 2.This is a migration of the codehereto a standalone pip package that won't conflict with thetensorflow-model-optimizationpackage.Working in the docker image is annoying and this code should be standalone.Installpipinstallvitis-quantizerBuild from source:python3setup.pybdist_wheel
pipinstalldist/vitis_quantizer-0.1.0-py3-none-any.whlUsageUsage is the same as Vitis AI models.importtensorflowastfimportvitis_quantizer# Train/Get/Make a keras model somehowmodel=tf.keras.models.load_model("/path/to/keras/model")quantizer=vitis_quantizer.VitisQuantizer(model)withvitis_quantizer.quantize_scope():quantized_model=quantizer.quantize_model(calib_dataset=dataset)quantized_model.save("/path/to/save/quantized/model")After you have the quantized model saved, use vitis compile.sh script.
Package: vit-keras
vit-kerasThis is a Keras implementation of the models described inAn Image is Worth 16x16 Words:
Transformes For Image Recognition at Scale. It is based on an earlier implementation fromtuvovan, modified to match the Flax implementation in theofficial repository.The weights here are ported over from the weights provided in the official repository. Seeutils.load_weights_numpyto see how this is done (it's not pretty, but it does the job).UsageInstall this package usingpip install vit-kerasYou can use the model out-of-the-box with ImageNet 2012 classes using
something like the following. The weights will be downloaded automatically.fromvit_kerasimportvit,utilsimage_size=384classes=utils.get_imagenet_classes()model=vit.vit_b16(image_size=image_size,activation='sigmoid',pretrained=True,include_top=True,pretrained_top=True)url='https://upload.wikimedia.org/wikipedia/commons/d/d7/Granny_smith_and_cross_section.jpg'image=utils.read(url,image_size)X=vit.preprocess_inputs(image).reshape(1,image_size,image_size,3)y=model.predict(X)print(classes[y[0].argmax()])# Granny smithYou can fine-tune using a model loaded as follows.image_size=224model=vit.vit_l32(image_size=image_size,activation='sigmoid',pretrained=True,include_top=True,pretrained_top=False,classes=200)# Train this model on your data as desired.Visualizing Attention MapsThere's some functionality for plotting attention maps for a given image and model. See example below. I'm not sure I'm doing this correctly (the official repository didn't have example code). Feedback /corrections welcome!importnumpyasnpimportmatplotlib.pyplotaspltfromvit_kerasimportvit,utils,visualize# Load a modelimage_size=384classes=utils.get_imagenet_classes()model=vit.vit_b16(image_size=image_size,activation='sigmoid',pretrained=True,include_top=True,pretrained_top=True)classes=utils.get_imagenet_classes()# Get an image and compute the attention mapurl='https://upload.wikimedia.org/wikipedia/commons/b/bc/Free%21_%283987584939%29.jpg'image=utils.read(url,image_size)attention_map=visualize.attention_map(model=model,image=image)print('Prediction:',classes[model.predict(vit.preprocess_inputs(image)[np.newaxis])[0].argmax()])# Prediction: Eskimo dog, husky# Plot resultsfig,(ax1,ax2)=plt.subplots(ncols=2)ax1.axis('off')ax2.axis('off')ax1.set_title('Original')ax2.set_title('Attention Map')_=ax1.imshow(image)_=ax2.imshow(attention_map)
Package: vitor-core-test
Copyright (c) 2018 The Python Packaging AuthorityPermission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Package: vitpose-infer
ViTPose-Pytorch no mmcv neededViTPose (https://github.com/ViTAE-Transformer/ViTPose) + ByteTrack (https://github.com/ifzhang/ByteTrack) + yolov5 (https://github.com/ultralytics/yolov5)PreparationDownload the official weights from ViTPose. Create a dictionary called models.
Tested with both the vitpose-b models.mkdir modelsmv <weight_path> ~/ViTPose-Pytorch/models/RequirementsIf nvidia-tensorrt is not found install nvidia-pyindex first.pip3 insltall -r requirements.txtHow to runExport ViTPose TRT modelpython3 export.py --include engine --device 0Export yolov5 engine, either by cloning the official yolov5 repo and using the export function or via cd /.cache/torch/hub/yolov5_master and
exporting from there. Move the engine file into the root folder of ViTPose-Pytorch.With a webcam or another devicels /dev/vid*3 demo examples are provided . To use this lib as a package runpython3 -m buildInstall the whl in the dist folder via pip.ExamplesWith TRT
Package: vitrage
OpenStack Vitrage is the OpenStack RCA (Root Cause Analysis) Service for organizing, analyzing and expanding OpenStack alarms & events, yielding insights regarding the root cause of problems and deducing the existence of problems before they are directly detected.Enabling Vitrage in DevStackMore details in:README fileProject ResourcesProject documentation:https://docs.openstack.org/vitrage/latest/Wiki page:https://wiki.openstack.org/wiki/VitrageSource:https://opendev.org/openstack/vitrageStoryBoard:https://storyboard.openstack.org/#!/project/openstack/vitrageRelease notes:https://docs.openstack.org/releasenotes/vitrageDesign specifications:https://specs.openstack.org/openstack/vitrage-specs/
Package: vitrage-dashboard
Vitrage is the Openstack RCA (Root Cause Analysis) Engine for organizing,
analyzing and expanding OpenStack alarms & events, yielding insights
regarding the root cause of problems and deducing the existence of problems
before they are directly detected.Vitrage Dashboard is an extension for OpenStack Dashboard that provides a UI for
Vitrage.Project ResourcesWikiCode ReviewStoryboardRelease notesHow to use this packageWith DevstackAdd the following to your Devstack local.conf fileenable_plugin vitrage-dashboard https://opendev.org/openstack/vitrage-dashboardWith Horizongit clone https://github.com/openstack/horizon.git

git clone https://github.com/openstack/vitrage-dashboard.git

git clone https://github.com/openstack/python-vitrageclient.git

cd ../horizon

./run_tests.sh -f --docs

cp ./openstack_dashboard/local/local_settings.py.example ./openstack_dashboard/local/local_settings.py

pushd ../vitrage-dashboard

../horizon/tools/with_venv.sh pip install -e.

cp -a vitrage_dashboard/enabled/* ../horizon/openstack_dashboard/enabled/

popd

cd python-vitrageclient

../horizon/tools/with_venv.sh pip install -e.
Package: vitrage-tempest-plugin
Tempest plugin for Vitrage ProjectIt contains the tempest plugin for the functional testing of Vitrage Project.Free software: Apache licenseDocumentation:https://docs.openstack.org/vitrage/latest/Release notes:https://docs.openstack.org/releasenotes/vitrage/Source:https://opendev.org/openstack/vitrage-tempest-pluginStories and Bugs:https://storyboard.openstack.org/#!/project/openstack/vitrage-tempest-plugin
Package: vitriini
VitriiniShowcase (Finnish: vitriini) some packaged content - guided by conventions.License: MIT|Country of origin: Switzerland|Export control classification number(ECCN): EAR99Third party dependencies are documented in the folderthird-party.DocumentationUser and developerdocumentation of vitriini.Bug TrackerAny feature requests or bug reports shall go to thetodos of vitriini.Primary Source repositoryThe main source ofvitriiniis on a mountain in central Switzerland.
We use distributed version control (git).
There is no central hub.
Every clone can become a new source for the benefit of all.
The preferred public clones ofvitriiniare:on codeberg- a democratic community-driven, non-profit software development platform operated by Codeberg e.V.at sourcehut- a collection of tools useful for software development.ContributionsPlease do not submit "pull requests" (I found no way to disable that "feature" on GitHub).
If you like to share small changes under the repositories license please kindly do so by sending a patchset.
You can either send such a patchset per email usinggit send-emailor
if you are a sourcehut user by selecting "Prepare a patchset" on the summary page of your fork atsourcehut.StatusExperimental.Note: The default branch isdefault.
Package: vitriolic
vitriolicThis project unifies the various subprojects Touch Technology has created over the years that were intended to be
reusable in isolation, but in practice never stood alone for long. The maintenance burden has become too great.Origin of the nameI decided to do this on Tuesday 8th November, US Election day 2016. Thewiktionary word of the daywasvitriolicwhich, given the nature of Donald Trump's campaign to become American President, it seemed like a pretty good fit.As at time of authoring this document I have no idea if he'll win the election.This project will now forever remind me of the day that America shat the bed.Supported Django versionsThe aim is to only support LTS versions of Django. I don't work on this project all the time, so I need it to be as
stable as possible for as long as possible.As of this release, we target and test against the 3.2 and 4.2 releases.
Package: vitruvi-sdk
Vitruvi Python LibraryInstallationAdd this dependency to your project's build file:pipinstallvitruvi-sdk# orpoetryaddvitruvi-sdkAuthorizationYou can use either a JWT or a Bearer token to authenticate with Vitruvi.fromvitruvi.clientimportVitruvivitruvi_client=Vitruvi(api_key="Bearer YOUR_TOKEN")vitruvi_client=Vitruvi(api_key="JWT YOUR_JWT")Usagefromvitruvi.clientimportVitruvivitruvi_client=Vitruvi(api_key="Bearer YOUR_TOKEN")permission=vitruvi_client.create_auth_permissions(Vitruvi.Permission(id="permission-id",name="permission-name",codename="codename")))print(permission)Async clientThis SDK also includes an async client, which supports theawaitsyntax:importasynciofromvitruvi.clientimportAsyncVitruvivitruvi_client=AsyncVitruvi(api_key="Bearer YOUR_TOKEN")asyncdefcreate_permission()->None:permission=vitruvi_client.create_auth_permissions(Vitruvi.Permission(id="permission-id",name="permission-name",codename="codename")))print(permission)asyncio.run(create_permission())Beta statusThis SDK is in beta, and there may be breaking changes between versions without a major version update. Therefore, we recommend pinning the package version to a specific version in your pyproject.toml file. This way, you can install the same version each time without breaking changes unless you are intentionally looking for the latest version.ContributingWhile we value open-source contributions to this SDK, this library is generated programmatically. Additions made directly to this library would have to be moved over to our generation code, otherwise they would be overwritten upon the next generated release. Feel free to open a PR as a proof of concept, but know that we will not be able to merge it as-is. We suggest opening an issue first to discuss with us!On the other hand, contributions to the README are always very welcome!