Saravanan666/pypi-org huggingface dataset:
Package: ranking-sorting
# ranking_sortingRanking and Sorting algorithms for vtalks.net[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
[![CircleCI](https://circleci.com/gh/vtalks/ranking_sorting.svg?style=svg)](https://circleci.com/gh/vtalks/ranking_sorting)
[![codecov](https://codecov.io/gh/vtalks/ranking_sorting/branch/master/graph/badge.svg)](https://codecov.io/gh/vtalks/ranking_sorting)## LicenseCopyright © 20015-2018 vtalks.net authors.Licensed under the Apache License, Version 2.0 (the “License”);
you may not use this file except in compliance with the License.
You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an “AS IS” BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Package: ranking-table-tennis
ranking-table-tennisRanking system for table tennis players.The system keeps a record of championship points and rating points.Championship points aim at tracking the tournament achievements of players.
Their computation is based on the best rounds reached by players in each tournament.Rating points aim at tracking the relative skill level of players.
Their computation is based on the outcomes of one-versus-one matches.InstallationThis system has been developed for a Linux environment.System-wide installationsudo pip3 install ranking-table-tennisSingle-user installation (recommended)pip3 install --user ranking-table-tennisUninstallation[sudo] pip3 uninstall ranking-table-tennisUpdateSystem-wide updatesudo pip3 install -U ranking-table-tennisSingle-user update (recommended)pip3 install --user -U ranking-table-tennisUsageThe commands must be run in a bash terminal.Fill a sheet with the tournament matches. It must be saved in the Tournaments spreadsheet (xlsx).Players and Initial Ranking sheets must be in the same spreadsheet (it is used as a database).Runrtt preprocess.The scripts will read the Tournament spreadsheet and will ask for missing information of new players (city, affiliation, initial rating points, and category).
This information will be saved in the Players and Initial Ranking sheets.Runrtt compute.It will ask for the tournament that you want to process. 0 will compute all from the beggining.
The outcome will be saved in the Ranking spreadsheet.Runrtt publish.It will ask for the index of the tournament that you want to publish.
The outcome will be saved in a new spreadsheet.DevelopmentInstall locally from source (source directory will immediately affect the installed package
without needing to re-install):pip3 install --user --editable .Update version atsetup.pyand then create a source distributionpython3 setup.py sdist bdist_wheelUpload to PyPItwine upload dist/*Upload to TestPyPItwine upload --repository-url https://test.pypi.org/legacy/ dist/*
Package: rankit
Rankitis a project facilitating ranking process through pairwise
comparision.Suppose there’s a soccer/football/baseball competition consisting of a
series of matches, one needs to come up with the authentic power of each
team based on completed match results. Each match consists of two teams
and their corresponding final scores. This could not be done through
simply averaging each team’s score, since not all teams plays the same
number of matches and, besides that, the team that defeated early may
not necessarily be the weakest team since they may got paired with a
powerhouse at early stage.Rankitprovides two kinds of solutions to solve this problem:All records are presented at once, and then come up with a rating. We
provide the following ranking solutions in this way:Massey Rank (See more)Colley Rank (See more)Keener Rank (See
more)Markov Rank (Page rank)OD Rank (a.k.a. Offence-Defence Rating,see
more)Difference RankMatches have time sequence infomation, and player’s ratings are got
updated match by match. We provide the corresponding ranking
solutions:Elo Rank (See
more)Glicko 2 Rank (See more)TrueSkill Rank (pairwise only)(See
more)
Package: rank-llm
RankLLMWe offer a suite of prompt-decoders, albeit with focus on open source LLMs compatible withFastChat(e.g., Vicuna, Zephyr, etc.). Some of the code in this repository is borrowed fromRankGPT!Releasescurrent_version = 0.2.8📟 InstructionsCreate Conda Environmentcondacreate-nrankllmpython=3.10
condaactivaterankllmInstall Pytorch with CUDApip3installtorchtorchvisiontorchaudio--index-urlhttps://download.pytorch.org/whl/cu118Install Dependenciespipinstall-rrequirements.txtRun end to end Testpythonsrc/rank_llm/scripts/run_rank_llm.py--model_path=castorini/rank_zephyr_7b_v1_full--top_k_candidates=100--dataset=dl20\--retrieval_method=SPLADE++_EnsembleDistil_ONNX--prompt_mode=rank_GPT--context_size=4096--variable_passagesContributingIf you would like to contribute to the project, please refer to thecontribution guidelines.🦙🐧 Model ZooThe following is a table of our models hosted on HuggingFace:Model NameHugging Face Identifier/LinkRankZephyr 7B V1 - Full - BF16castorini/rank_zephyr_7b_v1_fullRankVicuna 7B - V1castorini/rank_vicuna_7b_v1RankVicuna 7B - V1 - No Data Augmentationcastorini/rank_vicuna_7b_v1_nodaRankVicuna 7B - V1 - FP16castorini/rank_vicuna_7b_v1_fp16RankVicuna 7B - V1 - No Data Augmentation - FP16castorini/rank_vicuna_7b_v1_noda_fp16✨ ReferencesIf you use RankLLM, please cite the following relevant papers:[2309.15088] RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models@ARTICLE{pradeep2023rankvicuna,
  title   = {{RankVicuna}: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models},
  author  = {Ronak Pradeep and Sahel Sharifymoghaddam and Jimmy Lin},
  year    = {2023},
  journal = {arXiv:2309.15088}
}[2312.02724] RankZephyr: Effective and Robust Zero-Shot Listwise Reranking is a Breeze!@ARTICLE{pradeep2023rankzephyr,
  title   = {{RankZephyr}: Effective and Robust Zero-Shot Listwise Reranking is a Breeze!},
  author  = {Ronak Pradeep and Sahel Sharifymoghaddam and Jimmy Lin},
  year    = {2023},
  journal = {arXiv:2312.02724}
}🙏 AcknowledgmentsThis research is supported in part by the Natural Sciences and Engineering Research Council (NSERC) of Canada.
Package: rankmetrics
IntroductionThis package contains functions for calculating various metrics relevant
for learning to rank systems such as recommender systems.IMPORTANT: This project is still in its very early stages. Results
should be taken with a grain of salt.scikit-learn-like APIsThis package aims to provide APIs that are familiar if you are used to
working with scikit-learn.Supported metricsRecall@kBag Recall@kMean Rank PercentileNDCG
Package: rankpy
rankpyVarious ranking and segmentation algorithms for lists of rankings.Package organizationdataSample .csv files representing survey data & input into the rankpy code.environmentsYAML file with the necessary Python packages for all code execution.notebooksJupyter notebooks to show execution of the rankpy code.rankpyprocess_example.py-- Function to convert raw survey data into the required input.rank.py-- Functions to apply Hodge ranking & validation testing.testsUnit tests for specific functions.
Package: rank-similarity
Rank SimilarityRank Similarity is a set of non-linear classification and transform tools for large multi-dimensional datasets that use the scikit-learn API.InstallationDependenciesrank-similarity requires:Scikit-learn (>= 0.23)Python (>= 3.7)NumPy (>= 1.14.6)SciPy (>= 1.1.0)Optionally for plotting examples:matplotlib (>= 2.2.2)Install via pippip install rank-similarityDevelopment versionTo get the latest development version, clone the GitHub repository:git clone https://github.com/KatharineShapcott/rank-similarityUsagefromranksimimportRankSimilarityClassifierX=[[0,1],[1,0]]y=[0,1]clf=RankSimilarityClassifier()clf.fit(X,y)pred=clf.predict(X)More InformationDocumentationMore details and background information is available in theonline documentation.LicenseThe package is new BSD licensed.CitationPlease cite the following publication (in preparation)[1].[1]Shapcott, Bird, & Singer. Confusion-based rank similarity filters for computationally-efficient machine learning on high dimensional data. In preperation. (2021)
Package: ranktier
ranktierranktier convertsrank_tiernumbers from APIs likeOpenDotato human-readable ranksSetupranktiercan be installed fromPyPi:pip install ranktierIt can also be installed by downloading the repo and runningpip install .Usage>>>importranktier>>>r=ranktier.Rank(42)>>>print(r)Archon[2]>>>p=ranktier.Player(86745912)>>>print(p.rank)Immortalrank3Rank.namecan also be used, but returns the same as above.rankhas to be a two-digit number for ranktier to work. Ranktier works regardless ofrankbeing astr-type orint-type variable.As of 1.4, Player objects also have names:>>>p.personaname天鸽>>>p.nameArteezypersonanamerefers to a profile's most recent alias, whilenameis the tag used by pros in-game.
Package: ranpass
ranpassSimple Random Password Generator CLI Tool.RequirementsThis package requires Python 3 (it is 2021 after all). What else, let's see... a human to use it I guess?InstallingTo install this CLI tool you can run the below commandpip3 install ranpassAlternatively, you clone this repo and then run this command from within the repository folderpython3 setup.py installBoth the above commands would install the package globally andranpasswill be available on your system.How to useGenerate a random passwordranpass generate -l <length of password desired> -o <option of password type>There are four options for password typeOnly lowercase alphabetsLowercase + uppercase alphabetsAlphanumericAlphanumeric + Special characters (Default option, because passwords should be as secure as possible)If you want to see these options in the terminal, runranpass generate -h. You could also runranpass -hto see the available commands. (generateis the only command right now).FeedbackPlease feel free to leave feedback in issues/PRs.
Package: ranploy
RanployTool to generate the transaction payloaddatathat will deploy a random hex string as a smart contract.Example$pythonmain.py--bytecode112233446004600d60003960046000f30011223344You then need to create a transaction and use this as the payload dataweb3.eth.sendTransaction({from: "0x8d26D6d498a01243820154c7Ddb63b47c00DbF6e", data: "0x6004600d60003960046000f30011223344"})Your contract will have this bytecodeweb3.eth.getCode("0xDdB083baD281D7242FF69E36c7565b003785cb1A")
'0x11223344'
Package: ransac
RANSACPython wrapper around Enric Meinhardt's C implementation of RANSAC distributed
inimscript.InstallationTheransacPython package can be installed from PyPI withpip install ransacAlternatively, it can be installed from sources in editable mode withgit clone https://github.com/cmla/ransac
cd ransac
pip install -e .Usageimport numpy as np
import ransac

matches = np.loadtxt("tests/data/matches.txt")
inliers, F = ransac.find_fundamental_matrix(matches)
Package: ranshark
ranshark===========This is the Python project that read 5g RAN packets using pyshark lib (a Tshark wrapper) and filter flows based below identities.5G Identifiers4G IdentifiersThis will automatically show call flow visualization view based on the filters determined from input pcap file and basic stats like rrc,ho and context call count etcQuick StartCreate your own Django project and follow belowdjango-admin startproject <your choice>Add drawranflow to your project INSTALLED_APPS settings like belowINSTALLED_APPS= [
  .....
  "drawranflow",
  ]Add url path as belowpath('drawranflow/', include('drawranflow.urls')),Add project settings.py with MEDIA_ROOT like belowMEDIA_ROOT = BASE_DIR/'drawranflow/pcapfiles'
Package: rant
# Rant #<http://github.com/lrvick/rant>## About ##“Rant” is a CLI driven blog-aware website generator written in python. It is
intended to make maintaining a blog or personal website easy using only your
favorite CLI editor such as vim, and a few simple commands.Insipired by great projects such as: [Jekyll](https://github.com/mojombo/jekyll),
[Pelican](https://github.com/ametaireau/pelican)
and [Goldbarg](https://github.com/Schnouki/Golbarg)## Current Features ##Simple post/page authoring as markdown text filessitemap.xml supportRSS / Atom supportFull jinja2 templating integrationPaginationPygments syntax hilightingDisqus commenting integration in default templatesOther stuff## Requirements ##Python 2.7+piplibyamljinja2pygments## Usage / Installation ##Install rant`bash pip install rant `Start a new rant projectCreate a folder where you intend your site to live and initialize rant.`bash mkdir my_rant_blog cd my_rant_blog rant install `This will populate the folder with the basic rant project ready to add posts to.Create a post or pageTo make a first blog post do:`bash rant publish `This will open your default $EDITOR with a template like the following:`bash---layout: post title: date:2011-09-2302:45 image: tags: comments: true draft: false---`Fill out the top [YAML](http://yaml.org/) block as you desire, then add
your post below the ‘—’ in
[Markdown](http://daringfireball.net/projects/markdown/) format.On saving it will automatically generate any needed html for the page
according to the ‘post’ templates found in ‘layouts/post.html’ .To edit a post in the future simply edit it and regenerate.`bash vimposts/201109230245-My_neat_blog_post.mdrant generate `From here you can also modify any of the media found in /static, or edit
any of the [Jinja2](http://jinja.pocoo.org/) layouts found in ‘layouts’
to your liking.Happy ranting :-)## Notes ##Use at your own risk. You may be eaten by a grue.Questions/Comments?You can find me on the web via:[Email](mailto://lance@lrvick.net) |
[Blog](http://lrvick.net) |
[Twitter](http://twitter.com/lrvick) |
[Facebook](http://facebook.com/lrvick) |
[Google+](http://plus.google.com/109278148620470841006) |
[YouTube](http://youtube.com/lrvick) |
[Last.fm](http://last.fm/user/lrvick) |
[LinkedIn](http://linkedin.com/in/lrvick) |
[Github](http://github.com/lrvick/)
Package: rantence
Sentence GeneratorWhat does it do?This NPM package that is used forPython, generates random sentences. Check out the code description below on how to use it!INSTALL$ pip install rantenceFOR LINUX$ pip3 install rantenceUSAGEimportrantence//Getsmodulerantence.rt()//Prints1outof3randomsentencesDISCLAIMER:You may need theRANDOMpython module installed.
Package: raok
Raokis very simple RADIUStestingserver which accepts any authentication or accounting and
prints it out. Unless you specify otherwise.
It supports challenges, and PAP/CHAP/MS-CHAP/MS-CHAP2 and various other small things good for testing.NOTE: before start, runraok-init.shto create default config files.You can configure it in:/etc/raok/raok.cfgor from current directory, if the above is not found../etc/raok.cfgRastais very simple program sending RADIUS accounting  using the same config file.SupportFor comments, feedback or new feature discussion feel free to
drop a message topplay-users@googlegroups.commailing list.
Package: rapdevpy
Rapid Development Library for Pythonsqlalchemy: database object relationship mappinglxml: parsing XML and HTMLnetworkx: graph, edge and vertex analysisDevelopment# Note: Install Python 3
# Update pip and install virtualenv (dependency encapsulator) and black (linter; IDE needs to be restarted)

# Note: install Poetry for Linux
$: curl -sSL https://install.python-poetry.org | python3 -

# Note: install Poetry for Windows
$: (Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | py -

$: curl -sSL https://install.python-poetry.org | python3 - --uninstall$: poetry install  # install all dependenciesdist$: pip install dist/rapdevpy-1.0.0-py3-none.any.whl

$: rapdevpydocs$: poetry shell
$: cd docs
# Note: review source/conf.py and source/index.rst
$: make html
# Note: see docs in docs/build/apidocs/index.htmlrapdevpy$: poetry run python ./rapdevpy/runner.pytests$: poetry run pytest --durations=0$: poetry run pytest --cov=poetry_template --cov-report=html tests
# Note: see coverage report in htmlcov/index.html
# Note: exclude directories from coverage report through .coveragercpoetry.lockDependencies, Python version and the virtual environment are managed byPoetry.$: poetry search Package-Name
$: poetry add [-D] Package-Name[==Package-Version]pyproject.tomlDefine project entry point and metadata.Linters$: poetry run black .MyPy$: poetry run mypy ./rapdevpy ./testscProfile$: poetry run python ./rapdevpy/profiler.pyBuild and publish$: poetry build

# Note: get the token from your PiPy account
$: poetry config pypi-token.pypi PyPI-Api-Access-Token$: poetry publish --buildhttps://pypi.org/project/rapdevpy/
Package: raphaelpy
RaphaëlPyA library for creating SVG drawings using Python.OverviewIts usage and most of the public API (and obviously its name, too) is strongly inspired byRaphaël JavaScript Library.
Some examples and some of the implementation details are borrowed from the original project, too.Seeexamplesto examine how to it works and how to use it.CompatibilityThe package works with both Python 2 and 3 (tested onUbuntu 18.04 LTSand Python 2.7.15 and Python 3.6.6).Usageas simple as:fromraphaelpyimportRaphael# Creates canvas 320 x 200 at 10, 50paper=Raphael("drawing.svg",320,200)# Creates circle at x = 50, y = 40, with radius 10circle=paper.circle(50,40,10)# Sets the fill attribute of the circle to red (#f00)circle.attr("fill","#f00")# Sets the stroke attribute of the circle to bluecircle.attr("stroke","#00f")# Saves the resulting drawing to the filepaper.save()Seeexamplesdirectory for more examples.InstallationUsingsetup.pyfile:python setup.py install [options], e.g.python setup.py --userUsingmake(callssetup.pyinternally):make install [options], e.g.make install USER=TRUE PYTHON=python3Usingpip[sudo] pip[3] install [options] raphaelpy, e.g.pip install --user raphaelpyorsudo pip3 install raphaelpyNote: usepipof Python 2 andpip3for Python 3What is heredirectorycontentraphaelpysource codeexamplesexamples how RaphaëlPy works and how to use itMakefilemakefile for the project (with targetshelp,install,doc,test,clean,dist)docssource codes to build HTML documentationtestsa few unit testssetup.pypython setup file for installationContributionPull RequestsAre welcome.Bug reportingIn case of any question or problem, please leave an issue at thegithup page of the project.ContributorsJan StránskýLicenseThis project is licensed under the LGPL License - see thelicense filefor details.AcknowledgementstoRaphaël JavaScript Libraryfor great job and inspiration.
Package: rapi-api
rapi-api-nodejsQuick Startimportrapi_apifromrapi_apiimportConfigBuilder,Rapiconfig=ConfigBuilder()\.setTestSuites(["test1.json"])\.addBrowser("http://url.to.selenium.server",{"browserName":"firefox",}).build()rapi=Rapi("path/to/rapi/runner",config)report=rapi.run()print(report.json)DocumentationPython
Package: rapiboy
A simple python wrapper for Google Maps API.
Use it to get the formatted address or co-ordinates of any location.The code is Python 2, but Python 3 compatible.InstallationFast install:pip install mygmapFor a manual install get this package:wget https://github.com/nikhilkumarsingh/mygmap/archive/master.zip
unzip master.zip
rm master.zip
cd mygmap-masterInstall the package:python setup.py installExamplefromgeoimportlocator# get formatted address of any locationprintlocator.get_address("rohini, delhi")# get co-ordinates of locationprintlocator.get_coordinates("delhi")Here is the output:Rohini, New Delhi, Delhi, India
(28.7040592, 77.10249019999999)
Package: ra-pickles
RA PicklesIn many applications, elements from a large dataset, that cannot be stored in memory, need
to be sampled (with or without replacement). This simple package simplifies this process
by allowing storage of large datasets by splitting them over multiple files in a directory.
Once that's done, any dataset element can be queried. Further, most python objects as dataset elements can be used as pickles are used at the backend.As mentioned before, a dataset will be represented by a directory that contains
two sets of files, meta and data. The file identifiers are randomly generated and therefore,
two datasets can be added together to create a larger dataset without additional work.
This also allows multiple applications to add elements to the dataset in parallel. An example
is multiple simulations running in parallel.Installationpip3 install ra-picklesExampleFirst import all the packagesfrom ra_pickles import RandomAccessPicklesReader, RandomAccessPicklesWriter
import shutil
import os
import numpy as npSo to create a dataset intest_folder, use the following code.100here
specifies number of dataset samples in each file. If there are more than100files, multiple files will be created. Heuristically, this number can be chosen
such that resulting data files are approximately1 GB, although this wouldn't
affect performance much as a complete file is not fully loaded into memory.
On the other hand, a too small number can also affect performance as some file
systems create issues if there are too many files.fold = 'test_folder'
writer = RandomAccessPicklesWriter(100, fold)Now entries to the dataset can be added as follows:for i in range(30):
    # d is the dataset element which can be any python object
    d = np.ones(4) * i
    
    # and you add it to the dataset
    writer.add(d)
writer.close()Here,30numpy arrays have been added.To sample elements in the dataset, use the following code:reader = RandomAccessPicklesReader(fold)
print("Total", reader.get_total())

print("Trying to retreive")
for i in range(30):
    print("Retrieving",i)
    a = reader.get_element(i)
    print(i, a[0])The index retrieval index can be randomly generated --[0, reader.get_total() )to sample random elements.Multiple elements can also be retrieved in parallel for fast access. To do so, first,
retrieval threads must be started (and closed at the end):reader.start_parallel_retrieval_threads(n_theads=5)
data = reader.get_multi_in_parallel([1,2,3])
reader.close_parallel_retrieval_threads()
reader.close()Good luck!