Saravanan666/pypi-org huggingface dataset:
Package: shttpd
Simple HTTP downloader written in PythonInstallationYou can install or upgrade shttpd with:$ pip install shttpd--upgradeOr you can install from source with:$gitclonehttps://github.com/RDCH106/pySimpleHTTPDownloader.git--recursive$cdpysimplehttpdownloader$pipinstall.Quick example$shttpd-uhttps://raw.githubusercontent.com/RDCH106/i-love-firefox/183266a9/I_Love_Firefox_220x56.pngThe example downloadsI_Love_Firefox_220x56.pngin current path and
shows download progress.HelpRun the following command to see all options available:shttpd--helporshttpd-h
Package: shtuff
shtuffShell stuff will stuff commands into a shell à latmux send-keysorscreen stuff.InstallationIf your environment is configured to use Python 3 by default:$ pip install shtuffOtherwise:$ pip3 install shtuffPlease note:shtuffonly works on Python 3.7+!ExamplesIn shell A, run:$ shtuff as shell-aIn shell B, run:$ shtuff into shell-a "git status"Observe how shell A rangit status.An example use case forshtuff newmight be a setup script to open a couple
shells automatically. Consider this script:#!/usr/bin/env bashtermite-e"shtuff new vim"&termite-e"shtuff new 'tail -f /var/log/somelog.log'"&This script will open two terminals, one running vim, and one
running tail.DevelopmentInstall your local copy:$pip3install-e.Unless you know what you are doing, we highly recommend running tests inside a virtual environment.
Here is how you can create and activate a virtual environment:$python3-mvenv.venv
$source.venv/bin/activateYou can leave the virtual environment viadeactivate:$deactivateRun tests:$maketestReleasingWe release using Makefile, choose the relevant target:$makerelease-major
$makerelease-minor
$makerelease-patchand wait for the automated deploy toPyPi!
Package: shtuka
shtuka(russian: "a thing"): Neat and tidy configs gadget with methods on
steroids 🔥Getting Startedpip install shtuka(py3.6+)TL;DR"""Basic stuff"""# flake8: noqaimporttorchimportshtuka@shtuka.mark('data',alias='D')# W/o explicit key - __name__ will be used.defget_data(part,source='mnist',image_size=28):passclassCustomResNet(torch.nn.Module):def__init__(self,input_size,num_classes=3,dropout:float=0):"""Docstring/inline type hinting helps correct parsing for cli."""super().__init__()deffit(self,data,lr):passdeftest(self,data,metrics):pass# Outside marking with alias.CustomResNet=shtuka.mark.model(CustomResNet)CustomResNet.test=shtuka.mark.T(CustomResNet.test)defmain(cfg):# 'shtuka' automatically propagate cfg.data kwargs to calls.train_data,eval_data=get_data('train'),get_data('eval')# But you can also add additional kwarg to override it.model=CustomResNet(# `x_` unwraps shtuka. Passing wrapped one also working for marked obj.input_size=cfg.data.image_size.x_,# `f_` is finalizing operator and outputs lambda result.num_classes=cfg.data.source.f_(lambdax:10ifx=='mnist'else2),)# Valid lr format could be: string, float, incorrect or missing.model.fit(train_data,lr=cfg.optim.lr.coerce_(float)|1e-3)# `fs_` applies lambda to composite structure.result=model.test(data=eval_data,metrics=cfg.test.metrics.fs_(','.join),)# Multi-dot set doesn't fail w/o 'stats' key. It creates dict on-the-fly.cfg.stats.num_weights=model.num_weights# Save full instances specification.cfg.eval,cfg.model=shtuka.describe(get_data),shtuka.describe(model)ifcfg.log.save_result:# If 'save_results' exists and is True.print(cfg.log.msg_file.f_('read'))# There are many such funcs.torch.save({cfg.frozen_():result},# `cfg.frozen_()` is immutable.# '/' chooses right value is 'save_path' is missing.cfg.log.save_path/'/data/result.pth',)if__name__=='__main__':# 'validate' checks collision with methods# (like 'f_' as a config key and as a method).shtuka.run(main,validate=True)base.yaml:optim:lr:'4e-3'T:metrics:-acc-recallCLI Run:pythontrain.py-cbase.yamlD.image_size=24T.metrics.0=f1FeaturesFirst Feature"""Non-basic stuff"""importshtukacfg=shtuka.cook({'kek':{'mem':0}})assertcfg.kek.mem0.miss_Second Feature"""Non-basic stuff"""importshtukacfg=shtuka.cook({'kek':{'mem':0}})assertcfg.kek.mem0.miss_Development & ContributingPick an issue, branch out from master, file a PR and comply with tox.Format/Lint/Test/Toxpipinstall-e'.[dev]'makeformat# => lint/test or just flt.make[clean]toxGit/ReleaseDon't forget to updatechangelogand createGitHub releasemanually.makesetup-pre-commit
makereleaseVERSION='?.?.?'Licenseshtukais MIT licensed, as could be found in theLICENSEfile.
Package: shtu-venus
### Installation* Install Hyperopt(Don't install by pip. The Hyperopt version in pip is too old. Install it from source.)- git clone https://github.com/hyperopt/hyperopt.git- python setup.py install- sudo apt-get install mongodb-server* install torchnet### DesignsA deep-learning project usually consists of data loading, model building, model training/testing phases.Also we need some auxiliary functions such as autosave/load, visualization, auto hyperparameter optimization and some debug tools, etc. to help us.#### Optimizing hyperparameters* Available libraries: Hyperopt, HPOlib2, neupy# torchnet_VenusThe base framework for deep learning based on pytorch, torchnet, etc.## TODO[TODO Issue](https://github.com/ShanghaiTechVENUS/torchnet_Venus/issues/1)## CreditsPrimarily referenced tnt of pytorch:  [Torchnet @pytorch](https://github.com/pytorch/tnt)Many thanks to [@pytorch](https://github.com/pytorch).# Code Structure: a lib that helps us to do some debugs, tune parameters, visualize, configWish the lib to be a wrapper, but users can also use the modules separately.* debug utilities## Recently* base* initializer* visual* hyperopt: tune hyper parameters* optimizer: multistep learner* config* autosave, autoload: If unexpected interruption or active keyboard interruption happens to the program, then will save the checkpoint and parameters automatically.* utils- seed initialization- weight initialization## Long-term goal* profiler* common dataloader* search structure* tnt such as engine, meter* autoselect idle graphic card# Class graphconfigEngine: Tune network parameters- autosave- train- test- load_test- load_trainStructureSearcherHyperopt            ->         Engine             -> config-> visualDataLoaderShould be a template or a library?Flexibility should be the first.Utilities follows.
Package: shuaifu
ShuaifuYet another languageInstallpipinstallshuaifuUsageimportshuaifushuaifu.believe()# print believe wordsprint(shuaifu.get_version())# print versionprint(shuaifu.translate('woxbyhukfu!'))# translate into pinyinorimportshuaifushuaifu.xbyh()# uuiuxbyhwfbfprint(shuaifu.bjbf())# uuiubjbfprint(shuaifu.fjyi('woxbyhukfu!'))# fjyidcpbybGet Holidaysimportshuaifuif__name__=='__main__':startYear=2000count=10foriinshuaifu.holidays(startYear,count):print(i)orimportshuaifuif__name__=='__main__':kdui=2000uull=10foriinshuaifu.jxqi(kdui,uull):print(i)the out put will be2002-12-14
2003-12-14
2008-12-14Advanced Usageimportshuaifu@shuaifu.believedefhello(name):print('Hello '+name)if__name__=='__main__':hello('World')the output will be函数hello受到了感化,函数hello开始信仰帅副了!
函数hello沐浴教旨,努力工作,终于有了结果
Hello World
Package: shub
shubis the Scrapinghub command line client. It allows you to deploy
projects or dependencies, schedule spiders, and retrieve scraped data or logs
without leaving the command line.RequirementsPython >= 3.6InstallationIf you havepipinstalled on your system, you can installshubfrom
the Python Package Index:pip install shubPlease note that if you are using Python < 3.6,
you should pinshubto2.13.0or lower.We also supply stand-alone binaries. You can find them in ourlatest GitHub
release.DocumentationDocumentation is available online via Read the Docs:https://shub.readthedocs.io/, or in thedocsdirectory.
Package: shub-workflow
A set of tools for controlling processing workflow with spiders and script running in scrapinghub ScrapyCloud.Installationpip install shub-workflowIf you want to support s3 tools:pip install shub-workflow[with-s3-tools]For google cloud storage tools support:pip install shub-workflow[with-gcs-tools]UsageCheckProject Wikifor documentation. You can also see code tests for lots of examples of usage.NoteThe requirements for this library are defined in setup.py as usual. The Pipfile files in the repository don't define dependencies. It is only used
for setting up a development environment for shub-workflow library development and testing.
Package: shucks
Installingpip3installshucksSimple UsageValidating a login form accepting email or phone and a password.importshucksimportmathschema=shucks.And(dict,{'id':shucks.If(shucks.And(str,lambdav:'@'inv),shucks.Con(lambdav:v.split('@',1)[1],shucks.contain({'gmail.com','hotmail.com','yahoo.com'})),shucks.And(shucks.Or(str,int),shucks.Con(str,shucks.Con(len,shucks.range(10,10))))),'password':shucks.And(str,shucks.Con(len,shucks.And(shucks.range(8,math.inf))),shucks.wrap(shucks.Not(lambdav:'logo'inv),'logo')),shucks.Opt('remember'):bool})data={'id':1234567890'password':'logo1234'}shucks.check(schema,data)LinksDocumentation
Package: shuffdi
Shuffles a dictfromshuffdiimportshuffle_dictprint(dict([('sape',4139),('guido',4127),('jack',4098)]))print(shuffle_dict(dict([('sape',4139),('guido',4127),('jack',4098)]))){'sape':4139,'guido':4127,'jack':4098}{'guido':4127,'sape':4139,'jack':4098}
Package: shuffle
A simple python module that is meant to simulate the action of shuffling a python List as if it were a deck of cards.TypesRifflehttp://en.wikipedia.org/wiki/Shuffling#RifflePredictable behaviours that make a human riffle shuffle imperfectOnce a deck of cards is divided to each hand, the amount of cards in each hand is not (likely) equal.
As each thumb releases from it’s half of the deck, sometimes more than one card drops from a single hand at a time.
As the deck in each hand gets more and more thin, the probability of larger chucks of cards dropping from each hand increases.:shuffle.riffle(List original[, int shuffles])Overhandhttp://en.wikipedia.org/wiki/Shuffling#Stripping_or_overhandPredictable behaviours that make a human overhand shuffle imperfectRandom amounts of cards (chunks) are taken from the top and placed placed in the opposite hand in reverse order (retaining the order within each chunk):shuffle.overhand(List original[, int shuffles])Mongeanhttp://en.wikipedia.org/wiki/Shuffling#Mongean_shuffleA very predictable shuffle, alternating placing the top card on the bottom/top of the new deck.:shuffle.mongean(List original[, int shuffles])Pilehttp://en.wikipedia.org/wiki/Shuffling#Pile_shufflePredictable shuffle, dealing items into N piles and then rejoining the piles.:shuffle.pile(List original, int piles[, int shuffles])Installationpip install shuffleOrgit clone git://github.com/jondavidjohn/Card-Shuffle-for-Python.git shuffle
cd ./shuffle
sudo python setup.py installLinux Users- Make sure you have the python-dev package installed.Usageimport shuffle
riffled_list = shuffle.riffle(original_list, 3)  # riffles the list 3 times
overhanded_list = shuffle.overhand(original_list, 2)  #overhand's the list 2 times
mongeaned_list = shuffle.mongean(original_list, 5)  #mongean shuffle 5 times
piled_list = shuffle.pile(original_list, 3, 6)  #pile shuffle, using 3 piles, 6 times
Package: shuffleboard2js
shuffleboard2js further lowers the barrier of entry for teams that want to build a custom HTML/Javascript dashboard by providing aShuffleboardlike interface built on top ofpynetworktables2js.Lots of students and mentors know how to create simple web pages to display content, and there’s lots of resources out there for creating dynamic content for webpages that use javascript. There is a lot of visually appealing content that others have created using web technologies – why not leverage those resources to make something cool to control your robot?DocumentationDocumentation can be found athttp://shuffleboard2js.readthedocs.org/InstallationMake sure to install python 3 on your computer, and on Windows you can
execute:py -3 -m pip install shuffleboard2jsOn Linux/OSX you can execute:pip install shuffleboard2jsUsageYou can run shuffleboard2js using the following command:python3 -m shuffleboard2jsOr on Windows:py -3 -m shuffleboard2jsThis will start a server which will serve from the current directory. You can create your custom widgets in theshuffleboard2js/widgetsfolder, which will automatically be created in the directory you ran shuffleboard2js.You will want to also pass either the--robotor--teamswitch:py -3 -m shuffleboard2js --robot roborio-XXXX-frc.local
py -3 -m shuffleboard2js --team XXXXDashboard mode currently doesn’t work, as the underlying support in
pynetworktables hasn’t been implemented yet for the newer FRC Driver Station.
Package: shufflecast
[![PyPI package](https://img.shields.io/pypi/v/shufflecast.svg)](https://pypi.python.org/pypi/shufflecast)Shufflecast is a simple script that, given a directory that contains video files
under its tree, will create and stream a shuffled playlist of the files to a
Chromecast.InstallationJust run:` pip install shufflecast `UsageJust run:` shufflecast <video directory> `Controlling playbackYou can’t. It’s meant to be like a TV channel that plays all your favorite
shows.LicenseShufflecast is released under the BSD license.
Package: shuffled
Shuffled: Random iterators for large integer rangesShuffled is a library for iterating randomly and without repetition over integer ranges.
It doesn't store all the integers in memory so that you can work with ranges of up to
2128elements, even with your standard RAM available.>>>shuffled_range=Shuffled(10)>>>list(shuffled_range)[4,1,2,9,8,5,3,0,6,7]>>>same_shuffled_range=Shuffled(10,seed=shuffled_range.seed)>>>list(same_shuffled_range)[4,1,2,9,8,5,3,0,6,7]>>>network=ipaddress.IPv4Network('10.0.0.0/8')>>>shuffled_range=Shuffled(network.num_addresses)>>>forindexinshuffled_range:...print(network[index])...10.24.41.12610.67.199.1510.240.82.19910.79.219.7410.166.105.2510.19.5.91[...]
Package: shuffle-dist-cards
DescriptionThis Program is written for hobby carders who want to shuffle and distribute deck of cards among themselves.Installationpip install shuffle_dist_cardsfrom shuffle_dist_cards import ShuffleDistCards
card_obj = ShuffleDistCards(4) # Here 4 is no_of_players
card_obj.create_n_shuffle_deck()
card_obj.dist_cards()
Package: shuffle-graph
shuffle_graphGraph shuffling package in python.InstallationInstallation can be done through pip. You must have python version >= 3.8pip install shuffle-graphUsageThe statement to import the package:from shuffle_graph_package import *Example:>>> from networkx.classes.graph import Graph
>>> G = Graph({0: {1: {}}, 1: {0: {}, 2: {}}, 2: {1: {}, 3: {}}, 3: {2: {}, 4: {}}, 4: {3: {}}})
>>> seed = 170141183460469231731687303715884105727
>>> shuffle_graph(G, seed).adj  #Set seed to make the results repeatable.
AdjacencyView({1: {0: {}, 2: {}}, 2: {1: {}, 3: {}}, 3: {2: {}, 4: {}}, 4: {3: {}}, 0: {1: {}}})
Package: shuffle-kit
shuffle-kitis a Python package for modelling and analyzing playing card shuffles.It implements several mathematical models of commonly used shuffles that can be composed into complex sequences.In addition, several utility functions are provided to faciliate analyzing the various shuffle models.InstallationDependenciesshuffle-kit requires:Python (>= 3.11)Numpy (>= 1.26.3)User installationThe easiest way to install shuffle-kit is via pip:pip install shuffle-kitExamplesBasic example of using shuffle-kitfromshufflimportgsr,strip,cut,sequence,simulate,Deckfromitertoolsimportaccumulate# Creates a list of integers from 1..52, representing a# standard deck of 52 cardsdeck=Deck(range(1,53))# Creates a riffle, riffle, strip, riffle, cut shuffle sequence# with the Gilbert-Shannon-Reeds model for riffle shufflingshuffle=sequence([gsr,gsr,strip,gsr,cut])# Simulate the shuffle a 1000 times. For each simulation, the# deck is reset to the initial orderresult=simulate(shuffle,deck,1000)# Compute the empirical cumulative density function of the# original top card, i.e., "1"ecdf=list(accumulate(result.probability[0]))# Print the probability that the original top card ("1") is# found within the top ten cards after shufflingprint(f"Probability of finding '1' within the top ten cards:{ecdf[9]:.2}")Simulating a guessing gameHere we play a round of the guessing game described in Bayer and Diaconis (1992). Consider a shuffled deck of 52 cards, face down on the table. The task is to guess the top card. After each guess, the top card is turned over and discarded.If the deck is perfectly shuffled the average number of correct guesses is around 4.5. However, if the deck is riffle shuffledktimes, then there exists a conjectural optimal strategy that achives a higher number of correct guesses depending onk.fromshuffl.gamesimportguessing_gamefromshufflimportgsr,Deck,sequence# Creates a list of integers from 1..52, representing a# standard deck of 52 cardsdeck=Deck(range(1,53))# Creates a sequence of two riffle shuffles following# the Gilbert-Shannon-Reeds modelshuffle=sequence([gsr,gsr])# Run a simulation of the guessing game described in# Bayer D., Diaconis P. (1992). Trailing the dovetail shuffle to its lair.# The Annals of Applied Probability, Vol. 2, No. 2, 294-313correct_guess=guessing_game(deck,shuffle)# Print the number of correct guesses. On average this should# be around 19.print(f"Number of correct guesses:{correct_guess}")
Package: shufflemilky
# ShuffleMilky![ShuffleMilky](https://github.com/samucafreitas/shufflemilky/blob/master/img/shufflemilky.png)<b>Terminal:</b> urxvt<br><b>Font:</b> Inconsolata# InstallationPython versions:* Python 3.4+Install:```shellpip install --user shufflemilky```# UsageCommand    |  Description---------- |  ---------`q`      | Quit`.`      | Vol Up`,`      | Vol Down## License[MIT](LICENSE)
Package: shuffle-playlist
shuffle_playlistCreates a shuffled m3u playlist from the files provided.InstallationEither install it from PyPi or clone this repository and install from its directory.pipinstallshuffle-playlistgitclonehttps://github.com/JohnDevlopment/shuffle_playlist.gitcdshuffle_playlist
pipinstall.UsageAt its most basic, the commandline will look like this:shuffle_playlistOUTPUTFILE[FILE...]For example:shuffle-playlistplaylist.m3ufile1.oggfile2.oggfile3.oggYou can either write the playlist to a file or specify-to print to stdout.
Playlists are in M3U format by default; however, you can also write to an mpl file (MPlayer playlist) by writing the output file to have a.mplextension, or by using the-foption:shuffle-playlistplaylist.mplfile1.oggfile2.oggfile3.ogg
shuffle-playlist-fmpl-file1.oggfile2.oggfile3.oggFor more information, pass-htoshuffle-playlist.
Package: shuft
A small command line tool for uploading and downloading files and folders to and from a sftp server.
Uses asyncssh and is pip installable for easy use in automated tasks.Upload a file or folder to a sftp server.Requires Python 3.5 or newer.Getting startedIn your virtual python environment of choice, install the shuft pip package.python pip install shuftBasic usage.python shuft --command upload --host files.mydomain.com --localpath my_folder --remotepath /uploads/Run with ‘’–help’ for addtional options.shuft --help

usage: __main__.py [-h] --command {upload} --host HOST [--localpath LOCALPATH]
                   [--remotepath REMOTEPATH] [--port PORT]
                   [--known_hosts KNOWN_HOSTS] [--username USERNAME]
                   [--password PASSWORD] [--client_keys CLIENT_KEYS]
                   [--compress]

Upload directories or files

optional arguments:
  -h, --help            show this help message and exit
  --command {upload}    the task to perform.
  --host HOST           the remote host to connect to.
  --localpath LOCALPATH
                        path to the local folder or file.
  --remotepath REMOTEPATH
                        path to the remote folder or file.
  --port PORT           port number on the remote (defaults to 22).
  --known_hosts KNOWN_HOSTS
                        list of known hosts, if set to None accepts any.
  --username USERNAME   username for logging in on the remote, defaults to the
                        current user
  --password PASSWORD   password for logging in on the remote
  --client_keys CLIENT_KEYS
                        list of client private key(s)
  --compress            whether to compress target folder or file before
                        transmission. Requires that the host accepts ssh
                        connections and has tar available
Package: shuhari-toolkit
shuhari-toolkitCommonly used python utilities.Build StatusFeatures includes:shuhari_toolkit.fileutilsget full path from relative to specified fileread/write text from file with ensure parent folderread/write bytes from file with ensure parent folderread/write json from file with ensure parent folderpurge folder contentshuari_toolkit.hashingget sha1 checksum of fileshuhari_toolkit.collectionsfind first matching element, by lambda/key/attr
Package: shui
SHUISpark-Hadoop Unix InstallerThis package uses Python to download and unpack a pre-built version of Spark/Hadoop from Apache.
Its primary use-case is simplifying unattended installs where the user wants "the latest available version" of these tools.Featuresdownload Spark/Hadoop release tarball from Apache.verify the tarball using the SHA512 sum provided by Apache.unpack the tarball to a target directory on your local system.InstallationFirst you'll need to installshuiusing pip:pip install shui.UsageVersionsTheversionscommand shows you all available Spark/Hadoop versions.USAGE
  shui versions [--latest]

OPTIONS
  --latest               Show only the latest available version

GLOBAL OPTIONS
  -h (--help)            Display this help message
  -q (--quiet)           Do not output any message
  -v (--verbose)         Increase the verbosity of messages: "-v" for normal output, "-vv" for more verbose output and "-vvv" for debug
  -V (--version)         Display this application version
  --ansi                 Force ANSI output
  --no-ansi              Disable ANSI output
  -n (--no-interaction)  Do not ask any interactive questionInstallTheinstallcommand will download, verify and install a particular Spark/Hadoop version.USAGE
  shui install [--latest] [--spark <...>] [--hadoop <...>] [--target <...>]

OPTIONS
  --latest               Use the latest available version
  --spark                Spark version (default: "any")
  --hadoop               Hadoop version (default: "any")
  --target               Directory to install into (default: "cwd")

GLOBAL OPTIONS
  -h (--help)            Display this help message
  -q (--quiet)           Do not output any message
  -v (--verbose)         Increase the verbosity of messages: "-v" for normal output, "-vv" for more verbose output and "-vvv" for debug
  -V (--version)         Display this application version
  --ansi                 Force ANSI output
  --no-ansi              Disable ANSI output
  -n (--no-interaction)  Do not ask any interactive question
Package: shuiyuan
ShuiYuan水源聚合了多个开放finance数据源，yahoo_finance（雅虎财经），wbdata（世界银行），knoema，pytdx（通达信），tushare，quandl，python_binance（币安）等（数据源在增加中...）Dependencies=========python 2.x/3.x[pandas](http://pandas.pydata.org/ "pandas")Installation====- 方式1：pip install shuiyuan- 方式2：python setup.py install- 方式3：访问[https://pypi.python.org/pypi/shuiyuan/](https://pypi.python.org/pypi/shuiyuan/)下载安装Upgrade=======pip install shuiyuan --upgradeStart======**Yahoo_finance（雅虎财经）:** [https://github.com/lukaszbanasiak/yahoo-finance](http://pandas.pydata.org/)import shuiyuan as syyahoo_financ = sy.get_yahoo_finance()**Wbdata（世界银行）:** [https://github.com/OliverSherouse/wbdata](https://github.com/OliverSherouse/wbdata)import shuiyuan as sywbdata = sy.get_wbdata()**Knoema :** [https://github.com/Knoema/knoema-python-driver](https://github.com/Knoema/knoema-python-driver)import shuiyuan as sysy.get_knoemaa()**Pytdx（通达信) :** [https://github.com/rainx/pytdx](https://github.com/rainx/pytdx)import shuiyuan as sypytdx = sy.get_pytdx()**Tushare :** [https://github.com/waditu/tushare](https://github.com/waditu/tushare)import shuiyuan as sytushare = sy.get_tushare()**Quandl :** [https://github.com/quandl/quandl-python](https://github.com/quandl/quandl-python)import shuiyuan as syquandl = sy.get_quandl()**Python_binance :** [https://github.com/sammchardy/python-binance](https://github.com/sammchardy/python-binance)import shuiyuan as sypython_binance = sy.get_python_binance()