Saravanan666/pypi-org huggingface dataset:
Package: hypothetical
hypothetical - Hypothesis and Statistical Testing in PythonPython library for conducting hypothesis and other group comparison tests.InstallationThe best way to installhypotheticalis throughpip.pipinstallhypotheticalFor those interested, the most recent development version of the library can also be installed by cloning or
downloading the repo.gitclonegit@github.com:aschleg/hypothetical.gitcdhypothetical
pythonsetup.pyinstallAvailable MethodsAnalysis of VarianceOne-way Analysis of Variance (ANOVA)One-way Multivariate Analysis of Variance (MANOVA)Contingency Tables and Related TestsChi-square test of independenceFisher's Exact TestMcNemar's Test of paired nominal dataCochran's Q testDescriptive StatisticsKurtosisSkewnessMean Absolute DeviationPearson CorrelationSpearman CorrelationCovarianceSeveral algorithms for computing the covariance and covariance matrix of
sample data are availableVarianceSeveral algorithms are also available for computing variance.Simulation of Correlation MatricesMultiple simulation algorithms are available for generating correlation matrices.Critical Value Tables and Lookup FunctionsChi-square statisticr (one-sample runs test and Wald-Wolfowitz runs test) statisticMann-Whitney U-statisticWilcoxon Rank Sum W-statisticHypothesis TestingBinomial Testt-testpaired, one and two sample testingNonparametric MethodsFriedman's test for repeated measuresKruskal-Wallis (nonparametric equivalent of one-way ANOVA)Mann-Whitney (two sample nonparametric variant of t-test)Mood's Median testOne-sample Runs TestWald-Wolfowitz Two-Sample Runs TestSign test of consistent differences between observation pairsWald-Wolfowitz Two-Sample Runs testWilcoxon Rank Sum Test (one sample nonparametric variant of paired and one-sample t-test)Normality and Goodness-of-Fit TestsChi-square one-sample goodness-of-fitJarque-Bera testPost-Hoc AnalysisTukey's Honestly Significant Difference (HSD)Games-Howell (nonparametric)Helpful FunctionsAdd noise to a correlation or other matrixTie Correction for ranked variablesContingency table marginal sumsContingency table expected frequenciesRuns and count of runsGoalThe goal of thehypotheticallibrary is to help bridge the gap in statistics and hypothesis testing
capabilities of Python closer to that of R. Python has absolutely come a long way with several popular and
amazing libraries that contain a myriad of statistics functions and methods, such asnumpy,pandas, andscipy; however, it is my humble opinion that
there is still more that can be done to make Python an even better language for data and statistics computation. Thus,
it is my hope with thehypotheticallibrary to build on top of the wonderful Python packages listed earlier and
create an easy-to-use, feature complete, statistics library. At the end of the day, if the library helps a user
learn more about statistics or get the information they need in an easy way, then I consider that all the success
I need!RequirementsPython 3.5+numpy>=1.13.0numpy_indexed>=0.3.5pandas>=0.22.0scipy>=1.1.0statsmodels>=0.9.0LicenseMIT
Package: hypothit
hypothitCommand line interface for Hypothesis property based tests$ hypothit trial --given "a=integers()" --assume 'a!=0' "assert a==42"
from hypothesis import given, assume
from hypothesis.strategies import integers


@given(a=integers())
def inner(a):
    assume(a!=0)
    assert a==42

inner()

Falsifying example: inner(a=1)
Traceback (most recent call last):
File ".../hypothit/cli.py", line 90, in trial
    exec(src, g)
File "<string>", line 10, in <module>
File "<string>", line 6, in inner
File ".../hypothesis/core.py", line 1024, in wrapped_test
    raise the_error_hypothesis_found
File "<string>", line 8, in inner
AssertionErrorFree software: MPL v2Documentation:https://hypothit.readthedocs.io.CreditsThis package was cut withCookiecutter, &audreyr/cookiecutter-pypackage.History0.1.0 (2019-05-01)First release on PyPI.
Package: hypothpy
# hypothtst
Hypothesis tests on various kinds of data and simulation routines for power and other performance metrics.Relationship of <img src=”/tex/c745b9b57c145ec5577b82542b2df546.svg?invert_in_darkmode&sanitize=true” align=middle width=10.57650494999999pt height=14.15524440000002pt/> with <img src=”/tex/9b4428e475444d94aa4664c4bc9fef13.svg?invert_in_darkmode&sanitize=true” align=middle width=10.57650494999999pt height=22.831056599999986pt/><p align=”center”><img src=”/tex/124c9859cba90cbc7110912b2dc9f3e6.svg?invert_in_darkmode&sanitize=true” align=middle width=112.6296534pt height=20.922262349999997pt/></p>
Package: hypothtst
# hypothtst
Hypothesis tests on various kinds of data and simulation routines for power and other performance metrics.Relationship of <img src=”/tex/c745b9b57c145ec5577b82542b2df546.svg?invert_in_darkmode&sanitize=true” align=middle width=10.57650494999999pt height=14.15524440000002pt/> with <img src=”/tex/9b4428e475444d94aa4664c4bc9fef13.svg?invert_in_darkmode&sanitize=true” align=middle width=10.57650494999999pt height=22.831056599999986pt/><p align=”center”><img src=”/tex/124c9859cba90cbc7110912b2dc9f3e6.svg?invert_in_darkmode&sanitize=true” align=middle width=112.6296534pt height=20.922262349999997pt/></p>
Package: hypotonic
HypotonicFast asynchronous web scraper with minimalist API inspired by awesomenode-osmosis.Hypotonic provides SQLAlchemy-like command chaining DSL to define HTML scrapers. Everything is executed asynchronously viaasyncioand all dependencies are pure Python. Supports querying by CSS selectors with Scrapy's pseudo-attributes. XPath is not supported due tolibxmlrequirement.Hypotonic does not natively execute JavaScript on websites and it is recommended to useprerender.InstallingHypotonic requires Python 3.6+.pip install hypotonicExamplefromhypotonicimportHypotonicdata,errors=(Hypotonic().get('http://books.toscrape.com/').paginate('.next a::attr(href)',5).find('.product_pod h3').set('title').follow('a::attr(href)').set({'price':'.price_color','availability':'p.availability'}).data())
Package: hypper
Hypper is a data-mining Python library for binary classification. It uses hypergraph-based methods to explore datasets for the purpose of undersampling, feature selection and binary classification.Hypper provides an easy-to-use interface familiar to well-recognized Scikit-Learn API.The primary goal of this library is to provide a tool for handling datasets consisting of mainly categorical features. Novel hypergraph-based methods proposed in the Hypper library were benchmarked against the alternative solutions and achieved satisfactory results. More details can be found in scientific papers presented in the section below.InstallationpipinstallhypperLocal installationspipinstall-e.['documentation']# documentationpipinstall-e.['develop']# development (with testing)pipinstall-e.['benchmarking']# benchmarking scriptspipinstall-e.['all']# install everythingTutorials:1. Introduction to data mining with HypperTestingpytestImportant linksSource code -https://github.com/hypper-team/hypperDocumentation -https://hypper-team.github.io/hypper.htmlCitation
Package: hyppo
hyppo (HYPothesis Testing inPythOn, pronounced "Hippo") is an open-source
software package for multivariate hypothesis testing. We decided to develop hyppo for
the following reasons:With the increase in the amount of data in many fields, hypothesis testing for high
dimensional and nonlinear data is importantLibraries in R exist, but their interfaces are inconsistent and most are not available
in Pythonhyppo intends to be a comprehensive multivariate hypothesis testing package and runs on
all major versions of operating systems. It also includes novel tests not found in other
packages. It is quick to install and free of charge. If you need to use multivariate
hypothesis testing, be sure to give hyppo a try!"
Package: hyppy
A Python interface for theHyperiumsAPI (HAPI).Aims to provide:A HAPI wrapper, allowing multiple connections (i.e. per user, per game),Parsing tools for daily list exports,Functions and formulae for some of the game’s mechanics.MIT licensed.Installation and quickstartTo install:pip install hyppyUsing the HAPI:from hyppy.hapi import HAPI

hapi = HAPI('Hyperiums6')

# Get a list of games
print hapi.games()

# Password authentication for list downloads
hapi.authenticate_basic('loginname', 'password')

# Download today's planet list for this game
hapi.download('planets', './planets.txt.gz')

# HAPI key authentication for everything else
hapi.authenticate_hapi('loginname', 'hapikey')

# Get all player's planets
print hapi.planet()
Package: hyprland
Hyprland-pyAn unofficial async python wrapper for Hyprland's IPC supposed to somewhat work like awesomewm api in luaTodoasync socketschange config optionsevent listenerskeybindswindowruleshyprland infomisc hyprland commands(change workspace, move active window etc...)(dispatchers)a nice way to handle colorsbuildsettings.pyfile based on current hl versionget config values from the current hyprland config instead of using default valuesgetting binds still dont workdocswidgets??Installgitfrom gitpipinstallgit+https://github.com/hyprland-community/hyprland-pyreleasefrompypipipinstallhyprlandExamplechange window border to a random number between 0 and 20 everytime a new window is openedimporthyprlandfromhyprlandimportBind,BindFlagclassConfig(hyprland.Events):def__init__(self):self.c=hyprland.Config()super().__init__()asyncdefterminal(self):awaithyprland.Dispatch.exec("kitty --single-instance")asyncdefon_connect(self):print("Connected to hyprland")awaitself.c.add_binds([# general bindsBind(["SUPER","m"],hyprland.Dispatch.exit),# mouse bindsBind(["SUPER","mouse:272"],"movewindow",BindFlag.mouse),Bind(["SUPER","mouse:273"],"resizewindow",BindFlag.mouse),# keyboard bindsBind(["SUPER","return"],self.terminal),Bind(["SUPER","q"],hyprland.Dispatch.kill_active),])# workspace bindsforiinrange(1,11):awaitself.c.add_bind(Bind([f"SUPER",str(i)ifi!=10elsestr(0)],hyprland.Dispatch.workspace,args=[i]))foriinrange(1,11):awaitself.c.add_bind(Bind([f"ALT",str(i)ifi!=10elsestr(0)],hyprland.Dispatch.move_to_workspace,args=[i]))c=Config()c.async_connect()
Package: hyprovo
hyprovois a minimal (~160 LOC) testing framework forHyheavily inspired by the chapter onPractical: Building a Unit Test
FrameworkinPractical Common Lisp.provo (Esperanto) ⇔ test (English)Installationpypi (recommended)pipinstallhyprovoManualInstall usingsetup.py(--useris optional)python3setup.pyinstall--useror in development mode,python3setup.pydevelop--userAPISeetutorial.ipynbfor the documentation.TestsEnsurehyis in the executable path. Run thetests.hycommand
line script from inside thetestsdirectory,./tests.hyA log file with the start timestamp will be created in thelogssubdirectory.GitHub Repository:https://github.com/prasxanth/hyprovo
Package: hyprpy
HyprpyHyprpyis a library that provides python bindings for theHyprlandwayland compositor.With Hyprpy you can very easily retrieve information about windows, workspaces and monitors
in a running Hyprland instance.
It also offers an event monitor, allowing you to write your own callback functions which
execute in response to Hyprland events.Hyprpy uses unix sockets to communicate with Hyprland, making itfastandefficient.Pleasecheck out the documentation!
Hyprpy is fully typed and extensively documented. Happy hacking :sunglasses:QuickstartInstallationpipinstallhyprpyUsage examplesfromhyprpyimportHyprlandinstance=Hyprland()# Fetch active window and display information:window=instance.get_active_window()print(window.wm_class)print(window.width)print(window.position_x)# Print information about the windows on the active workspaceworkspace=instance.get_active_workspace()forwindowinworkspace.windows:print(f"{window.address}:{window.title}[{window.wm_class}]")# Get the resolution of the first monitormonitor=instance.get_monitor_by_id(0)ifmonitor:print(f"{monitor.width}x{monitor.height}")# Get all windows currently on the special workspacespecial_workspace=instance.get_workspace_by_name("special")ifspecial_workspace:special_windows=special_workspace.windowsforwindowinspecial_windows:print(window.title)# Show a desktop notification every time we switch to workspace 6fromhyprpy.utils.shellimportrun_or_faildefworkspace_changed(sender,**kwargs):current_workspace_id=kwargs.get('active_workspace_id')ifcurrent_workspace_id==6:run_or_fail(["notify-send","We are on workspace 6."])instance.signal_active_workspace_changed.connect(workspace_changed)instance.watch()DevelopmentHyprpy is in active development! Please file an issue if you find any bugs or have a feature request.Your contributions are greatly appreciated.Roadmapdispatchers for components???
Package: hyprshade
HyprshadeFront-end to Hyprland's screen shader featureScreenshotsUnfilteredVibranceBlue Light FilterDescriptionHyprshade takes full advantage of Hyprland'sdecoration:screen_shaderfeature
by automating the process of switching screen shaders, either from a user-defined
schedule or on the fly. It can be used as a replacement[^1] for apps that adjust
the screen's color temperature such asf.lux,redshift, orgammastepwithblue-light-filter, which is installed by default.[^1]: Gradual color shifting currently unsupported.InstallationArch LinuxUse your favorite AUR helper (e.g.paru):paru-ShyprshadeOr manually:sudopacman-S--neededbase-devel
gitclonehttps://aur.archlinux.org/hyprshade.gitcdhyprshade
makepkg-siPyPIIf your distribution isn't officially supported, you can also install directly
fromPyPIwith pip:pipinstall--userhyprshadeOr withpipx:pipxinstallhyprshadeUsageUsage: hyprshade [OPTIONS] COMMAND [ARGS]...

Commands:
  auto     Set screen shader on schedule
  current  Print current screen shader
  install  Install systemd user units
  ls       List available screen shaders
  off      Turn off screen shader
  on       Turn on screen shader
  toggle   Toggle screen shaderCommands which take a shader name accept either the basename:hyprshadeonblue-light-filter...or a full path name:hyprshadeon~/.config/hypr/shaders/blue-light-filter.glslIf you provide the basename, Hyprshade searches in~/.config/hypr/shadersand/usr/share/hyprshade.Scheduling[!WARNING]
In order for for this to work, you must have the following lines in yourhyprland.conf:exec-once = dbus-update-activation-environment --systemd WAYLAND_DISPLAY XDG_CURRENT_DESKTOP
exec-once = systemctl --user import-environmentTo have specific shaders enabled during certain periods of the day, you can
create a config file in either~/.config/hypr/hyprshade.tomlor~/.config/hyprshade/config.toml.[[shades]]name="vibrance"default=true# shader to use during times when there is no other shader scheduled[[shades]]name="blue-light-filter"start_time=19:00:00end_time=06:00:00# optional if you have more than one shade with start_timeFor starters, you can copy the example config:cp/usr/share/hyprshade/examples/config.toml~/.config/hypr/hyprshade.tomlAfter writing your config, install the systemd timer/serviceuser unitsand enable
the timer unit:hyprshadeinstall
systemctl--userenable--nowhyprshade.timer[!TIP]
Runhyprshade installevery time you make changes tohyprshade.tomlto keep the user units in sync.TipsYou probably want the following line in yourhyprland.conf:exec = hyprshade autoThis ensures that the correct shader is enabled when you log in.
Package: hypua2jamo
hypua2jamoConvertHanyang-PUA code(U+E0BC~U+F8F7) to unicode Hangul Jamo (U+1100~U+11FF), i.e.Syllable-Initial-Peak-Final Encoding (첫가끝 코드).Example>>> from hypua2jamo import translate
>>> pua = u'\ub098\ub78f\u302e\ub9d0\u302f\uebd4\ubbf8\u302e'
>>> translate(pua)
u'\ub098\ub78f\u302e\ub9d0\u302f\u110a\u119e\ubbf8\u302e'
>>> print(_)
나랏말ᄊ미
>>> translate(pua, composed=False)
u'\ub098\ub78f\u302e\ub9d0\u302f\u1109\u1109\u119e\ubbf8\u302e'
>>> print(_)
나랏말ㅅㅅ미InstallationfromPyPI:pip install hypua2jamoSupported Python versionsPython 2.7Python 3.7 or above.Documentation & DevelopmentDocumentation:http://hypua2jamo.readthedocs.orgGitHub:https://github.com/mete0r/hypua2jamoIssue tracker:https://github.com/mete0r/hypua2jamo/issuesBug reports, feedbacks and contributions are welcome!HackingCurrently, development and maintenance is taking place in the Debian stable version environment. Following debian packages are required:sudo apt install python3.9 python3.9-dev python3.9-venv
sudp apt install python2.7 python2.7-dev
sudo apt install make build-essential cmakeTo bootstrap development environment, run following commands in the project root directory:python3.9 -m venv venv
. venv/bin/activate
pip install --upgrade setuptools pip pip-tools
make update-requirements
make testContributorsMaintainer:mete0rLicenseGNU Lesser General Public License Version 3(text version)DisclosureThis work is based onKTUGHanyang PUA Table Project.Changes0.7 (2023-05-22)Fixhypua2jamoscript to work.0.6 (2023-04-02)Build Win64 wheels.Add support for Python 3.9 / 3.10 / 3.11Drop support for Python 3.5 / Python 3.60.5.1 (2020-05-08)Re-release for Windows wheels.0.5 (2020-05-08)Add support for Python 3.80.4.5 (2019-12-15)Fix wheel building for MS Windows.Drop support for Python 3.40.4.4 (2019-03-21)Reintroduce codes2unicode() for backward compatibility.0.4.3 (2019-03-20)Fix wheel building for Python 3.5, 3.6 and 3.7.0.4.2 (2019-03-20)Add support for Python 3.5, 3.6 and 3.7.0.4.1 (2019-03-20)Release binary wheels.0.4.0 (2019-03-19)Modernize development environment.encoder / decoder
Package: hyputils
hyputilspython utilities for working with the hypothes.is api and websocket interfaceConfig fileszendeskinfo.yamlshould containzdesk_url: https://yoururl.zendesk.com
zdesk_email: your@email.com
zdesk_password: your_token_or_password
zdesk_token: TrueUsagehyputils checks the following enviornment variablesHYP_API_TOKENis your api token.HYP_USERNAMEis your username (not strictly required).HYP_GROUPis the 8 char group identifier.Fun!If you never modify your annotations, but instead
only add new replies to modify them you can view a
snapshot of the state of your annotation work and
understanding at time T by simply excluding all
anotations with updated > T!
Package: hypy-hypixel
A basic Hypixel API wrappercovering:/punishmentstats/key/player/resources/skyblock/skills/skyblock/auctions/skyblock/profile/friends/status/guild/countsDocumentationhttps://hypy.readthedocs.io/en/latest/index.htmlQuickstartInstall hypy:$pipinstallhypy-hypixelCreate a Hypixel object::fromhypyimportHypixelhypixel=Hypixel(api_key)awaithypixel.setup()Creditshttps://github.com/aio-libs/aiohttphttps://github.com/twoolie/NBThttps://github.com/ijl/orjsonhttps://pypi.org/project/aiofiles/https://github.com/Senither/Hypixel-Skyblock-Leaderboardfor the weight calculationshttps://github.com/Altpapier/SkyHelperAPIfor the networth api
Package: hypyp
HyPyP 🐍〰️🐍TheHyperscanningPythonPipeline⚠️ This software is in beta and thus should be considered with caution. While we have done our best to test all the functionalities, there is no guarantee that the pipeline is entirely bug-free.📖 See ourpaperfor more explanation and our plan for upcoming functionalities (aka Roadmap).🤝 If you want to help you can submit bugs and suggestions of enhancements in our GithubIssues section.🤓 For the motivated contributors, you can even help directly in the developpment of HyPyP. You will need to installPoetry(see section below).ContributorsOriginal authors: Florence BRUN, Anaël AYROLLES, Phoebe CHEN, Amir DJALOVSKI, Yann BEAUXIS, Suzanne DIKKER, Guillaume DUMAS
New contributors: Ghazaleh RANJBARAN, Quentin MOREAU, Caitriona DOUGLAS, Franck PORTEOUS, Jonas MAGO, Juan C. AVENDANO, Julie BONNAIREInstallationpip install HyPyPDocumentationHyPyP documentation of all the API functions is available online athypyp.readthedocs.ioFor getting started with HyPyP, we have designed a little walkthrough:getting_started.ipynbCore API🛠io.py— Loaders (Florence, Anaël, Ghazaleh, Franck, Jonas, Guillaume)🧰utils.py— Basic tools (Amir, Florence, Guilaume)⚙️prep.py— Preprocessing (ICA & AutoReject) (Anaël, Florence, Guillaume)🔠analyses.py— Power spectral density and wide choice of connectivity measures (Phoebe, Suzanne, Florence, Ghazaleh, Juan, Guillaume)📈stats.py— Statistics (permutations & cluster statistics) (Florence, Guillaume)🧠viz.py— Inter-brain visualization (Anaël, Amir, Florence, Guillaume)🎓Tutorials- Examples & documentation (Anaël, Florence, Yann, Ghazaleh, Caitriona, Guillaume)Poetry installation (only for developpers and adventurous users)Step 1:pip install poetryStep 2:git clone git@github.com:ppsp-team/HyPyP.gitStep 3:cd HyPyPStep 4:poetry installStep 5:poetry shellYou can now usejupyter notebookoripython!⚠️ If you need to install a new dependency (not recommended), you have to usepoetry add THE_NAME_OF_THE_LIBRARYinstead of your usual package manager.
Package: hypysagas
PySAGASPySAGASis a Python package for the generation ofSensitivityApproximations
forGeometric andAerodynamicSurface properties. It provides a
computationally-efficient method for generating surface sensitivity approximations from
existing flow solutions, to use in aerodynamic shape optimisation studies. The GIF below
is an example of this, where a hypersonic waverider was optimised for maximum L/D at Mach
6.Table of ContentsGetting StartedPrerequisitesInstallationUsageCitingLicenseGetting StartedPrerequisitesParaViewIf you plan on usingPySAGASwith Cart3D solutions, you should also install ParaView, or at
least the ParaView Python bindings. If you are using an Anaconda environment, you can install
the ParaView Python packages viaConda Forgeusing
the command below:conda install -c conda-forge paraviewIf you already have ParaView installed, you can append the path to the binaries to the Python
path using the snippet below.importsyssys.path.insert(0,"/opt/ParaView-5.6.2-MPI-Linux-64bit/bin")# Now the import should workimportparaviewFor more information on ParaView's Python packages, see theParaView Wiki.pyOptSparsePySAGASshape optimisation modules wrap aroundpyOptSparseto converge on optimal geometries. Follow theinstallation instructions, noting that special optimisers require custom builds.If using an Anaconda environment, you can also install PyOptSparse from Conda forge:conda install -c conda-forge pyoptsparsePyMeshHavingPyMeshinstalled can greatly enhance the capabilities
offered byPySAGAS. However, it can be difficult to install. Troubleshooting guide coming soon.InstallationAfter installing the dependencies above, clone this repo to your machine.git clone https://github.com/kieran-mackle/pysagasNext, use pip to install thepysagaspackage from the repo you
just cloned.cd pysagas
python3 -m pip install .[back to top]UsagePySAGASuses low-order methods to approximate sensitivities on the surface of aerodynamic
geometries. The user must provide a nominal condition of the flow properties on the surface, along
with the sensitivity of the geometric vertices to the design parameters. From here, one ofPySAGASsensitivity calculators can be used.[back to top]Citing PySAGASIf you use PySAGAS in any published work, please cite it using the BibTex reference below.@inproceedings{Mackle2024,
  author    = {Mackle, Kieran and Jahn, Ingo},
  booktitle = {AIAA Science and Technology Forum and Exposition},
  title     = {Efficient and Flexible Methodology for the Aerodynamic Shape Optimisation of Hypersonic Vehicle Concepts in a High-Dimensional Design Space},
  year      = {2024},
}[back to top]LicensePySAGAS is licensed underGPLv3.[back to top]