Saravanan666/pypi-org huggingface dataset:
Package: grattify
#<center> Grattify </center>
##Requirements:HomeBrew (OS X Package Manager):ruby -e “$(curl -fsSLhttps://raw.github.com/Homebrew/homebrew/go/install)”FFMPEG (audio converter, to convert between different audio formats):brew install ffmpegPip (comes with homebrewed python, use ‘homebrew install pip’ if using default python)NOTE:  if sudo needed to pip install packages its because default os x python being used. To avoid this, brew install python alongside it, and add /usr/local/bin to the beginning of paths file (/etc/paths)And Grattify!:pip install grattify##Basic Commands:grattifyShows you list of possible commandsgrattify -spotify mySpotifyUsernameBrings you to the spotify login page, then downloads your spotify playlistsIf you only want to download certain playlists, specify them after your username: ‘grattify -spotify myUsername “my playlist 1” “my playlist 2” … ‘grattify -song “the beatles” “come together”Download a single song by providing the artist and song namegrattify -album “the beatles” “abbey road”Download a whole album by providing the artist and album namegrattify -top 18 “the beatles”’Download the top N songs by an artist by providing the number N and the artistgrattify -file “songList.txt”’Download songs listed on a text file. The file can contain 3 types of lines:artist - song (must be hyphen separated, shouldnt need quotes around * artist or song)album: album - artisttop 16: artist
Package: gravatarcontacts-cmenon12
Gravatar to Google ContactsThis is a Python package to copy Gravatar profile pictures to your Google Contacts.DescriptionWhen run as a script (by running__main__.py) the program will first ask a user to grant the Google Cloud Platform app access to their contacts in their Google Account. It will then download all of their contacts and remove those that don't have an email address and a name.For each email address in each contact it will attempt to download the corresponding Gravatar photo. If a Gravatar photo is found for that contact then it will update the contact with that photo. If there are multiple possible Gravatar photos (due to a contact having multiple email addresses) then a GUI will be presented to choose one. The user is notified which contacts have been updated, and those contacts have the customGravatar Photofield set to"True"(so that the program can safely update them in the future).This program will not update contacts that already have a user-supplied photo that didn't previously come from Gravatar.Installation & SetupYou can install it usingpip install gravatarcontacts-cmenon12.DependenciesNote that the versions specified here are what I have been running it on, it may well work on older versions.Python>=3.7requests>=2.23.0google_api_python_client>=1.8.3google_auth_oauthlib>=0.4.1libgravatar>=0.2.3Pillow>=7.1.2protobuf>=3.11.0Creating a Google Cloud Platform Project and enabling the People APIYou will need to create your own Google Cloud Platform Project, enable the People API, and create & download some OAuth 2.0 Client ID credentials ascredentials.json.If you've not used Google Cloud Platform before then you can do all of this really easily by clicking on the large blue button labelledEnable the People APIhere. Choose to create aDesktop appand as per the instructions there in the resulting dialog clickDOWNLOAD CLIENT CONFIGURATIONand save the filecredentials.jsonto where you're working. You mustn't sharecredentials.jsonortoken.picklewith anyone.Use of the Google People API is (at the time of writing) free.Creating your own project helps to keep your contacts safe because you control the app that is asking to access them (and you can see my all of my source code here). You can stop your app accessing your contacts by revoking it athttps://myaccount.google.com/permissions.Usagepython -m gravatarcontactswill run the program after installation. Where necessary, the browser window and GUI will open automatically so this program should be run locally (and not over SSH for example).LicenseGNU GPLv3
Package: gravatarurl
Gravatar URLGet the URL to a Gravatar image from an emailScreenshotInstall$ pip install gravatarurlUsageimportgravatarurlasavataravatar.get('yoginth@zoho.com')# avatar.get('email@example.com')#=> https://secure.gravatar.com/avatar/ef5eb22b653730b5d7d7c32a73ff64e7?s=250avatar.get('yoginth@zoho.com',500)# avatar.get('email@example.com', size)#=> https://secure.gravatar.com/avatar/ef5eb22b653730b5d7d7c32a73ff64e7?s=500Get HelpThere are few ways to get help:Pleasepost questions on Stack Overflow. You can open issues with questions, as long you add a link to your Stack Overflow question.For bug reports and feature requests, open issues.For direct and quick help, you canemail me.How to contributeHave an idea? Found a bug? Seehow to contribute.Thanks!LicenseMIT
Package: gravely
gravely, a gravity simulator============================Introduction------------`gravely` is a gravity simulator,written to taste modern Python packaging practices.It uses [Cython](http://cython.org) compiled extensions,depends on [Numpy](http://www.numpy.org) and [h5py](http://www.h5py.org),compiles into a single binary with [PyInstaller](http://pyinstaller.org) andaims to support both Linux and Windows.Not exactly a walk in the park.License-------`gravely` is distributed under the terms of the MIT License;see [LICENSE.txt](LICENSE.txt).Usage-----Pyinstaller binary:./gravely test./gravely run./gravely animateInstalled Python package:python3 -m gravely testpython3 -m gravely runpython3 -m gravely animateInstallation------------**First of all, try using a precompiled binary made with PyInstaller.**If that doesn't suit you, you should report thatand proceed to installing the Python package.The base requirements to begin with are a working C compiler,`Python>=3.4` with development headers,`setuptools>=20`, `numpy>=1.8.2` and `pip>=8`.These should be enough to start installation of `gravely`from a source archive or a precompiled wheel (`.whl`) file:python3 -m pip install gravely-*.zippython3 -m pip install gravely-*.whlOther packages may or may not install automatically with pip/setuptools magic.`gravely` also depends on `cython>=0.21` (build) and `h5py>=2.2` (run-time).Rendering nice video animations requires `matplotlib>=1.4` and `ffmpeg`.Testing requires `nose>=1.0`.Try to satisfy as many of thesebefore attempting to build and install `gravely`.### Linux, Debian-basedapt-get install gcc python3 python3-dev python3-setuptools python3-pip \cython3 python3-numpy python3-matplotlib python3-nose ffmpeg### Install necessary upgrades with pippip3 install 'pip>=8'python3 -m pip install \'cython>=0.21' 'setuptools>=20' 'matplotlib>=1.4' 'nose>=1.0'python3 -m pip install -r requirements.txt### WindowsGood luck.Currently only Windows 10 and Python 3.5 are supported.Some say that it's better to use specialized Python distributions like[Anaconda](https://www.continuum.io) or[Enthought Canopy](https://www.enthought.com/products/canopy)to get the prerequisities straight.As for vanilla Python... Visual Studio with Python supportand several pip invocations could be a good start:python -m pip install cython numpy matplotlib nosepython -m pip install http://www.silx.org/pub/wheelhouse/h5py-2.6.0-cp35-cp35m-win_amd64.whl
Package: graveolens
The missing test library for theCeleryPython library. Some of the things graveolens can help with include:Provide resultss to Celery task calls without hitting your broker.Ensuring that you know exactly which tasks are called.Easily assert the arguments of task calls.Easily handle results when usingsend_taskin Celery.The binomial name for celery isApium graveolens.Returning Resultsfrommy_app.celeryimportappimportgraveolensdeftest_my_task():withgraveolens.activate()ascelery:celery.add('my_app.task',{'done':True,'status':'OK'})result=app.send_task('my_app.task','test',id=3)# The result is an EagerResult from Celery.assertresult.get()=={'done':True,'status':'OK'}# You can also check ALL the calls that Celery received.assertlen(celery.calls)==1assertcelery.calls[0].name=='http://twitter.com/api/1/foobar'assertcelery.calls[0].args==('test',)assertcelery.calls[0].kwargs=={'id':3}Asserting Celery CallsBy default, if a result is added and unused this raises anAssertionErrorwhen the context manager exits, e.g.:importgraveolensdeftest_my_task():withgraveolens.activate()ascelery:celery.add('my_app.task')# Assertion will be raised here because 'my_app.task' is never called.This can be configured using theassert_all_tasks_calledflag toactivate().Additionally, if a Celery task is called without having a result set-up thengraveolens.NotMockedTaskwill be raised.frommy_app.celeryimportappimportgraveolensdeftest_my_task():withgraveolens.activate()ascelery:try:result=app.send_task('my_app.task','test',id=3)exceptgraveolens.NotMockedTask:# Exception will be raised since my_app.task has no result.pass
Package: gravhopper
GravHopper"They told me computers could only do arithmetic." -- Grace HopperGravitational N-body simulation code written by Jeremy Bailin.Named in honour of pioneering computer scientist Grace Hopper. Doubly appropriate
because it uses a leapfrog integrator.This is a simple Python-interface code for performing gravitational N-body simulations. It combines a simple Python interface for ease of use with a C backend for speed, and has the following features:Choice of Barnes-Hut tree or direct summation algorithm.Ability to include external potentials from galpy, gala, or user-supplied functions.Ability to return output as pynbody snapshots.Functions that generate equilibrium or near-equilibrium initial conditions (ICs) for
several density profiles (Plummer, Hernquist, exponential disk), along with the ability
to create ICs from galpy distribution function objects or pynbody snapshots.Utility functions for plotting snapshots and making movies.For now, it uses a constant uniform timestep and constant uniform Plummer softening.Requirements:AstropyNumPy, SciPy, MatplotlibC compilerTo usegalpy,gala,
orpynbodyinterface functions, they will need to be installed.Saving movies requiresffmpeg.For example, this will create a Plummer sphere with 2000 particles, run it for a few dynamical times,
and plot the particle positions before and after to show that it is in equilibrium:from gravhopper import Simulation, IC
from astropy import units as u
import matplotlib.pyplot as plt

# Create Plummer initial conditions.
Plummer_IC = IC.Plummer(N=2000, b=1*u.pc, totmass=1e6*u.Msun)

# Create a new simulation with a time step of 0.005 Myr and a softening of 0.05 pc.
sim = Simulation(dt=0.005*u.Myr, eps=0.05*u.pc)
# Add the Plummer model to the simulation
sim.add_IC(Plummer_IC)
# Run for 400 time steps
sim.run(400)

# Plot the x-y positions at the beginning and end.
fig = plt.figure(figsize=(12,4))
ax1 = fig.add_subplot(121, aspect=1.0)
ax2 = fig.add_subplot(122, aspect=1.0)
sim.plot_particles(snap='IC', unit=u.pc, xlim=[-10,10], ylim=[-10,10], ax=ax1)
sim.plot_particles(snap='final', unit=u.pc, xlim=[-10,10], ylim=[-10,10], ax=ax2)To make a movie of the whole evolution of the simulation:# Make and save a movie of the simulation running
sim.movie_particles('Plummer_sim.mp4', unit=u.pc, xlim=[-10,10], ylim=[-10,10])DocumentationFull documentation, including installation instructions, examples, and library reference,
are atRead The DocsInstallationOption 1: PipIf all goes well, you should be able to install GravHopper simply with:pip install gravhopperOption 2: Install from sourceTo install directly from the current source:Clone or download the git repositorygit clone https://github.com/jbailinua/gravhopper.gitGo into the gravhopper directory and build the code.cd gravhopper
python setup.py build_ext --inplaceCopy the gravhopper subdirectory to wherever you want to use it.
Package: gravify
gravifygravifyis a simple package to generateGravatarURLs. :link:>>>user=Gravatar("example@example.com")>>>user.url'https://www.gravatar.com/avatar/23463b99b62a72f26ed677cc556c44e8'Installationgravify is available on PyPI:$pipinstallgravifygravify officially supports Python 3.5+.API ReferenceSeeRead the Docsfor gravify's documentation.
Package: gravilab
GraviLabPackage to analyze seismic data based onobspyandspicypypackages.InstallationpipinstallgravilabUsageThe main element of the package isSeismometerclass, which represents a seismic instrument.
It can be created by loading seismic data withopenfunction and specifying channels,
both their names in the file and "human-readable" names. The folder is then scanned for any suitable data
and only those channels are loaded. All functionality related to seismic time series data is
provided by the underlyingobspypackage (specificallyobspy.Trace).Seismometerclass also supports calculating spectrum
(Seismometer.asd(),Seismometer.psd()) usingspicypypackage.
Spectrum can be adjusted by the response of specific instrument specified by pole-zero model,
and units can be converted between displacement, velocity
and acceleration by specifying theomegafactor. Resulting spectrum isspicypy.FrequencySeries. Additionally,
time series can also be converted tospicypy.TimeSeriesto profit from its rich signal processing functionality.Minimal example:importgravilabasglSeismometer1=gl.open("seismic",channels={"vertical":"HNZ","north":"HNY","east":"HNX"},name="seismometer1")Seismometer1.time_series["north"].plot()response={"poles":[-0.036614+0.037059j,-0.036614-0.037059j,-32.55,-142,-364+404j,-364-404j,-1260,-4900+5200j,-4900-5200j,-7100+1700j,-7100-1700j],"zeros":[0,0,-31.63,-160,-350,-3177],"scale_factor":1202.5*8.31871e17*400000,#V/(m/s) times gain times counts/V"omega_exponent":-1,#convert from m/s to m}Seismometer1.response=responseSeismometer1.asd()["north"].plot()More detailed usage examples are provided ingravilab/examplesfolder.
Package: gravipython
#gravipythonREADME.mdThis python module is a basic module that can be used for small simulations.v 0.0.5class SolarSystem(width, height, **kwargs):**kwargscollisions=True (Set this to False if you want to deactivate collisions)Used to create a solar system to add stars in your simulation.SolarSystem.main():
Method that does all the work, don't forget otherwise nothing is going to appear.Click on A to spawn an asteroid of 0.000001 solar masses.Click on D to spawn a red dwarf of 0.35 solar masses.Click on B to spawn a brown dwarf of 0.07 solar masses.Click on S to spawn a star of 1 solar mass.Click on P to spawn a planet of 0.0001 solar masses.Click on M to spawn a moon of 0.00001 solar masses.Click on C to spawn a comet of 0.000001 solar masses.Click on W to spawn a white dwarf of 0.9 solar masses.Click on R to reset and remove all stars from the screen.class SolarSystemBody(solar_system, mass, position=(0, 0), velocity=(0, 0), color=(255, 255, 255))This class allows you to create your own stars.
From this class are created the classes :SunRedDwarfBrownDwarfAsteroidPlanetMoonCometWhiteDwarfEach of these classes can be instantiated with the same parameters as SolarSystemBody, except that they have a default value for the mass and adifferent one for the color.###Official examples :#####Simple system :importgravipythonasgp# v 0.0.3 and before, use 'import gravitypython as gp'ss=gp.SolarSystem(width=500,height=500,collisions=True)# collisions is set by default to Trueplanet1=gp.Planet(ss,mass=1,position=(0,70),velocity=(5,0),color=(0,0,255))# color for planets is by default set to (0, 0, 255)sun=gp.Sun(ss,mass=10000,position=(0,0))# you could use just sun = gp.Sun() because every arguments are set by defaultss.main()# runs the simulation#####Binary system :importgravipythonasgpss=gp.SolarSystem(500,500)sun1=gp.Sun(ss,mass=10000,position=(-20,0),velocity=(0,5))sun2=gp.Sun(ss,mass=10000,position=(20,0),velocity=(0,-5))ss.main()###Credits
A part of this code has been made thanks toStephen GruppettaonThePythonCodingBookIf you found any error, bug, or idea, you can send it by mail atlatomateultime@gmail.com
Package: gravitasml
GravitasMLGravitasML is a lightweight Python library for parsing custom markup languages. It provides a simple and intuitive API to convert markup into Python objects or dictionaries.FeaturesEasy-to-use parser for custom markup languages.Convert markup directly to Python dictionaries.Handles nested and multiple root tags.Customizable tag names with automatic whitespace conversion.Syntax error detection for unmatched or improperly nested tags.InstallationTo install GravitasML, use pip as follows:pipinstallgravitasmlQuick StartHere's a quick example to get you started:fromgravitasml.tokenimporttokenizefromgravitasml.parserimportParsermarkup="<tag1><tag2>content</tag2></tag1>"tokens=tokenize(markup)parser=Parser(tokens)obj=parser.parse()print(obj)# Output: {'tag1': {'tag2': 'content'}}LimitationsGravitasML is designed to be simple and intuitive, but there are some limitations to be aware of:It does not support XML namespaces or schema validation.It does not handle processing instructions or CDATA sections found in XML.Currently, there is no support for attributes within tags; only tag names and content are parsed.It does not provide functionality to write or generate markup, only to parse it.GravitasML is not optimized for extremely large documents or streaming parsing.DocumentationFor detailed usage and documentation, please refer to thedocsdirectory in this repository.TestsGravitasML comes with a comprehensive test suite. To run the tests, execute the following command:python-munittestdiscover-vContributingWe welcome contributions from the community. If you'd like to contribute, please fork the repository and submit a pull request.LicenseGravitasML is licensed under the MIT License - see the LICENSE file for details.
Package: gravitational
Author:Behrouz SafariLicense:MITgravitationalA package for gravitational simulationsInstallationYou can install the latest version ofgravitationalfromPyPI:pip install gravitationalThe only requirements arenumpyandmatplotlib.How to useAn example of simulating the inner planets:fromgravitational.simulationimportSimulationfromgravitational.solar_systemimportinitial_statefromgravitational.constantsimportConstant# Define the time as a datetime object or a string (default now)t='2021-02-17 04:26:00'sim=Simulation(t)c=Constant()# Get initial states from Horizons APIp0_sun,v0_sun=initial_state('sun',t)p0_venus,v0_venus=initial_state('venus',t)p0_earth,v0_earth=initial_state('earth',t)# Add bodiess=sim.add_body(name='Sun',color='y',size=25,mass=c.m_sun,position=p0_sun,velocity=v0_sun)v=sim.add_body(name='Venus',color='k',size=8,mass=c.m_venus,position=p0_venus,velocity=v0_venus)e=sim.add_body(name='Earth',color='b',size=10,mass=c.m_earth,position=p0_earth,velocity=v0_earth)# Run and play the simulationsim.play(path=True)
Package: graviteeio-cli
Gravitee.io CLIA command line client forGravitee.ioAPI Platform.graviteeio-cliis a CLI (Command Line Interface) which helps you to manage Gravitee.io eco-system.
It allows to automate actions for all modules of the platform.Gravitee CLI DocumentationGravitee cli documentation is published onhttps://docs.gravitee.io/cli/cli_introduction.htmlRequirementsPython 3.5 or moreSetupInstall cli usingpip.Use pip to install the latest stable version:$pipinstallgraviteeio-cliUsage$gio<module><command>Platform moduleModuleAPI ManagementapimAccess Managementam
Package: gravitorch
DependenciesThe following is the correspondinggravitorchversions and supported dependencies.gravitorch0.0.21python>=3.9,<3.12coola>=0.0.20,<0.0.23hya>=0.0.12,<0.0.14hydra-core>=1.3,<1.4minevent>=0.0.4,<0.0.5numpy>=1.22,<1.26objectory>=0.0.7,<0.0.8pytorch-ignite>=0.4.11,<0.5tabulate>=0.9,<0.10torch>=2.0,<2.1colorlog*>=6.7,<6.8matplotlib*>=3.6,<3.9pillow*>=9.0,<11.0psutil*>=5.9,<5.10startorch*>=0.0.5,<0.0.6tensorboard*>=2.10,<2.15torchdata*>=0.6,<0.7tqdm*>=4.64,<4.67*indicates an optional dependencyAPI stability:warning: Whilegravitorchis in development stage, no API is guaranteed to be stable from one
release to the next. In fact, it is very likely that the API will change multiple times before a
stable 1.0.0 release. In practice, this means that upgradinggravitorchto a new version will
possibly break any code that was using the old version ofgravitorch.Licensegravitorchis licensed under BSD 3-Clause "New" or "Revised" license available
inLICENSEfile.
Package: gravitum
GravitumGravitum is a library for implementing decompiled code with Python.RequirementsPython 3.6+Installation$ pip install gravitumUsageGravitum defines some interger types with fixed size. You can use shorthand functions (int8,int16,int32,int64,uint8,uint16,uint32,uint64) to create them.fromgravitumimportuint8v=uint8(0x53)Pointer operations are common in the decompiled code.unsigned__int8data[8]={71,114,97,118,105,116,117,109};unsigned__int8*p=data;unsigned__int8v=p[4];*((unsigned__int32*)p+1)=v;So Gravitum providesvptr.fromgravitumimportvptrdata=bytearray([71,114,97,118,105,116,117,109])p=vptr(data,'uint8')v=p.add(4).read()p.cast('uint32').add(1).write(v)In some cases, decompilers may use their built-in functions in the output. Gravitum implements some of them. You can look up fromgravitum.decompiler_builtins.fromgravitumimportuint32fromgravitum.decompiler_builtins.idaimportror4v=uint32(0x53683477)v=ror4(v,2)
Package: gravityai
Gravity-ai.comThis package includes helper scripts for interfacing your machine learning code with theGravity-ai.comcontainerization code.To install from pypi:pip install gravityaiTo install from source:python3 setup.py installExample Implementation Codefrom gravityai import gravityai as grav

# the following function is a callback (defined by you), that may be
# async or synchronous and that may be called multiple times, to
# transform input data against an algorithm or model (or whatever you want)
# If an error is experienced, return an error string message, or throw an exception.
def process_data(dataPath, outPath):
    # TODO:
    # Read data in from dataPath
    # Transform Data via model
    # Write data out to outPath
    # Return None if everything went ok.
    # return an error string if there was a problem.


# TODO Initialize models, etc. before calling wait_for_requests.

grav.wait_for_requests(process_data)Building a new VersionTo build a new version for pypi (only we do that):python3 -m pip install --user --upgrade setuptools wheel

python3 -m pip install --user --upgrade twine

python3 setup.py sdist bdist_wheel

python3 -m twine upload --repository pypi dist/*Use the saved credentials, and remember the username is __token__
Package: gravityforms-python
gravityforms-pythongravityforms-pythonis an API wrapper for Gravityforms (Wordpress plugin), written in Python.This library uses Oauth1 for authentication.Installingpip install gravityforms-pythonUsagefromgravityforms.clientimportClientclient=Client(base_url,consumer_key,consumer_secret)List Entriesentries=client.list_entries()Filter entriesentries=client.filter_entries(filter_field,filter_value,filter_operator,sorting_direction=None,page_size=None,form_id=None)List Formsforms=client.list_forms()Get Form detailform=client.get_form(form_id)
Package: gravity-front
Gravity Interface (TK) - написанный на tkinter графический интерфейс, служащий для взаимодействия весовщика
и Gravity Core.v 0.2.4
- Иконка версии в углу
- ar_ip, ar_port, mirrored передаются как аргументы при запуске приложения
- добавлен cmadb (блокировка дублей)