Saravanan666/pypi-org huggingface dataset:
Package: iLiaShahpy
iLiaShahpyElegant, modern and asynchronous Rubika MTProto API framework in Python for users and botslibrary iLiaShahpyiLiaShahpy library documents soon...How to import the Rubik's libraryfromiLiaShahpyimportiLiarub

Or

fromiLiaShahpyimportRoboRubikaHow to import the anti-advertising classfromiLiaShahpy.ZedLinkimportAntiadvertisementHow to install the librarypipinstalliLiaShahpy==3.8.6My ID in Telegram@Sourse_py
@iLiaShahpyAn example:fromiLiaShahpyimportiLiarubbot=iLiarub("Your Auth Account")gap="your guid or gap or pv or channel"bot.sendMessage(gap,"libraryiLiaShahpy")And Or:fromiLiaShahpyimportRoboRubikabot=RoboRubika("Your Auth Account")gap="your guid or gap or pv or channel"bot.sendMessage(gap,"libraryiLiaShahpy")Made by iLiaShahKey FeaturesReady: Install iLiaShahpy with pip and start building your applications right away.Easy: Makes the Rubika API simple and intuitive, while still allowing advanced usages.Elegant: Low-level details are abstracted and re-presented in a more convenient way.Fast: Boosted up by pycryptodome, a high-performance cryptography library written in C.Async: Fully asynchronous (also usable synchronously if wanted, for convenience).Powerful: Full access to Rubika's API to execute any official client action and more.Our channel in messengersOurchannelinIta

https://eitaa.com/Sourse_py

https://eitaa.com/iLiaShahpy

OurchannelinSoroushPlus

https://splus.ir/Sourse_py

https://splus.ir/iLiaShahpy

OurchannelinRubika

https://rubika.ir/Sourse_py

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OurchannelonTelegram

https://t.me/Sourse_py

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OurchannelinBale

https://bale.ai/Sourse_py

https://bale.ai/iLiaShahpy
Package: ilikepaintings
I Like PaintingsI Like Paintings is a Python package that can predict the painting appreciation (if people like or not the painting) from the image using a linear regressor trained on top of a frozen CLIP features extractor model on two paintings appreciation datasets. The package contains pre-trained weights for nine models on two datasets (VAPS-999 and Sidhu's one).
All linear predictors in this package assume that their input embeddings are L2 normalized.InstallationYou can install I Like Paintings via pip:pipinstallilikepaintingsUsageTo use the package, you need to load the weights of the linear regressor. Here is an example code snippet:fromilikepaintingsimportload_predictor,VALID_MODELS,VALID_DATASETS# Choose a model and datasetclip_model_name=VALID_MODELS[0]dataset_name=VALID_DATASETS[0]# Load the predictorpredictor=load_predictor(clip_model_name,dataset_name)For a fully working example on a real painting, look atdemo.ipynbor try on!BenchmarkThe following table shows the cross-validation scores (k=5) of the linear model with the best hyper-parameters, measured using the Pearson correlation coefficient.
These scores were obtained for each CLIP model backend and dataset. The final released models were retrained using the same hyper-parameters and fitted on the whole dataset.
All embeddings are L2 normalized.CLIPVAPS-999SidhuRN500.67850.8039🥉RN50x40.70630.7858RN50x160.7307🥉0.8150🥈RN50x640.7335🥈0.8199🥇RN1010.69040.7964ViT-B/160.69250.7863ViT-B/320.69070.7823ViT-L/140.72650.7941ViT-L-14@336px0.7382🥇0.7985LicenseThe license associated with this package is the Creative Commons Attribution 4.0 International LicenseCC-BY 4.0,WITHthe following additional conditions:Before using any part or whole of this package, you must star :star: this repository.If you use any file associated with this package, including the provided weights or results, you must cite the package using the following BibTeX citation:@software{ilikepaintings,author={BIZZOZZERO, Nicolas and BENDIDI, Ihab and RISSER-MAROIX, Olivier},title={I Like Paintings},url={https://github.com/VieVie31/i-like-paintings},version={0.0.1},date={2023-03-16},}The package authors make no representations or warranties of any kind concerning the code or the information contained herein. They disclaim all liability and responsibility for any errors or omissions in the code, or for any loss, injury, or damage resulting from the use of this package, including but not limited to indirect or consequential damages.
Package: ilinq
This project provides the module like linq of C# for Python.DocumentationHow To Install$ pip install ilinqFor developers, we enter$ pip install pipenv
$ pipenv install --devFirst Example#!/usr/bin/env python
# -*- coding: utf-8 -*-

from ilinq.ilinq import Linq


def is_prime(n):
    if n < 2:
        return False

    for j in range(2, n):
        if n % j == 0:
            return False

    return True


if __name__ == '__main__':
    print(
        Linq(range(10**4))
        .last(is_prime))
    # => 9973LICENSEApache 2.0
Package: ilivalidator
ilivalidatorPython package forilivalidator.Ilivalidator is compiled to anative shared librarywithGraalVM. This Python package calls the native shared library.The native shared libs are built with Github Actions and thus are available for macOS, Ubuntu and Windows (all OS are x86_64).Installationpip install ilivalidatorRunfrom ilivalidator import Ilivalidator

valid = Ilivalidator.validate(['path/to/foo.xtf'])
print("The file is valid: {}".format(valid))Options are set with a dictionary:from ilivalidator import Ilivalidator

settings = {Ilivalidator.SETTING_ALL_OBJECTS_ACCESSIBLE: True}
valid = Ilivalidator.validate(["file1.xtf","file2.xtf"], settings)Supported options:Python packageIlivalidatorSETTING_ILIDIRS--modeldirSETTING_MODELNAMES--modelsSETTING_ALL_OBJECTS_ACCESSIBLE--allObjectsAccessibleSETTING_LOGFILE--logSETTING_LOGFILE_TIMESTAMP--logtimeSETTING_XTFLOG--xtflogtrace--traceYou have to useTrue/Falsefor options without arguments, e.g.SETTING_ALL_OBJECTS_ACCESSIBLE.DevelopRequirementsOn Ubuntu 22.04:sudo apt update
sudo apt install python3-pip
sudo apt install python3.10-venv
sudo apt-get install unzip zip
sudo apt-get install build-essential libz-dev zlib1g-devThe latter two are needed for SDKMan and GraalVM Native Image.Python setuppython3 -m venv .venv
source .venv/bin/activate
python3 -m pip install --upgrade setuptools wheelBuildingpython3 setup.py sdist bdist_wheel
python3 setup.py sdist bdist_wheel --plat-name=manylinux2014_aarch64 
python3 setup.py sdist bdist_wheel --plat-name=manylinux2014_x86_64Install locallypip install -e .
pip install -e .[test]Running testspytest ilivalidatorDev environmentYou can use Multipass for using Ubuntu as Development environment:multipass launch jammy --cpus 4 --disk 20G --memory 8G --name pylitools-dev
multipass mount $HOME/sources pylitools-dev:/home/ubuntu/sources
multipass shell pylitools-dev
multipass stop pylitools-devInstall Java:sudo apt-get update 
sudo apt-get install gcc zlib1g-dev build-essential zip unzip

curl -s "https://get.sdkman.io" | bash
source "/home/ubuntu/.sdkman/bin/sdkman-init.sh"
sdk i java 21-graalceCompile shared lib:./gradlew clean test nativeCompileJAVA_HOMEmuss gesetzt sein. Notfalls einmal aus- und einloggen, wenn man in der gleichen Session Java installiert hat.TodoTests: Wie kann die shared lib getestet werden?
Package: ilkbyte
Ilkbyte Python ClientInstallationpip install ilkbyteUsagefromilkbyte.clientimportIlkbyteilkbyte=Ilkbyte(host='https://api.ilkbyte.com/',secret_key='SECRET',access_key='ACCESS')print(ilkbyte.get_all_servers())Developmentpip install -r requirements.txtTestpython -m unittest
Package: illinikey
# IlliniKey![](image.png)Generate one time passwords (OTP) offline for UIUC Duo login.  Based heavily on [local-boilerkey](https://github.com/elnardu/local-boilerkey).# Setup and usage` pip install illinikey illinikey `Follow instructions for adding a new device.# i3 configurationAdd to your i3 config to auto to auto-fill the passcode field on the Duo login screen.` bindsym $mod+x exec sh-c"xdotool type $(illinikey)" `# CaveatsKey secrets are stored in~/.cache/illinikey.json.  An attacker with access to this file can bypass two-factor on your UIUC account.
Package: illini-snake
illini_snakeRepository containing an Illini-themed snake game, written in Python using the PyGame library.YouTube VideoWatch the gameplayhere.Repo SetupInstall locallyClone the repositoryNavigate toillini_snakepip install -r requirements.txtpython main.pyInstall via pippip install illini_snakepython -m illini_snakeHow to PlayUse arrow keys to move your Illini snake around. Eat the other big ten teams to grow your snake and increase your score. Watch out for the walls and don't run into yourself!DocumentationDocumentation is present on the repo'sGitHub PagesAuthor(s)James Kabbes - John Deere
Package: illumidesk-theia-proxy
IllumiDesk Theia IDETheiais a configurable web-based IDE
that supportsVisual Studio Codecompatible extensions. This package was built using thejupyter-server-proxycookiecutter template.Installationpipinstallillumidesk-theia-proxyRequirementsInstall THEIA IDEThis package's executes the standardtheia start --hostname=0.0.0.0 --port=3000command. This command assumes thetheiaexecutable andpackage.jsonfile required to start the application are globally available.We recommend building adocker image based on this exampleto avoid configuration conflicts, particularly when mounting the user's home directory with a volume on a local host.Install Jupyter NotebookThis extension relies on the Jupyter Notebook to run.Refer to Jupyter's official documentaionfor installation instructions.Install illumidesk-theia-proxyInstall the package with pip:pip install illumidesk-theia-proxyRunning with jupyter/docker-stacks based imageTheTHEIA IDErequiresnode v10xfor compilation. Therefore the version of node that runstheiashould also equate to v10x. The jupyter/docker-stacks based images install more recent versions of node. To runtheiawith a container based on ajupyter/docker-stacksimage installNVMand a version10xofnode.NotesThis package is tested with an image based on one of theJupyter docker-stacksrunning with JupyterHub.THEIArequires Node 10x. The basejupyter docker-stacksimages need some tweaking to make them work withnvmand the correct version ofnode. Refer tothis Dockerfilefor an example.Why?IllumiDesk's setup requiresdocker volumemounts with the local host instance. Files copied to thejovyanhome directory during the docker build stage are overriden by the files located on the host directories when running a container based on the image. Thereforetheiais installed with adebian package (*.deb)with a docker multi-stage build.This package assumes thetheiacommand is globally available and that the user's settings are defined in thepackage.jsoninstalled with the *.deb package, which by default is placed in the/usr/share/theia-example/app/package.jsondirectory.Attributionsjupyter-theia-proxytheia docker appsjupyter-server-proxyLicenseBSD 3-Clause
Package: illuminatus
illuminatusA Python library and command line tool for managing visual digital media (photos
and videos) using sqlite, pillow, and ffmpeg.Command-lineThe package comes with a command-line script,illuminatus, that serves as a
command-line frontend to many of the features provided by the library. To get
help, just invoke the script:illuminatusThe script requires an operation to be specified; the operations provided by the
script are documented in more detail below, but first a word about databases.Specifying a databaseTo allow the script to do something useful, you’ll need to provide the location
of a database holding media metadata. You can do this in one of two ways:Provide the--dbflag when running the script.Specify a database location using theILLUMINATUS_DBenvironment
variable.If both are provided, the flag overrides the setting of the environment
variable.ImportingTheilluminatusscript can recursively import media from any filesystem
path.illuminatus import ~/PicturesExportingTheilluminatusscript can export media that are tagged in a specific way.
The export comes in a zip file and includes a metadata dump of the relevant tags
and such.illuminatus exportListingTheilluminatusscript can show items in the database that match certain
queries.illuminatus listTaggingTheilluminatusscript can add or remove tags to or from media.illuminatus retagThumbnailsTheilluminatusscript can regenerate the thumbnails for existing items in
the database.illuminatus rethumbServingTheilluminatusscript can provide a RESTful HTTP server (usingbottle.py) for media data and metadata.illuminatus serveLibrary
Package: illumio
illumioIllumio Policy Compute Engine REST client for python 3. Exposes PCE API endpoints as functions through a simple interface.Compatible with Illumio Core PCE version 21.2+.The main entrypoint for the client is thePolicyComputeEngineclass:>>>fromillumioimportPolicyComputeEngine>>>pce=PolicyComputeEngine('pce.company.com',port='8443',org_id='12')>>>pce.set_credentials('api_key','api_secret')>>>workloads=pce.workloads.get(...params={...'managed':True,...'enforcement_mode':'visibility_only'...}...)>>>workloads[Workload(href='/orgs/12/workloads/c754a713-2bde-4427-af1f-bff145be509b',...),...]For more information on the Illumio APIs, see theREST API guideand theAPI referencefor your version of Illumio Core.Read the DocsYou can find API documentation, code examples, and usage guides on ourreadthedocs page!InstallationTheillumiolibrary is nowavailable on pypi!$python-mpipinstallillumioTo build and install from source$gitclonegit@github.com:illumio/illumio-py.git
$cdillumio-py
$makeSupportTheillumiopackage is released and distributed as open source software subject to the includedLICENSE. Illumio has no obligation or responsibility related to the package with respect to support, maintenance, availability, security or otherwise. Please read the entireLICENSEfor additional information regarding the permissions and limitations. Support is offered on a best-effort basis through theIllumio app integrations teamand project contributors.ContributingSee the project'sCONTRIBUTINGdocument for details.LicenseCopyright 2022 IllumioLicensed 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 at

       http://www.apache.org/licenses/LICENSE-2.0

   Unless 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: illusional.cwlgen
python-cwlgen(From original repository)Python-cwlgen is a python library for the generation of CWL programmatically.
It supports the generation of CommandLineTool, Workflow and DockerRequirement.
The library works for both Python 2.7.12+ and 3.6.0.I've forked this repository to try and get my use of this repository working quickly without
worrying too much about proper code etiquette. I have and will continue to submit merge requests
back to theoriginal repository.Common Workflow LanguageCommon Workflow Language (CWL)is a method to describe workflows,
and any tools (software) that it may use. Theuser guidegives a gentle (and better) explanation of what its goals are, and how they are achieved, but broadly:Stop writing bash scripts for long complex jobs.Take pipelines anywhere (portability).Try to enforce reproducibility guidelines.This python repository is simply a python wrapper formostof the classes (work in progress),
allowing you to build the structure of the workflow in Python and have this module generate and export CWL for you.Nb:This isn't going to sanity or quality check Workflows or CommandLineTools for you, useCWLToolorWOMToolfor that.Quick-start guideThis is available through PIP!pip install illusional.cwlgenHow it works ?There's a pretty close copy of the cwl specifications (Workflow|CommandLineTool), where the Python classes mirror the CWL spec.
This repository also includes some of the docstrings to give you context of classes and their properties.I've tried to include direct links to a classes documentation, however this isn't always possible.There are some small examples in theexamples/folder, however for whatever class you need, you simply just init
that class, for example:Creating a CommandLineTool# if using gitsubmodules, you can use the following import statementimportcwlgenascwltool_object=cwl.CommandLineTool(cwltool_id="echo-tool",base_command="echo",label=None,doc=None,cwl_version="v1.0",stdin=None,stderr=None,stdout=None,path=None)tool_object.inputs.append(cwl.CommandInputParameter("myParamId",label=None,secondary_files=None,param_format=None,streamable=None,doc=None,input_binding=None,default=None,param_type=None))# fill in the fields as required# to get the dictionary representation:dict_to_export=tool_object.get_dict()# dump using a yaml exporteryaml.dump(dict_to_export)All of the classes should work in a similar way. I've removed theliteralrepresentation from my fork as I
didn't want to useruamelat the moment. Otherwise file an issue and I'll have a look into it.
Package: illusionist
illusionistIllusionist takes a Jupyter Notebook with widgets and converts it to a
an HTML report that maintains the interactivity of the widgets without a
running Jupyter kernel.It does this by making all computation upfront and serializing all the possible outputs.
It generates a self-contained asset that you can easily drop into a file server
and have an interactive report that scales.The main idea of Jupyter Notebooks and Jupyter widgets is to make data closer
to the code and data scientists while maintaining interactivity, they do a great job at that.
Illusionist maintains the same development workflow Jupyter users are used to by using
standard Jupyter tooling such asipywidgetsandnbconvert.
No need to import anything in your notebook to generate an interactive report using illusionist,
just run onenbconvertcommand.The generated assets are easy to deploy, scale and have a big longevity by
removing a lot of deployment requirements and dependencies.Learn more and see examples inthe docs.
Package: illustrate
illustrateSimplistic & powerful crypto analyticshttps://github.com/m9m/illustrate/assets/95250150/cf0c8638-4f44-40e3-8efe-46a2d67c7dbdOverview:the illustrate project is meant to give the tools necessary to paint a picture of the cryptocurrency scene. This involves tools for coin prices, coin history, NFTS, ENS data, and more, all in a graphical representation.illustrate Discord Botillustrate's flagship discord bot is a minimalistic, open source Discord bot that serves as a customizable engine for server-owners and crypto enthusiasts. illustrate’s UI and setup process is easy to follow, and visually appealing as a personal or public analytics platform. With scaling in mind, the bot comes bundled with a sqlite database wrapper for higher production means, and can support dozens of servers at once. Any webhooks in a server that illustrate has access to can be linked to a type of analytic for an easy-access and plug & play setup.Features:Bitcoin PriceEthereum PriceEthereum Gas(discontinued as of July 2023 due to provider shutdown)Edit update interval for all data, which runs asyncronouslyRoadmap:ENS DataMATIC DataSlack BotMore mediums for cryptocurrency dataInstallation:illustrate's Discord bot is available through pypi by the following commandpip install illustrateor on some mac/linux distributionspip3 install illustrateExample:fromillustrateimportIllustrateBot,IllustrateCogsimportjsonsettings={"discord_bot_token":"xxxxx.xxx.xxxx-xxxxx-xxxx",# edit this value"webhook_update_intervals":300,# edit this value"coinwatch_api_key":"xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxx",# edit this value"webhook_json_data":json.dumps({"username":"illustrate","embeds":[{"title":"TITLE_VALUE","description":"DATA_VALUE","color":1127128}]})}illustrate_bot=IllustrateBot(settings)illustrate_bot.add_cog(IllustrateCogs(illustrate_bot))illustrate_bot.run()Legal & Third Parties UsedDiscord API (Terms of Service|Developer Policy|Developer Terms)Live Coin Watch API (Public API|Terms of Service)ETH Gas Station API (Homepage|Parent Project)Py-cord (Github|License)Requests (Github|License)Python and all of its Subsequent Standard Libraries (Homepage|License)
Package: ilmulti
ilmultiThis repository houses tooling used to create the models on the
leaderboard of WAT-Tasks. We provide wrappers to models which are
trained viapytorch/fairseqto
translate. Installation and usage intructions are provided below.Training: We use a separate fork ofpytorch/fairseqatjerinphilip/fairseq-ilmtfor
training to optimize for our cluster and to plug and play data
easily.Pretrained Models and Other Resources:preon.iiit.ac.in/~jerin/bhashaInstallationThe code is tested to work with the fairseq-fork which is branched from v0.7.2 and torch version 1.0.0.# --user is optionalpython3-mpipinstall-rrequirements.txt--userpython3setup.pyinstall--userDownloading Models: The scriptscripts/download-and-setup-models.shdownloads the model and dictionary files required for runningexamples/mm_all.py. Which models to download
can be configured in the script.A working example using the wrappers in this code can be found in thisColab Notebook.Usagefromilmulti.translatorimportfrom_pretrainedtranslator=from_pretrained(tag='mm-all')sample=translator("The quick brown fox jumps over the lazy dog",tgt_lang='hi')
Package: ilo
A package that lets users control ilo the new educational robot using python command lines.FeaturesMoves the robot inmany directionswith python commands lineCreatesmovement loopsPlay with the robot inreal timewith your keyboardUsecolored platesto make the robot moveWhere to get it ?# with pip
pip install iloDependenciesKeyboard - Take full control of your keyboard with this small Python library. Hook global events, register hotkeys, simulate key presses and much more.Don't worry, this dependency is automatically installed with the ilo library.Exampleimport ilo

ilo.connection()

print("ilo is connected")

ilo.set_led_color_rgb(200,0,0)      # color is red
ilo.set_led_color_rgb(0,0,200)      # color is blue

while true:

    print("Ilo moves forward")
    ilo.move("front", 100)
    
    while ilo.get_distance() > 20:
        pass
        
    ilo.stop()
    print("ilo has encountered an obstacle")
    
    if ilo.get_distance() > 20:
        ilo.move("right", 80)
        print("ilo moves to the right at 80% speed")
    
    else:
        ilo.move("left", 70)
        print("ilo moves to the left at 70% speed")About usFind us on ourwebsite;)
Package: iload
Load or reload python objectimport module:import iloadload moudule:mod = iload.iload('mymodule')load function:func = iload.iload('mymodule.func')load class:MyClass = iload.iload('mymodule.MyClass')reload module:new_mod = iload.ireload(mod)reload function:new_func = iload.ireload(func)reload class:NewMyClass = iload.ireload(MyClass)Changes0.1.8(2014-09-16)Add CHANGES.rst and README.rst to MANIFEST.in0.1.3Add CHANGES.txtRefactor setup.pyUse reStructuredText in README