Saravanan666/pypi-org huggingface dataset:
Package: rudalle-paddle
ruDALL-E PaddlePaddleruDALL-E in PaddlePaddle.Install:pip install rudalle_paddle==0.0.1rc1Run with free v100 onAI Studio.Original Pytorch version Readme:ruDALL-EGenerate images from texts🤗 HF Models:ruDALL-E Malevich (XL)Minimal Example:generation by ruDALLE:fromrudalle_paddle.pipelinesimportgenerate_images,show,super_resolution,cherry_pick_by_clipfromrudalle_paddleimportget_rudalle_model,get_tokenizer,get_vae,get_realesrgan,get_ruclipfromrudalle_paddle.utilsimportseed_everything# prepare modelsdevice='cuda'dalle=get_rudalle_model('Malevich',pretrained=True,fp16=True,device=device)realesrgan=get_realesrgan('x4',device=device)tokenizer=get_tokenizer()vae=get_vae().to(device)ruclip,ruclip_processor=get_ruclip('ruclip-vit-base-patch32-v5')ruclip=ruclip.to(device)text='изображение радуги на фоне ночного города'seed_everything(42)pil_images=[]scores=[]fortop_k,top_p,images_numin[(2048,0.995,3),(1536,0.99,3),(1024,0.99,3),(1024,0.98,3),(512,0.97,3),(384,0.96,3),(256,0.95,3),(128,0.95,3),]:_pil_images,_scores=generate_images(text,tokenizer,dalle,vae,top_k=top_k,images_num=images_num,top_p=top_p)pil_images+=_pil_imagesscores+=_scoresshow(pil_images,6)auto cherry-pick by ruCLIP:top_images,clip_scores=cherry_pick_by_clip(pil_images,text,ruclip,ruclip_processor,device=device,count=6)show(top_images,3)super resolution:sr_images=super_resolution(top_images,realesrgan)show(sr_images,3)text,seed='красивая тян из аниме',6955Image Promptseejupyters/ruDALLE-image-prompts-A100.ipynbtext,seed='Храм Василия Блаженного',42skyes=[red_sky,sunny_sky,cloudy_sky,night_sky]🚀 Contributors 🚀@neverixthanks a lot for contributing for speed up of inference@oriBetelgeusethanks a lot for easy API of generation using image prompt
Package: rudderlabs.data.apps
This package containes scripts for creating new data apps project and running data apps pipeline using amazon sagemaker instance.DevelopmentConda environment setup# Create the enviroment$condaenvcreate-fconda/environment.yaml# Activate and install this repository in edit mode$condaactivaterudderlabs$pipinstall-e.Code checksAll the staged code changes needs to be passed pre-commit checks before committed and pushed to the remote repository#Adding all changes to staging$gitadd--all#Running pre-commmit checks$pre-commitrunPublishing new versionTo publish a new version of this package, you need to update the version number inversion.txtfile and run the following command# Create a new tag$gittagrelease/<version># Ex. release/0.0.1b28# Push the tag to remote$gitpushoriginmain--tagsDocumentationAll the documentation written inReStructuredTextmarkup language, FollowData Apps Utils Documentationfor generated html pages.
Package: rudderstack-airflow-provider
The Customer Data Platform for DevelopersWebsite·Documentation·Slack CommunityRudderStack Airflow ProviderTheRudderStackAirflow Provider lets you programmatically schedule and trigger yourReverse ETLsyncs from outside RudderStack and integrate them with your existing Airflow workflows.For more information on using the Airflow Provider utility, refer to thedocumentation.Installationpipinstallrudderstack-airflow-providerUsageA simple DAG for triggering syncs for a RudderStack source:withDAG('rudderstack-sample',default_args=default_args,description='A simple tutorial DAG',schedule_interval=timedelta(days=1),start_date=datetime(2021,1,1),catchup=False,tags=['rs'])asdag:rs_operator=RudderstackOperator(source_id='<source-id>',task_id='<any-task-id>',connection_id='rudderstack_conn')For the complete code, refer to thisexample.Operator ParametersParameterDescriptionTypeDefaultsource_idValid RudderStack source IDStringNonetask_idA unique task ID within a DAGStringNonewait_for_completionIfTrue, the task will wait for sync to complete.BooleanFalseconnection_idThe Airflow connection to use for connecting to the Rudderstack API.Stringrudderstack_defaultThe RudderStack operator also supports all the parameters supported by theAirflow base operator.For details on how to run the DAG in Airflow, refer to thedocumentation.ContributeWe would love to see you contribute to this project. Get more information on how to contributehere.LicenseThe RudderStack Airflow Provider is released under theMIT License.Contact UsFor more information or queries on this feature, you cancontact usor start a conversation in ourSlackcommunity.
Package: ruddocom.pdfiframer
ruddocom.pdfiframer: correct handling of PDFs in IFRAMEsThis Plone add-on adds a bit of JavaScript that turns all servedIFRAMEs
which embed a PDF into a clickable icon the user must tap or click before
the PDF is actually embedded and rendered.  This behavior is only active
on certain mobile browsers known not to display PDFs embedded.This not only saves you bandwidth, it also prevents a nasty behavior on
mobile devices when embedding PDFs usingIFRAMEs — instead of the PDF
being displayed, a download window pops up (yes, even when the server sends
aContent-Disposition: inlineHTTP header).Thus, visitors to your site can see the PDF onscreen with one click, and
mobile visitors can download the PDF by clicking / tapping on the icon.Note that, by default, Plone filtersIFRAMEtags out of content types.
Use the HTML filtering control panel configuration screen to allowIFRAMEs
to be used on your Plone site.NotesWe use a footer viewlet to include the JavaScript, because on mobile Fennec
or Firefox Focus, theIFRAMEhas already begun loading and the download
window pops up before theDOMContentLoadedevent has happened.SetupIt's a standard Plone add-on.  Add to your Plone eggs list, buildout.LicenseThe project is licensed under the GPLv2 or later at your choice.
Package: rudi
RudiIf you want to train a CNN, the custom dataset must be a collection of images of the same aspect ratio, extension, etc.
This script is gonna do that for you. Rudi is a command line tool for converting and augmenting your dataset of images.InstallationInstallPython3and then run the following command:pipinstallrudior clone the repo firsgitclonehttps://github.com/liashchynskyi/rudicdrudiand runpython setup.py installorpip install .UsageConvert a datasetDataset augmentationChangelogDonateConvert a datasetFor example, you have a basic tree of the root directory (the script will also work if the root containt only images without other dirs).root    
в””в”Ђв”Ђв”Ђclass1
в”‚   в”‚   image_c1.png
в”‚   в”‚   image_c2.png
в”‚   в””в”Ђв”Ђв”Ђsubdirectory    
в””в”Ђв”Ђв”Ђclass2
    в”‚   image_c1.png
    в”‚   image_c2.pngJust runrudi convert --helpLet's convert images in current directory tojpgformat and set new aspect ratio to224px.rudiconvert-tjpg--target-size=224./Output images will be saved inoutputdir of the root.Dataset augmentationCommand:rudi augment --helpThere are a few supported operations:flip- random image flipping followed by-poptionrotate- random image rotation followed by-p,-mlrand-mrroptionsdistortion- random image distortion followed by-p,-mgand-gwhoptionsskew- random image skewing followed by-poption and constantmagnitudevalue of0.7zoom- random image zooming followed by-p,-minfand-maxfoptionsOutput images will be saved inoutputdir of the root.Changelog1.0.1Fixed problem when converting images. Now if image is placed in subdirectory
then that subdir also will be created inoutputdir.DonateJust put a star on this repository рџЊћ Thanks!made by@liashchynskyi
Package: rudie-pomodoro-tracker
CLI tools forpomodoro techniqueRun withpomodorocommand.Avaiable flags:FlagAction--no-saveDo notstoresessions to file--no-clearDo not clear output after creating session--folder=newUse specific folder for storing sessions. Defaults todaily--extension=txtUse specific files' extension. Defaults to.pomodoroBy default all pomodoro logs stored in folder calleddailywhere you runpomodorocommand.
Files have extension .pomodoro, but they are simply text files.You can change both folder name and extension flags using corresponding cli flags.Then use input to manage sessions:lap or l      - make new lap
end or e      - exit
anything else - lap title
Package: rudiments
This package offers configuration handling and other basic helpers
for Python projects.Copyright ©  2015 - 2020 Jürgen Hermann <jh@web.de>Licensed under the Apache License, Version 2.0 (the “License”);
you may not use this file except in compliance with the License.
You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an “AS IS” BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Package: rudi-node-read
RUDI Node tools:rudi-node-readlibraryThis library offers tools to take advantage of
theexternal APIof a RUDI Producer node (also
referred as RUDI node).The Jupyter notebookREADME.ipynboffers
an overview of the available functionalities.Installationpipinstallrudi-node-readYou don't need installing any additional library to use this.UsageSeePython notebookfor use examples.TestingRudi-node-read supports unit test discovery using Pytest:dest_dir="rudi-node-read"gitclonehttps://github.com/OlivierMartineau/rudi-node-read.git$dest_dircd$dest_dirpython3-mvenv.venvsource.venv/bin/activate

pipinstall-rrequirements-dev.txt

pytestYou may have a look at thetestsif you wish to see how every class or function is used.
Package: rudi-node-write
Caution: this librairy is still a work in progress.RUDI Node tools:rudi-node-writelibraryThis library offers tools to take advantage of
theinternal APIof a RUDI Producer node (
also
referred as RUDI node).Installation$pipinstallrudi_node_writeAuthenticationTo use the RUDI node internal API/api/admin/..., you'll need an authentication JWT in every header request.This library provides aRudiNodeJwtFactoryconnector that calls aJWT
serverrunning locally or on the RUDI
node to create/renew the JWT.rudi_node_credentials={"url":"<rudi node url>","usr":"<my user name>",# either use 'usr' & 'pwd', or the base64url encoded usr:pwd pair in 'b64auth'"pwd":"<my password>","b64auth":"<base64url encoded usr:pwd pair>"# optional / alternative way of declaring the usr:pwd pair}fromrudi_node_write.connectors.io_rudi_jwt_factoryimportRudiNodeJwtFactorynode_jwt_factory=RudiNodeJwtFactory(rudi_node_credentials["url"],rudi_node_credentials)Usage: RudiNodeApiConnectorOne can create, read, update or delete metadata with a RudiNodeApiConnector object using the [RUDI API](.
/doc/rudi-api/RUDI producer internal API - 1.3.0.yml).fromrudi_node_write.connectors.io_rudi_jwt_factoryimportRudiNodeJwtFactoryfromrudi_node_write.connectors.io_rudi_api_writeimportRudiNodeApiConnectorrudi_node_url='https://bacasable.fenix.rudi-univ-rennes1.fr'node_jwt_factory=RudiNodeJwtFactory(rudi_node_url,{"usr":"<my user name>","pwd":"<my password>"})rudi_api=RudiNodeApiConnector(server_url=rudi_node_url,jwt_factory=node_jwt_factory)print("metadata count:",rudi_api.metadata_count)print("metadata alt count:",len(rudi_api.metadata_list))print("metadata producers declared on the node:",rudi_api.producer_names)print("searching a metadata with a file name:",rudi_api.find_metadata_with_media_name('toucan.jpg'))Usage: RudiNodeMediaConnectorThe upload of file is done with a RudiNodeMediaConnector that let you connect to a RUDI node Media server.
This also needs an authentication in the request header, that is created with the RudiMediaHeadersFactoryBasicAuth
object.fromrudi_node_write.connectors.io_rudi_media_writeimportRudiMediaHeadersFactoryBasicAuth,RudiNodeMediaConnectorrudi_node_url='https://bacasable.fenix.rudi-univ-rennes1.fr'media_headers_factory=RudiMediaHeadersFactoryBasicAuth(usr="<my user name>",pwd="<my password>")rudi_media=RudiNodeMediaConnector(server_url=rudi_node_url,headers_factory=media_headers_factory)print("listing the media stored on the RUDI node: ",rudi_media.media_list)TestingThetestscan be analyzed for further information about how to call the "RUDI API" and the "RUDI Media"
servers.$pytest
Package: rudolf
Colour output plugin for the nose testing framework.Only works on Unix-like systems (uses ANSI colour codes).Usenosetests--with-color(no “u”!) to turn it on.Known bugs:1. Errorclasses (e.g. skips, deprecations) crash rudolf.  This requires a
change to nose to fix, which is currently being discussed.2. When used with plugins that use the .report() plugin method, output from
those other plugins will be suppressed.  This includes the coverage plugin
that’s included with nose.  Again, this requires a change to nose.http://en.wikipedia.org/wiki/Rudolph_the_Red-Nosed_Reindeer“Rudolph the Red-Nosed Reindeer” is a popular Christmas story about Santa
Claus’ ninth and lead reindeer who possesses an unusually red colored nose that
gives off its own light that is powerful enough to illuminate the team’s path
through inclement weather.
Package: rudolph
[Colab]RUDOLPH 🦌🎄☃️One Hyper-Tasking Transformer can be creative as DALL-E and GPT-3 and smart as CLIPRUssianDecoderOnLanguagePictureHyper-tasking (RUDOLPH) is a text-image-text transformer designed for an easy fine-tuning for a range of tasks: from generating images by text description and image classification to visual question answering and more. This model demonstrates the power of Hyper-tasking Transformers.Hyper-tasking model is a generalized multi-tasking model, i.e., the model that can solve almost all tasks within supported modalities, mandatory including mutual pairwise translations between modalities (two modalities in case of RUDOLPH: images and Russian texts).Models350M (RUDOLPH)1.3B (RUDOLPH)2.7B (RUDOLPH)2.7B_FBC2 (RUDOLPH-fine-tuned)The following table shows the values of the parameters corresponding to different RUDOLPH versions.350M1.3B2.7Bl64128384r64128128m163224n163224Sparse Attention Mask350Mrow - col - row - [last] conv1.3Brow - col - row - [last] conv2.7Brow - col - row - [last] convInstallingpip install rudolph==0.0.1rc10Usage and Fine-TuningUsage and fine-tuning examples for different versions of RUDOLPH can be found in jupyters folder.Citation@misc{github2022ruDolph,
  title         = {RUDOLPH: One Hyper-Tasking Transformer can be creative as DALL-E and GPT-3 and smart as CLIP},
  author        = {AIRI},
  year          = {2022},
  howpublished  = {\url{https://github.com/ai-forever/ru-dolph}},
}Supported by
Package: rueckenwind
rückenwindA python web framework based on tornado, jinja2, babel.DocumentationHead over toRead The Docsand read the docs! Or build the docs from source using:sphinx-build-bhtml docs/ docs.html/and enjoy locally.Current StateThe framework does not yet provide a stable API.  When the API stabalizes the version is incremented to 1.x.  If used for anything that is remotely production-use make sure you stay within one 0.x branch of releases.  The current API (0.5.x / master) is not backward compatible to 0.4.x releases. The 0.4 branch is a major overhaul and is incompatible with 0.3.
Package: ruff2bitbucket
Ruff2BitBucketruffis an extremely fast Python linter and code formatter, written in Rust.BitBucketis an Atlassian product which provides a visual git interface (basically).With ruff2bitbucket you can run your ruff-validations and upload them as a code insight directly into BitBucket.Installationpipinstallruff2bitbucketUsageChange your directory to where the configuration file is stored and run:ruff2bitbucket[--user...][--pass...]⚠ It's important that you are in the right directory!ConfigurationYou should refer to theruff configuration docson how to modify yourpyproject.toml(orruff.toml, or.ruff.toml) in order to provide more extensive checks.SecurityIf no user or pass is passed, the environment variables are scanned for anything that looks likeUSER/USRandPASS/PW. When a match is found, this'll be used to attach the annotations to the current commit hash.
Package: ruffianTest
b'#Introduction\n    1.\xe6\xad\xa4\xe5\xba\x93\xe9\x9b\x86\xe6\x88\x90\xe6\xb5\x8b\xe8\xaf\x95\xe5\x9c\xa8\xe5\xbc\x80\xe5\x8f\x91\xe8\x84\x9a\xe6\x9c\xac\xe6\x97\xb6\xe5\xb8\xb8\xe7\x94\xa8\xe7\x9a\x84\xe4\xb8\x80\xe4\xba\x9b\xe5\x8a\x9f\xe8\x83\xbd\xef\xbc\x8c\xe9\x95\xbf\xe6\x9c\x9f\xe6\x9b\xb4\xe6\x96\xb0\n#Installing\n    pip install ruffianTest\n    python\xe2\x89\xa53.0\n\n#Author\nbugpz2779@gmail.com\n'
Package: ruffrgimportfixer
Fixes missing imports using Ruff and RipGrep (CLI and import)Tested against Windows / Python 3.11 / Anacondapip install ruffrgimportfixerA Python script for adding missing import statements in your Python code.
The script utilizes ruff and ripgrep to identify missing imports and organizes them based on various criteria, including the number of errors, the total number of imports, and the length of the import line.Usage:fromruffrgimportfixerimportfix_importsfix_imports('some_pythonfile.py')# or from the commandline ('some_pythonfile.py' as the only arg)# or a simple bat file:python-c"from ruffrgimportfixer import fix_imports;fix_imports(r'''%*''')"Dependencies:-ruff(https://github.com/astral-sh/ruff)-ripgrep(https://github.com/BurntSushi/ripgrep)# Both must be in sys.path
Package: ruffus
OverviewThe Ruffus module is a lightweight way to add support
for running computational pipelines.Computational pipelines are often conceptually quite simple, especially
if we breakdown the process into simple stages, or separatetasks.Each stage ortaskin a computational pipeline is represented by a python function
Each python function can be called in parallel to run multiplejobs.Ruffus was originally designed for use in bioinformatics to analyse multiple genome
data sets.DocumentationRuffus documentation can be foundhere,
withdownload notes,
atutorialand
anin-depth manual.BackgroundThe purpose of a pipeline is to determine automatically which parts of a multi-stage
process needs to be run and in what order in order to reach an objective (“targets”)Computational pipelines, especially for analysing large scientific datasets are
in widespread use.
However, even a conceptually simple series of steps can be difficult to set up and
maintain.DesignThe ruffus module has the following design goals:LightweightScalable / Flexible / PowerfulStandard PythonUnintrusiveAs simple as possibleFeaturesAutomatic support forManaging dependenciesParallel jobs, including dispatching work to computational clustersRe-starting from arbitrary points, especially after errors (checkpointing)Display of the pipeline as a flowchartManaging complex pipeline topologiesA Simple exampleUse the@follows(…)python decorator before the function definitions:from ruffus import *
import sys

def first_task():
    print "First task"

@follows(first_task)
def second_task():
    print "Second task"

@follows(second_task)
def final_task():
    print "Final task"the@followsdecorator indicate that thefirst_taskfunction precedessecond_taskin
the pipeline.The canonical Ruffus decorator is@transformwhichtransformsdata flowing down a
computational pipeline from one stage to teh next.UsageEach stage ortaskin a computational pipeline is represented by a python function
Each python function can be called in parallel to run multiplejobs.Import module:import ruffusAnnotate functions with python decoratorsPrint dependency graph if you necessaryFor a graphical flowchart injpg,svg,dot,png,ps,gifformats:pipeline_printout_graph ("flowchart.svg")This requiresdotto be installedFor a text printout of all jobspipeline_printout(sys.stdout)Run the pipeline:pipeline_run()
Package: rufmich
RufmichA Python server implementaion ofJSON-RPC 2.0over HTTP.Introductionrufmichis an HTTP server for JSON-RPC 2.0. To make the JSON-RPC 2.0 work over HTTP, following specifications are added:The transport protocol is HTTP. The response for an notification is an HTTP response with status code 204 (No Response) and empty content. The HTTP requests must have the headercontent-type: application/json, otherwise there will be an HTTP error 415 (Unsupported Media Type).A notification request will get an immediate response. Usually the server will start the procedure and return the response immediately (without having to wait for the procedure to finish). And there is no callback for the procedure, which means the client would not be aware of any errors.Method namespacing is supported (and recommended).NotificationNotification is implemented using threading. A method withoutidwill be invoked asynchronously in a new thread and the client will get an HTTP response with status code 204 after the creation of the thread.BatchIf multiple requests are sent in a batch, they will be processed concurrently by a thread pool. Only results of non-notification requests are returned. In case of that all the requests are notifications, the HTTP response will be of status 204.User GuideInstallationpip install rufmichDefine methodsCreate a folder with following structure:- <your_methods_workspace>
    - root
        root.py
        - <A>
            <A.py>
            - <B>
                <B.py>
        - <C>
            <C.py>An example is:- my_methods
    - root
        root.py
        - registration
            registration.py
            - by_email
                by_email.pyNote that there MUST BE a directory named root under your workspace folder.Each namespace folder MUST HAVE a.pyfile with the same name as the folder. The methods defined in those.pyfiles will be indexed according to the folder hierarchy.Examples:A methodfoobardefined inroot.pyis indexed to"foobar"and"::foobar"A methodsend_code_to_emaildefined inby_email.pyin the above example is indexed to"registration::by_email::send_code_to_email"(and"::registration::by_email::send_code_to_email")Application-specific errorsThe error codes from -32000 to -32099 are reserved for implementation-defined server-errors. The RPC server developer can raise an application-specific error by usingRMError:fromrufmich.errorimportRMErrordefdivision(a,b):ifb==0:raiseRMError(eid=0,message='divided by 0',data=[a,b])returna/bEach application-specific error should have an unique error ideid(0 <= eid <= 99). The error is mapped to [-32000, -32099] by the functionf: eid -> -32000-eid.Runfromrufmich.serverimportRMServerserver=RMServer(load_path='/workspace/methods')server.run(endpoint='/jsonrpc',port=8080)Client examplesCheck onthe website of JSON-RPC 2.0 Specification.
Package: rugosa
RugosaThe next generation ofkordesii.
This is a library (not a framework) for managing emulation and provides utilities
for interfacing with decompiled malware samples usingdragodis.Rugosa is meant to be used with an automation framework such asDC3-MWCP,
but can also be used in one-off scripting.Installpip install rugosaYou will also need to setup a backend disassembler by followingDragodis's installation instructions.UtilitiesThe following utilities are included with Rugosa:EmulationExtra Disssembly InterfacesRegexStringsYARAEmulator PluginRugosa includes a IDA and Ghidra plugin which provides a GUI for using theemulationutility.
For more information on how to install and use the plugin please see thedocumentation.
Package: rugplot
Connected bivariate scatter plots, in a rug.InstallationInstall library, perhaps within a virtualenv:$ pip install rugplotA short exampleThree scatter plots in a rug:import numpy as np
import svgwrite, random
from rugplot import CircleMarker, Scatter

N = 12
w = np.random.rand(N)
x = np.random.rand(N)
y = np.random.rand(N)
z = np.random.rand(N)

markers = []
for i in range(N):
    markers.append(CircleMarker(x=x[i], y=y[i], r=2.5,
                                fill=random.choice(['purple', 'blue',
                                                    'green', 'orange', 'red'])))

s0 = Scatter(x, y, markers, insert=(100,30), size=(200,200))
s0.drawBorder(stroke='grey', fill='white', stroke_width=0.4)
s0.drawMarkers()
s0.drawDotDash(['e','s'], dash_height=10, stroke="grey", stroke_width=0.4)


s1 = Scatter(w, y, markers, insert=(320,30), size=(350,200))
s1.drawBorder(stroke='grey', fill='white', stroke_width=0.4)
s1.drawMarkers()
s1.drawDotDash(['w'], dash_height=10, stroke="grey", stroke_width=0.4)


s2 = Scatter(x, z, markers, insert=(100,250), size=(200,300))
s2.drawBorder(stroke='grey', fill='white', stroke_width=0.4)
s2.drawMarkers()
s2.drawDotDash(['n','e', 'w'], dash_height=10, stroke="grey", stroke_width=0.4)


rug = svgwrite.Drawing('example.svg')
rug.add(s0.dwg)
rug.add(s1.dwg)
rug.add(s2.dwg)
rug.save()