Saravanan666/pypi-org huggingface dataset:
Package: remarkabletools-mx-smartsend
Mx.NET.SDK.SmartSend⚡ MultiversX SmartSend Python SDK: Library for interacting with Smart Send contracts on MultiversX blockchainHow to install?The content is delivered via PyPI package:remarkabletools_mx_smartsendMain FeaturesCreate EGLD/Token/MetaESDT/NFT/SFT transactions for Smart Send contractsQuick start guideBasic exampleprovider=ProxyNetworkProvider("https://devnet-gateway.multiversx.com")account=provider.get_account(Address.from_bech32("MY_ADDRESS"))network_config=provider.get_network_config()config=DefaultTransactionBuildersConfiguration(network_config.chain_id)smart_send=SmartSend(account,config,"MY_CONTRACT_BECH32_ADDRESS")input_transactions:List[TokenAmount]=[]foriinrange(1,10):input_transactions.append(TokenAmount("RECEIVER_ADDRESS",TokenPayment.egld_from_amount(f"0.0{i}")))# TokenPayment can also be fungible_from_amount / meta_esdt_from_amount / non_fungible / semi_fungibletry:# You can sync the account before creating transactions (to have the latest nonce)# account = provider.get_account(Address.from_bech32("MY_ADDRESS")) # get account data from network# smart_send.sync(account) # sync accounttxs=smart_send.create_egld_transactions(input_transactions)# or create_token_transactions / create_metaesdt_transactions / create_nft_transactions / create_sft_transactions# sign and send txsexceptExceptionasex:print(ex)Advanced exampleThe following example is using a walletsignerthat should not be used in production, only in private!provider=ProxyNetworkProvider("https://devnet-gateway.multiversx.com")account=provider.get_account(Address.from_bech32("MY_ADDRESS"))network_config=provider.get_network_config()config=DefaultTransactionBuildersConfiguration(network_config.chain_id)signer=UserSigner.from_pem_file(Path("/path/wallet.pem"))smart_send=SmartSend(account,config,"MY_CONTRACT_ADDRESS")input_transactions:List[TokenAmount]=[]foriinrange(1,10):input_transactions.append(TokenAmount("RECEIVER_ADDRESS",TokenPayment.egld_from_amount(f"0.0{i}")))try:txs=smart_send.create_egld_transactions(input_transactions)fortxintxs:tx.signature=signer.sign(tx)response=provider.send_transactions(txs)print(response)exceptExceptionasex:print(ex)
Package: remarkable-tweak
Tweak tool for the reMarkable paper tablet. Lets you organize your
templates with no fuss.Can now be installed with “pip”:InstructionsInstall python 3.x frompython.org(if you’re on
linux, this is probably already on your system)In a terminal or console window enterpip installremarkable-tweak. This should take care of the
installation for you, however on some systems you may have to usepip3as the command instead.Run the tool with the commandremarkable-tweakeither from a
terminal window, Windows’ ‘Run’ dialog, or similar. Your reMarkable
has to be connected via the stock USB cable.You also need your tablet’s password, which you find under
About->’GPLv3 Compliance’ (lower right corner of About-screen)To get to this menu, you simply tap the ‘rM’ logo in the top left
corner of your overview-screen.NOTE: This is currently in a BETA stage of development. Testing needs
to be done on Windows and iOS. Please contact if interested in
contributing.
Package: remarkable-update-fuse
reMarkable Update FUSEMount remarkable update files using FUSEUsagepipinstallremarkable_update_fuse
mkdir/mnt/signed/mnt/image
rmufusepath/to/update_file.signed/mnt/signedKnown IssuesWill report checksum errors for Directory inode, even though they are fineWill report checksum errors for extent headers, even though they are fineProgramatic Usagefromext4importVolumefromremarkable_update_fuseimportUpdateImageimage=UpdateImage("path/to/update/file.signed")# Extract raw ext4 imagewithopen("image.ext4","wb")asf:f.write(image.read())# Extract specific filevolume=Volume(image)inode=volume.inode_at("etc","version")withopen("version","wb")asf:f.write(inode.open().read())BuildingDependencies:curlpythonpython-buildpython-pippython-pipxpython-venvpython-wheelmake# Build wheel and sdist packages in dist/makewheel# Build wheel package in dist/makesdist# Build sdist package in dist/makedev# Test mounting 2.15.1.1189 to .venv/mntmakeinstall# Build wheel and install it with pipx or pip install --user
Package: remarkable-usb-web-interface-fuse
reMarkable USB Web Interface FUSEUserspace filesystem for remarkable usb web interface.Usagepipinstallremarkable_usb_web_interface_fuse
rmuwifuse10.11.99.1/mntBuildingmake# Build wheel and sdist packages in dist/makewheel# Build wheel package in dist/makesdist# Build sdist package in dist/makedev# Test mounting 2.15.1.1189 to .venv/mntmakeinstall# Build wheel and install it with pipx or pip install --user
Package: remarkdav
This is a small tool to sync webdav files (only PDF) to the reMarkable cloud (oneway).Setup (dev)Get rmapi (Go CLI application)see instructions athttps://github.com/juruen/rmapiClone from Gitgit clone git@github.com:hansegucker/remarkdav.gitGet poetrySee instructions athttps://python-poetry.org/docs/#installationInstall dependencies$ cd remarkdav/ # Go to your cloned directory
$ poetry installRun$ poetry run remarkdavSetup (production)Get rmapi (Go CLI application)see instructions athttps://github.com/juruen/rmapiGet it via poetry (use pip with Python 3)$ sudo pip install -G remarkdavRun$ remarkdavConfigurationCopy the example configuration file fromsettings-example.tomlto/etc/remarkdav/settings.tomland customise it.Copyright© 2020 by Jonathan Weth <dev@jonathanweth.de>remarkdav is licenced under GPL-3.0.
Package: remarkov
ReMarkovis a Python library for generating text from existing samples usingMarkov chains.
You can use it to customize all sorts of writing from birthday messages, horoscopes, Wikipedia articles, or the utterances of your game's NPCs.
Everything works without an omnipotent"AI"- it is dead-simple code and therefore fast.Check out theexamplesand feel free to contribute!Installationpip3installremarkovExampleScrape the Wikipedia page for "Computer Programming" and generate a new text from it:./tools/scrape-wiki.pyComputer_programming|remarkovbuild|remarkovgenerateYou can also useremarkovprogrammatically:fromremarkovimportcreate_modelmodel=create_model()model.add_text("This is a sample text and this is another.")print(model.generate().text())# "This is a sample text and this is a sample text and this is a sample text ..."DevelopmentMake sure you run pytest as module. This will add the current directory to the import path:python3-mpytestThis project usesblackfor source code formatting:black.Generate documentation for the project (this uses the original pdoc atpdoc.dev):gitcheckoutgh-pages
pdoc-tpdoc/template-opublic/docs<path_to_remarkov_module>Run type checks usingmypy:mypy-premarkovPublishing is done like this (don't forget to bump the version insetup.py):pip3installtwine# optionalgittag-a<version>
gitpush--tags

python3setup.pyclean--all
python3setup.pysdistbdist_wheel
twinecheck"dist/*"twineupload"dist/*"
Package: remarkuple
# Remarkuple 3Remarkuple - XML/HTML/SVG tag generation helper for Python 3Previous Python 2 version available at:https://github.com/markomanninen/remarkuplePlease see the following Jupyter notebooks for study and examples:[Remarkuple 3 examples](http://nbviewer.jupyter.org/github/markomanninen/remarkuple3/blob/master/Remarkable%203%20examples.ipynb)[Remarkuple 3 test cases](http://nbviewer.jupyter.org/github/markomanninen/remarkuple3/blob/master/Remarkuple%203%20test%20cases.ipynb)[Remarkuple 3 documentation](http://nbviewer.jupyter.org/github/markomanninen/remarkuple3/blob/master/Remarkuple%203%20documentation.ipynb)
Package: rembg-aws-lambda
Rembg (AWS Lambda)This is astripped-downfork ofdanielgatis/rembgdesigned forAWS Lambdaenvironments.rembg-aws-lambdais a tool to remove images background.Check out my similar project,profile-photo,
which can create aheadshotfrom an image.Requirementspython: >3.7, <3.11InstallationCPU support:pipinstallrembg-aws-lambdaGPU support:First of all, you need to check if your system supports theonnxruntime-gpu.Go tohttps://onnxruntime.aiand check the installation matrix.If yes, just run:pipinstallrembg-aws-lambda[gpu]Usage as a libraryInput and output as bytesfromrembgimportremoveinput_path='input.png'output_path='output.png'withopen(input_path,'rb')asi:withopen(output_path,'wb')aso:input=i.read()output=remove(input)o.write(output)Input and output as a PIL imagefromrembgimportremovefromPILimportImageinput_path='input.png'output_path='output.png'input=Image.open(input_path)output=remove(input)output.save(output_path)Input and output as a numpy arrayfromrembgimportremoveimportcv2input_path='input.png'output_path='output.png'input=cv2.imread(input_path)output=remove(input)cv2.imwrite(output_path,output)How to iterate over files in a performatic wayfrompathlibimportPathfromrembgimportremove,new_sessionsession=new_session()forfileinPath('path/to/folder').glob('*.png'):input_path=str(file)output_path=str(file.parent/(file.stem+".out.png"))withopen(input_path,'rb')asi:withopen(output_path,'wb')aso:input=i.read()output=remove(input,session=session)o.write(output)ModelsAll models are downloaded and saved in the user home folder in the.u2netdirectory.The available models are:u2net (download,source): A pre-trained model for general use cases.u2netp (download,source): A lightweight version of u2net model.u2net_human_seg (download,source): A pre-trained model for human segmentation.u2net_cloth_seg (download,source): A pre-trained model for Cloths Parsing from human portrait. Here clothes are parsed into 3 category: Upper body, Lower body and Full body.silueta (download,source): Same as u2net but the size is reduced to 43Mb.How to train your own modelIf You need more fine tunned models try this:https://github.com/danielgatis/rembg/issues/193#issuecomment-1055534289Some video tutorialshttps://www.youtube.com/watch?v=3xqwpXjxyMQhttps://www.youtube.com/watch?v=dFKRGXdkGJUhttps://www.youtube.com/watch?v=Ai-BS_T7yjEhttps://www.youtube.com/watch?v=dFKRGXdkGJUhttps://www.youtube.com/watch?v=D7W-C0urVcQReferenceshttps://arxiv.org/pdf/2005.09007.pdfhttps://github.com/NathanUA/U-2-Nethttps://github.com/pymatting/pymattingBuy me a coffeeLiked some of my work? Buy me a coffee (or more likely a beer)LicenseCopyright:(c) 2020-presentDaniel Gatis(c) 2023-presentRitvik NagLicensed underMIT License
Package: rembg-cars
rembg_carsExtension of Rembg tool to remove backgrounds for adding a car custom model from libraryRequirementspython 3.8 or newertorch and torchvision stable version (https://pytorch.org)How to install torch/torchvisionGo tohttps://pytorch.organd scrool down toINSTALL PYTORCHsection and follow the instructions.InstallationInstall it from pypipipinstallrembg_carrosUsage as a libraryExample: Using PILInapp.pyfromrembg.bgimportremoveimportnumpyasnpimportiofromPILimportImageinput_path='input.png'output_path='out.png'f=np.fromfile(input_path)result=remove(f,model_name="carros")img=Image.open(io.BytesIO(result)).convert("RGBA")img.save(output_path)Then runpython app.pyReferenceshttps://arxiv.org/pdf/2005.09007.pdfhttps://github.com/NathanUA/U-2-Nethttps://github.com/pymatting/pymattinghttps://github.com/danielgatis/rembgLicenseCopyright (c) 2021 poropezaPeter OropezaLicensed underMIT License
Package: rembg-greenscreen
Rembg Virtual Greenscreen Edition (Dr. Tim Scarfe)Rembg Virtual Greenscreen Edition is a tool to create a green screen matte for videosVideo Virtual Green Screen Edition15th Jan 2021 -- made a new YouTube explainerTake any  video file and convert it to an alpha matte to apply for a virtual green screenIt runs end-to-end non-interactivelyYou need ffmpeg installed and on your pathThere is also a powershell script./remove-bg.ps1which will do the job in a manual way i.e. first create frames, then run therembg -p ...command and then runffmpegto create the matte movie. This was my first approach to solve this problem but then I migrated onto just making a new version of rembg.If you have any ideas for speeding this up further, please let us know. We have tried quite a few things at this stage and are a bit stuck on how to proceed from here. See some of the "evolution" in  theWhimsical notes.Usage;pip install rembg-greenscreen

greenscreen -g "path/video.mp4"Experimental parallel green screen version;greenscreen --parallelgreenscreen "path/video.mp4" --workernodes 3 --gpubatchsize 5The command above will produce avideo.matte.mp4in the same folder, also works withmovandaviextensions. Uses ffmpeg under the hood to stream and re-encode the frames into a grayscale matte video.Be careful with the default parameters, my 11GB GPU is already pretty much maxed with 3 instances of the NN with 5 image gpu batches in forward pass.You can see how much free GPU ram you have withnvidia-smiCLI interfaceImportant notesDon't use VBR videos, it will run forever -- use Handbrake to convert them to CFRReferenceshttps://arxiv.org/pdf/2005.09007.pdfhttps://github.com/NathanUA/U-2-Net(thanks to these folks for making the semantic segmentation model and publishing online)LicenseCopyright (c) 2020-presentDaniel GatisCopyright (c) 2020-presentDr. Tim ScarfeCopyright (c) 2020-presentLucas Nestler(Making it go faster and more stuff running on the GPU, thanks Lucas!)Licensed underMIT License
Package: rembgpy
rembgpyA simple python api wrapper for remove.bg.Installationpip install rembgpyUsagefromrembgpyimportRemBgimportbase64api=RemBg("api-key","logged-error.log")withopen("titty.jpg","rb")asimage_file:encoded_string=base64.b64encode(image_file.read())print(api.remove_b64(encoded_string))Usage 2fromrembgpyimportRemBgapi=RemBg("api-key","logged-error.log")print(api.remove_img("https://sample.com/img_url.jpg"))
Package: rem-calc
rem-calcrem-calc helps you to calculate rem values based on pixel values. It has aninteractiveandcalculatemode.
Theinteractivemode is useful if you need to convert a lot of values, thecalcualtemode should be used for single
values.Installpipinstallrem-calcUsagePrinting Help$rem-calc
Usage:rem-calc.py[OPTIONS]COMMAND[ARGS]...

Options:--helpShowthismessageandexit.

Commands:calculateinteractiveSingle Rem Calculation$rem-calccalculate--base16--target201.25remSingle Pixel Calculation$rem-calcinverse--base16--rem2.75
44pxInteractive Value Calculation$rem-calcinteractive--base16Entertargetpixel:201.25rem
Entertargetpixel:402.5rem
Entertargetpixel:
^C
Aborted!
Package: remcmp
remcmpExtensible program to compare local and remote directories.Since it uses thefsmodule, any extensions (such asfs.smbfs) can be used simply by installing them, andyou can write your own.InstallationYou can install it usingpip:pip3installremcmpOr download it directly fromPyPI.Usage$ remcmp -h
usage: remcmp.py [-h] [-f] [-c] [-lf LOG_FILE] [-ll LOG_LEVEL] dir1 dir2

Remote compare directories.

positional arguments:
  dir1                  First directory to compare
  dir2                  Second directory to compare

optional arguments:
  -h, --help            show this help message and exit
  -f, --files-only      Do not recurse into folders, only compare the files
  -c, --no-color        Do not output colorful text
  -lf LOG_FILE, --log-file LOG_FILE
                        Log into a file. This disables colored output
  -ll LOG_LEVEL, --log-level LOG_LEVEL
                        Which logging level to use. SUMMARY can be used to
                        only show the summary. By default this is INFO for
                        terminal and DEBUG for log fileExit codesEach stat (e.g.Equal,File only exists on one side) has a flag. If it is encountered at least once then it is OR-ed with the exit code. E.g.Directory only exists on one sideandFile only exists on one side:8 | 32 = 40.No stat: 0
Error: 1
Equal: 2
Not equal: 4
Directory only exists on one side: 8
Directory is file on the other side: 16
File only exists on one side: 32
File is directory on the other side: 64
Package: remder
# remder
### Renders a Markdown Document in a Web BrowserUsage:$ remder document.md0.111.18.12        -       Initial release. serve a rended .md document on port 8080Todo: Provide a way to select another md doc, or input text for renderingOffer command line options - port, help/usage, etc.
Add some page style.0.212.19.12        -       Added console_script entry point.0.2.112.20.12        -       Changed name to reMDer, added port argument to cl script
Package: reme
Reme - A Discord bot that will send you remindersNOTE: Reme uses a 24 hour clock in order to simplify datetimesFlags-d, debug - Reme echos what you send it after converting it to an Entry object
-h, help  - Prints this usage docstringMessage Formating!reme <Flag> <Message> @ mm/dd/yyyy hh:mm
!reme <Flag> <Message> @ hh:mm
!reme <Flag> <Message> +<Delta>[DdHhMm]ExamplesPrint this help docstring!reme -h || !reme helpSend a reminder 30 minutes from now!reme Take the pizza out of the oven +30mSend a reminder at 5:30 pm!reme Go grocery shopping @ 17:30Send a reminder on October 30th at 4:30 pm!reme DND Session @ 10/30 16:30Install$ /usr/bin/env python3 -m pip install reme
Package: remecap
remecapBypasses H-Captcha automatically using yolov5Installationpip install remecapExamplefromremecapimportAISolverfromseleniumimportwebdriverif__name__=='__main__':driver=webdriver.Chrome()driver.get("https://democaptcha.com/demo-form-eng/hcaptcha.html")solver=AISolver(driver)solver.start()TodoMaking it more faster
Package: remedian
remedianThe  Remedian:  A  Robust  Averaging  Method  for  Large  Data  Sets - Python
implementationThis algorithm is used to approximate the median of several data chunks if
these data chunks cannot (or should not) be loaded into memory at once.Given a data chunk of sizeobs_size, andtdata chunks overall, the
Remedian class sets up a numberk_arrsof arrays of lengthn_obs.The median of thetdata chunks of sizeobs_sizeis then approximated
as follows: One data chunk after another is fed into then_obspositions
of the first array. When the first array is full, its median is calculated
and stored in the first position of the second array. After this, the first
array is re-used to fill the second position of the second array, etc.
When the second array is full, the median of its values is stored in the
first position of the third array, and so on.The final "Remedian" is the median of the last array, after alltdata
chunks have been fed into the object.Installationpip install remedianThe dependencies should be installed automatically by pip.Installation of most recent versionactivate your python environmentgit clone https://www.github.com/sappelhoff/remediancd remedianpip install -e .then you should be able tofrom remedian.remedian import RemedianUsageSee theexample in the docs.ReferencesP.J. Rousseeuw, G.W. Bassett Jr., "The remedian: A robust averaging method
for large data sets", Journal of the American Statistical Association, vol.
85 (1990), pp. 97-104M. Chao, G. Lin, "The asymptotic distributions of the remedians", Journal of
Statistical Planning and Inference, vol. 37 (1993), pp. 1-11Domenico Cantone, Micha Hofri, "Further analysis of the remedian algorithm",
Theoretical Computer Science, vol. 495 (2013), pp. 1-16
Package: remediation
Remediation ProjTools to support the remediation tasks, reporting and monitoringFree software: MIT licenseDocumentation:https://remediation-proj.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2019-12-07)First release on PyPI.
Package: remedy-py
Overviewremedy-pyis a Python package used to interface with the BMC Remedy REST API.
My search for a development tool to facilitate easy interactions with the Remedy API
in a Python program didn't turn up any results that suited my needs, so I decided to create
my own and open-source it. Your feedback and contributions are welcome (seeContributing), so
that we can make this package useful to as many people as possible.InstallationYou may installremedy-pydirectly fromPyPI - TODO, or via pip:pip install remedy-py.UsageImport the PackageOnce you have the package installed, import the RemedyClient class for use in your Python program as follows:from remedy_py.RemedyAPIClient import RemedyClientInstantiate a ClientTheRemedyClientconstructor has three required arguments:host,user, andpassword.
Optional positional arguments includeverify,proxies, andtimeout.
Once you have instantiated a client, authentication with the Remedy API
is automatically handled for you in the constructor based on the username
and password provided. Any subsequent calls to the API will include a user-specific
jwt in the headers to let Remedy know who you are.Example usage:client = RemedyClient("example.domain", "Allen", "password", verify=False)Create a form entryENTRY_TEMPLATE={"First_Name":"Allen","Last_Name":"Allbrook","Description":"REST API: Incident Creation","Impact":"1-Extensive/Widespread","Urgency":"1-Critical","Status":"Assigned","Reported Source":"Direct Input","Service_Type":"User Service Restoration","z1D_Action":"CREATE"}FORM_NAME="HPD:IncidentInterface_Create"RETURN_VALUES=["Incident Number","Request ID"]incident,status_code=client.create_form_entry(FORM_NAME,ENTRY_TEMPLATE,RETURN_VALUES)incident_id=incident["values"]["Incident Number"]request_id=incident["values"]["Request ID"]ContributingYour feedback and contributions and welcome through issues and pull requests on the GitHub repository.
Please be as descriptive as possible with issues or feature requests and provide testing instructions
with any pull requests.Thank you for helping to advance this project!ContributorsSpecial shout out to my good friend and colleague Ryan Gordon (@Ryan-Gordon & @Ryan-Gordon1)
for helping get this off the ground. I appreciate your open and honest feedback and bright ideas.
Package: rememberer
remembererRememberer is a tool to help your functions remember their previous results.The advantage of this package compared to other memoization packages is that
it will remember the result of the function even if you kill the program and restart it.It will also remember the result even if you restart the python interpreter because
it uses a pickle file to store the results.InstallationpipinstallremembererUsagefromremembererimportremdefadd(a,b):importtimetime.sleep(3)returna+brem(add,1,b=2)# this will take 3 secondsrem(add,1,b=2)# this will take ~0 secondsYou can use it as a decorator as well:fromremembererimportrem_dec@rem_decdefadd(a,b):importtimetime.sleep(3)returna+badd(1,b=2)# this will take 3 secondsadd(1,b=2)# this will take ~0 secondsIf you want to clear the cache, you can use theforgetmethod:fromremembererimportforgetforget(add,1,b=2)
Package: remembering
RememberingProject status: Runnable prototypeRememberingis a reminder application for things we'd like to stay aware of during the day when
using the
computerThe application runs in the background "in the system tray" and notifications are shown in the
systray menu. Clicking a
menu item will launch the associated actionThese actions are supported at the moment:Showing a textDisplaying an imageLaunching a websiteCustom command (for example launching an application)The time of the reminders can be set to a certain frequency or to specific times of day (or both)Examples of how this application can be used:Showing a reminder of a loved one by adding imagesQuotes and wisdom that we want to remember can be shownReminding us of an intention that we set at the start of the dayLaunching a website which has content that is updated dailyA kind and encouraging word from a friendSomeone expressing gratitude for something you have contributedIf you are looking for a more typical reminder application this may be interesting for you:remindRunning from SourceOn Ubuntu:sudo apt-get install python3sudo apt-get install python3-pipsudo -H pip3 install --upgrade pipDownload the latest code by
clickinghereGo to the directory where you downloaded the filestar xvf remembering-master.tar.gzcd remembering-mastersudo -H pip3 install -r requirements.txtpython3 remembering.py