Saravanan666/pypi-org huggingface dataset:
Package: toon-note
toon_noteExtension for creating comics based on Daye Kang's ToonNote CHI2021 paperRequirementsJupyterLab >= 3.0Installpipinstalltoon_noteContributingDevelopment installNote: You will need NodeJS to build the extension package.Thejlpmcommand is JupyterLab's pinned version ofyarnthat is installed with JupyterLab. You may useyarnornpmin lieu ofjlpmbelow.# Clone the repo to your local environment# Change directory to the toon_note directory# Install package in development modepipinstall-e.# Link your development version of the extension with JupyterLabjupyterlabextensiondevelop.--overwrite# If using a server extension, it must be manually installed in develop modejupyterserverextensionenable<extension_name># Rebuild extension Typescript source after making changesjlpmrunbuildYou can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.# Watch the source directory in one terminal, automatically rebuilding when neededjlpmrunwatch# Run JupyterLab in another terminaljupyterlabWith the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).By default, thejlpm run buildcommand generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:jupyterlabbuild--minimize=FalseUninstallpipuninstalltoon_note
Package: toontown.py
toontown.pyA simple Python API wrapper for the Toontown Rewritten/Corporate Clash APIFeaturesAsynchronous and synchronousAPI completeInstallingPython 3.8 or higher is required# Linux/macOSpython3-mpipinstall-Utoontown.py# Windowspy-3-mpipinstall-Utoontown.pyAboutAll methods return a tuple-like wrapper class with all the response data wrapped in objects (except Login and Status objects)e.g. This will print all the news article URLs for Rewritten and Corporate Clashasyncdefmain():"""Example main function"""session=aiohttp.ClientSession(raise_for_status=True)asyncwithRewrittenAsyncToontownClient(session=session)asttr_client,ClashAsyncToontownClient(session=session)asclash_client:news_list=awaitttr_client.news(all=True)fornewsinnews_list:print(news.article_url)news_list=awaitclash_client.news()fornewsinnews_list:print(news.article_url)
Package: toontown-utils
Toontown UtilsA package for Panda3D that streamlines the usage of Toontown Online assets, so that fan projects (games, videos, etc)
can easily use them.FeaturesToonActors and CogActorsToonActors and CogActors give a simple syntax to creating and modifying Toontown's character models. Creating characters
now only takes a few lines of code, and manipulating them can be done with simple API calls.ToontownJSONThough optional, Toontown Utils is primarily intended for use withToontownJSON. ToontownJSON provides data on the vanilla cogs and
toon parts. Its schema can also be used to add custom cogs, species and body parts.fromtoontown_utilsimportTemplateManagerfromtoontown_utils.cog.CogActorimportCogActorfromtoontown_utils.toon.ToonActorimportToonActorTemplateManager.loadFile("cog.json")cog=CogActor(cogType="ColdCaller")cog.reparentTo(render)cog.loop("neutral")TemplateManager.loadFile("toon.json")toon=ToonActor(species="cat",head="ls",torso="m",legs="s",clothingType="skirt",eyelashes=True)toon.reparentTo(render)toon.setX(5)toon.loop("neutral")Without ToontownJSON, the syntax is much uglier, as models, animations, etc must all be defined in code before they are
used.
Package: toori
tooriA minimal layer 3 tunnel over http(s).PrerequisitesMSVC Build ToolsInstallationpip install tooriUsageRun as Administrator:toori<serveraddress>Examplestoorihttps://toori.serverDon't tunnel DNS requeststoorihttps://toori.server-ndOnly tunnel SSH traffictoorihttps://toori.server-f"tcp.DstPort == 22"
Package: toori-server
IroServer for a minimal layer 3 tunnel over http(s).Deploying with DockerInstead of installing toori-server on the host, it can be deployed as a Docker container with much convenience.Pull from GHCR:sudodockerpullghcr.io/kokseen1/toori-server:latestRun the container:sudodockerrun-d--cap-add=NET_ADMIN-p80:80ghcr.io/kokseen1/toori-serverHTTPSTo deploy with HTTPS, run the container with a bind mount and pass the port and certs directory as arguments:sudodockerrun-d-v/etc/letsencrypt:/etc/letsencrypt--cap-add=NET_ADMIN-p443:443ghcr.io/kokseen1/toori-server443/etc/letsencrypt/live/toori.server/Installationpip3installtoori-server--no-binary:all:PrerequisitesLibtins(optional, will fallback to Scapy (slow) if not installed)RST PacketsBecause the Linux kernel sends aRSTto connections it did not establish, use the following command to ensure that outgoing packets are sent successfully:sudoiptables-AOUTPUT-ptcp--tcp-flagsRSTRST-s<localaddress>-jDROPSee herefor more information.UsageRun with root permissions:iro<port>Example with HTTPS:iro443-c"/etc/letsencrypt/live/toori.server/"
Package: too-short-url
too-short-urlshorturl based on too.stInstall itpipinstalltoo-short-url# or pip install git+https://github.com/ffreemt/too-short-url# or clone the repo andUse itCommand linetoo-sthttp://baid.com# too.st/bWith inpythonfromtoo_short_urlimporttoo_stprint(too_st("http://baidu.com"))# too.st/bDocstoo-st--help

Usage:too-st[OPTIONS]URLGeneratetoo.stshorturl.e.g.*too-stbaidu.com# https://too.st/b*too-stbaidu.com-kabc# https://too.st/b*too-stbaidu.com-kabc-b# https://too.st/abc or https://too.st/bdependentonwhetherhttps://too.st/abcisalreadytakenorreservedbythadminoftoo.st.

Arguments:URLurltobeshortened[required]Options:-k,--keyword,--kwKEYWORDdesiredkeyword,e.g.https://too.st/abcforKEYWORDsettoabc-b,--best-effort,--besteffortwhethertotryhardtogeneraetthedesiredshorturlhttps://too.st/KEYWORD-v,-V,--versionShowversioninfoandexit.--helpShowthismessageandexit.
Package: too-simple-server
Simple Mock ServerThis is single-purpose web server having 2 endpoints:/entities— for listing all existing entities/entity,/entity/<uuid>— for creating and retrieving existing entitiesServer can use either debug sqlite DB or PostgreSQL databaseServer configuration is done with configuration yaml file:debug:trueserver_port:5449pg_bd_url:'localhost:9999'pg_database:'users'pg_username:'admin'pg_password:'qwertyui!'Default location of configuration file is/etc/too-simple/config.yml,
this can be changed using--configargumentDebug mode is switched using--debugargument and enabled by default
Package: tootapari
tootapariA plugin to send Mastodon toots from napariInstallationYou can installtootapariviapip:pip install tootapariTo install latest development version :pip install git+https://github.com/kephale/tootapari.gitSetupSetup your.envfile in your XDG config directory. On MacOS this is/Users/<username>/Library/Application\ Support/tootapari/It should include:MASTODON_INSTANCE_URL="https://mastodon.social"
MASTODON_ACCESS_TOKEN="<your access token>"You can generate your access token by following these instructions:https://learn.adafruit.com/intro-to-mastodon-api-circuitpython/generate-your-mastodon-tokenTODO: someone should port these instructions to this readme.Start tooting!ContributingContributions are very welcome. Tests can be run withtox, please ensure
the coverage at least stays the same before you submit a pull request.LicenseDistributed under the terms of theBSD-3license,
"tootapari" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: tootbot
This is a Python bot that looks up posts from specified subreddits and automatically posts them onMastodon.
It is based onreddit-twitter-bot.Features:Tootbot posts toMastodonMedia from direct links, Gfycat, Imgur, Reddit, and Giphy is automatically attached in the social media post.
Tootbot attaches up to the first 4 pictures for imgur albums and reddit gallery posts.Links that do not contain media can be skipped, ideal for meme accounts like@babyelephantgifsNSFW content, spoilers, and self-posts can be filteredTootbot can monitor multiple subreddits at onceTootbot is fully open-source, so you don’t have to give an external service full access to your social media accountsTootbot also checks the sha256 checksum of media files to stop posting of the same media file from different subreddits.Tootbot can ping aHealthchecksinstance for monitoring continuous operation of TootbotOptionally throttle down frequency of tooting when mastodon errors are detected.!!! Tootbot no longer supports posting to Twitter. !!!If you need twitter functionality look intoreddit-twitter-botas a possible alternative.!!! Tootbot no longer supports deleting old toots. !!!If you’d like to delete older toots from your Mastodon account look intoFedinesiaas a tool that might
work for you.DisclaimerThe developers of Tootbot hold no liability for what you do with this script or what happens to you by using this
script. Abusing this scriptcanget you banned from Mastodon, so make sure to read up on proper usage of the API
for each site.Setup and usageFor instructions on setting up and using Tootbot, please look atthe documentationSupporting TootbotThere are a number of ways you can support Tootbot:Create an issue with problems or ideas you have with/for TootbootYou canbuy me a coffee.You can send me small change in Monero to the address below:Monero donation address:87C65WhSDMhg4GfCBoiy861XTB6DL2MwHT3SWudhjR3LMeGEJG8zeZZ9y4Exrtx5ihavXyfSEschtH4JqHFQS2k1Hmn2LktChangelogSee theChangelogfor any changes introduced with each version.LicenseTootbot is licences under theGNU General Public License v3.0
Package: tooth.paste
Tooth.pasteTooth.paste creates shiny new Python packages. Start your new packages with a prepared
Sphinx documentation section, a test folder for your unit tests and a Makefile containing
all the tools needed to keep your Python code clean.Links:The full documentation is located at :http://toothpaste.readthedocs.org/en/latest/The repository and issue tracker are at GitHub :https://github.com/maikroeder/tooth.paste/issuesCreditsBased on ideas found in Circus -http://pypi.python.org/pypi/circusChangelog2.0 (2012-09-25)DocumentationAdd information on webhooksAdd the three types of modules as examples inside the package.Bug fixesfix travis.yml file name, which was set as travis.cifix Read the docs by adding missing indexsidebar.htmlInternalA lot of polishing to make the package squeaky cleanrefactor invisible varsrename the Paster templates to package, dotpackage and dotdotpackage
for clarityRemove long description from interactive fields, because this is a combination
of the README.txt and the CHANGES.txt files anyway1.2 (2012-09-22)improved documentation and unit testsadd dryrelease mkrelease1.1 (2012-09-12)fix pylint, add pep8 and pyflakes, add sloccount1.0 (2012-09-07)Package created using templer
[Maik Roder]
Package: toothpick-learn
Toothpick is a mini "library" which contains some implementation of machine learning algorithms in Python3.6. These algorithmare built on NumPy. **This "library" is just a toy**, the reason why I create it is to share my ideas and codes.All algorithms have `fit` and `predict` interface like `scikit-learn`. When I implemented these algorithms, I referencedsome books as follows: _Machine Learning_ writen by ZhiHua Zhou, _Statistical Learning Method_ writen by Hang Li and_Machine Learning in Action_ writen by Peter Harrington.By the way, I am a novice in python and machine learning field, so you can put forward issues if you find some bugs or questions.## Why named toothpick?A toothpick is a small stick of wood, plastic, bamboo, or other substance used to remove detritus from the teeth, usuallyafter a meal(from wikipedia). This library is similarly small and you can "take" it after meal :P.## How to guarantee the correctness?I compared my implementation with scikit-learn's when I was implementing these algorithms, which you can find in every single python fileand these performance were approximate on some very simple data set.## Algorithms implemented- Logistic Regression- Naive Bayes- K Nearest Neighbours- KMeans- Learning Vector Quantization- Ensemble Learning Algorithms- AdaBoost(only support binary classification)- Bagging- Stacking## Todo List- Decision Tree- SVM- Regression- Linear Regressiong- Ridge Regression- Lasso Regression- Neural NetworkPlatform: UNKNOWNClassifier: Development Status :: 3 - AlphaClassifier: Intended Audience :: DevelopersClassifier: License :: OSI Approved :: MIT LicenseClassifier: Programming Language :: Python :: 3Classifier: Programming Language :: Python :: 3.4Classifier: Programming Language :: Python :: 3.5Classifier: Programming Language :: Python :: 3.6Requires-Python: ~=3.6
Package: tootlogger
tootloggerJournal your toots to DayOneTake all your toots and make aDayOnejournal entry.This saves the last seen toot id so subsequent runs will only show all the toots since then.
If you miss a day of running this it, it will back fill up to the pagination limit.InstallEnsure you have at least Python 3.7 on your Machomebrewmakes this easy withbrew install pythonInstall theDayOne Command Line InterfaceInstall tootlogger withpython3 -m pip install tootloggerSetupYou will need to manually generate your access token and create a config fileLog into your mastodon instancego to/settings/applicationsand create the new appreadis the only checkbox neededNote down theaccess_tokenRepeat this for all accounts you want to logCreate a config file like the example below (or in this repo) in one of two places$HOME/.tootlogger.tomltootlogger.tomlin the local directory you run the command fromConfig file["account_name"]instance="https://mastodon.social"access_token="really big string"["cool account @ hachyderm.io"]instance="https://hachyderm.io"access_token="different big string"Usageruntootloggerto log all of your toots to DayOneSet uptootloggerto run daily or whenever you toot enough
Package: tootorch
tootorchImplemetation XAI in Computer Vision (Pytorch)Requirementstorch
opencv-python
pillow
h5py
tqdmInstallationpipinstalltootorchInterpretable MethodsAttribution MethodsVanilla Backpropagation (VBP) [Notebook]Input x Backpropagation (IB) [Notebook]DeconvNet [1] [Notebook]Guided Backpropagation (GB) [2] [Notebook]Integrated Gradients (IG) [3] [Notebook]Grad-CAM (GC) [4] [Notebook]Guided Grad-CAM (GB-GC) [4] [Notebook]Ensemble MethodsSmoothGrad (SG) [5]SmoothGrad-Squared (SG-SQ) [6]SmoothGrad-VAR (SG-VAR) [6]EvaluationCoherenceSelectivityRemove and Retrain (ROAR) [6]Keep and Retrain (KAR) [6]Attention MethodsResidual Attention Network (RAN) [7]Class Activation Methods (CAM) [8]Convolutional Block Attention Module (CBAM) [9]Wide Attention Residual Network (WARN) [10]Reference[1] Zeiler, M. D., & Fergus, R. (2014, September). Visualizing and understanding convolutional networks. In European conference on computer vision (pp. 818-833). Springer, Cham. [Paper] [Korean version][2] Springenberg, J. T., Dosovitskiy, A., Brox, T., & Riedmiller, M. (2014). Striving for simplicity: The all convolutional net. arXiv preprint arXiv:1412.6806. [Paper][3] Sundararajan, M., Taly, A., & Yan, Q. (2017, August). Axiomatic attribution for deep networks. In Proceedings of the 34th International Conference on Machine Learning-Volume 70 (pp. 3319-3328). JMLR. org. [Paper][4] Selvaraju, R. R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., & Batra, D. (2017). Grad-cam: Visual explanations from deep networks via gradient-based localization. In Proceedings of the IEEE International Conference on Computer Vision (pp. 618-626). [Paper] [Korean version][5] Smilkov, D., Thorat, N., Kim, B., Viégas, F., & Wattenberg, M. (2017). Smoothgrad: removing noise by adding noise. arXiv preprint arXiv:1706.03825. [Paper] [Korean version][6] Hooker, S., Erhan, D., Kindermans, P. J., & Kim, B. (2018). Evaluating feature importance estimates. arXiv preprint arXiv:1806.10758. [Paper] [Korean version][7]  Wang, F., Jiang, M., Qian, C., Yang, S., Li, C., Zhang, H., ... & Tang, X. (2017). Residual attention network for image classification. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 3156-3164). [Paper][8] Zhou, B., Khosla, A., Lapedriza, A., Oliva, A., & Torralba, A. (2016). Learning deep features for discriminative localization. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 2921-2929). [Paper][9]  Woo, S., Park, J., Lee, J. Y., & So Kweon, I. (2018). Cbam: Convolutional block attention module. In Proceedings of the European Conference on Computer Vision (ECCV) (pp. 3-19). [Paper][10] Rodríguez, P., Gonfaus, J. M., Cucurull, G., XavierRoca, F., & Gonzalez, J. (2018). Attend and rectify: a gated attention mechanism for fine-grained recovery. In Proceedings of the European Conference on Computer Vision (ECCV) (pp. 349-364). [Paper]
Package: tootroll
TootrollTootroll is a Python package to read timelines from the Mastodon network.PrerequisitesPythonPython 3.7 or higher is required to run this package.Mastodon account (optional)To read public timelines an account is not needed.A Mastodon account is required to read the Home timeline.
To setup a Mastodon account, visit:joinmastodon.org.To acquire a (private) API key ("access token"):go to "edit profile"click "<> Development"click "New application"
Application name can be anything. Leave the Redirect URI unchanged. Because we only want to read timelines, we recommend to only check "read" for Scopes. Write and follow is not needed.click "Submit" and open the link to the created ApplicationCopy the "access token" (Client key and secret are not needed)InstallThe package can be installed from PyPI:python -m pip install tootrollQuick setupConfigure public (default) profileWhen installed for the first time, API keys must be configured.
To allow easy switching between servers, public/ private APIs the package allows to define multiple named profiles.To setup the default profile, run the following command and follow instructions.
Pick a server from the list or set your own (hostname of Mastodon server).
For the default profile, we recommend to say (N)o when asked for private API key.python -m tootroll --configureTest if it works by getting timeline data for 1 toot.python -m tootroll --pub --limit 1Pipe through a JSON parserpython -m tootroll --pub --limit 5 |python -m json.toolConfigure private profilepython -m tootroll --configure --profile myProfileWhen asked to use private API, type (Y)es.
Copy the access token from your Mastodon account.All configuration files are stored under ~/.tootroll.python -m tootroll --home --profile myProfile --limit 5 |python -m json.toolUsagepython -m tootroll --helpusage: tootroll [-h] [--pub | --home | --tags TAGS | --configure | --show [profiles]] [--profile PROFILE] [-l LIMIT]

options:
  -h, --help            show this help message and exit
  --pub                 Show public timeline of server
  --home                Show home timeline
  --tags TAGS           Tag(s). Use comma-separated string to pass a list
  --configure           Create or update a profile
  --show [profiles]     Show configuration (e.g. list of profiles)
  --profile PROFILE     Select a profile to use. If left empty, lists configured profiles
  -l LIMIT, --limit LIMIT
                        Limit number of toots. Defaults to 10
Package: tootstagram
Tootstagramhttps://cvs.sonologic.net/gmc/tootstagramInstallationpip install tootstagramUsageCreate a configuration file nametootstragram.tomlbased on the
exampletootstragram.toml.exampleand place it in any of these
locations:In your home or user directoryIn a subdirectory.tootstagramunder your home or user directoryIn the current working directoryThe tool will search each of these locations in that order.Then simply invoke the tool with:tootstagramThis will fetch the feed from the Mastodon account and post any
images that were not already posted to the Instagram account.SecurityMake sure you keep the configuration file as well as the.tootstagramdirectory in your home or user dir private. The configuration file
contains your instagram username and password, and the.tootstagramdirectory contains a filesession.jsonwhich should be treated as
equivalent to your username and password.LimitationsOnly posts toots with images, not videos (I don't do videos myself)Any html tags in the toot are crudely removed by a simple regexpIf a toot has multiple images, but not all have alt text, none of the
instagram posts will have alt text (because it is impossible to derive
from the feed which alt text belongs to which image)Editing a toot will not alter on or repost to instagramOnly posts listed toots, as those are the only ones available from the
feedPlanned featuresHashtag translationReleasingpython -m build
python3 -m twine upload dist/*
Package: tooz
The Tooz project aims at centralizing the most common distributed primitives
like group membership protocol, lock service and leader election by providing
a coordination API helping developers to build distributed applications.Free software: Apache licenseDocumentation:https://docs.openstack.org/tooz/latest/Source:https://opendev.org/openstack/toozBugs:https://bugs.launchpad.net/python-tooz/Release notes:https://docs.openstack.org/releasenotes/toozJoin ushttps://launchpad.net/python-tooz
Package: top_100
Top 100 Visited Sites Web ScraperDescriptionThis Python script is a simple web scraper that fetches data from a Wikipedia's Top 100 Sites (https://en.wikipedia.org/wiki/List_of_most-visited_websites), specifically an HTML table, and converts it into a list of dictionaries. It also accesses each domain in the list and prints its response code.I created this script to automate testing of Firewall, Content Filtering and NAT related services. It can be used to test if a domain is accessible or not.
It can also be used to test if a domain is being redirected to another domain.Using this script helps me debug whether a rule (code) is working as expected or not. For example, if I have a rule that blocks access to a domain, I can use this script to test if the domain is indeed blocked or not. At the same time, I can get useful Syslogs for each run.DependenciesPython 3.6 or higherrequestslibraryBeautifulSoupfrombs4libraryurlparsefromurllib.parselibraryFunctionsis_valid_url(url: str) -> bool: Checks if the URL is valid.html_table_to_list(url: str, num_columns: int) -> list: Converts an HTML table into a list of dictionaries.access_domains(top_100: list) -> None: Accesses each domain in a list and prints its response code.UsageInstall the required dependencies.Run the script with Python 3.6 or higher.The script will fetch data from the specified URL, convert the HTML table into a list of dictionaries, and print the response code for each domain.Please note that the URL of the webpage containing the table and the number of columns in the table are parameters for thehtml_table_to_listfunction. The default number of columns is set to 5.Theaccess_domainsfunction takes in a list of dictionaries representing a table of domains and prints their response codes.Example# Use the functiontop_100_reference="https://en.wikipedia.org/wiki/List_of_most-visited_websites"# Replace with your URLtop_100_list=html_table_to_list(top_100_reference)access_domains(top_100_list)In this example, the script fetches data from a Wikipedia page that lists the most visited websites, converts the HTML table into a list of dictionaries, and prints the response code for each domain.DisclaimerPlease use this script responsibly and ensure that you are allowed to scrape the websites you choose to scrape. Some websites may prohibit scraping in their terms of service. Always respect others' intellectual property rights.