Saravanan666/pypi-org huggingface dataset:
Package: discocrash.py
discorash.pyThis module can be used to create crash bots.Installingpip install discocrash.pyExampleimportdisnakefromdiscocrashimportcrashfromdisnake.extimportcommands,tasksimportasynciointents=disnake.Intents.all()bot=commands.Bot(command_prefix="your token",intents=intents)bot.remove_command('help')token="your token"@bot.command()asyncdefcrush(ctx):awaitcrash.crash(ctx,"crashed server name","crash channel reason","crash role reason","crashed-channel-name","crashed-role-name",100,10)#the penultimate parameter is responsible for how many channels will be created. The last parameter is responsible for how many roles will be createdbot.run(token)
Package: discodo
DiscodoDiscodo is an enhanced audio player for discord.FeaturesStandalone Audio NodeYoutube Related Video AutoplayCrossfade and Audio effectsSynced Youtube Video SubtitleDocumentationMore information can be foundhere.InstallationDiscodo requires Python 3.7 or higherpython-mpipinstall--upgradediscodoOn Linux environments, more dependencies are required.ExecutionAudio Node ServerAdditional options can be seen with the --help flagpython-mdiscodoClient librariesdiscodo(Python)discodo.js(Node.JS)Supported sourcesAll sources that can be extracted fromyoutube_dlAll formats that can be demuxed bylibav
Package: discodoc
discodocAboutdiscodoc- createhard copy-like documents from Discourse content easily.It aims to make documentation generation effortless.There might still be dragons.Synopsis# Generate PDF document from all posts of given topic.
discodoc https://community.hiveeyes.org/t/anleitung-aufbau-und-installation-des-sensor-kits-grune-platine/2443 --format=pdfFor more information and further examples, please invokediscodoc--help.FeaturesAll output formats are provided by pandoc fame. These have been tested:
pdf, docx, odt, pptx, epub2, epub3, fb2, latex, texinfo, txt, text, html, html5, json, plain, rtf, revealjs, s5.InstallationPrerequisites# Debian
apt install texlive-latex-base pandoc

# macOS / Homebrew
brew install pandoc python3-requests
brew cask install basictexOptional:brew cask install wkhtmltopdfFor HTML slideshow rendering:yarn install


wget https://meyerweb.com/eric/tools/s5/v/1.1/s5-11.zip
cp -r ~/Downloads/s5-11/ui node_modules/s5Setuppip install discodocCaveatsIf you are hitting one of theglobal rate limits and throttling in Discourseindicated like:{"errors":["You’ve performed this action too many times, please try again later."]}You might want to authenticate using an appropriate API key like:export DISCOURSE_API_KEY=5c58bf5e4027622543f5179938182099c8b97188d00a9dc9f184cd3ca66db5eaCreditsDonald Knuthand theLaTeX Teamfor conceiving and maintaining TeX and LaTeX.John MacFarlaneand all contributors for creating and curatingpandoc.The amazingDiscourse Teamand all contributors for creating Discourse and its spirit.You know how you are. Thanks!Other programshttps://github.com/pfaffman/discourse-downloader- via:https://meta.discourse.org/t/struggling-with-pagination-within-search-query-json/59558/3
Package: discoecs
AWS ECS autodiscovery for PrometheusInstallation:$ pip install discoecsUsage examples - commandline:Scan ECS tasks every 70 seconds, outputting Prometheus config toecs-targets.jsonwith 8080 as default Prometheus metrics port.$ discoecs -v -f ecs-targets.json -p 8080 -i 70Important note: provide AWS credentials and default region in any of the boto3 library standard locations, such as ~/.aws/credentials or using environment variablesAWS_ACCESS_KEY_IDandAWS_SECRET_ACCESS_KEY,AWS_DEFAULT_REGION.Programmatic use>>> import boto3
    >>> import discoecs.get_cluster_tasks
    >>> ecs_client = boto3.client('ecs')
    >>> ecs_tasks = get_cluster_tasks(ecs_client)
Package: disco-generation
The 🕺🏽discotoolkit allows to control the properties of the generations by language models and other generative systems to match human preferences while avoiding catastrophic forgetting.To achieve this indisco, we first represent in what ways we want to update original model as a target distribution and then, generate samples from this new distribution through a combination of learning or monte-carlo methods, as follows.Step 1: We express how the target distributionshouldbeTo have a handle on the generative model, we define some feature over the generated samples. It can be anything we can compute. For example, on a language model it can be as simple as whether the generated text contains a certain word or as complex as the compilability of some generated piece of code. Importantly, there is no need for the feature to be differentiable.Then, we can express our preferences on the target distribution by defining the targetmomentsof this feature. For example, we might want to ask that a certain word appears 50% of the time when sampling from the model; or that 100% of the generated code is compilable. The resulting target distribution is expressed as an energy-based model or EBM, which is an unnormalized probability distribution that respects the desired moments while avoiding catastrophic forgetting, as a result of having minimal KL divergence to the original model.This representation of the target distribution canscoresamples, but cannot directly be used togeneratethem.Step 2: We generate samples from the target distributionTo generate samples from the target distribution, if not perfectly, we can tune a model to approximate it. The resulting model can generate samples directly from a close approximation of the target distribution. Furthermore, it can be used jointly with Quasi-Rejection Sampling (QRS), a Monte Carlo sampling technique that allows the generation of samples that are even more representative of the target distribution.Alternatively, it is then possible to use decoding methods such as nucleus sampling, top-k sampling, or beam search, which would return samples from a further updated target distribution.
Package: discoger
DiscogerDiscoger Bot is a Telegram bot that allows you to be notified when a new sale for a vinyl in your Discogs wantlist is available.UsageSearch for the Telegram bot "Discoger" or clickthis linkto open a conversation with the bot.How to use itInstallationInstallation is in three steps, the first is getting credentials from Discogs and Telegram.
You need to create aToken.For Telegram you need contact@BotFatherand follow a few simple steps for get your authorization token.ConfigurationAfter that you need create config.ini file[DEFAULT]
schedule_time = 30
disable_unofficial = True
log_level = INFO

[discogs]
secret = dbPVkGbCVVffggfgkdfgmlkknzezsbhmscskncno

[telegram]
token = 1766763279:AAFwufBsdfdsfgdfsgfgsfsgdfgsdfDockerdocker container run -v ./:/root/.config/discoger beudbeud/discogerUpgradeIf you use the old version of discoger you need to update your database.Example of database for the version 1.1chat_id: 249125421
release_list:
- release_id: '288931'
  artist: Aloud
  title: Track Lifting
  url: https://www.discogs.com/fr/master/288931-Julian-Jay-Savarin-Waiters-On-The-Dance
  type: master
  last_sell: {}
- release_id: '26741825'
  artist: Metallica
  title: 72 Seasons
  url: https://www.discogs.com/fr/release/26741825-Metallica-72-Seasons
  type: release
  last_sell: {}
Package: discogrify
discogrifydiscogrifyis a command line tool to create artist discographies as Spotify playlists.InstallationThe easiest way to installdiscogrifyis withpipx(seeherefor installation of pipx itself):pipx install discogrifyUsageFirst, authenticate with Spotify:d8y loginThis will open a browser where you would be asked to login with your Spotify account and givediscogrifyaccess to it.When done, create your playlist by providing a Spotify artist URL tod8y create. For example the following command
will create a playlist with all albums and singles of Joy Division:d8y create https://open.spotify.com/artist/432R46LaYsJZV2Gmc4jUV5For more details on usage:d8y create --help
Package: discogs-cli
imagediscogs-clidiscogs-cli bring the Discogs.com database to your terminal. Perform the
following actions from your terminalSearch artists, releases, labelsView artist information and their releasesView label details and its associated releasesView a release in detailAccess to search functionalityDiscogs requiresauthenticationwhen accessing the search APIs. If
you wish to use the search functionality, you’re required to generate a
personal access token for your discogs.com account. You can do so athttps://www.discogs.com/settings/developersby clicking generate new
token.Before starting your application set theTOKENshell variable. wheresys64738is your unique access token.$ export TOKEN=sys64738InstallationTo install from PyPi, please usepiporeasy_install. For
example$ pip install discogs-clior$ easy_install discogs-cliNote that installing into avirtualenvis generally recommended. If
you wish to install the latest and greatest via github source, please
ensure you’ve created a virtual environment.$ virtualenv ~/.virtualenv/discogs-cli
$ source ~/.virtualenv/discogs-cli/bin/activateFetch and install the package from github$ pip install git+https://github.com/jesseward/discogs-cli.gitOnce installed, rundiscogs-clito launch the interactive command
prompt.$ discogs-cliTo launch commands from the console$ ogs <command> [params] [options]TODOCurrently runs on a Unix like operating system only (Linux/OSX). If
you can test and patch use for windows, please log a pull request.Aboutdiscogs-cli builds upon the following awesome Python libraries * The
python-prompt-toolkithttps://github.com/jonathanslenders/python-prompt-toolkit* Discogs.com
api clienthttps://github.com/discogs/discogs_client* Haxor-news
string completion libraryhttps://github.com/donnemartin/haxor-news
Package: discogs-cli-savoy1211
imagediscogs-clidiscogs-cli bring the Discogs.com database to your terminal. Perform the
following actions from your terminalSearch artists, releases, labelsView artist information and their releasesView label details and its associated releasesView a release in detailAccess to search functionalityDiscogs requiresauthenticationwhen accessing the search APIs. If
you wish to use the search functionality, you’re required to generate a
personal access token for your discogs.com account. You can do so athttps://www.discogs.com/settings/developersby clicking generate new
token.Before starting your application set theTOKENshell variable. wheresys64738is your unique access token.$ export TOKEN=sys64738InstallationTo install from PyPi, please usepiporeasy_install. For
example$ pip install discogs-clior$ easy_install discogs-cliNote that installing into avirtualenvis generally recommended. If
you wish to install the latest and greatest via github source, please
ensure you’ve created a virtual environment.$ virtualenv ~/.virtualenv/discogs-cli
$ source ~/.virtualenv/discogs-cli/bin/activateFetch and install the package from github$ pip install git+https://github.com/jesseward/discogs-cli.gitOnce installed, rundiscogs-clito launch the interactive command
prompt.$ discogs-cliTo launch commands from the console$ ogs <command> [params] [options]TODOCurrently runs on a Unix like operating system only (Linux/OSX). If
you can test and patch use for windows, please log a pull request.Aboutdiscogs-cli builds upon the following awesome Python libraries * The
python-prompt-toolkithttps://github.com/jonathanslenders/python-prompt-toolkit* Discogs.com
api clienthttps://github.com/discogs/discogs_client* Haxor-news
string completion libraryhttps://github.com/donnemartin/haxor-news
Package: discogs_finder
FINDEveryRelease in your collectionThis is a small commandline tool that fetches your discogs collection
and performs a deep key value search.$ discogs-finder --u tim6her name=Chick
Searching for {'name': 'Chick'}
1)  Herbie Hancock & Chick Corea: An Evening With Herbie Hancock & Chick Corea In Concert 1978 (530041)
    basic_information.artists.1.name = Chick Corea
2)  Chick Corea & Friedrich Gulda: The Meeting (2210545)
    basic_information.artists.0.name = Chick Corea
3)  Wolfgang Amadeus Mozart, Chick Corea, Friedrich Gulda, Concertgebouworkest, Nikolaus Harnoncourt: Double Concerto / Compositions (4764105)
    basic_information.artists.1.name = Chick CoreaIt can also return the whole json entry for the matched releases using
the--voption.$ discogs-finder --u tim6her --v name=Pob
Searching for {'name': 'Pob'}
{
  "instance_id": 207732124,
  "date_added": "2017-01-14T05:32:34-08:00",
  "basic_information": {
    "formats": [
      {
        "qty": "1",
        "descriptions": [
          "LP",
          "Album", ...For help on usage rundiscogs-finder--helpor consult theDocs.
Package: discogslearner
DiscogsLearner - ML library for DiscogsIntroductionThis package enables predicting similar releases using your Discogs Wantlist and/or Collection. To accomplish this, a 2-step process is executed: Data retrieval using the monthly data dumps and data learning using a list of identifiers obtained from your Wantlist and/or Collection. It produces release identifiers together with probabilities of similarity to your input. SeeDetailsfor an in-depth explanation. This package requires about 3GB of free RAM to process the whole 'Electronic' genre.Installationpip install discogslearnerUsageObtain a Discogs personal access token. Seehttps://www.discogs.com/settings/developerson how to obtain one.Execute a script like the following:importdiscogslearnerif__name__=="__main__":output_file="Data/discogs_db.tsv"my_genre="Electronic"my_token="your_token_here"extracter=discogslearner.Extracter(genre=my_genre)extracter.extract(output=output_file)learner=discogslearner.Learner(db_path=output_file,use_wantlist=True,use_collection=True,token=my_token)outcome=learner.learn_and_predict(n_models=10)print(outcome)DetailsIn order to learn from Discogs data, the fields Format, Year, Country, Style(s) and Number of Tracks are considered factors of a Release. Fields with categorical values (Format, Country & Styles) are formatted using One-Hot encoding, using only Releases from the given Wantlist and/or Collection.  Next, a PCA transformation is applied on these Releases, before applying the transformation on all extracted Releases from Discogs. Note that during this process, only the Styles within the Wantlist and/or Collection are kept in the database as Releases with other styles are most likely not interesting.Artists, Labels, and Companies are considered to be groups of Releases, so to incorporate these, the mean and variance of the grouped PCA data is taken and attached to the original PCA data. In the current version, collaborating groups (e.g. two Artists together) are seen as a single entity, but this will be updated in future versions.The Wantlist and/or Collection are seen as positive predictors, but negative predictors are usually not saved. Therefore, a random set of Releases of equal size as the positive predictors is taken as negative predictors. This introduces bias and thus, this package combines 10 models with 10 different negative predictors and multiplies the probabilities to obtain a single score for each Release. Note that Releases part of the Wantlist and/or Collection are not returned in the predictions.
Package: discogspy
DiscogspyDiscogspy is a  type-safe and easy to use python wrapper around the Discogs API.General informationWhat's the use case for discogspy?I have a small label/distro, and I sell my items via Discogs and my own website. To keep both stores in sync is tidies. That's why I want to automate this process. Therefore I need to be able to get information from my Discogs store. That can be done via the official Discogs python client. However, I also need to be able to update orders, add and remove items etc. and this doesn't seem to work via the Discogs python client. That's why I decided to wrap the Discogs API myself.Important information:Requests to the Discogs API are throttled by the server by source IP to 60 per minute for authenticated requests, and 25 per minute for unauthenticated requests, with some exceptions.Installpip install discogspyRoad MapCreate type save python wrapper around the Discogs APIa) Wrap database calls (done - except search request cause I personally dont have any use case for it)b) Wrap marketplace calls (done)c) Wrap inventory export calls (done)d) Wrap inventory upload calls (done)e) Wrap user identity calls (maybe later - I personally dont have any use case for it)f) Wrap user collection calls (done)g) Wrap user wantlist calls (done)h) Wrap user lists callsCreate response wrapperHow to useFor a detailed explanation and more examples, please visit thedocumentation.Currently, you have two options for starting requests to Discogs.Create a user object without authentication. This will limit your options cause a lot of API calls do require authentication.fromdiscogspy.core.discogs_userimportUserWithoutAuthenticationfromdiscogspy.coreimportrq_databaseuser=UserWithoutAuthentication()resp=rq_database.get_release(user,1972502)Create a user object with user token authentication. This will allow you to send any request.fromdiscogspy.core.discogs_userimportUserWithUserTokenBasedAuthenticationfromdiscogspy.coreimportrq_databaseuser_with_authentication=UserWithUserTokenBasedAuthentication(user_token="your_user_token",user_agent="your_user_agent")resp=rq_database.get_release(user,1972502)
Package: discogs-track
discogs trackA tool for completists and other pop music collectors.
It is inspired by R.I.P the discogs.comTracks Beta project.InstallationThis tool is not yet in pypi.org.$pip-vinstallhttps://github.com/decitre/discogs_track.gitTo install the dev/test tools and contribute to the project, do in your virtualenv:$pipinstall-e".[dev]"To start Redis service on Macos:$brewservicesstartredisShell completionon zsh:_DISCOGS_TRACK_COMPLETE=zsh_sourcediscogs_track>~/.discogs_track-complete.zshecho". ~/.discogs_track-complete.zsh">>~/.zshrcUsagediscogs_track --help
Usage: discogs_track [OPTIONS] COMMAND [ARGS]...

Options:
    --version             Show the version and exit.
    -v, --verbose         [x>=0]
    --cache / --no-cache
    --help                Show this message and exit.

Commands:
    artistExamples:$discogs_trackartist-i3281311show-tracks
$discogs_trackartist-i3281311show-completing
$discogs_track--no-cacheartist-i3281311show-completing--for-sale
$discogs_trackartist-i3281311release-i20846845showThe tool expects in~/.dt.cfga INI config file containing a Discogs user credentials:[Discogs]user_name=...consumer_key=...consumer_secret=...access_token_here=...access_secret_here=...SDKSome classes can be used as a SDK giving access to a subset of Discogs API features.classcommentapi.APIA very light asynchronous wrapper around theDiscogs API.Uses a local redis instance ifcached=Trueis passed to its constructor.artist.ArtistHosts the Json returned by/artists/{artist_id}.and a few derived attributes.record.Recordrecord.TrackAn abstraction of releasestracklistarray elementsmissing tracks ratioIt calculates for a specified artist, a per recordmissing_tracks_ratio:
The number of tracks none of the records of the user's collection contain, over the number of tracks in the record.
A record with a 0% score is either already in the collection as one of its various releases, or all its tracks are contained by a set of other records in the collection.
A record with a 100% score only contains tracks not present in any other record of the user's collection.
Package: discogs-wrapper-python
Discogs Python API WraperThis is a python API wrapper for the discogs API. It includes methods for API endpoints in the Database section in discogs.Installationpipinstalldiscogs-wrapper-pythonQuickstartfromdiscogs_wrapperimportDVdv_instance=DV("FooBarApp/3.0")response=dv_instance.get_search(genre='rock',q='nirvana',token='abcde123')AuthenticationThere are two primary methods of authentication: Discogs Auth Flow and Auth Flow. As of now, only Discogs Auth Flow is supported by this wrapper. This is a simple yet secure way of authenticating a user. A user can be authenticated either by using aUser tokenor using aConsumer keyandsecret.
Package: discoin
Discoin for PythonThis is the official discoin library for python. Here is discoin'sGitbookRequirementsPython 3.6 or upaiohttpInstallation$pipinstalldiscoinDocumentation can be foundhereCreditsDr_Ari_Gami(Main Developer)DeveloperAnonymous(Collaborator)Theelgirl(Collaborator)PizzaFox(Main developer of discoin)Austin Huang(Owner of discoin)
Package: discoIPC
Connect to the local Discord IPC Socket, for features likeRich
Presence.InstallationThis is aPythonmodule available through thePyPI.Before installing,download and install Python. We recommend
installing version 3.5+ of Python.Installation is done using thepip installcommand:$pipinstalldiscoIPCFor more info, seepip installdocs.Get StartedRead theWikito see the available classes and methods and
know how to use them.LinksDiscord Rich Presence WebsiteDiscord Developer DocumentationOfficial Discord RPC BindingsContributorsThe developer of thediscoIPCpackage isk3rn31p4nicList of all contributorsLicenseGPL-3.0If you liked this project you can⭐ Starit onGitHubto show
your love.
Package: discolinks
discolinksDiscolinks looks for broken links on a website.Features:Starts on one page and recursively finds the other reachable pages on the website.Asynchronous: Maximum number of parallel requests is configurable.JSON output available: Useful for testing and scripting.Getting Started$discolinks--urlhttps://example.net
📂Results:13links(10ok,3failed)├──📄https://example.net/foo
│├──🔗/bad_absolute_href:302→404│└──🔗bad_relative_href:404└──📄https://example.net/bar└──🔗https://example.org/bad_external_href:ConnectionerrorDevelopment...# Activate virtualenv.poetryinstall
makecheckReleaseCreate a branch with a name likerelease-1.2.3.Update version insrc/discolinks/__version__.py.Update version inpyproject.toml.Update changelog.Open a pull request and get it merged.Tag the releasegit tag --message 'Version 1.2.3' 1.2.3Push tags:git push --tags
Package: discombed
DiscombedDiscombed is a very bad wrapper for discord embeds
It is made in python and can support python 3.6 and above (hopefully)Quickstartimportdiscombedwebhook=discombed.Hook(url="https://discord.com/api/webhooks/id/token",content="Hello, World!")webhook.send()Functions and Classesdiscombed.Hook(url, content=None, username=None, avatar_url=None, tts=False)URL : str for discord webhook
Username : str defaults to the one specified in webhook creation
avatar_url : str defaults to the one specified in webhook creation
tts : bool defaults to false..add_embed(Embed)Takes an embed object to add to the webhook (Max 10).send(silent=True)Sends the webhook to discordif silent is false it will return status codedicombed.Embed(title=None, colour=None, url=None, description=None, timestamp=None)title = title for embed
colour = decimal value of colour (use dischook.hex_to_decimal for converting hex to decimal)
description = description for embed
url = redirection url
timestamp = timestamp, must be in datetime.datetime formatset.author(name, icon_url, url)Sets author for embedname = author nameicon_url = icon urlurl =  redirect urlset_image(url)sets embed imageurl = url for imageset_thumbnail(url)sets embed thumbnailurl = url for thumbnailset_footer(text, icon_url)sets embed footertext = text for footericon_url = icon for footeradd_field(name, value, inline=False)adds field for webhook, supports markdownname = name of fieldvalue = value of fieldinline=False, set to true if you want inlinedicombed.hex_to_decimal(hex)param = hexreturns decimal value of hex (useful for embed colours)