Saravanan666/pypi-org huggingface dataset:
Package: human-time
HumanTimeConvert numerical times to their human readable English language equivalent.Examples:15:00becomes"Three o'clock"15:15becomes"Quarter past three"15:27becomes"Twenty seven minutes past three"Distributed on PyPI -https://pypi.org/project/human-time/System requirementsPython >= 3.6 is required. The instructions below are focused on creating a Python 3 virtual environment in order to
ringfence the dependencies.Running the applicationThe package can be installed from source:cdhuman-time
python3-mvenvvenvsourcevenv/bin/activate

python-mpipinstall-rrequirements.txt

python-mpipinstall-e.--upgradeAlternatively the package can be pulled from PyPi:python3-mpipinstallhuman-timeThe installed application can then be invoked in two says, either as command line tool, which simply performs a single
time conversion, or as a server, which provides a REST API with single endpointapi/humantimeto convert the time.humantime-serverstarts by default on port 5000, this can be changed by setting theHUMANTIME_PORTenvironment variable.humantime-t15:00
humantime-serverBoth methods either return the human time corresponding to the current time, or if thenumeric_timeparameter is
provided, the human time for the given numeric time.If usinghumantime-server, an OpenAPI user interface is available to test it's endpoint, which can be found atTestingBefore testing ensure that the Python virtual environment is set up, and both unit test and application dependencies
are installed by runningpython3 -m pip install -r requirements.txt -r test/requirements.txtTo run the tests runpython3 -m pytest --cov=src --pyargs testBuild and PublishThe package is built, and deployed to PyPi viatwine, as shown below.python3-mpipinstallsetuptoolstwine
python3-msetupsdist
twineuploaddist/*
Package: human_time_formatter
Human-readable time delta formatter with relative precision ("ndigits")Gives human-readable output for basic timing benchmarksReturns a string formatted in: "Y years, W weeks, D days, HH:MM:SSs"(or ms, us, ns, ps, fs for very small times)Automatically reduces fields which are larger than the time passed orsmaller than the requested precision.Examples with ndigits=4:format_seconds(0.00096685) -> "966.9us"format_seconds(0.00387514) -> "3.875ms"format_seconds(0.01553157) -> "15.53ms"format_seconds(0.06225062) -> "62.25ms"format_seconds(0.24950074) -> "0.2495s"format_seconds(1.0       ) -> "1s"format_seconds(4.008004  ) -> "4.008s"format_seconds(16.0640960) -> "16.06s"format_seconds(64.3849612) -> "1:04.4s"format_seconds(258.055182) -> "4:18.1s"format_seconds(1034.28620) -> "17:14s"format_seconds(4145.42323) -> "1:09:05s"format_seconds(16614.8729) -> "4:36:55s"format_seconds(66592.4771) -> "18:29m"format_seconds(266902.914) -> "3 days, 02:08m"format_seconds(1069747.94) -> "1 week, 5 days, 9h"format_seconds(4287554.06) -> "7 weeks, 0 days, 14h"format_seconds(17184533.8) -> "28 weeks, 2 days"format_seconds(68875680.3) -> "2 years, 9 weeks, 4 days"format_seconds(276054002.) -> "8 years, 39 weeks, 2 days"
Package: huma-signals
Decentralized Signal PortfolioThe Decentralized Signal Portfolio (DSP) is an open source package that enables access to high-quality signals about a borrower's income, assets, and liabilities. These signals are collected through Signal Adapters, which gather data from a variety of on-chain and off-chain sources. Any developer can contribute to the platform by adding a new Signal Adapter for a specific data source.Overview📜Huma Whitepaper🏠HomepageDocumentationFor additional guides, examples, and APIs, see thedocumentation.Want to help?Give a ⭐️ if this project helped you!Want to file a bug, contribute some code, or improve the documentation? Excellent! Read up on our guidelines forcontributing.📝 LicenseThis project isAGPL v3licensed.
Package: humble
Features:Lists a user’s repos.InstallationTo install humble, simply:$ pip install humbleOr, if you absolutely must:$ easy_install humbleBut, you really shouldn’t do that.License:ISC License.Copyright (c) 2011, Kenneth Reitz <me@kennethreitz.com>

Permission to use, copy, modify, and/or distribute this software for any
purpose with or without fee is hereby granted, provided that the above
copyright notice and this permission notice appear in all copies.

THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES
WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR
ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF
OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.ContributeIf you’d like to contribute, simply forkthe repository, commit your changes
to thedevelopbranch (or branch off of it), and send a pull request.
Package: humblebee
# Humblebee  (version 1.10) #Humblebee is a scraper and renamer/organizer for TV shows.
It is made with the intention to automatically organize the most disorganized collections without any manual user input.Keep in mind, this program is in development stages and there will be (potentially dangerous) bugs.## Features ##
* Parse tv show filenames and gather metadata from thetvdb
* Create a portable, local database of metadata
* Rename and organize tv shows based on metadata
* Create a virtual TV directory structures using symlinks
* Extract rar-ed scene release episodes
* Locate duplicate episodes and determine which one has better video quality## Install ##
I will assume a debian-based environment (e.g. ubuntu, mint, etc) for this guide. Adapt following commands to your distro’s package management system.Easiest way to install is by using pip.
If you don’t have pip, install it with:sudo apt-get install python-pipHumblebee also requires a couple of extra packages for all features to work, lets grab them:sudo apt-get install mediainfo unrarNow we install can humblebee using:sudo pip install humblebeeThat’s it. Now lets see how we use this thing.## Usage ##
Humblebee comes with a command line interface with various options. To see a description the available options, use:humblebee –helpNow one common use case would be to scrape your disorganized TV directory and make a structured presentation of it with symlinks. This can be achieved with:humblebee -s /home/user/TV /home/user/cleanTV/home/user/TVbeing your original TV directory and/home/user/cleanTVwhere the symlinks are made.
The default naming scheme for renamed directory isSeries Name/season 01/Series Name s01e02 Episode Name.mkv. Currently it’s the only naming scheme available, but more will come in future releases.You can substitute-sfor-rif you’d like humblebee to move your files to/home/user/cleanTVinstead of making symlinks. If you do this, a second database is made in/home/user/cleanTVScraping can take a while depending on the size of your collection, so grab a soda.## How can I help? ##
Easiest way to help is to simply use the program and report any bugs and issues you encounter herehttps://github.com/steinitzu/humblebee/issuesYou may also submit code patches and documentation to the official repohttps://github.com/steinitzu/humblebeeIf you improve something, it will most likely be accepted.…to be continued### TODO ###
* Documentation
* support Windows
* Test cases
* Take over world
Package: humblebundle
humblebundle-python is an unofficial library for querying the undocumented Humble Bundle API.UsageBasic usage looks something like:client = humblebundle.HumbleApi()

client.search_store("ftl")

client.login("username@example.com", "secret")

gamekeys = client.get_gamekeys()

for gamekey in gamekeys:
    order = client.get_order(gamekey)
    for subproduct in order.subproducts:
        print(subproduct)See examples.py for more exampleshumblebundle-python is not affiliated in any way with Humble Bundle, Inc.
Package: humblebundle-downloader
Humble Bundle DownloaderDownload all of your content from your Humble Bundle Library!The first time this runs it may take a while because it will download everything. After that it will only download the content that has been updated or is missing.Featuressupport for Humble Trove(--troveflag)downloads new and updated content from your Humble Bundle Library on each run(only check for updates if using--update)cli command for easy use (downloading will also work on a headless system)works for SSO and 2FA accountsoptional progress bar for each item downloaded(--progressflag)optional filter by file types using an includeorexclude list(--include/--excludeflag)optional filter by platform types like video, ebook, etc...(--platformflag)Installpip install humblebundle-downloaderInstructions1. Getting cookiesFirst thing to do is get your account cookies. This can be done by getting a browser extension that lets you see or export your cookies.Method 1 (recommended)Get the value of the cookie called_simpleauth_sessand pass that value using-s "COOKIE_VALUE"Method 2Export the cookies in the Netscape format using an extension.If your exported cookie file is not working, it may be a formatting issue, this can be fixed by running the commandcurl -b cookies.orig.txt --cookie-jar cookies.txt http://bogus2. Downloading your libraryUse the following command to download your Humble Bundle Library:hbd --cookie-file cookies.txt --library-path "Downloaded Library" --progressThis directory structure will be used:Downloaded Library/Purchase Name/Item Name/downloaded_file.extNotesInside your library folder a file named.cache.jsonis saved and keeps track of the files that have been downloaded. This way running the download command again pointing to the same directory will only download new or updated files.Use--helpwith allhbdcommands to see available optionsFind supported platforms for the--platformflag by visiting your Humble Bundle Library and look under thePlatformdropdownDownload select bundles by using the-kor--keysflag. Find these keys by going to yourPurchasessection, click on a products and there should be adownloads?key=XXXXin the url.
Package: humble-explorer
HumBLE ExplorerHuman-friendly Bluetooth Low Energy ExplorerThis is a cross-platform (Windows, Linux, macOS) human-friendly program to scan for Bluetooth Low Energy (BLE) advertisements on the command line. It’s mostly useful for people who develop BLE software or want to debug problems with BLE devices.InstallationYou can install HumBLE Explorer as a pip package from PyPI:pip install humble-explorerUsageHumBLE Explorer understands some command-line arguments, which you can see with the--helpoption:humble-explorer --helpDocumentationRead HumBLE Explorer’sonline documentation.Learn more about Bluetooth Low Energy developmentIf you want to learn more about Bluetooth Low Energy development, read the bookDevelop your own Bluetooth Low Energy Applications for Raspberry Pi, ESP32 and nRF52 with Python, Arduino and Zephyrand the accompanying GitHub repositorykoenvervloesem/bluetooth-low-energy-applications.LicenseThis project is provided by Koen Vervloesem as open source software with the MIT license. See the LICENSE file for more information.
Package: humble-get
# CLI for getting your Humble Bundle Books
- It’s a script that I wrote to get books from Humble Bundle automatically
- Makes a folder then  grabs all of the formats for each book and puts it in it
- It’s using humble bundle apihttps://www.humblebundle.com/api/v1/order/key?wallet_data=true## How to use it?
In order to use this script, you would need to have a humble bundle key.You can get it by checking the URL right after buying your bundle.
![](./resources/img.png)`bashhttps://www.humblebundle.com/downloads?key=YOUR_KEY`` $ python humbleGet.py your_key `
Package: humbletray
Table of ContentsInstallationLicenseInstallationhumbletray is distributed onPyPIas a universal
wheel and is a WIP.These are helper methods to install justpy as a systray app as a python-all-the-way alternative to Electron.Also a basic Quasar wrapping layout and the ability to launch as a chrome app if installed.$pipinstallhumbletrayLicensehumbletray is distributed under the terms of bothMIT LicenseApache License, Version 2.0at your option.
Package: humdrum
This a CLI tool for youtube data v3 APIInstallationInstall with pip:pip install humdrumOr from git:git clone https://github.com/princekrroshan01/humdrum/
cd humdrum
virtualenv venv
source venv/bin/activate
pip install -r requirements.txtPrerequisitesGet the youtube data v3 api key from
(https://console.developers.google.com/apis/) and set a environment
variable with the name API_KEY Reference for setting environment
variable in linux
(https://www.redhat.com/sysadmin/linux-environment-variables) and for
windows
(https://docs.oracle.com/en/database/oracle/r-enterprise/1.5.1/oread/creating-and-modifying-environment-variables-on-windows.html#GUID-DD6F9982-60D5-48F6-8270-A27EC53807D0)Make a python alias by typingalias humdrum="python3 (location of file cli.py)" in terminal

No need to create alias if you download this package using pipusingTypehumdrum--helpin terminal This will guide you through the
processhumdrum --help
Usage: humdrum [OPTIONS]

Options:
   --count INTEGER  enter the number of video you are looking for.
   --title TEXT     enter the title name of video you are looking for
   --order TEXT     to sort the video by date rating viewCount
   --type TEXT      to search for type of video like channel video playlist
   --help           Show this message and exit.ContributingPull requests are welcome. For major changes, please open an issue first
to discuss what you would like to change.
Package: hume
Hume AI Python SDKIntegrate Hume APIs directly into your Python applicationTo get started, create an account atbeta.hume.ai.NoteOur current version is not yet considered a stable release. As we are still in the development phase, we have chosen to continue releasing under the 0 major release until we are ready to launch version 1.0.0. Our APIs might undergo breaking changes that are necessary for us to improve our tooling and ensure a more stable and reliable release in the future. We encourage you to keep up with ourAPI changelogand mailing list to stay up to date with the latest changes.Documentation & ExamplesFor complete documentation check out thePython SDK docs siteortry some recipesfrom our platform documentation.Example notebooks can be found in theexamples folder.Other ResourcesHume AI HomepagePlatform DocumentationCitationsHume's expressive communication platform has been built on top of published scientific research. If you use this SDK in your work please seeCITATIONS.mdfor the best way to reference that research.SupportIf you have questions, require assistance, or wish to engage in discussions pertaining to this SDK,reach out to us on Discord! For particular issues or feedback, we invite you toopen a new issue on Github.
Package: humed
TL;DR: Add hume commands inside your scripts to better report to a central
location.  Currently supporting Slack, syslog, remote-syslog, logstash, etcImagine this: You have some cron scripts.  They need to run correctly, and
you need to know if anything happens.  You usually check logs via email or
some cool dashboard.  Yeah.  But it gets boring, repetitive and you end up
not checking the logs.  It is a well known sysadmin syndrome.Hume client works and can be used in bash scripts, or during a screen
session, to provide real time updates to your managers, customers, etc.So, for instance write those scripts adding hume commands in them:
Package: humfrey
humfrey is a Django-based RESTful linked data interface to a SPARQL endpoint.FeaturesSerialization to HTML, RDF, JSON, CSV.Template selection based on rdf:types.Semantic pingbackSPARQL rate-limitingUsinghumfrey provides a lot of the framework you need for producing a linked data
site. You will need to produce a minimal Django project to pull it all
together. Examples includedata.ox.ac.uk,data.clarosnet.org, andopencitations.net. In
due course we plan to provide a simple demonstration site that will run out of
the box.It requires a backing SPARQL endpoint to run queries against. The sites listed
above useFuseki, but it should work with
any endpoint. If it doesn’t, raise an issue inthe GitHub issue tracker.You will also need runningmemcachedandredisinstances.Running the test suiteIn the root of the humfrey module run:PYTHONPATH=.. python manage.py test --settings=humfrey.tests.settingsIf using Jenkins, you can use tox or run the following:PYTHONPATH=.. python manage.py jenkins --settings=humfrey.tests.settingsThis will produce a bunch of reports using django_jenkins, which will turn up in areportsdirectory.Requirementsmemcachedredis
Package: humhelpers
Provides different shortcuts functions (helpers) for humanity.Created to be something like Ramda or Lodash for Python, but withoutfunctional style.For strings:`reverse` - Reverse a string.`replace` -Replaces one substring in string to another.Analog to string method with same name,but also adds ability to change direction, from which to replace substring.For collections:`get` - Returns or element from collection by index (key), or None if not found.For asyncio:`run_async` - Asynchronously runs coroutine (function, defind with 'async def') until it completes.
Package: humidifier
humidifierCreate human-friendly IDs from strings.The typical use case forhumidifieris that you have some string (a word, a name, a phrase...) that you want to turn into a human-friendly ID.
For example, your project has URLs containing IDs, and it would be nicer to have/record/an-exampleinstead of/record/21937218.
Such IDs are easy to remember and can function as a preview for the database entry.
This can be achieved with the excellentpython-slugify, to which humidifier adds the option to generate unique IDsUsageUsinghumidifieris rather simple:fromhumidifierimporthumidifyid_1=humidify("dog",unique=True)# 'dog'id_2=humidify("dog",unique=True)# 'dog-1'id_3=humidify("dög",unique=True)# 'dog-2'id_4=humidify("ʔɚ",unique=True)# 'null'id_5=humidify("ʔɚ",unique=True)# 'null-1'If your strings come from different populations that you would like to keep distinct in the generated IDs, there is an optionalkeyargument:fromhumidifierimporthumidifyid_1=humidify("dog",key="animals",unique=True)# 'dog'id_2=humidify("dog",key="quadripeds",unique=True)# 'dog'id_3=humidify("dög",key="animals",unique=True)# 'dog-1'id_4=humidify("dög",key="animals",unique=True)# 'dog-2'If you are working with an existing set of IDs:fromhumidifierimportHumidifierhum=Humidifier(["dog"])hum.humidify("dog",unique=True)# 'dog-1'If you only want to generate a new ID for each distinct string:fromhumidifierimporthumidifyhumidify("dög")# 'dog'humidify("dög")# 'dog'humidify("dog")# 'dog-1'You can also use any of the arguments described forpython-slugify.
The argumentsmax_lengthfor truncating,separatorfor something other than-in between parts, andreplacementsmay be of particular interest when generating IDs.
Package: humilis-asg
Ahumilisplug-in layer that deploys an Autoscaling Group.Installationpip install humilis-asgTo install the development version:pip install git+https://github.com/humilis/humilis-asgDevelopmentAssuming you havevirtualenvinstalled:make developConfigure humilis:make configureTestingYou can test the deployment with:make testIf the tests break you can make sure you are not leaving any
infrastructure behind with:makedeleteMore informationSeehumilisdocumentation.ContactIf you have questions, bug reports, suggestions, etc. please create an
issue on theGitHub project
page.LicenseThis software is licensed under theMIT
license.SeeLicense
file.© 2020 German Gomez-Herrero,Find
Hoteland others.
Package: humilis-batch
# Humilis plug-in to deploy AWS Batch resourcesA [humilis][humilis] plug-in layer that deploys all the AWS Batch resources necessary to build a fully operational batch computing system in the AWS cloud.[humilis]:https://github.com/humilis/humilis## Installation` pip installhumilis-batch`To install the development version:` pip installgit+https://github.com/humilis/humilis-batch`## DevelopmentAssuming you have [virtualenv][venv] installed:[venv]:https://virtualenv.readthedocs.org/en/latest/` make develop `Configure humilis:` make configure `## TestingYou can test the deployment with:` make test `If the tests break, you can make sure you are not leaving any infrastructure
behind with:`bash make delete `## More informationSee [humilis][humilis] documentation.[humilis]:https://github.com/humilis/blob/master/README.md## ContactIf you have questions, bug reports, suggestions, etc. please create an issue on
the [GitHub project page][github].[github]:http://github.com/humilis/humilis-batch## LicenseThis software is licensed under the [MIT license][mit].[mit]:http://en.wikipedia.org/wiki/MIT_LicenseSee [License file][LICENSE].[LICENSE]: ./LICENSE.txt© 2020 German Gomez-Herrero, [FindHotel][fh] and others.[fh]:http://company.findhotel.net
Package: humilis-batch-job
Ahumilisplug-in
layer that deploys all the AWS Batch resources necessary to run a batch
job on a given schedule.Installationpip install humilis-batch-jobTo install the development version:pip install git+https://github.com/humilis/humilis-batch-jobDevelopmentAssuming you havevirtualenvinstalled:make developConfigure humilis:make configureTestingYou can test the deployment with:make testIf the tests break, you can make sure you are not leaving any
infrastructure behind with:makedeleteMore informationSeehumilisdocumentation.ContactIf you have questions, bug reports, suggestions, etc. please create an
issue on theGitHub project
page.LicenseThis software is licensed under theMIT
license.SeeLicense file.© 2017 German Gomez-Herrero,Find
Hoteland others.
Package: humilis-decrypt
Ahumilisplug-in
layer that deploys a custom Cloudformation (CF) resource that can be
used to decrypt secrets that are embedded in CF templates.CREDIT:All credit goes toCasecommons
lambda-cfn-kms. This
repo is just the result of bundling thelambda-cfn-kmsrepository as
a humilis plugin.Installationpip install humilis-decryptTo install the development version:pip install git+https://github.com/humilis/humilis-decryptDevelopmentAssuming you havevirtualenvinstalled:make developConfigure humilis:make configureHow does it work?First create the Lambda function that backs the custom resource:make createThe deployment will produce two artifacts:The ID of the KMS key associated with the custom resource.The ARN of the deployed Lambda function.You can use the KMS key ID to encrypt your secrets locally, e.g.
assuming you want to encrypt the dummy DB passworddummywith key3ea941bf-ee54-4941-8f77-f1dd417667cd:aws kms encrypt --key-id 3ea941bf-ee54-4941-8f77-f1dd417667cd --plaintext 'dummy'The output will be something like this:{
    "CiphertextBlob": "AQICAHi2zdvZYfUQOQV8yX/HLdcIMqHHkubAYAei2Qo498KheQFDELPYHds8169cc9EqggEuAAAAZjBkBgkqhkiG9w0BBwagVzBVAgEAMFAGCSqGSIb3DQEHATAeBglghkgBZQMEAS4wEQQM+gDfP3DDVgbFYNidAgEQgCMrz1beR+s0XqWTVIuCbJ+E/cC7sqUzmPEB0weOhQ3GOE65rg==",
    "KeyId": "arn:aws:kms:eu-west-1:XXXXX:key/a86x4dd8-6b8e-41ce-aa65-4aa370d9ccbf"
}Whenever you want to use your secret in a CF template you would do
something like this:---
resources:
  DbPasswordDecrypt:
    Type: "Custom::KMSDecrypt"
    Properties:
      ServiceToken: <lambda_function_arn>
      Ciphertext: "AQICAHi2zdvZYfUQOQV8yX/HLdcIMqHHkubAYAei2Qo498KheQFDELPYHds8169cc9EqggEuAAAAZjBkBgkqhkiG9w0BBwagVzBVAgEAMFAGCSqGSIb3DQEHATAeBglghkgBZQMEAS4wEQQM+gDfP3DDVgbFYNidAgEQgCMrz1beR+s0XqWTVIuCbJ+E/cC7sqUzmPEB0weOhQ3GOE65rg=="
  DbInstance:
    Type: "AWS::RDS::DBInstance"
    Properties:
      AllocatedStorage: "20"
      DBInstanceClass: "db.m1.small"
      Engine: "MySQL"
      EngineVersion: "5.5"
      MasterUsername: "admin"
      MasterUserPassword:
        Fn::Sub: ${DbPasswordDecrypt.Plaintext}where you will need to replace<lambda_function_arn>with the ARN of
the Lambda function that backs the custom CF resource that implements
the decryption logic.More informationSeehumilisdocumentation.ContactIf you have questions, bug reports, suggestions, etc. please create an
issue on theGitHub project
page.LicenseSee the original license in thelambda-cfn-kmsrepository.