Saravanan666/pypi-org huggingface dataset:
Package: whoshome
# Who's Home[![Build Status](https://travis-ci.org/fabiocody/Whos-Home.svg?branch=master)](https://travis-ci.org/fabiocody/Whos-Home)This tool uses ARPing to determine who is at home (i.e.: connected to the local network).**IMPORTANT**: *Who's Home* works only in Python3.## How to install```pip3 install whoshome```## How does it work?*Who's Home* send an ARP-Request to every possible address of your local network; the answers are then parsed, looking for target's MAC addresses (of which only the last three bytes are taken into account, to ensure compatibility with some network devices that may change the vendor part of the address, e.g.: Wi-Fi repeaters). This is done every 30 seconds.A person is considered at home if the associated MAC address is found in one of the ARP-Replies, or if it has been less than 15 minutes since the last time it was found. The reason for this is that *Who's Home* requires that the devices being monitored are connected to the local network. iPhones (and probably others) deliberately disconnect from the network once the screen is turned off to save power, but just because the device isn't connected, it doesn't mean that the device's owner isn't at home. Fortunately, iPhones (and probably others) periodically reconnect to the network to check for updates, emails, etc. This tool works by keeping track of the last time a device was seen, and comparing that to a threshold value. I've found that a threshold of 15 minutes seems to work well for iPhone, but for different phones this may or may not work.## .people.jsonTo make *Who's Home* work, you have to provide a JSON file (located in your home directory and named `.people.json`) containing the target addresses (only the last 3 bytes) and the corresponding names. Here's an example of how it should look.```json[{ "name": "Bob", "target": "00:00:00" },{ "name": "John", "target": "aa:bb:cc" }]```Make sure you use colons as separators.## Change thresholdThe time threshold is implemented with the integer variable `max_cycles`, whose value is double the value of the threshold in minutes.The default value is 30 (15 minutes), but you can pass your desired value along with the other arguments.Please type `whoshome -h` in your terminal for more information.## InvocationPlease type `whoshome -h` in your terminal for more information.
Package: whos-there
Who's there?The spiritual successor toknockknockforPyTorch Lightning, to get a notification when your training is complete or when it crashes during the process with a single callback.🚀 FeaturesSupports E-Mail, Discord, Slack, Teams, Telegram🎯 InstallationYou can installwhos-therewithpiporpoetryorconda.with pippipinstall-Uwhos-therewith poetrypoetryaddwhos-therewith condacondainstall-cconda-forgewhos-there🤯 How to use itfromwhos_there.callbackimportNotificationCallbackfromwhos_there.senders.debugimportDebugSendertrainer=pl.Trainer(callbacks=[NotificationCallback(senders=[# Add your senders hereDebugSender(),])])E-MailRequires your e-mail provider specific SMTP settings.fromwhos_there.senders.emailimportEmailSender# ...EmailSender(host="smtp.example.de",port=587,sender_email="from@example.com",password="*********",recipient_emails=["to1@example.com","to2@example.com",])DiscordRequires your Discord channel'swebhook URL.fromwhos_there.senders.discordimportDiscordSender# ...DiscordSender(webhook_url="https://discord.com/api/webhooks/XXXXXXXXXXXXXX/XXXXXXXXXXXXXXXXXXXXXXXXXXXXXX")SlackRequires your Slack roomwebhook URLand optionally youruser id(if you want to tag yourself or someone else).fromwhos_there.senders.slackimportSlackSender# ...SlackSender(webhook_url="https://hooks.slack.com/services/T00000000/B00000000/XXXXXXXXXXXXXXXXXXXXXXXX",channel="channel_name",user_mentions=["XXXXXXXX"])TeamsRequires your Team Channelwebhook URL.fromwhos_there.senders.teamsimportTeamsSender# ...TeamsSender(webhook_url="https://XXXXX.webhook.office.com/",user_mentions=["twsl"])TelegramYou can also use Telegram Messenger to get notifications. You'll first have to create your own notification bot by following the three steps provided by Telegramhereand save your API accessTOKEN.
Telegram bots are shy and can't send the first message so you'll have to do the first step. By sending the first message, you'll be able to get thechat_idrequired (identification of your messaging room) by visitinghttps://api.telegram.org/bot<YourBOTToken>/getUpdatesand get theintunder the keymessage['chat']['id'].fromwhos_there.senders.telegramimportTelegramSender# ...TelegramSender(chat_id=1234567890,token="XXXXXXX:XXXXXXXXXXXXXXXXXXXXXXXXXXX")🛡 LicenseThis project is licensed under the terms of the MIT license. SeeLICENSEfor more details.🏅 CreditsThis project was generated withBig thanks toknockknockfor the idea and code snippets.
Package: whosyouragent
WhosyouragentSelf updating package for generating random user agent strings.Install with:pip install whosyouragentNew browser versions will be checked for when the module is imported if it's been a week or more since the last update.Usage:from whosyouragent import get_agent
print(get_agent())produces:Mozilla/5.0 (Windows NT 11.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/108.0.5359.98 Safari/537.36 Vivaldi/5.6
Package: whotrackme
<imgalt="whotracks.me"style="width: 200px"src="https://raw.githubusercontent.com/cliqz-oss/whotracks.me/master/static/img/who-tracksme-logo.png">Bringing Transparency to online tracking - built by Cliqz and Ghostery.___This repository contains:* data on trackers and websites as shown on [whotracks.me](https://whotracks.me) (`./data`)* database mapping tracker domains to companies (`./db`)* code to render the [whotracks.me](https://whotracks.me) site# InstallationPython 3.x is needed to build the site. We recommend creating a[virtualenv](http://docs.python-guide.org/en/latest/dev/virtualenvs/) (or`pipenv`) to install the dependencies.## From Pypi```sh$ pip install whotracksme```## From source```sh$ pip install -e .```That's all you need to get started!# Using the dataTo get started with the data, everything you need can be found in`whotracksme.data`:```pythonfrom whotracksme.data import (load_apps,load_companies,load_overview,load_sites,load_tracker_db,)print(load_apps())```For more examples of scripts, have a look in the [contrib](./contrib) folder!# Building the siteBuilding the site requires a few extra dependencies, not installed by default tonot make the installation heavier than it needs to be. You will need to install`whotracksme` this way:```sh$ pip install 'whotracksme[website]'```Or if you do it from source:```sh$ pip install -e '.[website]'```*Furthermore* you also need to [install sass](http://sass-lang.com/install).Once this is done, you will have access to a `whotracksme` entry point that canbe used this way:```sh$ whotracksme website [serve]```The `serve` part is optional and can be used while making changes on thewebsite.All generated artifacts can be found in the `_site/` folder.## TestsTo run tests, you will need `pytest`, or simply install `whotacksme` with the`test` extra:```sh$ pip install -e '.[test,website]'$ pytest```# ContributingWe are happy to take contributions on:* guest articles for our blog in the topics of tracking, privacy and security. Feel free to use the data in this repository if you need inspiration.* Curating our database of tracker profiles.# LicenseThe content of this project itself is licensed under the [Creative Commons Attribution 4.0 license](https://creativecommons.org/licenses/by/4.0/), and the underlyingsource code used to generate and display that content is licensed under the [MIT license](https://github.com/cliqz-oss/whotracks.me/blob/master/LICENSE.md).
Package: whotracksme
Bringing Transparency to online tracking - built by Cliqz and Ghostery.This repository contains:data on trackers and websites as shown onwhotracks.me(WTM)database mapping tracker domains to companiescode to render thewhotracks.mesiteInstallationPython 3.6 is needed to build the site. We recommend creating avirtualenv(orpipenv) to install the dependencies.From Pypi$pipinstallwhotracksmeFrom source$pipinstall-e.That’s all you need to get started!Using the dataTo get started with the data, everything you need can be found inwhotracksme.data:fromwhotracksme.data.loaderimportDataSourcedata=DataSource()# available entitiesdata.trackersdata.companiesdata.sitesFor examples of scripts, have a look in thecontribfolder!Building the siteBuilding the site requires a few extra dependencies, not installed by
default to not make the installation heavier than it needs to be. You
will need to installwhotracksmefrom the repository, because not
all assets are packaged withwhotracksmereleased on pypi:$pipinstall-e'.[dev]'Once this is done, you will have access to awhotracksmeentry point
that can be used this way:$whotracksmewebsite[serve]Theservepart is optional and can be used while making changes on
the website.All generated artifacts can be found in the_site/folder.TestsTo run tests, you will needpytest, or simply installwhotacksmewith thedevextra:$pipinstall-e'.[dev]'$pytestPublishing a new version$pipinstalltwine$pythonsetup.pysdistbdist_wheel$twineupload--usernamecliqz-ossdist/*ContributingWe are happy to take contributions on: * Guest articles for our blog in
the topics of tracking, privacy and security. Feel free to use the data
in this repository if you need inspiration. * Feature requests that are
doable using the WTM database. * Curating our database of tracker
profiles. Open an issue if you spot anything odd.Right to AmendPlease read ourGuideline for 3rd partieswanting to suggest
corrections to their data.LicenseThe content of this project itself is licensed under theCreative
Commons Attribution 4.0 license, and the underlying source code used
to generate and display that content is licensed under theMIT
license.
Package: whr
Whole History RatingDescriptionA Python implementation of theWhole History Ratingalgorithm proposed byRémi Coulom.The implementation is based on theRuby codeofGoShrine.Installationpip install whrUsageIn [1]: import whr
...:
...: base = whr.Base(config={'w2': 30})
...: base.create_game('Alice', 'Carol', 'D', 0) # Alice and Carol had a draw on Day 0
...: base.create_game('Bob', 'Dave', 'B', 10)   # Bob won Dave on Day 10
...: base.create_game('Dave', 'Alice', 'W', 30) # Dave lost to Alice on Day 30
...: base.create_game('Bob', 'Carol', 'W', 60)  # Bob lost to Carol on Day 60
...:
...: base.iterate(50)                           # iterate for 50 rounds

In [2]: print(base.ratings_for_player('Alice'))
...: print(base.ratings_for_player('Bob'))
...: print(base.ratings_for_player('Carol'))
...: print(base.ratings_for_player('Dave'))
[[0, 78.50976252870765, 114.0890917675107], [30, 79.47183295485291, 116.02912272478814]]
[[10, -15.262552175731381, 108.50075126605397], [60, -18.08603087778281, 111.07152016073245]]
[[0, 103.9187774903099, 108.03027219107216], [60, 107.30695193277161, 111.12369929419124]]
[[10, -176.6773935927304, 134.07989121465133], [30, -177.31877387682724, 135.25422816732765]]

In [3]: print(base.get_ordered_ratings())
[('Carol', [[0, 103.9187774903099, 108.03027219107216], [60, 107.30695193277161, 111.12369929419124]]), ('Alice', [[0, 78.50976252870765, 114.0890917675107], [30, 79.47183295485291, 116.02912272478814]]), ('Bob', [[10, -15.262552175731381, 108.50075126605397], [60, -18.08603087778281, 111.07152016073245]]), ('Dave', [[10, -176.6773935927304, 134.07989121465133], [30, -177.31877387682724, 135.25422816732765]])]ReferencesRémi Coulom. Whole-history rating: A Bayesian rating system for players of time-varying strength. InInternational Conference on Computers and Games. 2008.https://www.remi-coulom.fr/WHR/WHR.pdf
Package: whratio
whratioCalculate integer and decimal aspect ratio for dimensions.CLI examples$whratio1024768431.3333333333333333$whratio-d-n22561961.31whratio-WH25601080|tr" ":64:27Python package examples>>>importwhratio>>>whratio.as_int(1920,1080)(16,9)>>>whratio.as_float(1920,1080)1.7777777777777777>>>round(whratio.as_float(1920,1080),2)1.78InstallationUsingpip:# pip3 install whratio
Package: whs.utils.rwlock
WHS Ltd provides collection of pure-python modules.This is implementation of lock, that allows only one kind of operation be
executed at the time (reading or writing). Any number of callers
can acquire reading or writing at once, but if someone tries to acquire writing
while reading is acquired, it will wait, until all readers that acquired lock
release it (and vice versa).At the moment it works only with threading, but few simple modifications will
result in multiprocessing-enabled implementation.whs.utils.rwlock is a package, but should be used as a module (all code is in
__init__.py).
Package: whuapi
新版武汉大学教务系统API基于最新版(2020/06)武汉大学教务系统，而制作的Python第三方库，方便他人的二次开发。目录背景功能安装用法更新日志相关项目主要项目负责人参与贡献方式贡献人员开源协议背景由于你武教务系统常年奔溃，遭人诟病。终于在本学期彻底改头换面，导致原有旧教务系统的api接口面临失效的风险。所以我根据@NeroAsmarr的新版正方教务教务系统API项目 进行了本地化的适配而创建了此项目。功能自动登陆、cookies获取个人信息学校通知成绩课程表安装使用pip命令安装pip install whuapi在克隆本项目进行安装gitclonehttps://github.com/yaoyue123/whuapi.gitcdwhuapi
pythonsetup.pybuild
pythonsetup.pyinstall用法推荐直接结合调用例子：examples更新日志v 0.0.1初始版本对个人信息，成绩，课程表等进行了修改。相关项目新版正方教务教务系统API项目主要项目负责人@yaoyue123参与贡献方式提交PR申请，我会视情况通过。贡献人员感谢所有贡献的人。@yaoyue123开源协议MIT© yaoyue123
Package: whych
A tool to locate the Python modules that your interpreter has access to.whych is only run as a “command-line module” with the-mflag to the Python
interpreter, from the REPL or from a notebook.  whych is not as a standalone
executable, so that the Python interpreter that is used is obvious.Examples>From the command-line:$ python3 -m whych collections
Python executable: /usr/bin/python3
Module "collections" found at location: /usr/lib/python3.5/collections


$ python -m whych numpy --module-version
Python executable: /usr/bin/python
Module "numpy" found at location: /usr/lib/python2.7/dist-packages/numpy
numpy version: 1.12.0b1>From an interpreter:>>> import whych
>>> whych.whych('pip')
Python executable: /usr/bin/python3
Module "pip" found at location: /home/pierre/.local/lib/python3.5/site-packages/pipInstallationpip install whych
Package: whyis
Whyis is a nano-scale knowledge graph publishing,
management, and analysis framework. Whyis aims to support domain-aware management
and curation of knowledge from many different sources. Its primary goal is to enable
creation of useful domain- and data-driven knowledge graphs. Knowledge can be
contributed and managed through direct user interaction, statistical analysis,
or data ingestion from many different kinds of data sources. Every contribution to
the knowledge graph is managed as a separate entity so that its provenance
(publication status, attribution, and justification) is transparent and can
be managed and used.
Package: whyis-author-affiliation-agent
whyis_author_affiliation_agentInstallationinstallwhyisusing this commandWHYIS_BRANCH=master bash < <(curl -skL https://raw.githubusercontent.com/tetherless-world/whyis/master/install.sh)whyis will be installed in /apps/whyisIn your knowledge graph directory, add the author affiliation agent to the list of inferencers in your config.py file:Add the following import line:import whyis_author_affiliation_agent.affiliation_agent as aaAdd the following line to theinferencersitem in theConfigdictionary constructor:"AffiliationAgent": aa.AffiliationAgent()Runauthoraffiliationsetup -e email [-u arcgis_username -p arcgis_password -r referer]to set up your credentials for requesting author and affiliation data.The ArcGIS username and password are optional, but without them you may be unable to retrieve affiliation location dataThe referer flag is optionalRunauthoraffiliationtestto test the installation is working properlyReload your knowledge graph to run the inferencer over it
Package: whyis-classifier
whyis_classifierInstallationinstallwhyisusing this commandWHYIS_BRANCH=master bash < <(curl -skL https://raw.githubusercontent.com/tetherless-world/whyis/master/install.sh)whyis will be installed in /apps/whyisIn your knowledge graph directory, add the classifier agent to the list of inferencers in your config.py file:Add the following import line:import whyis_classifier.classifier_agent as clAdd the following line to theinferencersitem in theConfigdictionary constructor:"Classifier": cl.Classifier()Write your own classifier, usingwhyisclassifier.WhyisClassifieras its base classYou must provide your own identifier (anrdflib.URIRef) and write alabel()methodLocate yourwhyis_classifierinstallation, and in the fileuser_classifiers.py, import your classifier and add it to theuser_classifiersdictionary in the form'my_classifier_name': my_file.MyClassifier()To locate yourwhyis_classifierinstallation, runpython -c "import whyis_classifier as _; print(_.__path__[0])"Reload your knowledge graph to run the inferencer over it
Package: whyis-unit-converter
Whyis-unit-converterInstallationinstallwhyisusing this commandWHYIS_BRANCH=master bash < <(curl -skL https://raw.githubusercontent.com/tetherless-world/whyis/master/install.sh)whyis will be installed in /apps/whyisIn your knowledge graph directory, add the unit converter agent to the list of inferencers in your config.py file:Add the following import line:import whyis_unit_converter.unit_converter_agent as converterAdd the following line to theinferencersitem in theConfigdictionary constructor:"UnitConverter": converter.UnitConverter()Reload your knowledge graph to run the inferencer over itLoading unit definition and translation filesTo load your own unit definition and translation files, runimportconverterdict FILESYour translation files can be in one of the following forms:URI to unit mapping file. Used to map measurement types to their preferred units, ifhttp://nanomine.org/ns/hasPreferredUnitis not used in your knowledge graph.#mapping_file
http://nanomine.org/ns/CharpyImpactEnergy=http://www.ontology-of-units-of-measure.org/resource/om-2/joulePerSquareMetre
http://nanomine.org/ns/CrystalizationTemperature=http://www.ontology-of-units-of-measure.org/resource/om-2/kelvinTranslation file. Used to translate URIs into understandable units. Translations to understandable units are written as below. Seedefining pint unitsfor more specific information about formatting.#translation_file
http://www.ontology-of-units-of-measure.org/resource/om-2/degreeFahrenheit=5 / 9 * kelvin; offset: 233.15 + 200 / 9
http://www.ontology-of-units-of-measure.org/resource/om-2/amperePerSquareMetre=ampere / meter ** 2
http://nanomine.org/ns/unit/kpa=kilopascalTestingTo test the unit converter, rununitconvertertestfrom a pip enabled endpoint.
Package: whykay
WhyKayThe concept is to have a personal toolbar that contains all the handy functions that support efficient python software engineering workflows, connectivity to cloud, navigating file systems, parsing date/time formats and pushing notifications to different platforms.🚩 v0.4.0 is now available with the feature to calculate the stock exposure through your ETFs and stock portfolioInstallationTo run the code successfully, all the dependencies can either be installed usingpip:pipinstallwhykayCloning repository for contributionsTo run the code successfully, all the dependencies can either be installed usingpip:pipinstall-rrequirements.txtoruse the pre-define Makefile targetsmakesetupFeatures (Usage/Examples)Investments (Stock/ETF exposure calculator)Available for use from v0.1.0Limitations (in-scope features)This only works on ETFs or Stocks (Individual shares) based portfolioWill ignore any other investment holdings that you passIt takes in input in form of a JSON structure:[{"isin":"US30303M1027","investment":185.22,"category":"stock"# Optional field},{"isin":"IE00BQQP9H09","investment":298.22,"category":"ETF"# Optional field}]whereisinuniquely idenfies a holding, can get it fromYahoo Finance/Trading 212(personal choice)Returns the output in a JSON format>>>fromwhykay.investments.stocks_analyzerimportcalculate_exposure╔══════════════════════════════════════════════════════════════════════════╗║InvestmentAnalyzerImported║╚══════════════════════════════════════════════════════════════════════════╝>>>data=[{"isin":"US30303M1027","investment":185.22},{"isin":"IE00BQQP9H09","investment":298.22}]>>>calculate_exposure(holdings=data,display=True)+----+----------+-----------------------+--------------------+||symbol|AmountInvested($)|OverallExposure||----+----------+-----------------------+--------------------||0|AAPL|229.5500|32.7929||1|MSFT|28.1000|4.0143||2|AMZN|20.3000|2.9000||3|FB|11.4500|1.6357||4|GOOGL|10.1000|1.4429||5|GOOG|9.8500|1.4071||6|BRK.B|7.2500|1.0357||7|TSLA|7.2000|1.0286||8|NVDA|6.8500|0.9786||9|JPM|6.5000|0.9286|+----+----------+-----------------------+--------------------+Changelogv0.4.0Breaks previous functionality, as output is now typically returned in a json structureImport reverted back towhykay.investments.stock_analyzerfor future use casesTakes in new parameter:displaywhich returns the tabular display of results on screendata is now inputted in form of API convention JSON structures for API endpoint developmentsv0.3.0Breaks previous functionality, as output is now typically returned in a json structureImport changes fromwhykay.investments.stock_analyzertowhykay.investments.holdings_analyzerTakes in new parameter:displaywhich returns the tabular display of results on screenv0.2.0fixes to.gitignorefile which was preventing the requirements.txt file uploaddoes not break functionality changes in v0.1.0v0.1.0Minor release that supports the stock exposure feature calculatorfrom whykay.investments.portfolio_analyzer import calculate_exposurev0.0.xprevious versions were experimental and don't provide much functionalitywill be discarded onpypi.orgAuthorsYasir Khalid