Saravanan666/pypi-org huggingface dataset:
Package: waitress-fastlisten
This tiny package allows the waitress WSGI server to immediatly pre-bind to a port and listen to it.
It waits then for the app to start up and passes then requests further.UsageIn your paste based WSGI configuration in[server:main]set:paste-server-factorytowaitress_fastlisten:mainusetoegg:plone.recipe.zope2instance#mainfast-listentoHOST:PORTDonotset “listen =”.Example:[server:main]paste.server_factory=plone.recipe.zope2instance:mainuse=egg:plone.recipe.zope2instance#mainfast-listen=0.0.0.0:8080Changelog1.0.0rc1 (2021-12-04)Isolated code fromplone.recipe.zope2instance.
[jensens]
Package: waitress-raw
waitress-rawRaw HTTP Echo Server For Security Researchers and HTTP DebugInstallationPrerequisitesPython 3.7+.waitress (https://docs.pylonsproject.org/projects/waitress/en/latest/).From pippip3installwaitress-rawFrom Dockerdockerpullrealgam3/waitress-rawFrom Sourcegitclonehttps://github.com/realgam3/waitress-raw.gitcdwaitress-raw# Install python dependencies.pip3install-rrequirements.txt# Confirm that everything workspython3waitress-raw.py--helpBug reports on installation issues are welcome!UsageBasic Usagewaitress-raw-lh0.0.0.0-lp8000-c./examples/loggers/streamhandler.ymlDocker Usagedockerrun-v"${PWD}/examples/loggers/streamhandler.yml:/usr/src/app/config.yml:ro"-p8000:8000--rmrealgam3/waitress-rawCommand Line Argumentswaitress-raw--helpusage: waitress-raw [-h] [-v] [-lh HOST] [-lp PORT] [-s SCHEME] [-t CHANNEL_TIMEOUT] [-r] [-V] [-c CONFIG_PATH]

options:
  -h, --help            show this help message and exit
  -v, --version         show program's version number and exit
  -lh HOST, --host HOST
                        listen host. (default: 0.0.0.0)
  -lp PORT, --port PORT
                        listen port (default: 8000)
  -s SCHEME, --scheme SCHEME
                        url scheme (default: http)
  -t CHANNEL_TIMEOUT, --timeout CHANNEL_TIMEOUT
                        timeout in seconds (default: 5)
  -r, --reset-on-timeout
                        reset on timeout (default: False)
  -V, --verbose         verbose (default: False)
  -c CONFIG_PATH, --config CONFIG_PATH
                        config path (default: config.yml)
Package: wait-util
changelist1.1.2,  fix readme1.1.1,  update type hint1.1.0,  add wait_for1.0.0,  first releasefeedbacksend email todvdface@gmail.comvisithttps://github.com/dvdface/waitutilhow to installpip install wait-utilknown issuesNonetest infoName               Stmts   Miss  Cover
--------------------------------------
wait\__init__.py       2      0   100%
wait\wait.py          65      6    91%
--------------------------------------
TOTAL                 67      6    91%how to useinstall packagerunpip install wait-utilto install wait packageuse wait_until_change/wait_until_no_changefrom wait import wait_until_change, wait_until_no_change

def demo():
  return 1

wait_until_change(demo, interval=1, timeout=5)

wait_until_no_change(demo, interval=1, timeout=5)use wait_for_true/wait_for_falsefrom wait import wait_for_true, wait_for_false

def demo():
  return True

wait_for_true(demo, interval=1, timeout=5)

wait_for_false(demo, interval=1, timeout=5)use wait_forfrom wait import wait_for

def func():
    import random
    return random.randint(0, 1)

wait_for(func, 0)how to contributevisithttps://github.com/dvdface/waitutilsubmit your contribute
Package: waivek
Code - Print colored textfrom waivek import Code
print(Code.RED + "Hello, World!")commonfrom waivek import Date, Timestamp
dt = Date("2020-01-01"
timestamp = Timestamp(3600)>>> Date(1672511400) == Date('2023-01-01')
True

>>> date = Date(1672511400)
>>> date
12:00 AM, Jan 01 (5 months ago)

>>> date.epoch
1672511400

>>> date.string
2023-01-01T00:00:00+05:30

>>> date.timeago()
5 months ago

>>> str(date)
12:00 AM, Jan 01 (5 months ago)

>>> date.dt
2023-01-01 00:00:00+05:30from waivek import create_partitions, smart_pad, enumerate_countdbfrom waivek import db_init, insert_dictionaries
cursor, connection = db_init(db_path)
insert_dictionaries(cursor, table_name, dictionaries)errorfrom waivek import handler
with handler():
    main()getfrom waivek import aget
aget(urls)icfrom waivek import ic, ib
ic({"key": "value"})
ib(str)print_utils - Print and manipulate text.from waivek import head, truncate, abbreviatereltools - Do path manipulation relative tofrom waivek import rel2abs, read, writetimer - Measure execution time of code snippetsfrom waivek import Timer
Package: waiwera-credo
CREDOCREDO is a toolkit for running, analysing and benchmarking computational models.CREDO was originally developed to support better benchmarking and profiling
of the Underworld Geophysics modelling application, based on the StGermain
framework. For more on Underworld (and StGermain), see the Underworldwebsite.For more details about the design of CREDO and how to run it, see the
documentation in the doc sub-directory.This fork of CREDO was developed at the University of Auckland for
benchmarking theWaiwerageothermal
flow simulator.License and authorsCREDO is licensed under the LGPLv2.1, see COPYING.txt.The main contributors to CREDO's coding, design and development thus far are:Patrick Sunter (patdevelop AT gmail.com)Wendy SharplesJerico RevoteJulian GiordaniOwen KaluzaLouis MoresiSteve QuenetteThe Waiwera fork of CREDO was developed by:Angus YehAdrian CroucherAcknowledgementsWe kindly acknowledge the funding support of the Monash University
Simulation And Modelling (SAM) node by AuScope Limited in facilitating the
development of CREDO.AuScope is part of the Australian Federal Government's National
Collaborative Research Infrastructure Strategy (NCRIS) program.Change logsFor a list of changes that occurred in each release, see the files in the
"changelogs" subdirectory.Basic Installation instructionsThe Waiwera fork of CREDO can be installed fromPyPIusingpip,
e.g.pip install waiwera-credo(orpip install --user waiwera-credoto install locally, e.g. if you don't have permissions
to install system-wide Python packages).The installation instructions for the original CREDO toolkit are below.(For more detailed
installation instructions, see the "Installation & setup quickstart
instructions" section of the CREDO documentation.)To run CREDO scripts directly from the command line, you need to set up several
environment variables. These are:STG_BASEDIR: the path where your StGermain-based app has been checked out
and installed to.PYTHONPATH: You'll need to update your Python Path to include a reference
to the directory you installed CREDO into.In the application bundle CREDO was distributed as part of, there should be
a script you can edit to easily update these variables and then source, such
as "updatePathsCREDO.sh".After that, you should be good to go!If you wish to build a local copy of the CREDO documentation, you will need
to first install the 'Sphinx' documentation tool, and the 'Graphviz' plotting
library (for more on these see the doc appendix). Then:cd docmake htmlmake latex; pushd _build/latex; make all-pdf; popdThe documentation will then have been built in the_buildsubdirectory
ofdoc.
Package: wakachigaki
wakachigaki-py6.2Kb の軽量日本語分かち書きライブラリ動作確認用のデモサイトJS 向けに作成した同ライブラリwakachigakiの Python ポーティングです。詳しくはこちらをご参照下さい。https://github.com/yuhsak/wakachigaki使い方pipinstallwakachigakifromwakachigakiimporttokenizetokenize("非常に効果的な機械学習モデル")# => [ "非常", "に", "効果", "的", "な", "機械学習", "モデル" ]
Package: wakahiki
Wakahiki means crane in Maori, and that’s just what this package does,
it lifts up all your scritps and runs them in priority order on
multiple threads where possible.DescriptionSee the linked git hub repo for documentation, especially an example for the config
file required. You can group similar tasks that need to be in order
whilst having these tasks be part of a larger priority list that is
then used to determine the processing order. Scripts needing output and
user input need to be set toprompt = truein the config file as
this forces them to grab an IO lock to allow logical user interaction.
It uses the subprocess module to execute shell scripts or commands
entered into the config file.NoteThis project has been set up using PyScaffold 3.2.3. For details and usage
information on PyScaffold seehttps://pyscaffold.org/.
Package: wakalinus
wakalinusA simple sentiment analysis utility for Japanese.RequirementsPython 3Usageimportwakalinusanalyzer=wakalinus.Analyzer()analyzer.analyze('天国で待ってる。')# => [1.0]analyzer.analyze('遅刻したけど楽しかったし嬉しかった。すごく充実した！')# => [0.3333333333333333, 1.0]analyzer.count_polarity('遅刻したけど楽しかったし嬉しかった。すごく充実した！')# => [{'positive': 2, 'negative': 1}, {'positive': 1, 'negative': 0}])analyzer.count_polarity('そこにはいつもと変わらない日常があった。')# => [{'positive': 0, 'negative': 0}]analyzer.analyze_detail('お金も希望もない！')# => [{'positive': [], 'negative': ['お金-NEGATION', '希望-NEGATION'], 'score': -1.0}])analyzer.analyze_detail('お金がないわけではない')# => [{'positive': ['お金'], 'negative': [], 'score': 1.0}]Installation$pipinstallwakalinus
Package: wakamaro
wakamaroAbstractwakamaro is a package for visualizing the number of waka poetry composed by poets in Nijuichidaishu (21 waka poetry anthologies)Using a Nijuichidaishu dataset, Visualize the number of waka poetry per waka poet.The Nijuichidaishu dataset is downloadable from:http://codh.rois.ac.jp/pmjt/Overview of Datathe Center for Open Data in the Humanities“The Dataset of Pre-Modern Japanese Text (the National Institute of Japanese Literature)http://codh.rois.ac.jp/index.html.enLink to download datahttp://codh.rois.ac.jp/pmjt/package/text.zipHow to run wakamaro$ pip install wakamaroHow to run wakamaro$ wakamaroThe first argument: number of Nijuichidaishu (1 to 21)
The second argument: minimum number of appearances of the waka poets to be displayedExample of Running: waka poets that appeared more than 5 times in kokin wakashu
$ wakamaro 1 5The vertical axis shows number of appearances in waka poetry.
The horizontal axis show appearance of waka poets in waka poetry.
Package: wakame
wakamejanomeライクなインターフェイスを提供するmecabのラッパーです.利用方法importMeCabfromwakame.tokenizerimportTokenizerfromwakame.analyzerimportAnalyzerfromwakame.charfilterimport*fromwakame.tokenfilterimport*text='和布ちゃんこんにちは'# 基本的な使い方tokenizer=Tokenizer()tokens=tokenizer.tokenize(text)fortokenintokens:print(token)# 分かち書きtokens=tokenizer.tokenize(text,wakati=True)print(tokens)# 辞書をNEologdにする場合tokenizer=Tokenizer(use_neologd=True)tokens=tokenizer.tokenize(text)fortokenintokens:print(token)# filterを利用する場合char_filters=[RegexReplaceCharFilter('和布','wakame')]token_filters=[POSKeepFilter('名詞'),POSStopFilter(['名詞,接尾'])]analyzer=Analyzer(tokenizer,char_filters=char_filters,token_filters=token_filters)tokens=analyzer.analyze(text)fortokenintokens:print(token)# tokenの情報をDataFrameで用いる場合tokenizer=Tokenizer()analyzer=Analyzer(tokenizer)df=analyzer.analyze_with_dataframe(text)print(df)インストールMeCabのインストール(必須)brewinstallmecab
brewinstallmecab-ipadicmecab-ipadic-NEologdのインストール(任意)brewinstallgitcurlxz
gitclone--depth1git@github.com:neologd/mecab-ipadic-neologd.gitcdmecab-ipadic-neologd
./bin/install-mecab-ipadic-neologd-n詳しくはこちらを参照してくださいmecab-python3のインストール(必須)brewinstallswig
pipinstallmecab-python3wakameのインストール(必須)pipinstallwakame
Package: wakanda
WakandaThis tool is useful to extract data from various african's websites.New Features!Hitorical data for stocks from more than 8 africans markets (BRVM, Ghana, Nigeria, Kenya and more)Get real-time data ( at this point this worked only for BRVMInstallationFrom pypi with pip:$pipinstallwakandaUsage exampleUse afx.kwayisi as main source of data, ranging up to 7 years.$importwandakaaswkd# Initialize market (eg:brvm).you could also choose ghana(gse), nigeria(ngse)..$brvm=wkd.stock('brvm')# now you can collect stock data for all stocks under that market$brvm.DataReader('BICC')Datecloseprice009-16-201343000109-23-201342000209-26-201342000310-01-201342000410-02-201342000# you may specify start and end dates$gse=wkd.stock('gse')$gse.DataReader('MTNGH'start='01-09-2020',end='01-13-2020')Datecloseprice001-09-20200.7101-10-20200.7201-13-20200.7Get live quote from markets' official website$fromwakandaimportwkdbrvm=wkd.stock('brvm')brvm.get_quote('BICC')LicenseMITFree Software, Hell Yeah!
Package: wakapy
====================
IntroductionWakapy is a python library aiming for Python 3.6+ versions whose purpose
is to provide easy data manipulation to the developer... note:: 1. This project is not related toWakaTime <https://wakatime.com/>_ or its developer team in any way.
2. This project revolves around the json file that you can download from yourWakatime accountWakapy basically loads thebigjson file containing all of your data provided for free by WakaTime and
group every piece of data in convenient classes. The Wakatime json file is big, a 161 days file, where only 121 days actually
contain relevant data is roughly 75k long (in my case).Wakapy features:Extensive data class containerization(Every bit of data from the json file is accessible with the library).Extra functionalitiesadded to ease
the data manipulation.Date slicing, in other words, you can get the data from a chosen  range,
similar to the Wakatimepaid featuresSome nicechartsout of the box for the people who just want to
get a quick insight of the data without putting too much effort
on itQuick example:Code: ::from wakapy import User

user = User('/home/surister/data.json')
chart = user.pie_chart('lan')
# lan = languages. See the different options here.
chart.show()
# Shows the chart.
chart.save('/home/surister/mychart.png')
# Saves the chart to the desired filepath.This would output:.. image:: /docs/source/_static/example1.png
Package: wakaranai
わからない (wakaranai) literally means "I don't understand" in Japanese.
It is a phrase worth learning, specially if you plan to visit Japan anytime soon.
If you'd like to learn more than just a couple of key phrases,
it might be useful to learn hiragana and katakana as well.
This Python package, calledwakaranai, helps non-Japanese speakers
learn these two syllabaries by generating and applying random tests.UsageIf you ever feel like practicing your Japanese, simply run the following command.
You must choose to practice either hiragana or katakana.python-mwakaranai{hiragana,katakana}You will be prompted with characters from the selected kana in random order,
and you must answer with their correct romanizations.
The accepted romanizations are: Hepburn, Nihon-shiki, and Kunrei-shiki.
Obsolete syllables such as ゐ and ヰ are ignored.お? o
た? ta
わ? re
...After all characters have been prompted, the results will be displayed.
Wrong answers are accompanied by the correct answer(s).お --> o ✓
た --> ta ✓
わ --> re ✗ (correct: wa)
...
Package: wakatime
wakatime-cli pipThis wraps the Gowakatime-cliin a Python package, replacing thelegacy Python wakatime-cli.Installingpip install wakatimeInstalling runsinstall_cli.pyand downloads the latest Go wakatime-clireleaseto~/.wakatime/wakatime-cli.Usingwakatime --helpFor more info, seewakatime-cli usage docs.
Package: wake
wake🍰 Making Wikipedia and Wikidata Processing Easy, Like Eating a Piece of Cakeinstallationpip3 install wakeorpipenv install wakemethodsget_wikidata_entitiesStream Wikidata Entitiesfromwakeimportget_wikidata_entitiesforentityinget_wikidata_entities():print(entity)You can also filter entities by their type.  For example, to get all entities that are humans (Q5) run:fromwakeimportget_wikidata_entitiesforhumaninget_wikidata_entities(instance_of="Q5"):print(human)clean_titletakes in a title of a Wikipedia page as a string and escapes and cleans it of weird characters, so it can be put in a normal databasedownload_if_necessarydowloads a url to the system's temp directory if a file by its name isn't already thereget_most_recent_available_dumpfigures out what Wikipedia dump has certain subdumps completetokenizepass in the page text from a dump and get a list of tokens in returnget_linksget links in an article(i.e. what's between '[[' and ']]')testpython3 -m unittest wake.testlicenseCC0-1.0 / Public DomaincontactPost an issue! Thank you!
Package: wakeblaster-sdk
For more information, seehttps://proplanen.info/wakeblaster.Keywords: wakeblaster windfarm modelling simulation
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Requires-Python: ==3.*
Package: wakeonlan
A small python module for wake on lan.For more information on the wake on lan protocol please take a look atWikipedia.Installationpip install wakeonlanUsageTo wake up a computer using wake on lan it must first be enabled in the BIOS
settings. Please note the computer you are trying to power on does not have an
ip address, but it does have a mac address. The package needs to be sent as a
broadcast package.As a python moduleImport the module>>> from wakeonlan import send_magic_packetWake up a single computer by its mac address>>> send_magic_packet('ff.ff.ff.ff.ff.ff')Wake up multiple computers by their mac addresses.>>> send_magic_packet('ff.ff.ff.ff.ff.ff',
...                   '00-00-00-00-00-00',
...                   'FFFFFFFFFFFF')An external host may be specified. Do note that port forwarding on that host is
required. The default ip address is 255.255.255.255 and the default port is 9.>>> send_magic_packet('ff.ff.ff.ff.ff.ff',
...                   ip_address='example.com',
...                   port=1337)A network adapter may be specified. The magic packet will be routed through this interface.>>> send_magic_packet('ff.ff.ff.ff.ff.ff',
...                   interface='192.168.0.2')As a standalone scriptusage: wakeonlan [-h] [-i ip] [-p port] [-n interface] mac address [mac address ...]

Wake one or more computers using the wake on lan protocol.

positional arguments:
  mac address  The mac addresses of the computers you are trying to wake.

optional arguments:
  -h, --help   show this help message and exit
  -i ip        The ip address of the host to send the magic packet to. (default 255.255.255.255)
  -p port      The port of the host to send the magic packet to. (default 9)
  -n interface The ip address of the network adapter to route the magic packet through. (optional)DependenciesPython 3.xLicenseMIT©Remco Haszing
Package: wakepy
⏰😴 wakepySimple cross-platform wakelock written in Python. Comes with python API and a single executable for CLI usage.SupportsPython: 3.7 to 3.12OS: Windows, Linux and macOSWhat it can do?Prevent your system from going to sleep in the middle of a long running task (e.g. training machine learning models, video encoding, web scraping, ...)Prevent starting a screensaver or screenlock automatically (showing a video, updating dashboard, monitoring apps, ...)Used byviskillz-blender— Generating assets of Mental Cutting Test exercisesmpc-autofill— Automating MakePlayingCards' online ordering systemlakeshorecryotronics/python-driver— Lake Shore instruments python DriverUCSD-E4E/baboon-tracking— In pipelines of a Computer Vision project tracking baboonsdavlee1972/upscale_video— Upscaling video using AIminarca— Cross-platform data backup softwareDocumentation👉wakepy.readthedocs.io⚖️👑 Key selling pointsWakepy supports multiple operating systems and desktop environmentsWakepy has permissive MIT licenceIt has a simple command line interface and a python APIWakepy has very little python dependencies:Zero if using Windows or macOS or Linux + systemdOne if using linux +jeepneyor linux +dbus-python.Deprecation timeline (wakepy 0.7.0+)Since deprecations may affect many users, they are communicated well before and time is given for project maintainers for migration. Timeline:June 11th 2023: Release wakepy 0.7.0 with DeprecationWarnings for keepawake, set_keepawake and unset_keepawake, and the CLI option -s.Migration Guidepublished.September 1st 2023(or few days later): Release wakepy without the deprecated keepawake, set_keepawake and unset_keepawake; Only new API supported.
Package: wakis
wakisWAKIS stands for (WA)ke and (I)mpedance (S)olver. It is a postprocessing tool that can obtain the longitudinal and transverse Wake Potential and Impedance from pre-computed electromagnetic fields. These magnitudes are important to quantify the losses of accelerator structures with a passing beam.Procedural version available in :file_folder: source/OOP version available now in pyPIwakis 0.2.0Check :file_folder: examples/ on how to use!More information about theory, installation and usage can be found on:https://wakis.readthedocs.io/en/latest/Github link:https://github.com/ImpedanCEI/wakis
Package: wakong
WakongWakong: An appropriate and robust masking algorithm for generating the training objective of text infillingThis project is the Python library of ARP 1:The Wakong Algorithm and Its Python Implementation.This project is supported by Cloud TPUs from Google'sTPU Research Cloud(TRC) as a part of my project on large-scale language model pre-training.InstallationWakong supports Python 3.10 and above:pipinstallwakongYou can also install from source:flitinstallUsagefromwakongimportWakongwakong=Wakong(seed=42)sentence='I can eat glass , it does not hurt me .'.split(' ')print(wakong(sentence))Output:['I', '<mask>', 'eat', 'glass', '<mask>', ',', 'it', 'does', 'not', 'hurt', 'me', '.']
Package: waktusolat
python-waktu-solatA simple API wrapper forwaktu-solat-api. (Malaysia only)InstallationpipinstallwaktusolatBasic usageList all states:fromwaktusolatimportWaktuSolatclient=WaktuSolat()print(client.states())List all zones:fromwaktusolatimportWaktuSolatclient=WaktuSolat()print(client.zones())List all prayer times:fromwaktusolatimportWaktuSolatclient=WaktuSolat()print(client.prayer_times())LicenseMIT
Package: waky
WakyWaky is a web application to manage Wake-On-Lan supporting devicesRequirementsPython 3BowertoxLocal devdocker run -it --rm -v $PWD:/workspace -w /workspace ubuntu /bin/bash
tox -e dev
WAKY_CONF=waky.conf
env/bin/wakyTestingtoxRuntox -e runReleasebump2version minorBuildtox -e buildBuild & Publish to PyPItox -e uploadResourcesfavicon.ioRighteous font
Package: wala
walaWeb interface to execute scripts and get status feedback.DevelopmentClone the projectgh repo clone Adnn/wala
pushd walaCreate and use a virtual envpython3 -m venv .venv
source .venv/bin/activateInstall the project and its dependenciespip3 install -e .Run the development server, then point your web browser tohttp://localhost:5000flask --app wala run --debugVagrant deploymentvagrant/provides a vagrant environment where thewalaweb application is deployed
in a way amenable to production.It is usinggunicornWSGI server, automatically monitored viasystemd.
It also setupnginxas a reverse proxy.
(Seevagrant/deploy.shfor the actual steps.)Up the machine, the deployment will setup the environment:pushd vagrant
vagrant upOnce deployment is complete, point your browser tohttp://localhost:8080
Package: walden
GoalDevelop a simple automated journaling system that removes the pain points of maintenance and
organization, allowing the user to focus on writing.InstallAvailable via pip:pip install waldenUsageWalden will create ajournals/folder in your home directory. This is where all your output and
.tex files will be stored. The commands are:FlagDescriptionwalden -hshow help dialogwalden deleteDelete an existing journalwalden todayNew entry in specified journalwalden listList names of journalswalden buildCompile journal as .pdfwalden viewView journal as .pdfTODO:better support for journal names with spaces (replace " " with _ for path)better cli support using click or argparsechange path where journals are storedallow journal import/exportplug-in system for things like weather/question of the day