Saravanan666/pypi-org huggingface dataset:
Package: watching-testrunner
WhyBecause unit testing is way more funwhen you don't have to switch out of your editor to get feedback from unit tests.when the feedback period from a change to feedback from your tests is shorter.I've seen the usefullness of a tool like this when toying with rubys
autotest command, but didn't like the complications of getting that
highly optimized code to work with setups like VMs and Docker Containers
where file system notifications don't reliably work.So this skips all the optimizations and just uses the simplest possible
algorithm - iterate all files and see what changed. And that works
surprisingly well.In addition to that it's dead simple, has no dependencies and isreallysmall.Usage%watching_testrunner--help
Usage:watching_testrunner[options][--]command[arguments...]Options:-h,--helpshowthishelpmessageandexit-bBASEPATH,--basepath=BASEPATHbasepathtowatchforchanges-pWATCH_WILDCARD,--pattern=WATCH_WILDCARDglob-stylepatternforfilenamestowatchExamples$watching_testrunnernosetestsThis will run nosetests whenever any python file below the current directory changes$watching_testrunner--nosetests$NOSETESTS_ARGUMENTSWill run nosetests all the same, but will not try to parse any of the nosetests arguments.$watching_testrunner--basepathfoo/bar--pattern="*"nosetests$NOSETESTS_ARGUMENTSThis will run nosetests whenever any file below ./foo/bar changes.$watching_testrunner--basepathpath/to/js_tests--pattern="*.js"jasmine--consoleThis will run jasmine --console whenever any js file below./path/to/js_testschanges (i.e. you
can use the watching testrunner to get auto test execution using any tool for any language)Many thanks toFelix Schwarzfor the original implementation after me pestering him about this ideaTony Narlockfor prompting me to port this to python 3, hosting it on his account and caring for it's continued development
Package: watchio
WatchioWatchIO - Python package to watch process IO.Thewatchiopackage provides utilities to watch for IO activities of Unix processes. It
works by reading the Unix process information file/proc/{pid}/ioperiodically. You can
only use it on a system where/procis mounted, and for processes that you have tracing
access to.An example use case is a microserver displaying static web pages created by a separate
program that takes a moderate amount of resources. A sensible implementation updates the
static pages only when users are viewing the results. Thewatchiomodule helps to watch
for IO activities of the server when the server has no other convenient indications of
activities
(such as saving accesses to a log file).Install the package frompypi.orgbypipinstallwatchioUsageIn a polling loop in Python code:watcher=watchio.WatchIO([123,456])## Use in a polling loop to update static web pages## poll() will return an integer##    -1:  every 600 seconds, or##    >0:  there are IO activities (checked every 10 seconds)whileTrue:ifwatcher.poll(timeout=600,step=10):## main work....On the Unix command linewatchiopoll1234vim--timeout600--step10./update_script.cshOnly processes owned by you are allowed. You can supply a process name instead of a
numerical process ID andwatchiowill look up all processes owned by you having that
name.See AlsoUnix /proc file system man pageiostat man pageCode on github:https://github.com/koobedoc/watchioPackage on PyPI:https://pypi.org/project/watchio/Online documentation:https://koobedoc.github.io/watchio/Project Informationpython-depends: psutil
docs: mkdocs
python-modules:  watchio
python-packages: watchio
Package: watchlib
watchlibwatchlibis a python module for loading, analyzing and visualizing Apple Watch health data.
A detailed documentation can be found in theWiki. To see the module in action you can try out thewatchlib demonstratoror look at some of thedemo notebooks.Disclaimer:This is still a work in progres! If you want to help with further development feel free to join me onDiscordwhere we can discuss together or write anIssuehere on GitHub.How to export Apple Watch health dataTo use this Python package you first have to export the health data like this:OpenHealthappOpen your profile in the upper right cornerScroll downTap on "Export all health data"Confirm that you want to export all health dataWait until the export has finished (this might take some minutes)Select "Save in files"Choose a folder and tap "Save"Last step is to unzip the "Export.zip" fileECGECG AnalysisCalculate various heart rate metrics from a 30 second ECG:beats per minute (bpm)time between heartbeats in msheart rate variability (hrv)coming soon: ECG wave detectionECG Plotting and Animationplot ECGplot ECG together with metricsanimate ECGWorkout RouteFiltering workout routes by:countrybounding box size in kmlength of workout in min3D animation of workout routes:coloring based on:elevationspeedcoursehorizontal accelerationvertical accelerationOther Health Dataloading and converting other health dataAnalysis of other health datacoming soonNotebook demosDataLoader DemoWorkout Route DemoElectrocardiogram DemoStreamlit demoECG heartbeat calculationWorkout AnimationWatch an example workout animationhere
Package: watchlion
A simple shell utility to monitor file system events on Mac OS X 10.7+ (Lion or newer).Shell UtilitiesWatch Lion comes with a utility script calledwatchlion.
Please typewatchlion--helpat the shell prompt to
know more about this tool.watchlioncan read.watchlion.ymlfiles and execute command within them in
response to file system events. The.watchlion.ymlfile will be monitored and
loading when it has been updated.An example.watchlion.ymlfile:build:
  coffee: make js
  haml:   make html
  py:     make test
  sass:   make css
loglevel: infoAn exampleMakefilefile:.SUFFIXES: .coffee .js
.coffee.js:
      coffee -b -c $<
.SUFFIXES: .js .min.js
.js.min.js:
      uglifyjs -nc -o $@ $<
COFFEE = $(wildcard *.coffee)
JS = $(COFFEE:.coffee=.js)
MINJS = $(JS:.js=.min.js)

.SUFFIXES: .haml .html
.haml.html:
      haml -f html5 -t ugly $< $@
HAML = $(wildcard *.haml)
HTML = $(HAML:.haml=.html)

.SUFFIXES: .sass .css
.sass.css:
      compass compile $< -c config.rb
.SUFFIXES: .sass .min.css
.sass.min.css:
      compass compile --environment production $< -c config.rb
      mv $*.css $@
SASS = $(wildcard *.sass)
CSS = $(SASS:.sass=.css)
MINCSS = $(SASS:.sass=.min.css)

css: $(MINCSS) $(CSS)
html: $(HTML)
js: $(JS) $(MINJS)
test:
      py.testThen runwatchlioncommand:$ watchlion
INFO:root:load_config: loading .watchlion.yml
...Will start building js files when you update a coffee file:...
INFO:root:make js
coffee -b -c main.coffee
uglifyjs -nc -o main.min.js main.js
...You can use control-C to stopwatchlion.InstallationInstalling from PyPI usingpip:pip install watchlionInstalling from PyPI usingeasy_install:easy_install watchlionInstalling from source:python setup.py installInstallation CaveatsThewatchlionscript depends onPyYAMLwhich links withLibYAML,
which brings a performance boost to the PyYAML parser. However, installingLibYAMLis optional but recommended. On Mac OS X, you can usehomebrewto install LibYAML:brew install libyamlSupported PlatformsMac OS X 10.7+ (requireFSEvents)DependenciesPython 2.6 or above.XCodePyYAMLLicensingWatch Lion is licensed under the terms of theMIT.Copyright 2012 ENDOH takanao.Projectsource codeis available at Github. Please report bugs and file
enhancement requests at theissue tracker.
Package: watchlist
Useswishlistto monitor an
Amazon wishlist and send an email when prices change.InstallationInstall:$ pip install watchlistOr be bleeding edge:$ pip install "git+https://github.com/Jaymon/watchlist#egg=wishlist"You’ll need to setup aSendgridaccount (if
you don’t have one already, there is a free tier).And you’ll need some environment variables:export SENDGRID_KEY=YOUR_SENDGRID_API_KEY
export BROWSER_CACHE_DIR=/var/watchlist
export PROM_DSN_1="prom.interface.sqlite.SQLite://${BROWSER_CACHE_DIR}/watchlist.db#watchlist"Make sure yourBROWSER_CACHE_DIRactually exists.Installwishlist’s dependencies
also.If you have a private wishlist, then you’ll need to login to Amazon
before you can run watchlist, you can follow thewishlist
directionsto signin.Then you can run this:$ watchlist NAMEWhereNAMEis the Wishlist name, basically the string in the urlhttps://www.amazon.com/gp/registry/wishlist/NAME. You can set this
command up in a cron job to have it run periodically and send you
updates.
Package: watchlog
watchlogwatchlogis a Python package for monitoring log files and sending parsed logs to a specified URL using HTTP POST
requests.name = "watchlog"description = "monitoring log files and sending parsed logs to a specified URL"authors = ["Euraxluoeuraxluo@outlook.com"]license = "The MIT LICENSE"repository = "https://github.com/Euraxluo/watchlog"version = "0.1.*"InstallationYou can installwatchlogusing pip:pipinstallwatchlogUsageTo usewatchlog, you need to create a configuration file in JSON format. Here is an example configuration file:{"check_interval":5,"check":true,"files":[{"path":"/path/to/log/file.log","reg":"^(?P<time>[^ ]*) (?P<level>[^ ]*) (?P<module>[^ ]*) (?P<line>[^ ]*) (?P<message>.*)$","url":"http://example.com/api/logs","latest":true,"enable":true,"headers":{"Content-Type":"application/json"},"auth":{"username":"user","password":"pass"}}]}path: The path of the log file to monitor.reg: A regular expression used to parse the log file.url: The URL to send the parsed logs to.latest: Start monitoring from the latest logs.enable: Indicates that this configuration will be enabled, which defaults to true.headers: A dictionary of headers to include in the HTTP POST request.auth: A dictionary withusernameandpasswordkeys for basic authentication.check: if open check ,it will loop check the config filecheck_interval: circle check interval time(s)Once you have created the configuration file, you can start monitoring the log file by calling thestart()function
from thewatchlogmodule:importasynciofromwatchlogimportstartloop=asyncio.get_event_loop()loop.run_until_complete(start('path/to/config.json'))You can also use we provide small scriptswatchlogpath/to/config/fileThis will start monitoring the log file specified in the configuration file and sending parsed logs to the specified URL
using HTTP POST requests.exampleexample use zinc_observe as log search_engine,Illustrates the use of the process.                     
├── __init__.py       
├── config.json             config file
├── docker-compose.yml      log search engine service
├── log.log                 log file
└── main.py                 main python file to monitor log fileLicensewatchlogis licensed under the MIT license.
Package: watchlog-connect-py
watchlogA python client forwatchlogserver .Usagefromwatchlog_connect_pyimportwatchlogConnectimportasyncioasyncdefmain():ws_client=watchlogConnect()awaitws_client.connect()# Send Metric: Increments a stat by a value (default is 1)awaitws_client.increment("page.view")awaitws_client.increment("page.view",75)# Send Metric: Decrements a stat by a value (default is 1)awaitws_client.decrement("Your_metric")awaitws_client.decrement("Your_metric",25)# Send Metric: Percentage a stat by a value (value is required. min is 0 and max is 100)awaitws_client.percentage("Your_metric",12.23)# Send Metric: To measure a specific metric (value is required)awaitws_client.gauge("Your_metric",12.23)# Send Metric: To send byte of a metric (value is required)awaitws_client.systembyte("Your_metric",1024000000)# for example : 1024000000 is 1 GB#Log managerawaitws_client.log("app or service","info message")awaitws_client.successLog("app or service","success message")awaitws_client.errorLog("app or service","error message")awaitws_client.warningLog("app or service","warning message")if__name__=="__main__":asyncio.get_event_loop().run_until_complete(main())
Package: watchlogs
watchlogswatchlogsis a simple command line utility for watching multilpe log files and interleaving their contents tostdoutas each log is appended to.  It aims to achieve the functionality oftail -F, but with more colour.Usagewatchlogs --log_files /path/to/log1.txt,/path/to/log2.txt,....InstallationInstall viapip install watchlogs.  If you prefer to hack around with the source code, it's asingle python file.Behaviourwatchlogshas the following behaviour whenlog.txtis updated (assuming thatwatchlogs --log_files log.txthas been run):action:appending(supported)echo "x" >> log.txt(printsxto screen)action:moving/rotating(supported)touch log2.txt ; echo "y" > log2.txt ; mv log2.txt log.txt(printsyto screen)action:overwritng in-place(not supported):echo "z" > log.txt(zis lost)Implementationwatchlogsuses thetailflibrary to monitor OS events.DependenciesPython >= 3.6seaborncoloredtailfpsutil
Package: watchmap-sdk
# watchmap
A simple service to map microservices and API endpoints to create a dependency graph. Built over Express.js and utilizes express middlewares/request API.The High Level DesignMiddleware (implimented as an sdk) acts as live watcher for the incoming request to an API of a particular microservice from the concerned macroservice.The watchmap server runs as a next.js application which recieves anlytics logs from middleware to process the API dependency graph.The analytics dashboard and watchmap server make up as next app, the analytics dashboard provide visual presentation of API dependency graph.
Package: watchme
WatchMeReproducible watching of web changes. Good for:Monitoring system resources (battery, network, memory, cpu, etc.)Waiting for job postings to change or appearMonitoring some subset of prices from different vendorsTracking changes in GitHub repositories (stars, etc.) over timedocumentationWatchMe can watch for changes to an entire page, or a specific section of it.
It's appropriate for research use cases where you want to track changes in one
or more pages over time. WatchMe also comes with psutils (system tasks) built
in to allow for monitoring of system resources. Importantly, it is a tool that
implementsreproducible monitoring, as all your watches, are stored in a
configuration file that can easily be shared with others
to reproduce your watching protocol. For more information, see thedocumentation.Docker basesare
also available for monitoring processes inside containers.LimitationsWatchme usescronfor
scheduling jobs. This means that if a system was shutdown and then started again
after some time, watchme will not recover missing jobs during that period. If
you have ideas for how to better schedule jobs that you want added to the library,
pleaseopen an issue!LicensesThis code is licensed under the MPL 2.0LICENSE.
Package: watch-norminette
watch-norminetteUm script em Python que fica observando uma pasta e rodando o norminette nos arquivos quando forem salvosInstalaçãoClone o repositório com o seguinte comando:gitclonehttps://github.com/NiumXp/watch-norminette.git..instale os comandoswnewatch-norminetteutilizandopipinstall./watch-norminetteexportPATH=/home/coder/.local/bin:$PATHTrapaçaEsse script foi desenvolvido para rodar onorminetteda 42 toda vez que um arquivo for salvo e mostrar no terminal, mas pode ser considerado trapaça utilizar o watch-norminette nobasecampjá que"Durante avaliações, o camper precisa ter total conhecimento do código e das ferramentas que usa."Se você não souber como o código funciona, não utilize, caso esteja confuso em alguma parte, abra uma Issue e tire sua dúvida!ExemplosVocê pode utilizarwne/ouwatch-norminettepara utilizar o script.Sem flagsUtilizando apenaswatch-norminetteo script irá observar opathatual e toda vez que um
arquivo for salvo ele mostrará seus erros, se tiver.coder@nximenes-workspace-6cc74fc6b8-xm6kf:~$ watch-norminette
/home/coder/watch/teste.c:17:9  Found space when expecting tab
/home/coder/watch/teste.c:20:1  Empty line in function
/home/coder/watch/teste.c:21:12 Return value must be in parenthesis

[!] https://github.com/NiumXp/watch-norminette--errorsUtilizando a flag--errors, o script irá coletar todos os arquivos e mostrar a
quantidade dos que possuem erros.coder@nximenes-workspace-6cc74fc6b8-xm6kf:~$ watch-norminette --errors
  2 /home/coder/a.c
 22 /home/coder/b.c
  4 /home/coder/watch/teste.c

[!] https://github.com/NiumXp/watch-norminette
Package: watchntouch
This is essentially a horrible hacky solution to the fact that CIFS mounts cannot forward file-system event to inotify on linux. This in turn makes it so any number of “on-demand” compilers (e.g. compass, coffee-script) stop working when applied to mounted shares (among other things).The idea is to use the watchdog library to monitor a given directory using shitty-old polling, and then poke at the local filesystem so that inotify (and hopefully your apps/tools) pick up the changes. It is almost certainly a very bad idea to run this on a large file structure and/or over a slow network.Also note that only modification events can sanely be simulated this way. If you absolutely need some form of rm or mv event simlation, you may enable a less-then-sane behavior for such things using–simulate-rmand–simulate-mvrespectively.With that in mind, simply runwatchntouchin the directory you’d like to watch, or seewatchntouch -hfor more options.Installation on most platforms should be available viapip install watchntouch.Good luck!
Package: watch-open
Installingwatch-open can be installed via pip as follows:pip install watch-openUsagepython -m watchopen /path/to/file.pdf
watch-open /path/to/file.pdf
watch-open /path/to/dir -i "*.pdf" "*.xls"AuthorStanislav Doronin <mugisbrows@gmail.com>Licensewatch-open is distributed under the terms of MIT license, checkLICENSEfile.ContributingIf you’d like to contribute, fork the project, make changes, and send a pull
request. Have a look at the surrounding code and please, make yours look
alike :-)
Package: watchpylint
watchpylintA simple utility script which watches for changes in the given Python files, and runspylinton them. It then groups the output together by message type and saves the output
to a file.It will run lint processes in parallel (up to 8), and also has an option to wait for
output to be available before printing it. That allows you to setwatchpylint -w lint.txtas your editor's linter or compiler for easy browsing of the output.Examplecd ~/py/myproject
watchpylint *.py -o lint.txtThen, inemacs:M-x compile
watchpylint -w lint.txt
Package: watchserver
LivereloadA easy to use fully features live reloading and file watching http server. The server uses watchdog, queue, and ThreadedServer to create a live reloading environment. The interactions are fully customizable where a callback is called for file creation, update, and removal. The defaults are intuitive, but user customization is also easy.Features:Live reloadon html changeon static,cssorjs, changeAuto load custom error pagesIgnore patterns for files and directoriesUser defined values with smart defaultsWatch paths: defaults tocwdIgnore files/paths: defaults to nothing being ignoredFile event callbacks: defaults to reloading page on html change or static file changeserver port: defaults to3031server host: defaults tolocalhostbase directory, this is where the server discovers custom error files: defaults tocwdroot directory, this is where the server attaches and serves from: defaults tocwdsuppress, stops all server logging, defaults toFalseAuto open server in browser
Package: watchtower-cash-py
watchtower-cash-pyLibrary for building Python applications that integrate with Watchtower.cashInstallpipinstallwatchtower-cash-pySubscribe an AddressFor Watchtower to keep watch of the transactions of an address, it needs to be subscribed. A convenient function is included here to subscribe an address.importwatchtower# Subscribe function accepts either BCH or SLP addressaddress_index=0data={'addresses':{'receiving':'simpleledger:qqz95enwd6qdcy5wnf05hp590sjjknwfuq8sjhpv6x',# Receiving addresses generated from 0/address_index'change':'simpleledger:qr0rfdmntpdxn6le5ua7pc8v256n8vtj0u65c929le'# Change addresses generated from 1/address_index},'project_id':'0000-0000-0000',# <-- Generate this ID by creating a project at Watchtower.cash'wallet_hash':'abcd0123456',# <-- (Optional) You generate this to track which HD wallet the address belongs to'address_index':address_index,# <-- (Optional) The index used to generate the addresses from HD wallet'webhook_url':'https://xxx.com/webhook-call-receiver'# <-- (Optional) Your webhook receiver URL}result=watchtower.subscribe(**data)
Package: watchtower-pipeline
WatchtowerFollow these instructions to deploy Watchtower in your production pipeline.RequirementsPython 3.9+A working installation of Kitsu (optional)In order to generate data for Watchtower, follow these steps:Create a new folder, step into it and run:python -m venv .venvsource .venv/bin/activatepip install watchtower-pipelineSetup with example dataTo create an example project that will give you an idea of how the pipeline works:Runpython -m watchtower_pipeline.example -bNavigate to thewatchtowerfolder and runpython -m http.serverSetup with Kitsu-sourced dataIf you have a working Kitsu (and Zou) install and want to extract and visualize data from it:Create a.env.localfile as follows:KITSU_DATA_SOURCE_URL=https://<your-kitsu-instance>/api
KITSU_DATA_SOURCE_USER_EMAIL=user@example.org
KITSU_DATA_SOURCE_USER_PASSWORD=passwordRunpython -m watchtower_pipeline.kitsu -bCopy the content of thewatchtowerfolder into your webserverRunning the command without the-bflag will only fetch the data, and place it in a directory
calledpublic/data, which can then be synced to where thewatchtowerfolder has been placedSetup with custom-sourced dataIf you use a different production/asset tracking service, some scripting will be required.
The following steps are recommended:Set up a new Python project (using virtualenv)Runpip install watchtower-pipelineCheckdocs/custom-sources.mdfor how to use thewatchtower_pipelinemodule
Package: watchui
WatchUIDocumentation|Tesena|PypiBasic InfoCustom library for works with image, pdf and tesseract with RF.Folder structureWatchUI
└── .github/workflows           # Folder with CI for github actions
└── assets                      # Folder with images used for documantation as well as test data
└── test                        # Folder with example how to write rf test.
│    └── unit_tests             # Pytest unit test cases
│    └── test.robot             # File with simeple Robot Framework TCs
└── WatchUI                     # Folder with WatchUI library
│    └── WatchUI.py             # Main library file
│    └── IBasics                # Basic utilities and error handling
│    └── Keywords               # Keywords for working with images, PDFs and text(tesseract)
└── README.MD                   # Here you are :-)
└── setup.py                    # File for easy setup use with pip install .InstallYou can find detail inDocumentationbut basically use pip:pip install WatchUIor some python dependencies management tools, likepipenvorpoetryand their respective methods of libraries installation.Sample resultsImage where the differences are stored + You can see two black box in left corner. These black box are ignored during comparison.The red rectangles outlining missing elements on compared screensImportant notice for usersFor users with WindowsThe scikit image library is used for image matching. Unfortunately, this is a scientific library.
You need to have these libraries for installed to use them properly on windows:Windows 10 SDKC++ x64/x86 build toolsThese libraries can be downloaded by usingVS studio(not vscode) and installing the msbuild tool from VS studio.
Alternatively,this libraryshould also work.WatchUI 1.0 vs 2.x.xWatchUI 2.0 brings breaking changes. Dev team decided to streamline the library and focus it solely on the image and text comparison. This allows us to remove the implicit dependency on browser automation libraries - namely SeleniumLibrary, which was implicit part of the library via RFBuiltIn()import of the SeleniumLibrary instance.This is no longer the case - user of the WatchUI thereforecan and have to choose, what UI automation library will useand provide screenshots to the WatchUI keywords to be compared. It could be now used with SeleniumLibrary, Browser library, Sikuli, Appium or any other UI library where visual validation is required.Version 1.x.x is no longer supported, but it is still available on [Pypi](pip install WatchUI==1.0.11).