Saravanan666/pypi-org huggingface dataset:
Package: pause
Suspend the execution of your program for a given amount of time. This works similarly totime.sleep, but uses your computers timestamp to track time, versus a counter.For example, traditionally usingtime.sleep(3600), will pause the program for 60 minutes. If your computer goes into standby mode during minute one, and wakes up several hours later, your program will continue to be paused for 59 minutes.On the other hand, withpause.seconds(3600), if your computer goes into standby mode for several hours, the program will continue immediately after the machine wakes back up since the minimum amount of time has passed since the pause was started.How it worksWhen you create a pause, it will determine what the end time of that pause should be. Then a loop will be started that will continually check the current time against the end time. When the current time is equal or greater than the end time, the method will allow your program can resume.PrecisionThe precisionshouldbe within 0.001 of a second, however, this will depend on how precise your system sleep is and other performance factors.This module computes the pause duration between now and the future date, and then sleeps for half of this duration. After this time, it recomputes the new pause duration, repeating this process until the desired time is reached.InstallDownload the source code and run the following command:sudo python ./setup.py installOr, without downloading, install withpip:sudo pip install pauseExamples:Pause for half a second:import pause
pause.milliseconds(500)Or:import pause
pause.seconds(0.5)Pause for 1 minute:import pause
pause.minutes(1)Pause for 2 days:import pause
pause.days(2)Pause until a unix time, with millisecond precision:import pause
pause.until(1370640569.7747359)Pause using datetime:import pause, datetime
dt = datetime.datetime(2013, 6, 2, 14, 36, 34, 383752)
pause.until(dt)Functionsdays(num)Pause for this many dayshours(num)Pause for this many hoursmilliseconds(num)Pause for this many millisecondsminutes(num)Pause for this many minutesseconds(num)Pause for this many secondstime(num)Same as PauseFor.seconds()until(time)Pause your program until a specific end time.
‘time’ is either a unix timestamp in seconds (i.e. seconds since Unix epoch) or datetime objectweeks(num)Pause for this many weeks
Package: pauseonlock
Automatically pause your music player when the screen gets
locked and resume plaback, once the screen is unlocked again.This is basicallythe bash script with the same namerewritten in Python.
The benefit of the Python version is that itshoulddetect the screensaver
you use and running player(s) automatically, as long, as they are visible on
the D-Bus. So, no need for ever growing arrays of supported applications in
the code and no configuration necessary.InstallationPause on Lock is available on pypi, so all you have to do is runpip install pauseonlock.UsageAfter installing, simply runpauseonlock. There will be no output, since the
program is intended to be run in the background. For maximum convenience configure
your desktop environment to startpauseonlockevery time you log in.DependenciesThe only dependency ispython-dbus-nextwhich itself has no further dependencies.
Package: pautobot
🔥 PⒶutoBot 🔥Private AutoGPT Robot- Your private task assistant with GPT!🔥Chatto your offlineLLMs on CPU Only.100% private, no data leaves your execution environment at any point.🔥Ask questionsto your documents without an internet connection. Engine developed based onPrivateGPT.🔥Automate taskseasily withPAutoBot plugins. Easy for everyone.🔥Easy coding structurewithNext.jsandPython. Easy to understand and modify.🔥Built withLangChain,GPT4All,Chroma,SentenceTransformers,PrivateGPT.The supported extensions are:.csv: CSV,.docx: Word Document,.doc: Word Document,.enex: EverNote,.eml: Email,.epub: EPub,.html: HTML File,.md: Markdown,.msg: Outlook Message,.odt: Open Document Text,.pdf: Portable Document Format (PDF),.pptx: PowerPoint Document,.ppt: PowerPoint Document,.txt: Text file (UTF-8),I. Installation and Usage1. InstallationPython 3.8 or higher.InstallPAutoBot:pipinstallpautobot2. UsageRun the app:python-mpautobot.appor just:pautobotGo tohttp://localhost:5678/to see the user interface. You can choose one of the two modes:Chat OnlyDocuments Q&AUpload some documents to the app (see the supported extensions above). You can trydocs/python3.11.3_lite.zipfor a quick start. This zip file contains 45 files from thePython 3.11.3 documentation.Force ingesting documents withIngest Databutton.You can also run PAutoBot publicly to your network or change the port with parameters. Example:pautobot--host0.0.0.0--port8080II. Development1. Clone the source codegitclonehttps://github.com/nrl-ai/pautobotcdpautobot2. Run your backendPython 3.8 or higher.To install Pautobot from source, frompautobotsource code directory, run:pipinstall-e.Run the app:python-mpautobot.appGo tohttp://localhost:5678/to see the user interface.2. Run your frontendInstall the dependencies:cdfrontend
npminstallRun the app:npmrundevGo tohttp://localhost:3000/to see the user interface. Use this address to develop the frontend.
Package: pavan-housing
Guid for Housing-ProjectCloning the RepositoryTo clone the repository, you will need to have git installed on your machine. You can check if git is installed by running the command git --version in your terminal. If git is not installed, you can download it from the official website.Once git is installed, you can clone the repository by running the following command:git clone https://github.com/pavanbongu7/mle-training-mlflow>.gitSetting up the EnvironmentTo set up the environment, you will need to have conda installed on your machine. You can check if conda is installed by running the command conda --version in your terminal. If conda is not installed, you can download it from the official website.Once conda is installed, you can create the environment by running the following command:conda env create -f env.ymlThis command will create an environment based on the specifications in the env.yml file.To activate the environment, run the following command:conda activate mle-devInstalling the PackageTo install the package, you can use the following command:pip install .The dot(.) here denotes the current folder
Package: paver-templates
Create the the layout of a paver-enable package, including:pavement.py;README.rst, with basic installation instructions;LICENSE (support BSD and (A/L)GPL licenses by default). For a GPL licenses,
it will copy the required GPL license copies;MANIFEST.in;docs/conf.py and docs/index.rst. docs/index.rst simple include the content
of README.rst;and your empty package.InstallationThe easiest way to get Paver-Templates is if you havesetuptoolsinstalled:easy_install paver-templatesUsageAs simple as:paster create -t paver_package <package name>DevelopmentIf you would like to help the development of this package,fork this projectorreport bugs.The Paver-template project contains a virtualenv bootstrap script
that will install all required packages for development:python bootstrap --no-site-packages
source virtual-env/bin/activate
paver developIf you would rather use virtualenvwrapper, the project contains a list of
requirement suitable for pip:mkvirtualenv --no-site-packages paver-templates
easy_install pip
pip install -r dev-requirements.txt
paver developChanges0.1.0b3 (Aug 4, 2009):Fix issues with installation of Paver. As a result, Paver-templates is not
anymore in paver’s namespace; paver_package template is now atpaver-templates#paver_package.0.1.0b2 (Jul 22, 2009):change name of the template’s readme file to README.rst0.1.0a2 (Jul 22, 2009):Add missing template files from distribution.Fix bug with markers (like “-- Marker Name: --“).0.1.0a1 (Jul 18, 2009):Initial release.
Package: pavilioncms-python
pavilioncms-pythonThis is the Python Library for PavilionCMSDocumentationA comprehensive documentation of our API is availablehereInstallationYou can install the library from Pypi usingpipwhich is Python's Package manager$pipinstallpavilioncms-pythonUsageUsing the PavilionCMS python library is relatively easy after installation.In your python script, simple import the library and instantiate it with your read token.You can find the Read Token on the Blog detail page. Each Readtoken is unique and is tied only to a singlular blogfrompavilion_cmsimportPavilionCMSclient=PavilionCMS(read_token="your-read-token")Functionstags=> Get all your tagscategory=> Get all your categoriesposts=> Get all your published blog postsThe client's tags function has theall,get,nextandpreviousmethods for making requests.Theallandgetfunctions also accept an optionalparamsargument to add additional data to the response.Thenextandpreviousfunctions accept only a url which is gotten from the response of theallmethod.Reponses that request for a list are paginated.Example Usageresponse=client.tags.all()tags=response["results"]# data resultscount=response["count"]# Get all tags count (for pagination)next_url=response["next"]# Get the url for the next page. Defaults to None if there's no data. You can pass this url into the `next` functionprevious_url=response["previous"]# Get the url for the previous page. Defaults to None if there's no data. You can pass this url into the previous functionprint(tags[0])#{#   'id': '0b4cff81-c655-452a-881f-3a8eeab7ed09',#   'name': 'top table',#   'detail_url': '/api/v1/tag/0b4cff81-c655-452a-881f-3a8eeab7ed09/view/'# }# To get the categoriescategories=client.category.all()# To get the blog postsposts=client.posts.all()..__history:Release History0.1.0b0 (2022-12-26)Initial release on PyPI.0.1.0rc (2023-02-19)Initial release candidate.0.1.0rc1 (2023-02-19)Initial release candidate.
Package: pavis
# Pavis基于 Python3 的平行语料版本管理引擎软件参考 git 的版本管理机制，并针对平行语料管理用途，对功能进行了优化。软件的版本管理粒度精细到单句，能够为基于平行语料的学术、科研用途提供更加丰富的基础数据支持。[详细文档：Pavis.md](docs/pavis.md)
Package: pav-logger
PavLoggerThis currently provides a easy to use sqlite and postgres database commands.  If you install SQLCypher, the library can also handle the encryption of the database.InstallationRun the following to install:pipinstallpav_loggerUsageOptional:log_name:Providesawaytospecifyanotherlogfilename:Default:debugandexceptionshow_backtrace:ProvidesawaytospecifytoshowthebacktraceofanmessageDefault:Debug:FalseError:Truelog_severity:ProvidesawaytospecifyanumberforthelogforSQLitedatabaseDefault:Debug:0Error:4line_divider:Providesawaytochangethedividinglinebetweenmessages.Default:'#'importpav_loggerpav_logger=pav_logger.PavLogger()pav_logger.log_path="<Location Folder Path>"pav_logger.debug('This is a debug message.')try:raiseValueError('There is an error')exceptExceptionaserror:pav_logger.error(error)pav_logger.log_to_database=Truepav_logger.debug('This is a debug message.')try:raiseValueError('There is an error')exceptExceptionaserror:pav_logger.error(error)
Package: pavlok
Pavlok Python ClientPurposeThe Pavlok package makes it easy to play with your Pavlok device.It works in two modeslocal development modeserver modeLocal ModeIt can be used to play around with your device in a local development environment. It spins up a simpleFastAPIserver.Server ModeIt can be used to plug the module into your existing express server and build features/workflows for your pavlok device.InstallationUsing pippip install pavlokSetupYou would need two keys for the module to workClient IDClient SecretNavigatehereand login with your Pavlok account to get one.You'll need to choose a callback URL ofhttp://localhost:8000/authorizefor local mode.UsageFirst thing you'd need to do is import the module into your app.from pavlok.main import PavlokThe simplest and quickest way to start using the module is to try it in the local mode.pavlok = Pavlok(
    client_id=os.environ.get("client_id"),
    client_secret=os.environ.get("client_secret"),
    title="Pavlok Python Client",
)
pavlok.start()This spins up a server on port 8000.  (ex:http://localhost:8000/).It initializes the Pavlok. Now you can login and start sending the stimuli to your device.If you would like to configure a custom port for the local mode, you can do so by passing a custom options object as the third paramater to theinitmethod. Make sure to mention the port in the callback URL of application you createdherepavlok = Pavlok(
    client_id=os.environ.get("client_id"),
    client_secret=os.environ.get("client_secret"),
    title="Pavlok Python Client",
)
pavlok.start()To Use the module in the server mode, you would need to pass a couple of more options in the theinitmethod and ensure you call it before your server starts listeningpavlok = Pavlok(
    client_id=os.environ.get("client_id"),
    client_secret=os.environ.get("client_secret"),
    title="Pavlok Python Client",
)

app = FastAPI(title=self.title, version="0.1.0")

app.add_middleware(SessionMiddleware, secret_key="secret")

@app.get("/authorize")
async def authorize(request: Request):
    token = await pavlok.authorize(request)
    user = self.get_user(request)
    return tokenNow that you are authenticated, you can start sending the stimuli to your Pavlok device from the server.Stimuli methods for the server mode take a required parameter in the options object i.e.request. It is the request object thatFastAPIgets when one of it's api is called. Stimuli methods expects an authorization token stored on the request object to verify the user.So a simple call to one of the stimuli method would look like@app.get("/vibrate")
@app.get("/vibrate/{strength}")
async def vibrate(request: Request, strength: str = "200"):
    if self.token is None:
        response = RedirectResponse(url="/login")
        return response
    stimuli_response = await self.vibrate(strength=strength)
    return templates.TemplateResponse(
        "index.html", {"request": request, "token": self.token, 
        "message": stimuli_response}, status_code=200
    )LicenseLicensed under the MIT license.
Package: pavlova
pavlovais a library that assists in mapping an unknown input into a
dataclass.fromdatetimeimportdatetimefromdataclassesimportdataclassfrompavlovaimportPavlova@dataclassclassInput:id:intname:strdate:datetimePavlova().from_mapping({'id':10,'name':100'date':'2018-08-10',},Input)# Input(id=10, name='100', date=datetime.datetime(2018, 8, 10, 0, 0))Pavlova was born out of frustration with the lack of typing support for
existing deserialization libraries. With the introduction of dataclasses in
Python 3.7, they seemed like the perfect use for defining a deserialization
schema.Supported functionalityParsing of booleans, datetimes, floats, ints, strings, decimals, dictionaries,
enums, lists are currently supported.There are more parsers to come, however to implement your own custom parser,
simply implementPavlovaParserinpavlova.parsers, and register it with the
Pavlova object with theregister_parsermethod.InstallationpipinstallpavlovaUsage with Flaskfromdataclassesimportdataclass,asdictfromflaskimportFlask,jsonifyfrompavlova.flaskimportFlaskPavlovapavlova=FlaskPavlova()app=Flask(__name__)@dataclassclassSampleInput:id:intname:str@app.route('/post',methods=['POST'])@pavlova.use(SampleInput)defdata(data:SampleInput):data.id=data.id*len(data.name)returnjsonify(asdict(data))app.run()Adding Custom TypesThere are a couple of different ways to implement new types for parsing in
pavlova. In general, the process is to add a parser a specific type. For
validation you should raise a TypeError or ValueError.The first one, is creating a new type that extends an existing base type. Here
is an example on how to implement an Email type, which is a string but performs
validation.frompavlovaimportPavlovafrompavlova.parsersimportGenericParserclassEmail(str):def__new__(cls,input_value:typing.Any)->str:ifisinstance(input_value,str):if'@'ininput_value:returnstr(input_value)raiseValueError()raiseTypeError()pavlova=Pavlova()pavlova.register_parser(Email,GenericParser(pavlova,Email))Another way, is to implement your own pavlova parser, rather than using your
the built inGenericParserparser.importdatetimefromtypingimportAny,TupleimportdateparserfrompavlovaimportPavlovafrompavlova.parsersimportPavlovaParserclassDatetimeParser(PavlovaParser[datetime.datetime]):"Parses a datetime"defparse_input(self,input_value:Any,field_type:Type,path:Tuple[str,...])->datetime.datetime:returndateparser.parse(input_value)pavlova=Pavlova()pavlova.register_parser(datetime.DateTime,DatetimeParser(pavlova))RequirementsPavlova is only supported on Python 3.6 and higher. With Python 3.6, it will
install thedataclassesmodule.
With Python 3.7 and higher, it will use the built-in dataclasses module.LicenseGNU LGPLv3. Please seeLICENSEandCOPYING.LESSER.
Package: pavo
PAVO: PAthological Visualization ObsessionWelcome topavo:wave:, a visualization tool forpado datasets.pavo's goal is to provide a testbed for easy prototyping of data
visualizations of whole slide images and metadata of digital pathology datasets.We strive to make your lives as easy as possible: If setting uppavois hard or unintuitive, if its interface is slow or if its
documentation is confusing, it's a bug inpavo.
Always feel free to report any issues or feature requests in the issue tracker!Developmenthappens on github:octocat:InstallationTo install pavo clone the repo and runpip install .Note that you need
a "nodejs==16.*" installation to be able to build from source.Usagepavois used to visualizepadodatasets. If you have apadodataset
just run:pavoproductionrun/path/to/your/datasetand access the web ui under the printed address.Development Environment SetupInstallgitandcondaandconda-devenvClone pavogit clone https://github.com/bayer-group/pavo.gitChange directorycd pavoRunconda devenv --env PAVO_DEVEL=TRUE -f environment.devenv.yml --print > environment.ymlRunconda env create -f environment.ymlActivate the environmentconda activate pavoSetup the javascript dependenciesnpm install .(optional, handled insetup.py)Note that in this environmentpavois already installed in
development mode, so go ahead and hack.Run tests viapytestRun the static type analysis viamypy pavoLaunch a development instance viapavo development runContributing GuidelinesCheck thecontribution guidelinesPlease usenumpy docstrings.When contributing code, please try to use Pull Requests.tests go hand in hand with modules ontestspackages at the same level. We usepytest.AcknowledgementsBuild with love by theMachine Learning Researchgroup at Bayer.pavo: copyright 2020 Bayer AG
Package: pavouk-ecs
pavouk-ecsAn Entity Component System (ECS) framework for Python.Installationpipinstallpavouk_ecsExampleimportpygameimportsysfromdataclassesimportdataclassfrompavouk_ecsimportManagerfrompavouk_ecs.systemimportSystemRESOLUTION=(160,160)BACKGROUND_COLOR=(10,10,10)###### COMPONENTS###@dataclassclassArea:w:int=0h:int=0@dataclassclassColor:r:int=0g:int=0b:int=0@dataclassclassTransform:x:int=0y:int=0@dataclassclassVelocity:x:float=0.0y:float=0.0###### SYSTEMS###classRenderSystem(System):defon_update(self,surface,deltatime):foreinself.manager.query([Transform,Area,Color]):t=self.manager.get(Transform,e)a=self.manager.get(Area,e)c=self.manager.get(Color,e)r=pygame.Rect(t.x,t.y,a.w,a.h)pygame.draw.rect(surface,(c.r,c.g,c.b),r)classBouncingSystem(System):defon_update(self,surface,deltatime):foreinself.manager.query([Transform,Area,Velocity]):t=self.manager.get(Transform,e)a=self.manager.get(Area,e)v=self.manager.get(Velocity,e)ift.x<=0andv.x<0ort.x+a.w>=RESOLUTION[0]:v.x=-v.xift.y<=0andv.y<0ort.y+a.h>=RESOLUTION[1]:v.y=-v.yt.x+=v.xt.y+=v.y###### GAME###classGame:def__init__(self):self.running=Truepygame.init()pygame.display.set_caption("Pavouk ECS Example")self.clock=pygame.time.Clock()self.screen=pygame.display.set_mode(RESOLUTION)self.manager=Manager()player=self.manager.create_entity()t=self.manager.assign(Transform,player)t.x=16*4t.y=16*4a=self.manager.assign(Area,player)a.w=16a.h=16c=self.manager.assign(Color,player)c.r=200c.g=200c.b=200v=self.manager.assign(Velocity,player)v.x=-1.0v.y=2.0self.manager.add_system(BouncingSystem)self.manager.add_system(RenderSystem)defrun(self):whileself.running:self.screen.fill(BACKGROUND_COLOR)events=pygame.event.get()self._handle_events(events)self.manager.update_systems(self.screen,0)pygame.display.flip()self.clock.tick(60)pygame.quit()sys.exit()def_handle_events(self,events):foreinevents:ife.type==pygame.KEYDOWN:ife.key==pygame.K_ESCAPE:self.running=Falseelife.type==pygame.QUIT:self.running=Falsedefquit(self):self.running=Falseif__name__=="__main__":game=Game()game.run()
Package: pawabot
pawabotA bot for many things: aria2 management, torrent sites crawling, media organization with filebot and plex.This bot provides a command to search for torrents on the web, and let you select them for download.
There is a basic permission system allowing to manage multiple users for one bot.Requirementspawabot requires Python 3.6 or above.To install Python 3.6, I recommend usingpyenv.# install pyenvgitclonehttps://github.com/pyenv/pyenv~/.pyenv# setup pyenv (you should also put these three lines in .bashrc or similar)exportPATH="${HOME}/.pyenv/bin:${PATH}"exportPYENV_ROOT="${HOME}/.pyenv"eval"$(pyenvinit-)"# install Python 3.6pyenvinstall3.6.8# make it available globallypyenvglobalsystem3.6.8InstallationWithpip:python3.6-mpipinstallpawabotWithpipx:# install pipx with the recommended methodcurlhttps://raw.githubusercontent.com/cs01/pipx/master/get-pipx.py|python3

pipxinstall--pythonpython3.6pawabotSetupCreate your Telegram bot account by talking to the@godfatherbot.Write your bot token in~/.config/pawabot/bot_token.txt,
or set and export the environment variableBOT_TOKEN.Register your Telegram main account as administrator in the database with:pawabot create-admin -i MY_TG_ID -u MY_TG_USERNAMEUsageusage: pawabot [-h] [-L {TRACE,DEBUG,INFO,SUCCESS,WARNING,ERROR,CRITICAL}]
               ...

optional arguments:
  -h, --help            show this help message and exit

Commands:
  
    run                 Run the bot.
    create-admin        Create an administrator in the database.
    create-user         Create a user in the database.
    list-users          List registered users.

Global options:
  -L {TRACE,DEBUG,INFO,SUCCESS,WARNING,ERROR,CRITICAL}, --log-level {TRACE,DEBUG,INFO,SUCCESS,WARNING,ERROR,CRITICAL}
                        Log level to useCommands:create-admincreate-userlist-usersruncreate-adminusage: pawabot create-admin [-h] [-i UID] [-u USERNAME]

Create an administrator in the database.

optional arguments:
  -h, --help            Show this help message and exit.
  -i UID, --uid UID     Telegram user id.
  -u USERNAME, --username USERNAME
                        Telegram user name.create-userusage: pawabot create-user [-h] [-i UID] [-u USERNAME] [-a]

Create a user in the database.

optional arguments:
  -h, --help            Show this help message and exit.
  -i UID, --uid UID     Telegram user id.
  -u USERNAME, --username USERNAME
                        Telegram user name.
  -a, --admin           Give admin access.list-usersusage: pawabot list-users [-h]

List registered users.

optional arguments:
  -h, --help  Show this help message and exit.runusage: pawabot run [-h]

Run the bot.

optional arguments:
  -h, --help  Show this help message and exit.Screenshots/start/help/search
Package: pawflim
pawFLIM: denoising via adaptive binning for FLIM datasetsInstallationpawFLIM can be installed from PyPI:pip install pawflimUsageimportnumpyasnpfrompawflimimportpawflimdata=np.empty((3,*shape),dtype=complex)data[0]=...# number of photonsdata[1]=...# n-th (conjugated) Fourier coefficientdata[2]=...# 2n-th (conjugated) Fourier coefficientdenoised=pawflim(data,n_sigmas=2)phasor=denoised[1]/denoised[0]Note that we use the standard FLIM definition for the $n$-th phasor $r$:$$ r_n = \frac{R_n}{R_0} $$where$$ R_n = \int I(t) , e^{i n \omega t} dt $$is the $n$-th (conjugated) Fourier coefficient.See the notebook inexamplesfor an example with simulated data.