Saravanan666/pypi-org huggingface dataset:
Package: cligpt
Command Line Inferface for ChatGPTInstallationpipinstall--upgradecligptGetting Started# Fill in your OpenAI API keyexportOPENAI_API_KEY=[sk-xxxx]# Launchcligpt# Switch roles (you may use abbreviations as long as they do not clash with other roles)@revise(or@revis|@revi|@rev|@re|@r)Advanced OptionsCustomize your rolesEdit the configuration file:vim~/.cligpt/config.jsonTurn on/off Auto-copy (default=on)cligptautomatically copies the last response to your clipboard. To enable/disable it, launchcligptwith the following command:cligpt--no_auto_copyAdjust context length (default=6)Context length refers to the number of prompts+responsescligptshould remember. For example, if you want it to remember the last 3 prompts + 3 responses, launchcligptwith the following command:cligpt--context_length=6Turn on/off stream mode (default=on)Stream mode displays words popping up one by one. To enable/disable it, launchcligptwith the following command:cligpt--no_streamProxy (default=None)Use a proxy for the OpenAI API:cligpt--proxy=http:127.0.0.1:9000Uninstallationpipuninstallcligpt(rm-rf~/.cligpt)
Package: cli-helpers
CLI Helpers is a Python package that makes it easy to perform common tasks when
building command-line apps. It’s a helper library for command-line interfaces.Libraries likeClickandPython Prompt Toolkitare amazing tools that help you create quality apps. CLI Helpers complements
these libraries by wrapping up common tasks in simple interfaces.CLI Helpers is not focused on your app’s design pattern or framework – you can
use it on its own or in combination with other libraries. It’s lightweight and
easy to extend.What’s included in CLI Helpers?Prettyprinting of tabular data with custom pre-processingConfig file reading/writingRead the documentation athttp://cli-helpers.rtfd.io
Package: cliifs
cliifsCommand Line Interface Iterated Function SystemsRender and view fractals, using the chaos game, from iterated functions systems right on your terminal.ScreenshotsInstallationInstall via pip withpip install cliifsor download the appropriate binary fromreleasesHow To Usecliifs reads in a plaintext file that contains the univariate linear functions you wish to use for your IFS.The first line must begin with either1Dor2D.The following lines each represent the coefficients of linear equations, and you may add as many as you like.See below for specifics on how to write these files.See the included examples for more details.Invocation exampleTo render the IFS stored in a file calledexampleFile, simplycdinto the directory that containsexampleFileand run:cliifs exampleFileTo render, with animation and color, runthe command:cliifs exampleFile -c -aFlagscliifs accepts the following flags-hfor help.-cto render in random colors.-i Nto render using N iterations.-ato animate.-d Dto delay each frame by D milliseconds if animating.-m Mto set the collection of markers to be used at random.1 Dimensional SystemsOne dimensional systems are given as a test file whose first line reads simply1D.Each subsequent line has the forma bwhich represents the functionf(x) = ax+b.For example, the Cantor set, generated byf(x) = x/3+0andg(x) = x/3+2/3, would be given as a text file with the following lines:1D0.333 00.333 0.6662 Dimensional SystemsTwo dimensional systems are given as a test file whose first line reads simply2D.Each subsequent line has the forma1 b1 a2 b2 c1 c2which represents the vector functionf(v) = Av+b.In this function,Ais the matrix with rows{a1, b1}and{a2, b2},bis the vector{c1, c2}andvis the position vector{x,y}.For example, the Sierpinski Gasket, generated byf(x,y) = (0.5x+0y, 0x+0.5y)+(0,0),g(x,y) = (0.5x+0y,0x+0.5y)+(0.5,0),
andh(x,y) = (0.5x+0y,0x+0.5y)+(0.25,0.5)would be given as a text file with the following lines:2D0.5 0 0 0.5 0 00.5 0 0 0.5 0.5 00.5 0 0 0.5 0.25 0.5
Package: clij2-fft
clij2-fft (featuring non-circulant rltv deconvolution)clij2-fft is a prototype implementation of a framework for OpenCl based FFT algorithms.  The most used algorithm from this project is the OpenCL implementation of the non-circular Richardson Lucy deconvolution algorithm with total variation regularization, which can be called as followsfrom clij2fft.richardson_lucy import richardson_lucy_nc
decon_clij2=richardson_lucy_nc(im,psf,100,0.0002)or for large image that need to be split up into chunks with daskfrom clij2fft.richardson_lucy_dask import richardson_lucy_dask
decon=richardson_lucy_dask(img, psf, 100, 0.0001)If you need support for the library please post a question on theImage.sc Forum.Long term we hope to integrate FFT based math more closely with theClic project.  The goal is to make it easy to write algorithms such as convolution, correlation, registration and deconvolution that consist of a series of FFTs combined with other math operations.
Package: cli-jarvis
Jarvis-CLIA custom CLI tool built in Python that is my personalized assistantHow I created it:Developmentvirtualenv venvvenv\Scripts\activatepython setup.py developDistributingpy -m pip install --upgrade buildpy -m buildtwine upload dist/*Important Docs:https://packaging.python.org/en/latest/tutorials/packaging-projects/https://medium.com/nerd-for-tech/how-to-build-and-distribute-a-cli-tool-with-python-537ae41d9d78
Package: cliks
cliksCLI for facilitate and standardize commit message.Format:ACTION(TOPIC): COMMIT_MSG #TICKET_NUM [!TAG ...]ACTION:feat: is for new features, big improvementfix: is for bug fixesrefactor: is for code refactoring, without any visual user changechore: is for any else but the apptest: is for any kind of tests (functionnal, unitary...)style: is for cosmetic changes (spaces vs tab...)docs: is for documentationTOPICis optional and to specify the part on the app you're working on is WHO is concerned by the change.dev:  is for developpers (API changes, refactors...)usr:  is for final users (UI changes)pkg:  is for packagers   (packaging changes)test: is for testers     (test only related changes)COMMIT_MSGis ... well ... the commit message itself.#TICKET_NUMis the ticket number associated. If you don't want to specify a ticket number, use:#noticket; or#ntTAGsAre additionnal adjective as 'refactor' 'minor' 'cosmetic'. They are preceded with a '!' or a '@' (prefer the former, as the latter is wrongly interpreted in github.) Commonly used tags are:refactor: is obviously for refactoring code onlyminor: is for a very meaningless change (a typo, adding a comment)cosmetic: is for cosmetic driven change (re-indentation, 80-col...)wip: is for partial functionality but complete subfunctionality.Example:git commit -m "feat(ansible):adding configuration with common roles #INF-4"git commit -m "fix(docker):disabling systemd and installing sysvinit #noticket"git commit -m "docs():removing unwanted files on the doc #noticket"git commit -m'Please note that multi-line commit message are supported, and only the first line will be considered as the "summary" of the commit message. So tags, and other rules only applies to the summary.  The body of the commit message will be displayed in the changelog without reformatting.'
Package: clilabs
DEPRECATED BY clitoohttps://yourlabs.io/oss/clitooAnd djclihttps://yourlabs.io/oss/djcliclilabs: the python CLI that gets things done.Sometimes I want to execute a python callback with some args on the command
line, but i get frustrated that it always requires to wrap my command in a
wrapper of some sort. Clilabs unfrustrates me.Install:$ pip install clilabsHelp:$ clilabs
clilabs automates python callables parametered calls.

Things starting with - will arrive in clilabs.context.

Examples:

    clilabs help your.mod:main
    clilabs debug your.mod -a --b --something='to see' how it=parses
    clilabs your.mod:funcname with your=args
    clilabs help clilabs.django
    clilabs help django
    clilabs clilabs.django:list auth.user
    clilabs django:list auth.user  # also works
    # refer to the root one
    clilabs ~django.db.models:somefunc somearg some=kwargDemo:$ clilabs debug ~your.mod:yourfunc -a --b --something='to see' how it=parses
Could not import your.mod
Args: ('how',)
Kwargs: {'it': 'parses'}
Context args: ['a', 'b']
Context kwargs: {'something': 'to see'}Moar in tutorial.mdMaking your own commandAdd to your setup.py:entry_points={
    'console_scripts': [
        'yourcmd = yourpkg.cli:cli',
    ],
},Add in yourpkg/cli.py:'''Your documentation that shows by default:

    yourcmd somefunc ...
'''
import clilabs

def cli(*argv):
    argv = list(argv) if argv else ['help', 'yourpkg.cli']
    cb = clilabs.modfuncimp(*clilabs.funcexpand(argv[0], 'yourpkg.cli'))
    args, kwargs = clilabs.expand(*argv[1:])
    return cb(*args, **kwargs)

def main(...):
    '''Put your help text, that will show when the
    user runs the command without argument.'''
Package: cli-lite
Cli-LiteA simple framework to build a cli tool. Base onAlconnainstallpipinstallcli-liteexamplewrite as sample:# example.pyfromclilteimportBasePlugin,CommandLine,PluginMetadatafromarclet.alconnaimportAlconna,Arparma,Args,CommandMetaclassMyPlugin(BasePlugin):definit(self)->Alconna|str:returnAlconna("hello",Args["name",str],meta=CommandMeta("test command"))defmeta(self)->PluginMetadata:returnPluginMetadata("hello","0.0.1","my first plugin",["dev"],["john"])defdispatch(self,result:Arparma)->bool|None:returnprint(f"Hello!{result.name}")if__name__=='__main__':cli=CommandLine(title="My first CLI",version="example 0.0.1")cli.add(MyPlugin)cli.load_register('builtin.cache')cli.main()and execute the line:pythonexample.pyhelloworldyou will get the result:Hello!world
Package: cli-logger
cli_loggerEasy logger for python command line programs using click.What it doesUse this script in your programs to get pretty-printed messages printed to STDOUT. To see what it does, just execute the script in test_manuell (which does not contain a unit test, but a script to see what it does.Here's a screenshot:It comes with these features:Setting a severity level, to hide non-relevant / verbouse output.Printing text at level Debug, Information, Warning and Error.Retrieve a return code in case a warning (1) or an error (2) has been raised.Configurable progress bar.How to useProgram initialisationAt program initialisation, useset_minimum_severity_levelto decide from which level and above messages should be printed.LevelRankMessageClass=Description1LowestDEBUGInformation helping to understand the program flow or to search for errors. Of course, developers might use debuggers, but consider a productive use where debugging is not possible.2INFORMATIONDefault level. Information to the user that does not require to intervent.3WARNINGHint that something hasn't been as expected. Results might be erreneous.4HighestERRORSomething went wrong and it wasn't possible to resolve the situation.Program executionPrint to the screeneeeUsedebug('my message'),information('my message'),warninganderrorto create output.
log, information, set_minimum_severity_level, error, debug, warning, returnCode,Print a progress barprintProgressBarProgram terminationRetrieve a return codereturnCode()which indicates if a warning or error has been issued. For sure, a discussion could be opened wether this is a good method or wether exceptions would suit better.Rules to create a return code (last verified rule wins):EventReturn CodeOnly messages of typeDEBUGorINFORMATIONhave been issued.0At least oneWARNINGhas been issued.1At least oneERRORhas been issued.2InstallationThe code has been published onPyPi. To install, just use the commandpip --install cli-logger.
Package: clima-anom
Climatology and Anomalies in PythonOverviewThis code provides experimental and simples tools for differents operations on climate data, mainly obtaining climatologies and anomalies values, in addition to others operations such as data extraction from continent, ocean or a shapefile.Pip installpipinstallclima_anomManual installationclone clima_anom and install in exists or new conda env.Clone repo and installgitclonehttps://github.com/mhacarthur/clima_anom.gitcdclima_anom
pipinstall.DependenciesPython >= 3.5cartopy == 0.18.0netcdf4 == 1.5.7pyshp == 2.1.3Option: LinuxHow to install dependencies# cartopycondainstall-cconda-forgecartopy# netcdf4condainstallnetcdf4# pyshppipinstallpyshpDataThe data use for examples is in directory data. For complete data see:TRMM Precipitation L3 daily 0.25x0.25 V7ExampleRead  dataimportosimportclima_anomascadata_dir='..'+os.sep+'data'+os.sep+'3B42_199901_201212.nc'data=ca.read_netcdf(data_dir,2)lat=data['lat']lon=data['lon']pre=data['prec']pre_dictionary=ca.data_dictionary(pre)Colorbar exampleimportclima_anomascaimportmatplotlib.pyplotaspltcmap=plt.cm.Spectral_rcmap_midle_white=ca.colorbar_middle_white(cmap,'middle')Remove ocean or continentimportnumpyasnpimportclima_anomascadata_dir='..'+os.sep+'data'+os.sep+'3B42_199901_201212_climatology.nc'data=ca.read_netcdf(data_dir,2)lat=data['lat']lon=data['lon']pre=data['pre']pre_continent=ca.remove_continent_ocean(pre,lat,lon,'continent')pre_ocen=ca.remove_continent_ocean(pre,lat,lon,'ocean')Extract data using shapefileimportclima_anomascaimportcartopy.io.shapereaderasshpreaderfile_shape='..'+os.sep+'shapefile'+os.sep+''+os.sep+'Amazonas.shp'amazonas=list(shpreader.Reader(file_shape).geometries())data_dir='..'+os.sep+'data'+os.sep+'3B42_199901_201212_climatology.nc'data=ca.read_netcdf(data_dir,2)lat=data['lat']lon=data['lon']pre=data['pre']pre_amazonas=ca.extract_shapefile('..'+os.sep+'shapefile'+os.sep+'Amazonas.shp',pre,lat,lon,0)
Package: climactic
A simple testing framework for running shell commands and verifying their behavior. Tests are written as YAML files which specify the commands to run, along with assertions about the output (currently, stdout and file/directory contents).NOTE: climactic is a Python 3 packageFeaturesPytest integration via an automatically registered pluginAggregate tests recursively in a directory matching the pattern “test_*.yml” using the commandline toolclimacticCompatibility with the standardunittestpackageTests are run in a temporary directory to avoid data loss and path-dependent resultsSet environment variables per-test with the ‘env’ taskCompare stdout, directory structure, and file contents to expected string valuesbash-like ${VAR} substitution for input commands and output validation
Package: climaf
CliMAF doc is available atReadthedocs, which includesinstallation instructionsThe aim of CliMAF is to allow for an actual,easy, collaborative development of climate model outputs assessment suites by climate scientists with varied IT background, and to ultimately share such suites for the benefit of the Climate Science.It is basically a scriptable way to process NetCDFCF compliantclimate model outputsCliMAF was designed by Stéphane Sénési, who also developped most of the code before version 2.
Package: climafeis
climafeisCLI Python application for scraping daily climate data fromCanal CLIMAUNESP Ilha SolteirausingrequestsandBeautifulSoup 4.InstallationMake sure Python 3.8 or higher and pip are installedRunpip install climafeisDevelopmentCheck Python's versionpython -VInstall Python 3.8 or higher and pip, if they aren't already installed:Windowswinget install Python.Python.3.X(replace X with the desired minor version)Ubuntu based distrosapt install python3 python3-pipArch based distrospacman -S python python-pipFedoradnf install python3 python3-pipInstall poetryClone this repogit clone https://github.com/joaofauvel/climafeis.git && cd climafeisInstall requirementspoetry installOutput headersHeaderDescriptionDateObservation date (dd-mm-yyyy)TmeanMean temperature (ºC)TmaxMax temperature (ºC)TminMin temperature (ºC)RHmeanMean relative humidity (%)RHmaxMax relative humidity (%)RHminMin relative humidity (%)PmeanMean pressure (kPa)RnNet radiation (MJ/m^2*day)RlLiquid radiation (MJ/m^2*day)GSoil heat flux (MJ/m^2*day)PAR(μmoles/m^2)ETcatEvapotranspiration Class A Tank (mm/day)ET0pmReference evapotranspiration Penman–Monteith (mm/day)ET0catReference evapotranspiration Class A Tank (mm/day)U2maxMax windspeed at 2 meters (m/s)U2meanMean windspeed at 2 meters (m/s)U2dirWind direction at 2 meters (º)RainRainfall (mm)InsolationSolar insolation (h/day)ReferenceUsageDaily data from ILHA_SOLTEIRA station from 30/05/2020 (dd/MM/YYYY) to 03/05/2020climafeis ILHA_SOLTEIRA 30/05/2020 03/06/2020Daily data from MARINOPOLIS station from 30/05/2020 to todayclimafeis MARINOPOLIS 30/05/2020Daily data from ILHA_SOLTEIRA station from 30/05/2020 to today, supplying username and passwordclimafeis ILHA_SOLTEIRA 30/05/2020 -U user -P passwordusage: climafeis [-h] [-U USER] [-P PW] [-o OUT] [-l LOG] [-v] station start [end]

Scrape daily climate date from Canal CLIMA (https://clima.feis.unesp.br)

positional arguments:
station               station name: ILHA_SOLTEIRA, MARINOPOLIS, JUNQUEIROPOLIS, PARANAPUA, IRAPURU, 
                        POPULINA, SANTA_ADELIA_PIONEIROS, SANTA_ADELIA, BONANCA, ITAPURA, DRACENA
start                 start date dd/MM/YYYY (30/05/2020)
end                   end date dd/MM/YYYY (03/05/2020). Default: today

options:
-h, --help            show this help message and exit
-U USER, --user USER  override Canal CLIMA user set in the environment variable $USER_CLIMAFEIS
-P PW, --pw PW        override Canal CLIMA password set in the environment variable $PASSWD_CLIMAFEIS
-o OUT, --output OUT  output file. Default: <station>.csv
-l LOG, --log LOG     output log file. Default: stdout
-v, --verbose
Package: climage
CLImageConvert images to beautiful ANSI escape codes for display in command line interfaces.Available as both a CLI application and a Python library.Features8/16/256/Truecolor supportsCustom system color palettesToggleable Unicode mode, allowing up to 4x more detailCustom output sizeExample usageCLI$ climage --unicode --truecolor --cols 80 barney.jpgFor more detail and available options, run$ climage --help.Pythonimportclimageoutput=climage.convert('image.png',is_unicode=True)print(output)# Converting downloaded filefromPILimportImageimportrequestsresponse=requests.get('https://www.python.org/static/community_logos/python-logo-master-v3-TM-flattened.png')# Convert to RGB, as files on the Internet may be greyscale, which are not# supported.img=Image.open(BytesIO(response.content)).convert('RGB')# Convert the image to 80col, in 256 color mode, using unicode for higher def.converted=climage.convert_pil(img,is_unicode=True)print(converted)# Convert the image into 50px * 50px, as the convert_array function does not# perform resizing.img=Image.open('image.png').convert('RGB').resize((50,50))arr=np.array(img)output=climage.convert_array(arr,is_unicode=True)print(output)View additional examples on theproject homepage.
Package: climailsystem
CLI Mail SystemThis Is a simple Mail System which is used to Read and send mails using gmail api. If You want to try the beta version of this then install it using python python package index(pip) via following command$ pip3 install climailsystemYou can use this module as command line tool or you can use it as python moduleCLI Guide$ climail --helpThis will show You all the valid commands availableUsage: climail [OPTIONS] COMMAND [ARGS]...

Options:
  --help  Show this message and exit.

Commands:
  deleteapicreds
  mdetails
  relogin
  sendmessage
  sendmessage-attach
  udetailsarguments of command$ climail sendmessage --help
Usage: climail sendmessage [OPTIONS] EMAIL_ID_OF_SENDER SUBJECT MSSG

Options:
  --help  Show this message and exit.Module Guideimport sendmail
mssg = sendmail.sendmessage(email_address_of_sender,subject,mssg)
#used for sending email without attachment
mssg_attach  = sendmail.sendmessage(email_address_of_sender,subject,mssg,path_of_file_to_be_shared)
#used for sending email with attachment
user_details = sendmail.userdetails()
#used for checking details of user like email id, displaydetails
user_mssg_details = sendmail.usermessagedetails()
#used for checking details of user messages like total number of messages, threads etc
logout = sendmail.login()
#used for changing the user 
delete_Creds = sendmail.deleteapicreds()
#used for changing api credsFor Using this module you need Api credentials of Gmail Api , You can use the credentials present in client.json simply copy the credentials and paste it or you can create your own credentials at developer console. Please note that this is the one time process only i.e you have to enter the credentials only on your 1st use. when you will run this module as command line Interface for 1st time or will import this module in your project for 1 st time then a message will be displayed on Your screen.Enter CredsThen copy your api credentials and paste it on console.
Package: climaker
CliMakerPython package which allows to define a CLI argument parser (with subcommands) with a schema.
The only dependency is theargparselibrary.
Tested (a bit) with Python 3.6+Please,create an issueif you have a bug-report or find this package needs an improvement. (It definitely needs an improvement.)Installationpip install climakerExampleimportsysfromclimakerimportParser,Subcommands,Arguments,Arg# Define commands structurespec=Subcommands({'bake':Subcommands({'cake':Arguments([Arg('-s','--size',type_=int,default=10),Arg('--color',default='pink'),]),'cookie':Arguments([Arg('--kind',default='biscuit'),]),}),'eat':Arguments([Arg('edible',default='cookie'),])})# Create a parserparser=Parser(spec)# Parse argumentsaction=parser.parse_arguments(sys.argv[1:])print(action.command)# ['bake', 'cake']print(action.params)# {'size': 10, 'color': 'pink'}
Package: climanager
# CliMan## 项目简介该项目用于解析CLI命令行参数，基于argparser，采用类似单例模式### 安装pip install climan### 使用初始化CliMan.init(“desc…”)添加选项或者参数CliMan.add_flag(“-f”, “–flag”)
CliMan.add_arg(“cmd”)解析CliMan.parse()取值v1 = CliMan.get_str(“cmd”)
v2 = CliMan.get_float(“flag”)
Package: climata
climatais a pythonic interface for loading and processing time series data
from climate and flow monitoring stations and observers. climata leverages
a number of webservices as listed below.  climata is powered bywq.io, and shares its goal of maximizing the reusability of
data parsing code, by smoothing over some of the differences between various data formats.Getting Started# Recommended: create virtual environment
# python3 -m venv venv
# . venv/bin/activatepipinstallclimataSeehttps://github.com/heigeo/climatato report any issues.Available ServicesModuleClassesData SourceAgency/Org.climata.acisStationMetaIO,StationDataIOACISNOAA RCCsclimata.epaWqxDomainIOWQXEPAclimata.cocorahsCocorahsIOCoCoRaHSCoCoRaHSclimata.hydrometDailyDataIO,InstantDataIO,AgrimetRecentIOHydrometUSBRclimata.nwsHydroForecastIO,EnsembleForecastIO,EnsembleSiteIOCNRFCNWSclimata.snotelStationIO,StationDailyDataIO,RegionDailyDataIOSNOTEL AWDBNRCSclimata.usgsSiteIO,DailyValueIO,InstantValueIONWISUSGSUsageCommand-line interface:# Load metadata for sites in Upper Klamath Lake basinwqcatclimata.acis.StationMetaIO"basin=18010203">sites.csv# Load daily average temperature for these sitesPARAMS="basin=18010203,start_date=2017-01-01,end_date=2017-01-31,parameter=avgt"wqcatclimata.acis.StationDataIO"$PARAMS">data.csvPython API:fromclimata.acisimportStationDataIO# Load average temperature for sites in Upper Klamath Lake basinsites=StationDataIO(basin="18010203",start_date="2017-01-01",end_date="2017-01-31",parameter="avgt")# Display site information and time series dataforsiteinsites:printsite.nameforevtinsite.data:printevt.date,evt.avgtMore Python code examples are available via theclimata-viewer website.