Saravanan666/pypi-org huggingface dataset:
Package: cli-progress
Python Project TemplateA low dependency and really simple to start project template for Python Projects.See alsoFlask-Project-Templatefor a full feature Flask project including database, API, admin interface, etc.FastAPI-Project-TemplateThe base to start an openapi project featuring: SQLModel, Typer, FastAPI, JWT Token Auth, Interactive Shell, Management Commands.HOW TO USE THIS TEMPLATEDO NOT FORKthis is meant to be used fromUse this templatefeature.Click onUse this templateGive a name to your project(e.g.my_awesome_projectrecommendation is to use all lowercase and underscores separation for repo names.)Wait until the first run of CI finishes(Github Actions will process the template and commit to your new repo)If you wantcodecovReports and Automatic Release toPyPIOn the new repositorysettings->secretsadd yourPYPI_API_TOKENandCODECOV_TOKEN(get the tokens on respective websites)Read the fileCONTRIBUTING.mdThen clone your new project and happy coding!NOTE:WAITuntil first CI run on github actions before cloning your new project.What is included on this template?🖼️ Templates for starting multiple application types:Basic low dependencyPython program (default)use this templateFlaskwith database, admin interface, restapi and authenticationuse this template.or Runmake initafter cloning to generate a new project based on a template.📦 A basicsetup.pyfile to provide installation, packaging and distribution for your project.Template uses setuptools because it's the de-facto standard for Python packages, you can runmake switch-to-poetrylater if you want.🤖 AMakefilewith the most useful commands to install, test, lint, format and release your project.📃 Documentation structure usingmkdocs💬 Auto generation of change log usinggitchangelogto keep a HISTORY.md file automatically based on your commit history on every release.🐋 A simpleContainerfileto build a container image for your project.Containerfileis a more open standard for building container images than Dockerfile, you can use buildah or docker with this file.🧪 Testing structure usingpytest✅ Code linting usingflake8📊 Code coverage reports usingcodecov🛳️ Automatic release toPyPIusingtwineand github actions.🎯 Entry points to execute your program usingpython -m <cli_progress>or$ cli_progresswith basic CLI argument parsing.🔄 Continuous integration usingGithub Actionswith jobs to lint, test and release your project on Linux, Mac and Windows environments.Curious about architectural decisions on this template? readABOUT_THIS_TEMPLATE.mdIf you want to contribute to this template please open anissueor fork and send a PULL REQUEST.❤️ Sponsor this projectcli_progressAwesome cli_progress created by hiddifyInstall it from PyPIpipinstallcli_progressUsagefromcli_progressimportBaseClassfromcli_progressimportbase_functionBaseClass().base_method()base_function()$python-mcli_progress#or$cli_progressDevelopmentRead theCONTRIBUTING.mdfile.
Package: cli-progressbar
It’s a lightweight and easy to use progress-bar for
command-line/terminal applications.Installpip installcli-progressbarFeaturesSimple,LightweightandEasyto use.Single progress bar mode.Multiple progress bar mode.Custom bar characters.iteratefunction to auto handle progress bar inforloops.UsageSingle modefromcli_progressbarimportProgress# define progressbar instanceprogressbar=Progress(85)# start function pass 0 to update function and print progressbar# you can pass an string to show as statusprogressbar.start('start status')users=find_users()# return a list of users# you can fill goal like thisprogressbar.goal=len(users)fori,userinenumerate(users):# this function will update progressbar with new data and statusprogressbar.update(i,'processing status')# Do your stuff# stop function pass goal itself to update functionprogressbar.stop('stop status')But it’s boaring… so useiteratefunction:fromcli_progressbarimportProgressprogressbar=Progress()progressbar.start('start status')users=find_users()foruserinprogressbar.iterate(users,'processing status'):# Do your stuffprogressbar.stop('stop status')iteratefunction also support dynamic status, by passing a function
and each element of list as it input.foruserinprogressbar.iterate(users,lambdauser:'processing '+user):# Do your stuffMultiple modefromcli_progressbarimportProgress,MultiProgressManager# define multi progress instancemanager=MultiProgressManager()# now define any progress bar you needprogress_1=Progress()progress_2=Progress()# now add them to multi progress managermanager.append(progress_1)manager.append(progress_2)# Done! It's ready to use like a single progress!progress_1.start('start progress 1')progress_2.start('start progress 2')foriinprogress_1.iterate(range(8),'state progress 1'):forjinprogress_2.iterate(range(5),'state progress 2'):# Do your stuffprogress_1.stop('stop progress 1')progress_2.stop('stop progress 2')But maybe you want it more simple, so I have an easier solution!fromcli_progressbarimportMultiProgressManager# define multi progress instance; but this time, pass 2 argumentsmanager=MultiProgressManager(progress_count=2,# default: 0progress_prefix='progress_'# default: progress_)# now you can access 2 progressbar, just request them from managermanager.progress_1.start('start progress 1')manager.progress_2.start('start progress 2')foriinmanager.progress_1.iterate(range(8),'state progress 1'):forjinmanager.progress_2.iterate(range(5),'state progress 2'):# Do your stuffmanager.progress_1.stop('stop progress 1')manager.progress_2.stop('stop progress 2')Parametersgoalto change goal in between of process, it’s useful for
dynamic tasksbar_lenlength of progress bar (default: 60)fillbar fill symbol (default: █)zfillbar zero fill symbol (default: -)decimalspositive number of decimals in percent complete
(default: 1)Any Questions? Report a Bug? Enhancements?Please open a new issue onGitHubLicenseCLI-ProgressBar is OpenSource and licensed under the terms ofThe MIT
License (X11). You’re welcome tocontribute!Version 1.1.0AddMultiProgressManagerclass
Package: cli-proton-python
Proton Python clients is a collection of reactive messaging test clients built onpython-qpid-protonAMQP1.0 based messaging library. cli-proton-python is a part of Unified Messaging Test Clients that offers equivalent functionality when using different programing languages or APIs.current related projects:cli-javacli-rheacli-netlitecli-proton-rubyInstallationcli-proton-python requiresPythonv2.6+ to run.$ pip install cli-proton-pythonUsingUsing the command line clients (please refer to –help to discover the available options)$ cli-proton-python-sender --broker-url "username:password@localhost:5672/queue_test" --count 1 --msg-content "text message" --log-msgs dict
$ cli-proton-python-receiver --broker-url "username:password@localhost:5672/queue_test" --count 1 --log-msgs dictUsing in scriptimportprotonfromcli_proton_pythonimportsenderparser=sender.options.SenderOptions()opts,_=parser.parse_args()opts.broker_url='username:password@localhost:5672/examples'opts.count=1opts.msg_content='text message'opts.log_msgs='dict'container=proton.reactor.Container(sender.Send(opts))container.run()DocumentationDocumentation may be found on readthedocs.io:read the docummentationLicense
Package: clips
ClipsA simple parser for building graceful command-line interfaces, with chained commands and colorful usage messages. Clips usesgetoptfor parsing command arguments and options (scanning mode is GNU-flavoured).Colors are implemented through ANSI codes and they are not expected to work on Windows. More generally, please note that Clips is not tested for Windows environment.Quick startInstall withpip:pip install clipsUsage exampleA console with a chained command:from clips import ArgParser

# init console
console = ArgParser(
    'myconsole',                # prog. name
    description=description,    # prog. description
    banner=banner               # usage banner
)

# add a console-level argument
console.add_argument('-v', '--version', help='Show version')

# add a console command
cmd = console.add_command('command', help='A command')

# add a subcommand
subcmd = cmd.add_command('subcommand', help='A subcommand')

# add an argument to subcommand
subcmd.add_argument('arg', help='Argument for this subcommand')Parsing method returns a dictionary of user context,# parse arguments
args = console.parse_args(['command', 'subcommand', 'this'])
print(args)so that output is:{
    '-h': False,
    '--help': False,
    '-v': False,
    '--version': False,
    'command': True,
    'subcommand': True,
    'arg': 'this'
}Argument can have default values:console.add_argument('-o', '--opt', valued=True, default=10)To display usage help:# console-level usage
print(console.usage_help())

# command-level usage
print(console.usage_help(['command']))
print(console.usage_help(['command', 'subcommand']))To disable internal management of help option:# init console
console = ArgParser(
    'myconsole',                # prog. name
    add_help=False              # no help hook
)Use colors for title and text:# init console
console = ArgParser(
    'myconsole',                # prog. name
    title_fg='orange',          # title foreground color
    title_bg='green',           # title background color
    text_fg='green',            # text foreground color
    text_bg='orange'            # text background color
    )Group commands by sections (this affects only usage help):# create section with commands
console.add_section('First section')
cmd1 = console.add_command('cmd1')
cmd2 = console.add_command('cmd2')

# another section
console.add_section('Second section')
cmd3 = console.add_command('cmd3')
cmd4 = console.add_command('cmd4')Available colors for titles and text parts:foreground:black,red,green,orange,blue,cyan,lightgrey,darkgrey,lightred,lightgreen,yellow,lightblue,pink,lightcyanbackground:black,red,green,orange,blue,purple,cyan,lightgrey
Package: clipsai
ClipsAIQuickstartClips AI is an open-source Python library that automatically converts long videos into
clips. With just a few lines of code, you can segment a video into multiple clips and
resize its aspect ratio from 16:9 to 9:16.Note:Clips AI is designed for audio-centric, narrative-based videos such as
podcasts, interviews, speeches, and sermons. It actively employs video transcripts to
identify and create clips. Our resizing algorithm dynamically reframes and focuses on
the current speaker, converting the video into various aspect ratios.For full documentation, visitClips AI Documentation.
Check out aUI demowith clips generated by this library.Installationpipinstallclipsaipipinstallwhisperx@git+https://github.com/m-bain/whisperx.gitCreating clipsClips are created based on the transcript of a video. You'll first need to transcribe
the video, and then you can create clips based on the transcript.WhisperXis utilized under the hood to transcribe
videos.fromclipsaiimportclip,transcribetranscription=transcribe("video.mp4")clips=clip(transcription)print("StartTime: ",clips[0].start_time)print("EndTime: ",clips[0].end_time)Resizing a videoYou'll need to create an access token on hugging face to resize a video becausePyannoteis utilized for speaker
diarization. You won't be charged for using Pyannote and instructions are on thePyannote HuggingFacepage.fromclipsaiimportresizecrops=resize(video_file_path="video.mp4",pyannote_auth_token="pyannote_token",aspect_ratio=(9,16))print("Crops: ",crops.segments)
Package: clip-score
CLIP Score for PyTorchThis repository provides a batch-wise quick processing for calculating CLIP scores. It uses the pretrained CLIP model to measure the cosine similarity between two modalities. The project structure is adapted frompytorch-fidandCLIP.InstallationRequirements:Install PyTorch:pip install torch  # Choose a version that suits your GPUInstall CLIP:pip install git+https://github.com/openai/CLIP.gitInstall clip-score fromPyPI:pip install clip-scoreUsageTo compute the CLIP score between images and texts, make sure that the image and text data are contained in two separate folders, and each sample has the same name in both modalities. Run the following command:python -m clip_score path/to/image path/to/textTo run the evaluation on a GPU, use the--device cuda:Nflag, whereNis the index of the GPU to use.Computing CLIP Score within the Same ModalityIf you want to calculate the CLIP score within the same modality (e.g., image-image or text-text), follow the same folder structure as mentioned above. Additionally, specify the preferred modalities using the--real_flagand--fake_flagoptions. By default,--real_flag=imgand--fake_flag=txt. Examples:python -m clip_score path/to/imageA path/to/imageB --real_flag img --fake_flag img
python -m clip_score path/to/textA path/to/textB --real_flag txt --fake_flag txtCitingIf you use this repository in your research, consider citing it using the following Bibtex entry:@misc{taited2023CLIPScore,
  author={SUN Zhengwentai},
  title={{clip-score: CLIP Score for PyTorch}},
  month={March},
  year={2023},
  note={Version 0.1.0},
  howpublished={\url{https://github.com/taited/clip-score}},
}LicenseThis implementation is licensed under the Apache License 2.0.The project structure is adapted frommseitzer's pytorch-fidproject. The CLIP model is adapted fromOpenAI's CLIP.The CLIP Score was introduced in OpenAI'sLearning Transferable Visual Models From Natural Language Supervision.
Package: clipShare
clipShareA single TCP server/client bundle that allows you to sync your clipboard between systems.FeaturesSync clipboard between systems.Has a Web UI.Server IP:Portorngrok-tunnel-hostTo view clipboard on mobile devices.To sync clipboard if not using the Python client.Advertise the server on the local network.Authentication using passcode. (Passcode should be shared via some external safe channel)Scan for servers on the local network.The same script can be used as a server or client.Encrypted communication for clipboard sharing with AES Encryption (Key should be shared via some external safe channel)Installationpip install clipShareUsageUsage: 
    clipShare [... OPTIONS]
    

Options:
    -h, --help                      Show this help message and exit
    -s, --server [SERVER_PORT_NUMER], --server [SERVER_PORT_NUMER]
                                    Run as server on the specified port.
    -c, --client SERVER_IP:SERVER_PORT_NUMBER, --client SERVER_IP:SERVER_PORT_NUMBER
                                    Run as a client, that connects to specified server IP and port.
    -t, --serve-on-ngrok-tunnel     Enable Serve on ngrok tunnel. This option requires ngrok authtoken to be present in {current_dir}/ngrok-auth-token.txt
    -a, --advertise                 Enable Advertising server on the local network.
    -n, --name                      Name of the server to be advertised.
    -p, --passcode                  Passcode for authentication.
    -ep, --encryption-password      Encryption password for data transfer.
    -toh, --tcp-over-https          Enable TCP over HTTPS for ngrok tunnel.
    -d, --debug                     Enable debug mode.

Examples:
    clipShare -s 5000
    clipShare -s 5000 -d
    clipShare -s 5000 -a
    clipShare -s 5000 -p RandomPasscode -ep 5up3rS3cu3_3ncrY9t1on_P45sw0rd
    clipShare -s 5000 -p RandomPasscode -ep 5up3rS3cu3_3ncrY9t1on_P45sw0rd -t -a -d
    clipShare -c 192.168.0.1:8080
    clipShare -c -d
    clipShare -c -d -p RandomPasscode -ep 5up3rS3cu3_3ncrY9t1on_P45sw0rd
    clipShare -c "abc.com" -toh -d -p RandomPasscode -ep 5up3rS3cu3_3ncrY9t1on_P45sw0rd
    clipShare -c "abc.com:120" -d -p RandomPasscode -ep 5up3rS3cu3_3ncrY9t1on_P45sw0rd
    clipShare -c -d -p RandomPasscode -ep 5up3rS3cu3_3ncrY9t1on_P45sw0rdDo you Want to help me to work more on Open-Source Projects like this?so that I can get one more sleepless night to work on this kind of stuff.Or use other sponsoring methods if you like.
Package: clip-similarwords
The clip_similarwords is the implementation of finding similar 1-token words of OpenAI'sCLIPin less than one second.OpenAI's CLIP uses text-image similarities so its text-text similarities may also be text's typical image similarities unlikeWordNetor other synonym dictionaries.Note that, for speed and storage reason (PyPI is limited to 60MB), the words composed by 2 or more tokens are not supported.Installationclip_similarwords is easily installable via pip command:pipinstallclip_similarwordsorpipinstallgit+https://github.com/nazodane/clip_similarwords.gitUsage of the command~/.local/bin/clip-similarwords[word_fragment|--all]Usage of the modulefromclip_similarwordsimportCLIPTextSimilarWordsclipsim=CLIPTextSimilarWords()forkey_token,sim_token,cos_similarityinclipsim("cat"):print("%s->%s( cos_similarity:%.2f)"%(key_token,sim_token,cos_similarity))Requirements for model usesLinux (should also works on other environmets)no PyTorch nor CUDA are required.Requirements for model generationLinuxPython 3.10 or laterPyTorch 1.13 or laterCUDA 11.7 or laterDRAM 16GB or higherRTX 3060 12GB or higherThe patches and informations on other enviroments are surely welcome!LicenseThe codes are under MIT License. The model was converted under Japanese law.
Package: clipsnip
ClipSnipClipSnip is a command line tool that that automates the creation of GIFs from media files.UsageSimple usage:snip -q "nicest" -v "Community.S01E01.1080p.BluRay.x264.mkv"Parameters:The quote to search for (-q)The video file to snip (-v)output-1output-2Key FeaturesMedia file identificationSubtitle sourcing, syncing and searchingFrame perfect scene extractionInstallationEnsure you haveffmpeginstalledsudo apt-get install ffmpegInstall ClipSnip with OpenCVpip install clipsnip[opencv]Otherwise, if you already have OpenCVpip install clipsnipCreditsPySceneDetectfor detecting start and end of scenesffsubsyncfor syncing subtitles to audio streamsffmpegfor being awesome
Package: clipspy
PythonCFFIbindings for the ‘C’ Language Integrated Production SystemCLIPS6.41.Source:https://github.com/noxdafox/clipspyDocumentation:https://clipspy.readthedocs.ioDownload:https://pypi.python.org/pypi/clipspyInitially developed at NASA’s Johnson Space Center, CLIPS is a rule-based programming language useful for creating expert and production systems where a heuristic solution is easier to implement and maintain than an imperative one. CLIPS is designed to facilitate the development of software to model human knowledge or expertise.CLIPSPy brings CLIPS capabilities within the Python ecosystem.InstallationLinuxOn Linux CLIPSPy is packaged forx86_64architecture as a wheel according toPEP-513guidelines.
Most of the distributions should be supported.$pipinstallclipspyMacOsxApple Silicon is supported for Python versions greater than 3.11.$pipinstallclipspyWindowsCLIPSPy comes as a wheel for most of the Python versions and architectures.>pip install clipspyBuilding from sourcesThe provided Makefiles take care of retrieving the CLIPS source code and compiling the Python bindings together with it.$make# make installPlease check thedocumentationfor more information regarding building CLIPSPy from sources.ExampleimportclipsDEFTEMPLATE_STRING="""
(deftemplate person
  (slot name (type STRING))
  (slot surname (type STRING))
  (slot birthdate (type SYMBOL)))
"""DEFRULE_STRING="""
(defrule hello-world
  "Greet a new person."
  (person (name ?name) (surname ?surname))
  =>
  (println "Hello " ?name " " ?surname))
"""environment=clips.Environment()# define constructsenvironment.build(DEFTEMPLATE_STRING)environment.build(DEFRULE_STRING)# retrieve the fact templatetemplate=environment.find_template('person')# assert a new fact through its templatefact=template.assert_fact(name='John',surname='Doe',birthdate=clips.Symbol('01/01/1970'))# fact slots can be accessed as dictionary elementsassertfact['name']=='John'# execute the activations in the agendaenvironment.run()
Package: clipster-desktop
Clipster - Desktop ClientClipster is a multi platform cloud clipboard:Copy a text on your smartphone and paste it on your desktop, or vice versa.Easy, secure, open source.Supports Android, Linux, MacOS, Windows and all browsers.You can use the web front-end of the public server atclipster.cc.For the Android client seeClipster-Android.To run your own server checkClipster-Server.SetupLinuxInstall via pip:pipinstallclipster-desktopThen,clipsterwill be available as a terminal command. To enable auto-start, execute the following setup script:clipster_enable.shThis will add a Clipster service tosystemd. (To disable auto-start, runclipster_disable.sh)Alternatively, install the latest version from GitHub. Copy and paste the following in the console to clone the git repo and start theinstall.shscript:gitclonehttps://github.com/mc51/Clipster-Desktop.git&&cdClipster-Desktop&&shscripts/install.shThe install script takes care of everything.WindowsDownloadclipster.exefrom the latest Windows release and start it. To automatically start Clipster, open the current user's auto-start folder by opening Explorer and typingshell:startup. Copyclipster.exethere.MacOSDownloadclipster.zipfrom the latest MacOS release, move it toApplicationsand start it. You might get a warning message, that you need to ignore. Newer MacOS versions might even prevent you from opening it entirely at first. You havetwo options:Open it in the Finder viaright click --> openAfter failing to open it, go toSystem Preferences --> Security & Privacy. In theGeneralTab the App will be listed and you can start it from thereTo automatically start Clipster, right click on the icon in your Dock and click onOptions --> Open at Login.Now, you canuseclipster!UsageOn the first startup, you can either register a new account or enter your existing credentials for the login. Your credentials will be stored in yourHOMEPATHin./config/clipster/config.Clipster will add an Icon to your system tray which you can click for opening up a menu with the following options:Get last Clipwill fetch the last shared Clip from the server.Get all Clipswill fetch all shared Clips from the server.Share Clipwill share your current clipboard. Then, it's available for all your devices.Edit Credentialsallows you to register a new account or change your login credentials.Exitwill terminate the app.RoadmapEncrypt / Decrypt clipboard locally and only transmit encrypted data to serverAdd clipboard history: share multiple ClipsAdd PyPi packageSupport image sharingiOS ClientContributionsContributions are very welcome. If you come across a bug, please open an issue. The same thing goes for feature requests.CreditsClient based oncloud-clipboard.Install script based onDocker.