Saravanan666/pypi-org huggingface dataset:
Package: clean-ffmpeg-python-utils
clean_ffmpeg_python_utilsEasy-to-use ffmpeg python utils with simpler argumentsInstallingInstall:pip install clean_ffmpeg_python_utilsUsageclean_ffmpeg_python_utils --help

usage: clean_ffmpeg_python_utils --input_filepath INPUT_FILEPATH [--output_extension OUTPUT_EXTENSION] [--output_filepath OUTPUT_FILEPATH] [--fps FPS]
                           [--start_time START_TIME] [--duration DURATION] [--width WIDTH] [--height HEIGHT] [-h]

optional arguments:
  --input_filepath INPUT_FILEPATH
                        (Path, required)
  --output_extension OUTPUT_EXTENSION
                        (Union[str, NoneType], default=None)
  --output_filepath OUTPUT_FILEPATH
                        (Union[pathlib.Path, NoneType], default=None)
  --fps FPS             (Union[int, NoneType], default=None)
  --start_time START_TIME
                        (Union[int, NoneType], default=None)
  --duration DURATION   (Union[int, NoneType], default=None)
  --width WIDTH         (Union[int, NoneType], default=None)
  --height HEIGHT       (Union[int, NoneType], default=None)
  -h, --help            show this help message and exitExample 1: Convert mp4 to gifclean_ffmpeg_python_utils --input_filepath openai_rubiks_cube.mp4 --output_extension gifExample 2: Trim video lengthclean_ffmpeg_python_utils --input_filepath openai_rubiks_cube.mp4 --start_time 25 --duration 10Example 3: Modify FPSclean_ffmpeg_python_utils --input_filepath openai_rubiks_cube.mp4 --fps 10
Package: clean-folder-by-MK
Clean FolderClean Folder is a Python package that provides a command-line interface for sorting files within a folder. It helps organize cluttered directories by moving files into specific subfolders based on their file types. Additionally, it offers an optional backup feature that creates an archive of the folder before sorting.InstallationYou can install Clean Folder using pip:pipinstallclean-folder_by_MKUsageTo use Clean Folder, open a command prompt or terminal and run theclean-foldercommand followed by the path to the folder you want to sort. The path argument is required.clean-folder/path/to/folderOptional Backup (for now only for Windows based systems)You can include the optionalbackupargument to create a backup of the folder before sorting the files. This can be useful to preserve the original state of the folder in case you want to revert the changes.clean-folder/path/to/folderbackupThe backup will be created as an archive file with thebackpupappenden to the name, e.g.,/path/to/folder_backup.zip.ExampleLet's consider an example where we want to sort the files in the~/Documentsfolder with a backup:clean-folder~/DocumentsbackupThis command will organize the files within~/Documentsinto subfolders based on their file types. A backup of the~/Documentsfolder will be created before sorting.LicenseThis project is licensed under the MIT License. See theLICENSEfile for details.AcknowledgementsClean Folder makes use of the following libraries:shutil: File and directory management operationspathlib: Object-oriented filesystem pathsdatetime: Date and time manipulationre: Regular expression operationsThese libraries greatly contribute to the functionality and efficiency of Clean Folder.AuthorsMaksym Klym -GitHub
Package: clean-folder-RSA
ЗавданняУ цьому домашньому завданні ми зробимо із скрипта розбору папки Python-пакет та консольний скрипт, який можна викликати у будь-якому місці системи з консолі командою clean-folder. Для цього вам треба створити структуру файлів та папок:├── clean_folder
│    ├── clean_folder
│    │   ├── clean.py
│    │   └──init.py
│    └── setup.pyУ clean_folder/clean_folder/clean.py треба помістити все, що ми зробили на попередніх домашніх завданнях по розбору папки. Ваше основнє завдання написати clean_folder/setup.py, щоб вбудований інструментарій Python міг встановити цей пакет та операційна система могла використати цей пакет як консольну команду.
Критерії прийому завданняПакет встановлюється в систему командою pip install -e . (або python setup.py install, потрібні права адміністратора).
Після установки в системі з'являється пакет clean_folder.
Коли пакет встановлений в системі, скрипт можна викликати у будь-якому місці з консолі командою clean-folder
Консольний скрипт обробляє аргументи командного рядка точно так, як і Python-скрипт.
Package: cleanfreak
A sanity checking framework for cg production, fully customizable through yaml configuration files. Use CleanFreak to check for and fix various issues in a scene prior publication.InstallationCleanFreak is available through PyPi <http://pypi.python.org/pypi/cleanfreak>. Install using pip.pip install cleanfreakIf you need pip get it here <http://pip.readthedocs.org/en/latest/installing.html>.DocumentationFor more information visit the docs hosted on readthedocs.org.
<http://cleanfreak.readthedocs.org/en/latest>
Package: clean-git-branches
clean-git-branchesclean-git-branches is a command line utility for cleaning stale branches from your local git repository. The program will check for branches that have been deleted on the remote and prompt the user to confirm before deleting them locally.InstallationTo install clean, simply run the following command:pip3 install clean-git-branchesUsageTo use clean-git-branches, navigate to the root of your local git repository in the command line and run the following command:clean_git_branchesIt is also possible pass the path as the first argument:clean_git_branches "/Users/butler/my_repo/"The cleaner is set the be cautious by default, asking the user to verify deleting the local branches.
In order to bypass this, passFalseas the second argument. Examples:clean_git_branches "/Users/butler/my_repo/" Falseclean_git_branches "" False- will default the path to the current working directoryThe program will then check for stale branches and prompt the user to confirm before deleting them (unless bypassed).By default, the program will also protect certain branches from being deleted (master, main, dev) in case they exist on the remote repository. To change the list of protected branches, you can modify the "protected_branches" variable in the clean-git-branches.py file.Please note that this program is only compatible with Git.ContributingIf you would like to contribute to the development of clean-git-branches, please feel free to fork the repository and submit pull requests with your changes.Licenseclean-git-branches is released under theMIT License.
Package: clean-graph
Clean GraphClean Graph was a Python package for IBCS-like graphs based on matplotlib. This package will no longer be maintained and has been replaced by ‘Clean Business Chart’, with pandas support.See:https://pypi.org/project/Clean-Business-Chart/Free software: MIT licenseDocumentation:https://clean-graph.readthedocs.io.FeaturesColumnWithWaterfall, the first chart released with clean-graph!CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.1 (2023-04-12)Announcement that the name “Clean Graph” was a working title. The maintained package with the same (and more) functionality is called “Clean Business Chart”. See:https://pypi.org/project/Clean-Business-Chart/0.1.0 (2023-02-21)First release on PyPI. Column chart with waterfall.
Package: cleanify
cleanifyCLI utility to remove remove newlines, tabs from a file and copy it to your clipboardPure 🐍 with onlyklembordused in the Tech Stack as a clipboard APIInstallationFrom PyPI (requires Python and PIP)pip install cleanifyFrom source (requires Python)Clone this repositoryStart a terminal in the repository's folderRunpython setup.py installUseIn your terminal, typecleanify --file {your filepath - relative OR absolute}The cleanified string will be copied to your clipboardSupported Flags:FlagRequiredDescription-file,-ftrueThe path {relative or absolute} to the target file--repQuotes,--rqfalseWhether you want to replace double quotes with single ones (useful for HTML stored as JSON). Defaults tofalse
Package: clean-image-crop-uploader
clean-image-crop-uploader (CICU)================================``clean-image-crop-uploader`` is a django widget to upload an image via Ajax and crop it using `Jcrop<https://github.com/tapmodo/Jcrop>`_. It provides a simple workflow: first one, using modal,(by `twitter bootstrap <http://twitter.github.com/bootstrap/javascript.html#modals>`_) the image can be uploaded and croped.Second one, you can see the image cropping preview in the form and finally submit the result.``clean-image-crop-uploader`` is perfect when you use an ImageField on your model where is necessary to have a specific portion of image. It's easy to configure and to use.You can use different configurations , with fixed aspect ratio or minimal image size.It works with jQuery = 1.8.3 and twitter bootstrap.Screenshot:#. Modal window with upload button:.. image:: http://asaglimbeni.github.com/clean-image-crop-uploader/images/screenshot1.jpg#. Modal window with crop area:.. image:: http://asaglimbeni.github.com/clean-image-crop-uploader/images/screenshot2.jpg#. Form with preview.. image:: http://asaglimbeni.github.com/clean-image-crop-uploader/images/screenshot3.jpgInstallation------------#. Install django-image-cropping using pip. For example::pip install clean-image-crop-uploader#. Add ``south`` and ``cicu`` to your INSTALLED_APPS.#. run migrate commando to your django project::python manage.py migrateDependencies------------* jQuery = 1.8.3* Twitter-BootstrapConfiguration-------------#. Add into url.py ::(r'^ajax-upload/', include('startproject.cicu.urls'))#. Create your model-form and set  CicuUploaderInput widget to your imageField  ::from cicu.widgets import CicuUploderInputclass yourCrop(forms.ModelForm):class Meta:model = yourModelcicuOptions = {'ratioWidth': '600',       #fix-width ratio, default 0'ratioHeight':'400',       #fix-height ratio , default 0'sizeWarning': 'False',    #if True the crop selection have to respect minimal ratio size defined above. Default 'False'}widgets = {'image': CicuUploderInput(options=cicuOptions)}#. Download `twitter bootstrap <http://twitter.github.com/bootstrap/>`_  to your static file folder.#. Add in your form template links to jquery, bootstrap, form.media::<head>....<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.8.3/jquery.min.js"></script><link href="{{ STATIC_URL }}css/bootstrap.css" rel="stylesheet" type="text/css"/><script src="{{ STATIC_URL }}js/bootstrap.js"></script>{{ form.media }}....</head>Run the example---------------The Example is available only in github repository: https://github.com/asaglimbeni/clean-image-crop-uploader/tree/master/exampleTo run the example inside this package follow these commands::> cd ./example/> python manage.py syncdb> python manage.py migrate # only if you use South!!!> python manage.py collectstatic> python manage.py runserver domain:8000Go to examples :#. Free crop : <http://domain:8000/cicu-freecrop/>#. Fixed aspect ratio: <http://domain:8000/cicu-fixedratio/>#. Fixed aspect ratio with minimal size: <http://domain:8000/cicu-warningsize/>
Package: cleaning-scripts
cleaning-scriptsThis is a repository of Python scripts used in the FHIR integration pipeline to clean input data for different external sources.ScriptsThere are 4 types of scripts:scripts/customUser defined scripts to perform specific tasks like cleaning a Patient phone number for examplescripts/utilsBasic scripts (like capitalize, test if empty, etc.)scripts/logic(Beta) Scripts that operate like logic statement and take other scripts as argumentscripts/customcan be extended by users, either by completing new scripts or by adding new ones when no one is addressing their needs. This is done using the API.Start contributingWe have reported several issues with the labelGood first issuewhich can be a good way to start! You can also join ourSlackto contact us if you have trouble or questions :)If you're enthusiastic about our project, :star: it to show your support! :heart:
Package: cleaning-utils
cleaning-utilscleaning-utils is a collection of small Python functions and classes which make
cleaning pipelines shorter and easier.Installpip3installcleaning-utilsContributingTesting:makeinstall
maketest&&makecoverage&&makecheck-codestyle&&makemypy&&makecheck-safety&&makeextrabadgesChecks on various versions:python3.8-mvenv.venv_38
..venv_38/bin/activate
python3-mpipinstall--upgradepip
makeinstall
maketest&&makecoverage&&makecheck-codestyle&&makemypy&&makecheck-safety
deactivate

python3.9-mvenv.venv_39
..venv_39/bin/activate
python3-mpipinstall--upgradepip
makeinstall
maketest&&makecoverage&&makecheck-codestyle&&makemypy&&makecheck-safety
deactivateBuild Package:pre-commitrun--all-filesFirst, change theversioninsetup.py,pyproject.toml, and change the__version__in__init__.py. Then:python3setup.pysdistbdist_wheelCommit Changes:pre-commitrun--all-files
gitadd.
gitcommit-m":sparkles: new feature"gitpull
gitpush-uoriginmasterMake a release:gittag-a<writetheversione.g.,v0.1.2>-m"message of release"gitpush--tags
makereleaseCommit Changes toREADME.md:pre-commitrun--all-files
gitadd.
gitcommit-m":books: README.md updated"gitpull
gitpush-uoriginmasterIcon made fromIcon Fontsis licensed by CC BY 3.0CreditsThis project was generated withpython-package-template
Package: cleaninsights
Clean Insights Python SDK 📏🐍💡Privacy-preserving measurement and analytics for Python.Clean Insightsgives developers a way to plug
into a secure, private measurement platform. It is focused on assisting in
answering key questions about app usage patterns, and not on enabling invasive
surveillance of all user habits. Our approach provides programmatic levers to
pull to cater to specific use cases and privacy needs. It also provides methods
for user interactions that are ultimately empowering instead of alienating.This Python SDK is part of the wider Clean Insights ecosystem that includes
SDKs in other languages, a consent user interface toolkit and server plugins.
All these tools can be found on theClean Insights Developers
Page.Online DocumentationDeveloper documentation is available athttps://cleaninsights.gitlab.io/clean-insights-python-sdk/.Copyright(C) Iain R. Learmonth 2021. SeeCOPYINGfor permissions.
Package: cleaninty
cleanintyPerform operations in ECommerce and some others.Work-in-progress, use at own discretion.This tool currently only does 3DS aka CTR, but can be expanded for WiiU in the future too.This is an early release.Important noticeI cannot stress this enough,DO NOT SHARE ANY GENERATED JSON OR OTPfor any console, asIT ALLOWS ANYONE TO IMPERSONATE YOUR CONSOLE ON NINTENDO'S SERVERS. If you must share with someone, do it privately and be sure to trust this person. Proceed with caution.I am not responsible for what other's may do with your console data on Nintendo's servers.InstallingReadNotesfirst.You may runpython3 setup.py installto install to system or add--userto install to user.You may also install it from PyPI withpip install cleaninty.Usagecleaninty ctr -hfor details.For the first run, I recommend you to use theGM9 scriptExtractSystemElements.gm9to extract necessary system elements for keys and certificates on your console, these elements are non-unique. Use extracted files withSetupConstants, checkcleaninty ctr SetupConstants -hfor help. You'll still need the AES HW Constant C in hexadecimal string as part of this command's arguments, which you'll have to find out yourself.NotesTested in python 3.7 to 3.11 in Linux. You may have trouble installingpycurlon windows, need to have libcurl binaries and MSVC to install it.TODOProper setup.pyMore proper loggingMore SOAPsNUS connect simulationOthers I forgotLicenseThe Unlicense license, checkLICENSE.mdfor details.Any files that were taken from any other project have their individual licenses added to them as a header.cleaninty/ctr/_env.pyis under MIT License,from pyctr/util.py
Package: cleanipynb
### cleanipynb[![](https://img.shields.io/pypi/v/clean_ipynb.svg)](https://pypi.python.org/pypi/cleanipynb)
[![](https://img.shields.io/travis/i008/clean_ipynb.svg)](https://travis-ci.org/i008/clean_ipynb)This package will cleanup your jupyter notebook by:removing unused imports (globally)moving all imports to the first cell and reordering themreformatting your code with autopep8All this with preserving the cell structure thanks to jupytext smart export to python features.>WARNING: Cleaning happens in-place - Be careful### Usage:`bash pip install cleanipynb cleanipynb path_to_your_notebook.ipynb `### Demo:
![](beforeafter.gif)### Credits:jupytextimportanizeautoflakeautopep8
Package: cleanit
CleanItSubtitles extremely clean.Project pagehttps://github.com/ratoaq2/cleanitCleanItis a command line tool that helps you to keep your subtitles
clean. You can specify your own rules to detect entries to be removed or
patterns to be replaced. Simple text matching or complex regex can be
used. It comes with standard rules out of the box:ocr: Fix common OCR errorstidy: Fix common formatting issues (e.g.: extra/missing spaces after
punctuation)no-sdh: Remove SDH descriptionsno-lyrics: Remove lyricsno-spam: Remove ads and spamsno-style: Remove font style tags like <i> and <b>minimal: includes only ocr and tidy rulesdefault: includes all rules except no-styleUsageCLIClean subtitles:$ cat mysubtitle.srt
1
00:00:46,464 --> 00:00:48,549
-And then what?
-| don't know.

2
00:49:07,278 --> 00:49:09,363
- If you cross the sea
with an army you bought ...


$ cleanit -t default mysubtitle.en.srt
1 subtitle collected / 0 subtitle filtered out / 0 path ignored
1 subtitle saved / 0 subtitle unchanged

$ cat mysubtitle.srt
1
00:00:46,464 --> 00:00:48,549
- And then what?
- I don't know.

2
00:49:07,278 --> 00:49:09,363
If you cross the sea
with an army you bought...


$ cleanit -t ocr -t no-sdh -t tidy -l en -l pt-BR ~/subtitles/
423 subtitles collected / 107 subtitles filtered out / 0 path ignored
Cleaning subtitles  [####################################]  100%
268 subtitles saved / 155 subtitles unchangedUsing docker:$ docker run -it --rm -v /medias:/medias -u $(id -u username):$(id -g username) ratoaq2/cleanit -t default /medias
1072 subtitles collected / 0 subtitle filtered out / 0 path ignored
Cleaning subtitles  [####################################]  100%
980 subtitle saved / 92 subtitles unchangedAPIfromcleanitimportConfig,Subtitlesub=Subtitle('/subtitle/path/subtitle.en.srt')cfg=Config.from_path('/config/path')rules=cfg.select_rules(tags={'ocr'})ifsub.clean(rules):sub.save()YAML Configuration filetemplates:-&ocrtags:-ocr-minimal-defaultpriority:10000languages:enrules:replace-l-to-I-character[ocr:en]:<<:*ocrpatterns:'\bl\b'replacement:'I'examples:?|And if l refuse?:|And if I refuse?
Package: cleanliness
# 🛀 CleanlinessCleanliness is a package for doing (very) basic cleaning of text. It can be used for preprocessing input to various
natural language processing tasks.## InstallInstall using from PyPI as follows:`python pip install cleanliness `Alternatively, you can download the source from GitHub, then install using pip (from the repo directory):`python pip install-e. `## Usage`python from cleanliness import normalize_whitespace clean_text =normalize_whitespace("This\ntext\t\containsodd\n\twhitespace.")`
Package: clean_links
clean-linksTools for cleaning up links.Remove cruft from URLs using the rules fromhttps://github.com/ClearURLs/RulesUnshorten URLs by making requests and following redirects.Are these two links the same?link1="https://trib.al/5m7fAg3"link2="https://bit.ly/dirtylank"resolved1=unshorten_url(link1).get("resolved")cleaned1=clear_url(resolved1)resolved2=unshorten_url(link2).get("resolved")cleaned2=clear_url(resolved2)cleaned1==cleaned2# True!
Package: cleanlog
cleanlogPython package for nice colored logs.InstallationpipinstallcleanlogAt a glance# log.pyimportcleanloglogger=cleanlog.ColoredLogger('mylogger')# Note that since cleanlog just wraps built-in logging module,# this is equivalent to logger.setLevel(logging.DEBUG).logger.setLevel(cleanlog.DEBUG)logger.critical('A critical message.')logger.error('An error message.')logger.warning('A warning message.')logger.info('An info message.')logger.debug('A debug message.')TODOImplement cleanlog.BasicLogger.
Package: clean-loop
CleanLoopAn extremely simple Python script that repeats another script,
every given number of seconds.UsageIn this example, thetest/test.shscript is chosen to loop, with a delay between loops of
3 seconds.➜python3src/cli.py--delay3--scripttest/test.shInstallationThesrc/cli.pycan be installed as theclean-loopcommand usingpip.You can install it fromGitHub:➜pipinstallgit+https://github.com/MolassesLover/CleanLoop.gitAlternatively, fromPyPi:➜pipinstallclean-loopLicenseAll files within this repository are licensed under theApache v2.0 licenseorMIT licenseat your choice.
Package: cleanm
# CleanM<b>[This project is in active development and not currently recommended for public use.]</b>CleaM is a set of tools for improving population genomes. It provides methods designed to improve the completeness of a genome along with methods for identifying and removing contamination. CleanM comprises only part of a full genome QC pipeline and should be used in conjunction with existing QC tools such as [CheckM](https://github.com/Ecogenomics/CheckM/wiki). The functionality currently planned is:<i>Improve completeness:</i>
* identify contigs with homology to closely related reference genome(s)
* identify contigs with compatible GC, coverage, and tetranucleotide signatures
* indetify partial population genomes which should be merged together (requires[CheckM](https://github.com/Ecogenomics/CheckM/wiki))<i>Reducing contamination:</i>
* taxonomically classify contigs within a genome in order to identify outliers
* identify contigs with divergent GC content, coverage, or tetranucleotide signatures
* identify contigs with a coding density suggestive of a Eukaryotic origin## InstallThe simplest way to install this package is through pip:
> sudo pip install cleanmThis package requires numpy to be installed and makes use of the follow bioinformatic packages:CheckM relies on several other software packages:[prodigal](http://prodigal.ornl.gov/): Hyatt D, Locascio PF, Hauser LJ, Uberbacher EC. 2012. Gene and translation initiation site prediction in metagenomic sequences. <i>Bioinformatics</i> 28: 2223-2230.[blast+](http://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastDocs&DOC_TYPE=Download): Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, Madden TL. 2009. BLAST+: architecture and applications. <i>BMC Bioinformatics</i> 10:421: doi: 10.1186/1471-2105-10-421.[diamond](http://ab.inf.uni-tuebingen.de/software/diamond/) Buchfink B, Xie C, Huson DH. 2015. Fast and sensitive protein alignment using DIAMOND. <i>Nature Methods</i> 12: 59–60 doi:10.1038/nmeth.3176.## CiteIf you find this package useful, please cite this git repository (https://github.com/dparks1134/CleanM)## CopyrightCopyright © 2015 Donovan Parks. See LICENSE for further details.
Package: cleanml
cleanmlA python package for cleaning and preparing data for downstream analysis or ML modeling.Installation$pipinstallcleanmlUsagecleanmlcan be used to clean and prepare data.fromcleanml.cleanmlimportmake_column_namesimportpandasaspdfile_path="data"# path to your filedata=pd.read_csv(file_path)data=make_column_names(data)column_names=data.columns.to_list()print(column_names)ContributingInterested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.Licensecleanmlwas created by Thulasiram Gunipati. It is licensed under the terms of the MIT license.Creditscleanmlwas created withcookiecutterand thepy-pkgs-cookiecuttertemplate.