Saravanan666/pypi-org huggingface dataset:
Package: tagpy
TagPyTagPy is a a set of Python bindings forScott Wheeler's TagLib. It builds uponBoost.Python, a wrapper generation library which
is part of theBoost set of C++ libraries.Just like TagLib, TagPy can:read and write ID3 tags of version 1 and 2, with many supported frame types
for version 2 (in MPEG Layer 2 and MPEG Layer 3, FLAC and MPC),access Xiph Comments in Ogg Vorbis Files and Ogg Flac Files,access APE tags in Musepack and MP3 files.access ID3 version 2 tags in WAV filesAll these have their own specific interfaces, but TagLib's generic tag
reading and writing mechanism is also supported.You can find examples in the test/ directory.Installing TagPyIf you're lucky (Python 3.7-3.9 on x86 Linux currently), you can probably just runpip install tagpywhich will use the precompiled wheels. If this fails due to compilation
issues, you'll need to install some things first.Debian:apt-get install libboost-python-dev libtag1-devFedora:dnf install boost-python3-devel taglib-develAlpine 3.17:apk add taglib-dev boost1.80-python3(or anotherboost*-python3for other alpine versions)
Other setups are not currently supported, but patches with CI checking for others are welcomed.TagPy works withTagLib 1.4Boost.Python 1.74gcc 10.2.1Slightly older versions of gcc and Boost.Python should be fine, but the 1.4 requirement for TagLib is
firm. Anything newer is probably ok, and please file bugs for anything that fails.Using TagPyUsing TagPy is as simple as this:>>> import tagpy
>>> f = tagpy.FileRef("la.mp3")
>>> f.tag().artist
u'Andreas'Thetest/directory contains a few more examples.In general, TagPy duplicates the TagLib API, with a few notable
exceptions:Namespaces (i.e. Python modules) are spelled in lower case.
For example,TagLib::Ogg::Vorbisis nowtaglib.ogg.vorbis.Enumerations form their own scope and are not part of any
enclosing class scope, if any.For example, the valueTagLib::String::UTF16BEfrom the
enumTagLib::String::Typeis nowtagpy.StringType.UTF16BE.TagLib::Stringobjects are mapped to and expected as Python
unicode objects.TagLib::ByteVectorobjects are mapped to regular Python
string objects.
Package: tagreader
tagreader-pythonTagreader is a Python package for reading timeseries data from the OSIsoft PI and Aspen Infoplus.21
Information Manufacturing Systems (IMS) systems. It is intended to be easy to use, and present as similar interfaces
as possible to the backend historians.InstallationYou can install tagreader directly into your project from pypi by using pip
or another package manager. The only requirement is Python version 3.8 or above.pip install tagreaderThe following are required and will be installed:pandasrequestsrequests-kerberoscertifidiskcacheUsageTagreader easy to use for both Equinor internal IMS services, and non-internal usage. For non-internal usage
you simply need to provide the corresponding IMS service URLs and IMSType.
Seedata sourcefor details.Usage exampleimporttagreaderc=tagreader.IMSClient("mysource","aspenone")print(c.search("tag*"))df=c.read_tags(["tag1","tag2"],"18.06.2020 08:00:00","18.06.2020 09:00:00",60)Note, you can add a timeout argument to the search method in order to avoid long-running search queries.Jupyter Notebook QuickstartJupyter Notebook examples can be found in /examples. In order to run these examples, you need to install the
optional dependencies.pipinstalltagreader[notebooks]The quickstart Jupyter Notebook can be foundhereFor more details, see theTagreader Docs.DocumentationThe full documentation can be found inTagreader DocsContributeTo starting contributing, please seeTagreader Docs - Contribute
Package: tagrenamer
tagrenamerMass music collection renamer.Tagrenamer completely cleans up your music folder for you, all you needto do is to make sure all music files have the right tags.Imagine this is inside your music folder:Music/
├── MUTTER (2001) - Adios.mp3
├── MUTTER (2001) - Feuer Frei.mp3
├── MUTTER (2001) - Ich Will.mp3
├── MUTTER (2001) - Links 2 3 4.mp3
├── MUTTER (2001) - Mein Herz Brennt.mp3
├── MUTTER (2001) - Mutter.mp3
├── MUTTER (2001) - Nebel.mp3
├── MUTTER (2001) - Rein Raus.mp3
├── MUTTER (2001) - Sonne.mp3
├── MUTTER (2001) - Spieluhr.mp3
└── MUTTER (2001) - Zwitter.mp3What a mess, let’s clean it up:$tagrenamer--format'{artist}/{album}/{artist}-{title}.{ext}'Music/- Tagrenamer version 0.0.2.
 - Leftovers directory '__LEFTOVERS/' created.
 - Stage directory '__STAGE/' created.
 - Traverse the collection and extract music tags.
 - Validating tag input and sanitizing variables.
 - Moving non music files to '__LEFTOVERS/'.
 - Moving music to new tree in stage directory '__STAGE/'.
 - Remove empty directories (except stage/leftover directories).
 - Move everything from stage into the final location.
 - Deleting the temporary stage directory '__STAGE/'.
 - Deleting the empty leftovers directory '__LEFTOVERS/'.
 - DONE! Processed 11 files.Music/
└── rammstein
    └── mutter
        ├── rammstein-adios.mp3
        ├── rammstein-feuer frei.mp3
        ├── rammstein-ich will.mp3
        ├── rammstein-links 2 3 4.mp3
        ├── rammstein-mein herz brennt.mp3
        ├── rammstein-mutter.mp3
        ├── rammstein-nebel.mp3
        ├── rammstein-rein raus.mp3
        ├── rammstein-sonne.mp3
        ├── rammstein-spieluhr.mp3
        └── rammstein-zwitter.mp3FeaturesPythonPure Python command-line application that is cross-platform and strives to
meet all modern quality criteria such as PEP8-compliance and test coverage.FormatsSupports.mp3,.oggand.flacfiles and more are easy to add.Only deals with musicFiles that are not music, are moved into a folder named__LEFTOVERS/which contains the original structure they were originally in. Letting you
decide what to do with them.Fail-safeTagrenamer leverages an internal staging process in which it detects failures
before it touched a single file. The paranoid can combine--dry-runand-vvvvto see what is going on under the hood or even run with--shellto generate Shell commands for you to inspect without renaming anything.ScalabilityRenames a few music albums as well as a 2Tb music collection.InstallationInstall Tagrenamer directly fromPyPIusingpip:$pip3installtagrenamerChangelogUnreleased0.0.2 (2021-11-26)Development procedures refined and release tested.Integrated readthedocs:https://tagrenamer.readthedocs.io/Updated changelog to reflect 0.0.1 release.0.0.1 (2021-11-26)Ported the code from 2013 to Python 3.Reorganized the project to become a first-class Python package.Updated majority of PEP8 violations but not all.Added documentation.
Package: tags
With tags you can generate HTML code by programming python. For every Tag type
there is a corresponding class, for every tag an object. This way you can
program HTML code by programmatically coding in python. The advantage of this
style is that you can easily structure and reuse your HTML code, something that
pure HTML is missing. For example, you can create a widget and use it at many
different places, or create a template and plug some other html code in. Tags
takes care of only creating valid html code.Example Code:from tags import *head = Head().append(Title().append(Text(“Page Title”)))body = Body().append(P().append(Text(“Page Content”)))root = Doctype()root = Doctype().append(Html().append(head).append(body))This project is still in development. There is enough code to play around, but
some tags are missing.This version requires Python 2.
Package: tags2vec
json_stock下の方に日本語の説明がありますOverviewA tool that converts information such as tags in multiple strings into features in the form of vectors with 1s and 0s as elementsUsageimporttags2vec# Convert training datatrain_tags=[["Spicy","Red","Delicious"],["Sweet","Green"]]# Convert training data Tag info -> Vector (training) [tags2vec]train_x,tags_info=tags2vec.train_tr(train_tags)"""train_x (numpy array):[[1. 1. 1. 0. 0.][0. 0. 0. 1. 1.]]tags_info: ["Spicy", "Red", "Delicious", "Sweet", "Green"]"""# Convert test datatest_tags=[["Sweet","Red","Delicious"],["Spicy","Yellow"],]# Tag info -> Vector (prediction) [tags2vec]test_x=tags2vec.pred_tr(test_tags,tags_info)"""test_x (numpy array):[[0. 1. 1. 1. 0.][1. 0. 0. 0. 0.]]"""detailed explanationThis tool is designed for pre-processing of supervised learning.The vector output is therefore a numpy matrix.During the training phase, a list of tag information is output in the form of tags_info variablesDuring the prediction phase, a vector is generated based on the tags_info information (list of tags and their order)This ensures that prediction is consistent with the training phaseIf a tag appears during prediction that was not present during training, it is ignored概要タグ情報をベクトル特徴量に変換するツール具体的には、複数の文字列のタグのような情報を、1と0を要素として持つベクトルの形の特徴量に変換するツール使用例importtags2vec# 学習データの変換train_tags=[["Spicy","Red","Delicious"],["Sweet","Green"]]# タグ情報 -> ベクトル (学習時) [tags2vec]train_x,tags_info=tags2vec.train_tr(train_tags)"""train_x (numpy array):[[1. 1. 1. 0. 0.][0. 0. 0. 1. 1.]]tags_info: ["Spicy", "Red", "Delicious", "Sweet", "Green"]"""# 推論データの変換test_tags=[["Sweet","Red","Delicious"],["Spicy","Yellow"],]# タグ情報 -> ベクトル (推論時) [tags2vec]test_x=tags2vec.pred_tr(test_tags,tags_info)"""test_x (numpy array):[[0. 1. 1. 1. 0.][1. 0. 0. 0. 0.]]"""詳細説明このツールは教師あり学習の前処理を想定して作られていますそのため、ベクトルの出力はnumpy行列で出力されます学習のフェーズでタグ情報の一覧がtags_info変数の形で出力されます推論フェーズでは、tags_infoの情報 (タグ一覧とその順序) にもとづいてベクトルが生成されますこれによって、学習時と一貫した推論を行うことができます学習時に存在しなかったタグが推論時に現れた場合は、そのタグは無視されます
Package: tagscounteralexdoka
Script has a goal to capture and count tags from the site. You can either
use terminal version or UI. There is possibility to use aliases for
sites (you can edit it in filesynonims.yaml(site-packages/tagscounteralexdoka/…))1 stepFirst step is creating Db for tags. (optional, if it does not exist)tagcounter--createdb2 stepTo use terminal version (to load tags info to DB), you can run commans
like:tagcounter--getgoogle.com# or if use aliastagcounter--gettut3 stepTo show info from DB use :tagcounter--showgoogle.com# or if use aliastagcounter--showtutIf you run script without parameters, program will start with UI, with
the same functionality.
Package: tags-generator
Tags GeneratorA Python library to generate a tags list from a text using OpenAI.FeaturesGenerate tags list from a textLimit the number of tags (max_tags)Order tags by relevance or randomly (order)InstallationInstall the package using pip:pip install tags-generatorUsagefromtags_generatorimportTagsGenerator# Set your OpenAI API keyopenai_api_key="your_openai_api_key"# Initialize the TagsGenerator with custom attributestg=TagsGenerator(openai_api_key,max_tags=5,order='relevance')# Generate tags from a texttext="Create a step-by-step guide on building a pip library to distribution the library."tags=tg.generate_tags(text)print(tags)Attributesmax_tags (integer, default=5): Define the maximum number of tags in the output list.order (string, default='relevance'): Specify the order of tags based on their relevance. Options are 'relevance' or 'random'.LicenseThis project is licensed under the MIT License.
Package: tagsimplify
TagSimplyIt takes list as an input and return string of simplified tags.Installationpip install tagsimplyHow to use it?from tagsimply import text_postprocessinginput_list=['The','','India',']return_simplified_tag=text_postprocessing(input_list)For further detailed use of it refer GitHub link.LicenseÂ© 2020 Bhuvnesh SainiThis repository is licensed under the MIT license. See LICENSE for details.
Package: tag-spy
Identify the latest DD-DeCaF tag on a particular Docker image.The package was designed to only depend on the standard library in order to not have
any fast moving dependencies. It depends on Python 3.7+ forfromisoformatdate
parsing.UsageThe main purpose of this package is to provide a command line interface (CLI) for
retrieving the latest of all of a Docker image’s tags. The DD-DeCaF organization uses a
particular tag format in order to manage dependencies between Docker images. Takedddecaf/wsgi-base:alpine_2020-04-28_24fe0a0as an example, it consists of the base
tagalpine, the date when it was built, and the short hash of the git commit from
which the image was generated. The corresponding “latest” image isdddecaf/wsgi-base:alpine, however, child images should depend on the explicit tag.
In order to manage this more easily, this package provides a script for retrieving the
correct information. Sometimes, multiple images exist for the same date which is why
the label for the exact build timestamp is required. The following commandtag-spy dddecaf/wsgi-base alpine dk.dtu.biosustain.wsgi-base.alpine.build.timestampmay result in something likealpine_2020-04-28_24fe0a0For more information, also check out the help.tag-spy --helpInstallIt’s as simple as:pip install tag-spyCopyrightCopyright © 2020, DD-DeCaF.Free software distributed under theApache Software License 2.0.
Package: tags.py
How to install using pip:Stable:pipinstalltags.pyDevelopement:pipinstallgit+https://github.com/proguy914629bot/tags.pySimple guide on how to use:fromtagsimportTagtag=Tag()#Without aliases:tag.add_tag(r"{user}","user123")#With aliases called "{users}" and "{usr}":tag.add_tag(r"{user}","user123",r"{users}",r"{usr}")#Converting the string:string=r"{user}is the same as{users}and{usr}!"tag.convert(string)# "user123 is the same as user123 and user123!"#Getting a tag by name:tag.get_tag("Insert-Name-Here")#Getting a tag by id:tag.get_tag("Insert-ID-Here")#Get a tag ID by name:#Way 1:tag.get_tag("Insert-Name-Here").id#Way 2:tag.get_id("Insert-Name-Here")#All these ways are the same. get_tag.id returns tag.get_id.Contribution:You can contribute by forking this repository, or cloning this repository. This is fully open-sourced inGithub.License:MIT
Package: tagtool
Mass clean metadata of downloaded MP3 songs.I wrote the initial version as asimple
scriptthat just worked. This tool later became an exercise in command line
application design as I’d never done it before. It usesdocopt(along with some hackery to allow
sub-commands)installpip install tagtoolYou could also use`pipsi<https://github.com/mitsuhiko/pipsi>`__ to
install.usageUsage:
    tagtool [--no-skip] <command> [<args>...]

Commands:
    replace     Perform regex replace on tags
    remove      Remove tag frames
    rename      Rename files to format: "%TrackTitle%.mp3"
    help        Read about a specific command

Options:
    --no-skip   Do not skip already tagged filescommands``replace``Perform regex replace on tags like artist name, track title etc.

Usage:
    tagtool replace --pattern=<pattern> [--repl=<replacement>] <file>...
                    [--prune] [--frames=<tags>] [--frames_skip=<tags>]

Options:
    <file>                       MP3 file(s) to process
    --pattern=<pattern>          Pattern to search for
    --repl=<replacement>         Replacement text
    --prune                      Remove empty frames
    --frames=<frames>            Comma separated list of frames to
                                 restrict replacement to
    --frames_skip=<frames>       Comma separated list of frames to skip

Examples:
    tagtool replace --pattern='\s+\d+\s+' --repl='' --prune SomeSong.mp3 --frames_skip=TOPE,TIT2``remove``Remove tag frames.

Usage:
    tagtool remove  --frames=<tags> <file>...
                    [--prefix]

Options:
    <file>                       MP3 file(s) to process
    --frames=<frames>            Comma separated list of frames to remove
    --prefix                     Consider the list of frames as prefixes

Examples:
    tagtool remove --frames=APIC,COMM,USLT *.mp3``rename``Rename a file with it's track title.

Usage:
    tagtool rename <file>...

Options:
    <file>                       MP3 file(s) to process

Examples:
    tagtool rename *.mp3tagfixTagfix is a script that uses the available tagtool commands as building
blocks and performs multiple cleaning operation on files in one pass. If
you download music from sites likesongspk,djmazaetc. then this script is for you. It
removes all mention of these websites from the tags.
Package: taguchimethod
This library is used to find best level of control factors using taguchi method.
Two things you need to use this library. First you have to select which array you want to use. I have given my github link.
There you wil see different orthogonal arrays csv file. You have to select your choise load this csv file into pandas dataframe.
second thing you need is your experimental results which you get from experiments by conducting them according to your selected array.
(For reference I have given “result.csv” file of “thickness of aluminium layer on silicon wafers” in github link.This result get from experiments conducted according to
L16 (2^15) array)
Then you have to load this csv file as pandas dataframe.for example,
your selected array csv file name is “L16 (2^15).csv” and
results csv file is “result.csv”||
number of levels in your array used are “2”||
column number corresponding to your control factor is “1”||
then your code will be ||
from taguchimethod import getresults_levelwise ||
data=pd.read_csv(“L16 (2^15).csv”) ||
results=pd.read_csv(“result.csv”) ||
getresults_levelwise(data,1,2,results)||
we wil get results levelwise||
if output is [0.866 1.26] then it means if you use level “1” for your selected control factor then you will get result 0.866 and for level “2”
yuo will get 1.26||
github_link=https://github.com/akashsathe ||
medium link=https://medium.com/@akashsathe79||
I am going to publish a article about this method on medium.Change Log0.0.2 (21/08/2020)First Release
Package: taguette
A spin on the phrase “tag it!”,Taguetteis a free and open source qualitative research tool that allows users to:Import PDFs, Word Docs (.docx), Text files (.txt), HTML, EPUB, MOBI, Open Documents (.odt), and Rich Text Files (.rtf).Highlight words, sentences, or paragraphs and tag them with the codesyoucreate.(not yet) Group imported documents together (e.g. as ‘Interview’ or ‘Lit Review’).Export tagged documents, highlights for a specific tag, a list of tags with descriptions and colors, and whole projects.Check out our website to learn more about how to install and get started.Motivation and goalQualitative methods generate rich, detailed research materials that leave individuals’ perspectives intact as well as provide multiple contexts for understanding the phenomenon under study. Qualitative methods are used by a wide range of fields, such as anthropology, education, nursing, psychology, sociology, and marketing. Qualitative data has a similarly wide range: observations, interviews, documents, audiovisual materials, and more.However - the software options for qualitative researchers are eitherfar too expensive, don’t allow for the seminal method of highlighting and tagging materials,or actually perform quantitative analysis, just on text.It’s not right or fair that qualitative researchers without massive research funds cannot afford the basic software to do their research.So, to bolster a fair and equitable entry into qualitative methods, we’ve made Taguette!InstallationYou can find complete installation instructions onour website, including installers for Windows and MacOS.Development setup from the repositoryYou can install from a local clone of this repository, which will allow you to easily change the sources to suit your needs:Clone this git repository from the terminal:git clonehttps://gitlab.com/remram44/taguette.gitNavigate on the command line to the repository you’ve just cloned locally, using thecdcommand. To get help usingcd, usethis tutorial.Taguette usesPoetryfor its packaging and dependency management. You will need toinstall Poetry.Install Taguette and its dependencies by runningpoetry install. Poetry will create a virtual environment for you by default, activate it by runningpoetry shell.Build translation files usingscripts/update_translations.sh.You can start taguette in development mode usingtaguette--debug(ortaguette--debugserver <config_file>). This will start Tornado in debug mode, which means in particular that it will auto-restart every time you make changes.Navigate tolocalhost:7465to use Taguette!LicenseCopyright (C) 2018, Rémi Rampin and Taguette contributorsLicensed under aBSD 3-clause “New” or “Revised” License. See theLICENSE.txtfile for details.
Package: tagui
RPA for Python’s simple and powerful API makes robotic process automation fun! You can use it to quickly automate away repetitive time-consuming tasks on websites, desktop applications, or the command line.Built on AI Singapore’s TagUI open-source RPA tool, RPA capabilities out-of-the-box for this package include website automation, computer vision automation, optical character recognition, keyboard & mouse automation.Tables can’t be displayed here, please refer to RPA for Python homepage for full API -https://github.com/tebelorg/RPA-Python
Package: tagup
taguptagupis a Python module which provides a reference implementation of theTagup Language.This module currently implementsversion 1.0.0of the Tagup Language.Quick StartfromtagupimportBaseRenderer,TagDictMixinclassTagupRenderer(TagDictMixin,BaseRenderer):passrenderer=TagupRenderer(# Optional initial markup tags.tags={'bold':r'<span style="font-weight: bold">[\\1]</span>',})# Manipulate tags using dictionary syntax.renderer['link']=(r'<a href="[\\1]" [\if target\target="_[\\target]"]>'r'[bold [\if 2\[\\2]\[\\1]]]'r'</a>')html=renderer.render_markup(r'Click [link target\\blank\[\\url]\here] to visit [link\[\\url]]',# Provide optional named (and positional) arguments.named_args={'url':'http://example.com'})print(html)Changelogv0.2.3Added "StaticTagMixin," "TagDictMixin" and "TrimMixin" for "BaseRenderer."Added new errors "ImproperlyConfigured," "NamedArgumentMissing," "PositionalArgumentMissing," "TagNotFound" and "TagupSyntaxError."Renamed "stack_trace" to "tag_stack_trace" for all custom errors.Fixed bug in getitem method of "TagStackTrace."v0.2.2Added support for global named arguments.Added max tag depth enforcement.Fixed bug that prevented the positional loop from functioning when not provided an optional default value.v0.2.1Added tag prefetching.v0.2.0Renamed "Renderer" to "BaseRenderer."Refactored "BaseRenderer" to use method overriding for "get_tag" instead of providing "get_tag_callback" to constructor.Removed "cache_tag_ast_callback" from "BaseRenderer" constructor.Removed "trim_args" from "BaseRenderer" constructor.Added a node pre and post processing hook system.Added test cases.Various internal optimizations.v0.1.3Fixed bug where the "trim_args" option didn't properly remove leading and trailing whitespace in some situations.v0.1.2Fixed bug where code called "trim()" rather than "strip()."v0.1.1Added non-standard option to trim whitespace from arguments before tag evaluation.Fixed bug where whitespace was considered when specifying a name/position for argument substitution.v0.1.0Initial release.
Package: tag-utils
tag-utilstag-utils is a collection of Pungi/Koji tag utilities for release-depot.Prerequisitestag-utils runs on Python 3.Installingtag-utils is available on PyPI; it can be installed by running:pip install tag_utilsAlternatively, one could simply clone this repository and run:python setup.py installDocumentationThere is none.ContributingPlease fork and issue pull requests.LicenseThis project is licensed under the MIT license.
See the [LICENSE](LICENSE) file for detailsHistory0.0.8 (2020-09-10)Use argparse for tag-overAdd trunk-update wrapper for tag-over0.0.7 (2020-03-19)Optimize to avoid double-tagging in tag-over0.0.6 (2020-01-22)Add Errata support0.0.5 (2019-12-18)Fix install requirements for PyPI0.0.4 (2019-12-03)Support separate destination tagAdd “–print” to display packages that would be
tagged, but without actually performing any tagging0.0.3 (2019-04-25)Support koji inheritanceFixes for tag-delta output0.0.1 (2019-04-25)First published to github