Saravanan666/pypi-org huggingface dataset:
Package: ttrac
ttraca script to track your working timesinstallationpip install ttracusagedata fileThe data file will be created on your firstttrac start. The default path is~/.config/ttrac/data.json, but you can use every command with-f/--fileargument to specify a different filecommands$ ttrac
Usage: ttrac [OPTIONS] COMMAND [ARGS]...

Options:
  --help  Show this message and exit.

Commands:
  break    combines subcommand that allows you to take a break
  cat      prints content of the data file
  file     prints path to the data file
  start    start timetracking
  status   show all tracked times of the given day
  stop     stop timetracking
  version  prints the installed ttrac versionexampleHere is an example howttrac statusoutput looks like:+----------+----------------+
| day      | 21-05-2021     |
+----------+----------------+
| start    | 09:15:44       |
| duration | 0:28:07.180515 |
| stop     | -              |
+----------+----------------+if you append-t\--total, all tracked days will be printed+------------+------------+
| day        | 19-05-2021 |
+------------+------------+
| start      | 07:04:18   |
| duration   | 7:24:15    |
| stop       | 14:28:33   |
| Breaks     |            |
| - start    | 08:59:41   |
| - stop     | 09:21:11   |
| - duration | 0:21:30    |
+------------+------------+
+------------+------------+
| day        | 20-05-2021 |
+------------+------------+
| start      | 07:04:18   |
| duration   | 7:25:42    |
| stop       | 14:30:00   |
| Breaks     |            |
| - start    | 13:02:02   |
| - stop     | 13:03:59   |
| - duration | 0:01:57    |
+------------+------------+
+----------+----------------+
| day      | 21-05-2021     |
+----------+----------------+
| start    | 09:15:44       |
| duration | 0:23:05.789542 |
| stop     | -              |
+----------+----------------+The corresponding data file looks like this(ttrac cat):{
    "19-05-2021": {
        "start": "07:04:18",
        "breaks": [
            {
                "start": "08:59:41",
                "stop": "09:21:11"
            }
        ],
        "stop": "14:28:33"
    },
    "20-05-2021": {
        "start": "07:04:18",
        "stop": "14:30:00",
        "breaks": [
            {
                "start": "13:02:02",
                "stop": "13:03:59"
            }
        ]
    },
    "21-05-2021": {
        "start": "09:15:44"
    }
}
Package: ttrace
ttrace - strace as a treeUsesstraceto trace a program call and displays what's going on in a human
friendly manner.Project pageInstallation and UsageInstallttracevia pip:[<python executable> -m] pip install [-U] ttraceA new executable is then provided which can be used instead ofstrace:ttrace [<ARGS>] <CMD>Note that you would'nt providestracearguments sincettraceprovides them
automatically.Alternatively you can clone and use the current development tree, see below.Intended interfaceThe following commands and outputs reflect the current development plan:ttrace<CMD|LOGFILE>Prints annotated, pre-formatted and filtered output next to the process' originalstdoutandstderr.ttrace--attach<PID|NAME>Attaches to the given process and displays all butstdoutandstderrof the
process of course.<CMD>|ttrace[<OTHER-ARGS>]Same as withattachbut using pipe semantics (limited due to the mixing ofstderrandstraceoutput.ttrace--grep<PATTERN><CMD>Applies pattern to the originalstraceoutput and only outputs the matching
content.ttrace--tree<CMD>Populates and displays a tree while the program is running.ttrace--hybrid<CMD>Not sure yet - plan is to havencursesbased split views for optionally any
of the following elements:tree outputcombinedstdoutandstderralternatively splitstdoutandstderrstrace consoleconsole with only warning character (whatever that means)ttrace--timing<CMD>ToDo for v1.0trace process terminationoutput growing process treereport / visualize abnormal process terminationreport / visualize file accessoptionally turn PIDs into PID counters for comparabilityoptionally print timestamp, pid, line numberno colorloggingOther ideastrace changes environmenttrace docker image usagehighlight failed processesDevelopment & Contributionpip3 install -U poetry pre-commit
git clone --recurse-submodules https://projects.om-office.de/frans/ttrace.git
cd ttrace
pre-commit install
# if you need a specific version of Python inside your dev environment
poetry env use ~/.pyenv/versions/3.10.4/bin/python3
poetry installLicenseSeeLicense.mdReadThe Difference Between fork(), vfork(), exec() and clone()HN: The Magic of straceThe Magic of strace (archive.org)
Package: ttrs-quicfire
ttrs_quicfirettrs_quicfire is a Python library to easily configure burn models for plots of land defined using shape files for the quicfire model.InstallationDISCLAIMER:This is currently the only verified and supported installation method. Other methods may work but will not be troubleshooted by the authors.Download and install anacondahere.Start by downloading the fastfuels.yml from the GitHubrepo. This can also be done using:(base)system:~ user$wgethttps://raw.githubusercontent.com/QUIC-Fire-TT/ttrs_quicfire/main/fastfuels.ymlNavigate to where the fastfuels.yml is located and create a new conda enviornment using:(base)system:~ user$condaenvcreate-ffastfuels.ymlOnce the enviornment has been created, activate it using:(base)system:~ user$condaactivatefastfuelsNext, install ttrs_quicfire using:(fastfuels)system:~ user$pipinstallttrs_quicfireNOTE:All additional packages will be installed with this step.ttrs_quicfire by Tall Timbers is licensed under a MIT License
Package: ttrss
UsageThis tool can be used to synchronize feeds from aTiny Tiny RSSserver.
If you’re a bit like me and prefer reading your feeds through the browser, you’ll sure have been in the situation of not being able to access your feeds due to the lack of an internet connection.ttrsswill help you to read articles offline in a very simple manner.For a quick introduction, let me show how you would use the tool to get started.$ ttrss synchronize -d ~/news/ --url https://ttrss.example.com/ --username example --keyring-service ttrss.example.comAs can be seen above, you have to specify a directory where all unread articles will be saved in.
Additionally, server information and login credentials must be provided.
For now, the only way of specifying a password is by using thekeyringcommand line tool, which is passed the--usernameand the--keyring-service.InstallationFrom PyPIpip install ttrssFrom Source./setup.py installConfigurationA configuration file can be saved to~/.config/ttrss/config.inito avoid specifying the path and other information for each invocation.
Of course,$XDG_CONFIG_HOMEcan be set to change your configuration path.
Alternatively, the path to the configuration file can be set via the--config-fileargument.[GENERAL]
RootDir = ~/news/
Url = https://ttrss.example.com/
Username = example
KeyringService = ttrss.example.comDevelopmentThe source code is located onGitHub.
To check out the repository, the following command can be used.git clone https://github.com/eikendev/ttrss.git
Package: ttrss-python
ttrss-python - A Tiny Tiny RSS client libraryHave you ever wanted to write a python application to interface with your Tiny Tiny RSS server? Read on!At a glanceNow with Python 3 support!Getting started is easy! Just typepip installttrss-pythonin the virtualenv of your choice.Usage example:from ttrss.client import TTRClient
client = TTRClient('http://url-to-rss-installation', 'username', 'super-secret-password', auto_login=True)
cats = client.get_categories()
cat = cats[0]
cat.title
u'News'
feeds = cat.feeds()
feed = feeds[0]
feed.title
u'MacRumors: Mac News and Rumors - All Stories'
headlines = feed.headlines()
# etc...More detailed documentation can be found athttps://ttrss-python.readthedocs.org/en/latest/Developmentttrss-python is still in early development and not yet feature complete. If there’s a specific feature
you’d like me to prioritize, feel free to submit an issue or a pull request.The source code is available athttps://github.com/Vassius/ttrss-pythonAuthorttrss-python is written and maintained by Markus Wiik <vassius@gmail.com>.Contribution & feedbackContributions are welcome! Submit a pull request, file a bug report or write some docs if you’d like.
Feature requests and other kinds of feedback are also appreciated.Licensettrss-python is MIT licensed. See LICENSE for details.
Package: ttrun
Simple CLI to run testtools testsIn atestrepositorybased workflow, sometimes you want/need to run individual
tests. Additionally, someitmes you want to use a pre-existing tox virtualenv
to do so. Or, at least, I do.Typing.tox/py27/bin/python-mtesttools.runsome.testGot boring. So this is a simple wrapper.It has two modes.ttrunsome.testWill run that test with the system python.If you want to re-use a tox virtualenv.ttrun-epy27some.testWill run some.test in the given tox venv.Both modes can be run with no parameters to have testtools run all the tests.
Package: ttrw
TTRWIt's a simple python package that returns a string with a few random words similar to name generator for twitch.tv clips.
Words are chosen from built in dictionary and capitalized.
The first one is an adverb, the second is an adjective and the third is a noun.You can also choose to get single word (adjective/adverb/noun).There are english and polish dictionaries available (Polish words without national/accented characters).>>> ttrw.get_random_words()  
VerySadFish$ python -m ttrw
SlightlyHandsomePotatoInstallation:Use pip:pip install ttrwUsage:Sample usage:importttrwprint("Available languages:")print(ttrw.languages)print(ttrw.get_random_words())print(ttrw.get_random_words("en"))print(ttrw.get_random_words(lang="pl"))print(ttrw.random_noun())print(ttrw.random_adjective(lang="pl"))You can also just execute the module in terminal:python -m ttrw
python -m ttrw en
python -m ttrw plReferences:English dictionary is based on WordNet®.Polish Dictionary is based on ArkadiaWiki andhttps://sjp.pl/.Licenses for each dictionary are in their respective folders.License:Code is under MIT license. See "LICENSE" file.
Package: tt_sass
Collection ofSassstyles and mixins for use at theTexas Tribune.Installation and ConfigurationYou can install this usingpiplike this:pip install tt_sassOnce installed, you need to add it to yourINSTALLED_APPS.  You can do that
however you like or you can copy-and-paste this in after yourINSTALLED_APPSare defined.INSTALLED_APPS += ['tt_sass', ]tt_sassrelies ondjango-staticfilesin order to work.  You must run
thecollectstaticcommand inside your project like this:python manage.py collectstatic --linkRemember, you must re-run this command any time you add new staticfiles.Now you’re ready to start usingtt_sass.UsageYou can use this inside your Sass by adding the following:@import "tt_sass/texastribune"Once you’ve done that, you need to compile your Sass.  Assuming you’re using the
default Texas Tribune setup of having astaticdirectory at your project root,
you should run the following:sass --load-path=static/ --watch --poll --compass staticThis command setups up the path correctly for all of your code and watches the
file for changes.Using the GridThe grid is based off ofChris Coyer’ssimple grid.  The syntax has been
changed around a little bit and it’s been mixinified, but the concept is the
same.To create a grid, similar to a row in frameworks like Foundation and Bootstrap,
you use the.gridclass.  Inside a grid, you add cells and tell them how far
to span.  For example, you do this to create a grid with 12 columns (the
default) and two cells, one of 8 columns and one of 4 columns:<div class="grid">
    <div class="cell w-8"></div>
    <div class="cell w-4"></div>
</div>Creating a Semantic GridTODOUsing the Responsive Mixinstt_sassprovides you with abreakpointmixin for handling responsive
design.  It ships with the following breakpoints built-in:mobile-portraitdefaults tomax-width:320pxmobiledefaults tomax-width:720pxtabletdefaults tomin-width:720pxclassicdefaults tomin-width:960pxYou can over ride any of these values by setting a variable by their name prior
to importingtt_sass/texastribune.You use the mixin like this:p
    +breakpoint(mobile)
        font-size: 1.2em
    +breakpoint(tablet)
        font-size: 1.1em
    +breakpoint(classic)
        font-size: 1.0emYou can specify an arbitrary breakpoint as well:div
    +breakpoint("max-width: 500px")
        background-color: redVarious HelpersTODOExamplesAll of these are being documented in theexample/Django project.  See that
directory for instructions on how to run that project.ContributingThis project is released in hopes that it helps people understand how you might
build your own Sass framework for use in the context of a Django project.  As
such, contributions from those outside the Texas Tribune probably won’t be
accepted.
Package: ttsbroker
ttsbrokerSimple TTS (Text-To-Speech) broker for PythonLicense: Apache License 2.0Warning: Refer to TTS provider license about caching, storing, redistributing
and playing rights for the audio files generated with TTS engine.The module contains providers for:gcloud: Google Cloud TTS (requires cloud service account key), requires
oauth2client python modulepolly: Amazon Polly (requires AWS API keys), requires boto3 python modulewatson: IBM Watson (requires Watson service credentials)Usage example:fromttsbrokerimportTTSEngineasTTSEe=TTSE(cache_dir='/data/cache/gcloud',cache_format='ogg',device=0,gain=0,provider='gcloud')e.set_key('client_service_key.json')e.say('test number one',gain=2)e.say('test number two',provider_options={'voice':'en-US-Wavenet-E'})(c) 2018 Altertech Group,https://www.altertech.com/
Package: ttscorpus
tts-corpus-creatorcollection of different source of tts api for generating corpus. feature:large scale ttssupport both free and charge sourceSourceChargeGoogle Cloud TTSinstallpip install google-cloud-texttospeechimportosos.environ["GOOGLE_APPLICATION_CREDENTIALS"]="xxx.json"fromttscorpus.sourceimportGoogleCloudgc=GoogleCloud()gc("hi,there",'output')FreeMacinstall ffmpegbrew install ffmpegfromttscorpus.sourceimportMACmac=MAC()mac('hello, there, I am mac','output')Google TTSinstallpip install gttsfromttscorpus.sourceimportGoogleTTSmac=GoogleTTS()mac('sixty six year old badly. independence of mutual fund boards represents discrete defeat.','test')Android TTSbuild android tts server app
from:https://github.com/voidful/android-tts-serverfromttscorpus.sourceimportAndroidTTSatts=AndroidTTS('http://xxxx:port')atts("CHAPTER SIXTEEN I MIGHT HAVE TOLD YOU OF THE BEGINNING OF THIS LIAISON IN A FEW LINES BUT I WANTED YOU TO SEE EVERY STEP BY WHICH WE CAME I TO …",'test')
Package: ttsdg
TTSDGTTSDG, or Text-To-Speech Data Generator, automates the simple-but-frustrating task of generating large amounts of TTS
data for tasks like machine learning. TTSDG contains an easy-to-use class that can generate text offline, in large
batches, and with control over the system voices that you have installed. TTSDG randomizes volume, speed, and voice of
each sample, and prevents duplicates from happening.TTSDG utilizespyttsx3andpydubto generate the
audio and convert it into multiple formats. All pydub-supported formats are supported in TTSDG, like WAV, MP3, and AIFF.InstallationTTSDG is available through pip:python3 -m pip install ttsdgUsagefromttsdgimportTTSDGforwordin["Apple","Orange","Banana"]:print(word)gen=TTSDG(verbose=True)gen.volume_range=[.5,1.0]gen.wpm_range=[200,300]gen.generate(word,100,out_format="wav")# A bug in pyttsx3 will cause hangs on generation# in loops sometimes. del the generator at the end# of the loop to solve thisdelgenMethodsset_volume_range(low, high, one)- Set low or high volume bounds, or setonefor a specific value.set_wpm_range(low, high, one)- Set low or high speed bounds (in words per minute), or setonefor a specific
value.set_voices(voices)- Only mess around with this if you know what you're doing. Sets the list of voices to choose
from, relies on what system voices you have installed.set_engine(engine)- Only mess around with this if you know what you're doing. Sets the pyttsx3 Engine object,
useful for importing settings if your project already has an engine.get_engine()- Gets the pyttsx3 engine object.generate(text, n, out_format)- Generatesnsamples of the inputtext, saves them to./(text)/(text)_index.(out_format)
Package: ttslearn
ttslearn: Library for Pythonで学ぶ音声合成 (Text-to-speech with Python)日本語は以下に続きます (Japanese follows)English: This book is written in Japanese and primarily focuses on Japanese TTS. Some of the functionality (e.g., neural network implementations) in this codebase can be used for other languages. However, we didn't prepare any guide or code for non-Japanese TTS systems.
We may extend the codebase for other languages in the future but cannot guarantee if we would work on it.Installationpip install ttslearnリポジトリの構成ttslearn: 「Pythonで学ぶ音声合成」のために作成された、音声合成のコアライブラリです。pip install ttslearnとしてインストールされるライブラリの実体です。書籍のサンプルコードとしてだけでなく、汎用的な音声合成のライブラリとしてもご利用いただけます。notebooks: 第4章から第10章までの、Jupyter notebook形式のソースコードです。hydra: 第6章で解説している hydra のサンプルコードです。recipes: 第6章、第8章、第10章で解説している、日本語音声合成のレシピです。JSUTコーパスを利用した日本語音声合成システムの実装が含まれています。extra_recipes: 発展的な音声合成のレシピです。書籍では解説していませんが、ttslearnライブラリの利用例として、JSUTコーパス、JVSコーパスを用いた音声合成のレシピをリポジトリに含めています。詳細なドキュメントは、https://r9y9.github.io/ttslearn/を参照してください。ライセンスソースコードのライセンスはMITです。商用・非商用問わずに、お使いいただけます。
詳細はLICENSEファイルを参照してください。学習済みモデルの利用規約本リポジトリのリリースページでは、JSUTコーパス・JVSコーパスを用いて学習した、学習済みモデルを配布しています。それらの学習済みモデルは、「非商用目的」でのみ利用可能です。
学習済みモデルを利用する際は、各コーパスの利用規約も併せてご確認ください。また、作者は、学習済みモデルの利用による一切の請求、損害、その他の義務について何らの責任も負わないものとします。付録付録として、日本語音声合成のフルコンテキストラベルの仕様をまとめています。
詳細は、docs/appendix.pdfを参照してください。問い合わせ書籍の内容、ソースコードに関する質問などありましたら、GitHub issue にてお問い合わせをいただければ、可能な限り返答します。お詫びと訂正本書の正誤表を以下のリンク先でまとめています。本書の正誤表もし、正誤表に記載されていない誤植などの間違いを見つけた場合は、GitHub issue にてご連絡ください。謝辞Tacotron 2の一部ソースコードは、ESPnetを元に作られました。(thanks to@kan-bayashi)発展的なレシピの実装のほとんどにおいて、kan-bayashi/ParallelWaveGANを利用しました。日本語音声合成のテキスト処理には、Open JTalkおよびそのPythonラッパーを利用しました。リンクAmazon:https://www.amazon.co.jp/dp/4295012270/インプレス書籍情報:https://book.impress.co.jp/books/1120101073
Package: ttsmms
ttsmmsText-to-speech with The Massively Multilingual Speech (MMS) projectThis project want to help you for use Text-to-speech model from MMS project in Python.Support 1,107 Languages! (See support_list.txt)VITS:GitHubMMS: Scaling Speech Technology to 1000+ languages:GitHubGoogle colabDon't forget the TTS model in MMS project use CC-BY-NC license.Installpip install ttsmmsUsageFirst, you need to download the model byfromttsmmsimportdownloaddir_path=download("eng","./data")# lang_code, dir for save modelor download file by yourselfLinux/Macdownloadcurlhttps://dl.fbaipublicfiles.com/mms/tts/lang_code.tar.gz--output lang_code.tar.gzextract a tar ball archive.Linux/Macmkdir -p data && tar -xzf lang_code.tar.gz -C data/and use code in python :DfromttsmmsimportTTStts=TTS(dir_path)# or "model_dir_path" your path dir that extract a tar ball archivewav=tts.synthesis("txt")# output:# {#    "x":array(wav array),#    "sampling_rate": 16000# }tts.synthesis("txt",wav_path="example.wav")# output: example.wav file
Package: ttspico
ContentsIntroductionHistoryLicenseSource codeIntroductionThis is a python wrapper to the SVOX pico text to speech engine.
The pico TTS engine is found in the android open source
repositories and is covered by an Apache 2.0 license.
It is very efficient and offers superior speech quality to most other
open source solutions that we could find.HistoryThe main port of the pico TTS to linux was done by DougGore/picopi
where this code was forked from.LicenseLicensed under the Apache License, Version 2.0 (the “License”);
you may not use this file except in compliance with the License.
You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an “AS IS” BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.Source codehttps://github.com/sevangelatos/py-ttspico
Package: ttspy
PyTTS is multi-platform Text-To-Speech module based on Google translate engine. Therefore it takes advantage of Google’s mixed engines,
and the 27 languages can be used.RequirementPyTTS requires an internet connection because every request are sent to Google’s engine.The python modules required are gstreamer and gobject. Gstreamer is used to read the speech stream from Google to play it back on Speakers.
Gobject is used to keep the handle while the speech is not played entirely. (Catch the gstreamer eos(End Of Stream) message)How to use it ?You can use this script either as a program either as a module. In both case it’s usage is fairly easy.As a scriptTo use it as a script you should give in first argument the language code followed by the text. Internaly it creates an pytts object and call the “say” methods which speech the text
and return when the speech is done. Example:./pytts en Hello world !As a python moduleTo use PyTTS as a module, you just need to import the module and instanciate a pytts object. Then you can for instance call the “say” method to speech the given text.from pytts import pytts
pytts().say(“Hello world !”,”en”)The available methods for pytts are:say(self, text, lang=’en’, volume=5.0)Speech the given text, and return when its done.sayNB(self, text, lang=’en’, volume=5.0)Same as say but non-blocking method. NB (for non blocking)download(self, text, lang=’en’, filename=”translate_tts.mp3”)Download the mp3 speech file instead of playing it. (Into the given file path)setVolume(self, val)Put the player volume at the given value
Package: ttss
TTSSA simple Python wrapper for TTSS (Traffic Tram Supervision System) API.RequirementsPython 3.8+Installationpip install ttssUsageFor MPK Kraków trams:fromttssimportTTSSttss=TTSS(base_url='http://www.ttss.krakow.pl')For MPK Kraków buses:ttss=TTSS(base_url='http://ttss.mpk.krakow.pl')Note: the base URL must not contain/internetserviceand must not end with/.
Package: ttstokenizer
ttstokenizer: Tokenizer for Text to Speech (TTS) modelsSee the original repositoryhttps://github.com/Kyubyong/g2pfor more information on English Grapheme to Phoneme conversion.Other than removing unused dependencies and reorganizing the files, the original logic remains unchangedttstokenizermakes it easy to feed text to speech models with minimal dependencies that are Apache 2.0 compatible.The standard preprocessing logic for many English Text to Speech (TTS) models is as follows:ApplyTacotrontext normalization rulesThis project replicates the logic found inESPnetConvert Graphemes to PhonemesBuild an integer array mapping Phonemes to their integer token positionsThis project adds a new tokenizer that runs the logic above. The output is consumable by machine learning models.InstallationThe easiest way to install is via pip and PyPIpip install ttstokenizerUsageAn example of tokenizing text for TTS models is shown below.from ttstokenizer import TTSTokenizer

tokenizer = TTSTokenizer(tokens)
print(tokenizer("Text to tokenize"))

>>> array([ 4, 15, 10,  6,  4,  4, 28,  4, 34, 10,  2,  3, 51, 11])