Saravanan666/pypi-org huggingface dataset:
Package: tlctl
tlctlWhat is this?by: axinertlctlThis is a tlctl.InstallationThis package can be installed using pip (>=Python3.7):pip install tlctlCopyrightCopyright (c) 2022 axinerPermission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Package: tldfinder
TLDFinderTLDFinder is a powerful Python package designed to effortlessly identify the valid top-level domains (TLDs) for a provided list of domains that include a wildcard character in the TLD.UsageThe usage of TLDFinder is simple. You can provide the domain using a wildcard character in the TLD scope through standard input (stdin). Here's an example:echo"example.*"|tldfinder
catdomains.txt|tldfinderPlease note that the first time you run the script, it may take a little more time to fetch the TLDs from the source. Subsequent runs should be faster as the TLDs will be cached.ContributingContributions to TLDFinder are welcome! If you find any issues or have suggestions for improvements, we appreciate your contribution. Your feedback helps us make TLDFinder better for everyone.
Package: tldgen
tldgenAppend TLD to words. Helps to perform domain enumeration.ExampleGive a word to append TLDs:$ tldgen contoso
contoso.aaa
contoso.aarp
contoso.abarth
contoso.abb
...
contoso.zippo
contoso.zm
contoso.zone
contoso.zuerich
contoso.zwInstallationpip install tldgen
Package: tld_name
A top-level domain (TLD) is one of the domains at the highest level in the hierarchical Domain Name System of the Internet.[1] The top-level domain names are installed in the root zone of the name space. For all domains in lower levels, it is the last part of the domain name, that is, the last label of a fully qualified domain name. For example, in the domain name www.example.com, the top-level domain is .com (or .COM, as domain names are not case-sensitive). Management of most top-level domains is delegated to responsible organizations by the Internet Corporation for Assigned Names and Numbers (ICANN), which operates the Internet Assigned Numbers Authority (IANA) and is in charge of maintaining the DNS root zone.http://en.wikipedia.org/wiki/Top-level_domainfrom tld_name import tld_nameprint tld_name(‘www.work.com’)print tld_name(‘zsp.com’)print tld_name(‘www.zsp.com’)print tld_name(‘www.zsp.edu.cn’)
Package: tldraw
Jupyter TldrawInstallation:python3.11 -m venv .venv
pip install jupyterlab
pip install tldraw
jupyterlab   (or alternative VS Code Jupyter Lab)Examplefrom tldraw import TldrawWidget
t = TldrawWidget()
tMakeReal Examplefrom tldraw import MakeReal
from api_key import api_key

m = MakeReal(width=1002, height = 500, api_key = api_key)
mINFO: To use GPT4-Vision, you need an API key.How do I get my API key?Create an OpenAI account atOpenAIIn your Openai API account, navigate toSettings > BillingClickAdd to credit balanceAdd at least$5to your accountNavigate toAPI KeysClickCreate new secret keyCopy the key to your clipboard.Back on your jupyter-tldraw folder, paste the key into the API key into a new file called api_key.pyAdd the key in this form:api_key = "sk-*************************".Addapi_key.pyinto your gitignore. WARNING: Don't upload your API KEY on GitHub!Now you're ready to run!For transparency, this is how the key is used:https://github.com/kolibril13/jupyter-tldraw/blob/main/src/tldraw/prompt.py#L5-L47Changelog2.0.6Tweak prompt parameter.2.0.5Add requests module
Tweak readme2.0.4Add experimental SVG/PNG export.Add experimental .txt export.Add makereal2.0.3Update to version2.0.0-alpha.192.0.2Add experimental TldrawImageArray2.0.1Switch to new version:@tldraw/tldraw@2.0.0-canary.b9d82466295e(Version from 6th November2023)2.0.0simplify to minimal template1.0.0Rename notebooks, and prepare 2.0.0 release.0.1.5add .venv to gitignore, so that it's not uploaded to pypi by hatch build.0.1.4Add experimental TldrawSegmentation0.1.3format toml0.1.2replace ipyreact backend with anywidget backend.this will make this package more reliable, because all js and css is shipped via pip and not anymore via cdn.Remove JupyterLite build.Remove experimental files.0.1.1add update_plot in TldrawMatplotlib0.1.0Added TldrawMatplotlib0.0.3refactor readmeadd jupyterlite demo0.0.2refactor code0.0.1init setup
Package: tldream
tldreamA tiny little diffusion drawing apphttps://user-images.githubusercontent.com/3998421/223580181-6375fc76-414a-4837-b7ab-4fb07509afd3.mp4FeaturesSupport any Stable Diffusion 1.5 model on HuggingFace or local ckpt/safetensorsSupport multi-language translation: zh, ja, ko, ruQuick Start# In order to use the GPU, install cuda version of pytorch first.# pip install torch==1.13.1+cu117 --extra-index-url https://download.pytorch.org/whl/cu117pipinstalltldream
tldream--modelrunwayml/stable-diffusion-v1-5--devicecudaIf you are not familiar with python/pip, you can try this installer:Windows 1-click InstallerCommand line arguments--listen / --no-listen: If true, start server at 0.0.0.0  [default: no-listen]--port INTEGER: [default: 4242]--device TEXT: Device to use (cuda, cpu or mps)  [default: cuda]--model TEXT: Any HuggingFace Stable Diffusion model id. Or local ckpt/safetensors path  [default: runwayml/stable-diffusion-v1-5]--lang TEXT: Translation language model. ['en', 'zh', 'ja', 'ko', 'ru']  [default: en]--low-vram / --no-low-vram: Use low vram mode  [default: no-low-vram]--fp32 / --no-fp32: Use float32 mode (For NVIDIA 16xx GPU)  [default: no-fp32]--nsfw-filter / --no-nsfw-filter: Enable nsfw filter  [default: nsfw-filter]--cache-dir TEXT: Model cache directory, by default model downloaded to ~/.cache/huggingface/hub--local-files-only / --no-local-files-only: Not connect to HuggingFace server, add this flag if model has been downloaded  [default: no-local-files-only]
Package: tldr-man
tldr-manA tldr-pages client that works just likemantldr-manis a command-line client fortldr-pages,
a collection of community-maintained help pages for command-line tools.
It differs from other clients because it displays its pages asmanpages.This client is also able to integrate with themancommand to fall back to displaying a tldr-page for a command when
no manpage exists.Features:Fully abides by thetldr-pages client specification.Supports all page languages, not just English pages.Displays tldr-pages in the same style as manpages.Integrates withmanto provide a fallback for missing manpages.Supports rendering markdown formatted tldr-pages with--render.Local cache abides by theXDG base directory specification.Supports shell completion forbash,zsh, andfishshells.And much more!InstallationWith HomebrewInstalltldr-manwithHomebrew:brewinstallsuperatomic/tap/tldr-manWith PipInstalltldr-manwith pip (version 3.10+):pipinstalltldr-mantldr-manadditionally depends onpandocbeing installed.After installation, you can view a tldr-page with thetldrcommand.UsageDisplay a tldr-page for a command:tldr<COMMAND>Update the local page cache:tldr--updateRender a page locally:tldr--renderpath/to/page.mdPrint tldr manpage paths as a colon-separated list (see theManpage Integrationsection):tldr--manpathDisplay usage information:tldr--helpSetting languagesAs specified by the tldr-pages client specification,
tldr-pages from other languages can be displayed by this client
(falling back to English if the page doesn't exist for that language).To do so, set any of the environment variables$LANG,$LANGUAGE, or$TLDR_LANGUAGEto the two-letter language code
for your language (e.g.export LANGUAGE=es),
or set the--languageoption when runningtldr(e.g.tldr <COMMAND> --language es).Setting platformsBy default, tldr-pages will be displayed based on your current platform.
To directly specify what platform's page to use, use the--platformflag.For example, to display the macOS version of thetopcommand's tldr-page, runtldr top --platform macos.
This is the default behavior on macOS,
but--platform macosis required to show the macOS version of this page on other platforms.Manpage IntegrationThe commandmancan be set up to fall back to displaying tldr-pages if no manpages are found.To do so,
add the provided line to your shell's startup script (e.g.~/.bash_profile,~/.zshenv,~/.config/fish/config.fish)
to add this behavior toman:Bash and ZshexportMANPATH="$MANPATH:$(tldr--manpath)"Fishset-gxaMANPATH(tldr--manpath)
Package: tldr-news
TLDR News TerminalThis is a simple terminal application that shows the latest tech news headlines from theTLDR Newsletter.The application is written in Python, uses theBeautifulSouplibrary to parse the HTML content of the newsletter and usesTextuallibrary to render the content in the terminal.Usagepipinstalltldr_newsInstallationTo install the application, simply run the following command after cloning the repository:Install dependenciespoetryinstall&&poetryshellRun the applicationpoetryruntldr_newsDISCLAIMERThis is not an official TLDR Newsletter product, but a personal project coming from my love with this newsletter. I am not affiliated with TLDR Newsletter in any way.All the newsletter content is owned by TLDR Newsletter and I am not responsible for any of the content.
Package: tldr-python
tldr-pythonPython wrapper for the TLDR text summarization and analysis API available onRapidAPI.Installationpip install tldr-pythonIntroduction - Getting Startedtldr-python is a wrapper over the TLDR text summarization and analysis API. To use this API, create an account onRapidAPIandsubscribe to the API.Once you have a RapidAPI key, initialize a TLDR instance as demonstrated below.from tldr_python import TLDR
tldr = TLDR('<your RapidAPI key>')Text SummarizationYou can use TLDR to summarize articles on the web with thesummarizefunction. This function accepts either a URL or the raw text of an article on the web.We can summarize a Wikipedia article about Python using the code below.summary = tldr.summarize('https://en.wikipedia.org/wiki/Python_(programming_language)', max_sentences=3)
print(summary.text)The code above produces the following summary:'[34][35][36][37][38] History[edit] Python was conceived in the late 1980s[39] by Guido van Rossum at Centrum Wiskunde & Informatica (CWI) in the Netherlands as a successor to ABC programming language, which was inspired by SETL,[40] capable of exception handling and interfacing with the Amoeba operating system.[67] The standard library has two modules (itertools and functools) that implement functional tools borrowed from Haskell and Standard ML.[69] Alex Martelli, a Fellow at the Python Software Foundation and Python book author, writes that "To describe something as \'clever\' is not considered a compliment in the Python culture.'Keyword ExtractionWe can also extract keywords from an article as shown below.keywords = tldr.extract_keywords('https://en.wikipedia.org/wiki/Python_(programming_language)', n_keywords=3)
print(keywords.json)The result of the code above is a JSON list with the top three scored keywords from the article.[{'keyword': 'python', 'score': 402}, {'keyword': 'language', 'score': 68}, {'keyword': 'software', 'score': 47}]Sentiment AnalysisWe can also analyze the sentiment of an article with theanalyze_sentiment function. This function returns a Sentiment object with sentiment and polarity attributes.sentiment = tldr.analyze_sentiment('https://en.wikipedia.org/wiki/Python_(programming_language)')
print(sentiment.json)The code above gives a dictionary with the sentiment and polarity of the article.{'sentiment': 'positive', 'polarity': 0.10235096701177092}
Package: tldsearcher
TLDSearcherThis Python tool searcher target domains for existing top-level domains(TLDs)Knowing which TLDs are active for a specific domain can be a helpful tool in reconnaissance during a scan. Instead of Google-dorking, and let's face it - failing to get enough results, useTLDSearcherto checkALL, currently available TLDs on the web.InstallationTLDSearchercan be installed viaGithuborPyPI. Details on each are listed below.GithubNavigate to the directory where you want to download the program.open a terminal and type:git clone https://www.github.com/plague-anon/TLDSearcherChange into the directory git made for you:cd TLDSearcherRun the following command to install the program:python3 setup.py installYou can now use thetldsearchercommand from anywhere on your systemPyPIYou can installTLDSearchervia pipMethod 1Issue the following command from the terminal to download thelatest versionfrompypi.orgpip3 install tldsearcherUsage ExamplesTo verbosely search forallTLDs forexample:tldsearcher -t example -vTo verbosely search for specific TLDs forexampleand output intoscan.txt:tldsearcher -t example -d com,net,info,org -o scan.txt -vTo see a list of TLD categories to scan forexample:tldSearcher -t example -dC -o scan.txt -vFor more examples and usage, please refer to theWiki.Metaplague –plague_anon@protonmail.comJoin me on the official Anonymous IRC webchat.anonops.com, or via an IRC client, irc.anonops.com:6697Distributed under the GNU General Public License v3.0. SeeLICENSEfor more information.https://github.com/plague-anon/TLDSearcherContributingFork it (https://github.com/plague-anon/TLDSearcher)Create your feature branch (git checkout -b feature/fooBar)Commit your changes (git commit -am 'Add some fooBar')Push to the branch (git push origin feature/fooBar)Create a new Pull RequestHistory1.2.0You can now specify a maximum number of scans to do with the--max_scansflagResults printing is now enhancedA sample output file has been added1.1.0You can now specify which domain to start from(when doing a full TLD scan)by using the -dc flag-dc <Domain_To_Continue_From>You can now save the output of a scan into a file by using the-o <output_file_name>flag1.0.6Fixed bug with files1.0.5Addedmainfile to root directory to prevent error when starting via python31.0.4Corrected errors in documentation and git trees1.0.3Added more documentationNew installation instructions1.0.2Small documentation changes1.0.1Fixed 'Module not recognised' bugAdded start time to beginning of scan processFixed verbose mode not printing negative results1.0.01.0.0 full package release
Package: tle2czml
tle2czmlPython package which takes in Two Line Element's (TLE's) and returns a czml file visualising their orbits.https://pypi.python.org/pypi/tle2czmlBackgroundCZML is a JSON format for describing a time-dynamic graphical scene, primarily for display in a web browser runningCesium.ATLEis a data format encoding a list of orbital elements of an Earth-orbiting object for a given point in time.This package usessgp4.pyto predict the satellites fututure postion, and a slightly modifiedczml.pyto create the .czml files.Requirementspython3pipText file containing list of two line elements, example:ISS (ZARYA)             
1 25544U 98067A   20293.22611972  .00000497  00000-0  17003-4 0  9991
2 25544  51.6436  94.7185 0001350  46.8729 126.5595 15.49312821251249
KESTREL EYE IIM (KE2M)  
1 42982U 98067NE  20293.11355452  .00022129  00000-0  15728-3 0  9999
2 42982  51.6336   8.5058 0001619 215.9884 144.1006 15.73808685170523
DELLINGR (RBLE)         
1 43021U 98067NJ  20292.66572402  .00020201  00000-0  13900-3 0  9998
2 43021  51.6343   8.5926 0000331  53.4398 306.6632 15.74631224166254
UBAKUSAT
1 43467U 98067NQ  20293.19063114  .00070844  00000-0  29473-3 0  9996
2 43467  51.6335   1.3662 0002867   6.9343 353.1700 15.85064344139669
CUBERRT
1 43546U 98067NU  20292.65915576  .00130902  00000-0  58528-3 0  9997
2 43546  51.6326   6.1225 0002465  18.8688 341.2406 15.83306046129681Installpip install tle2czmlUsageimporttle2czml# Creates a file in the current directory called "orbit.czml", containing the orbits of the satelites over the next 24 hours.tle2czml.create_czml("tle.txt")importtle2czmlfromdatetimeimportdatetime# You can specify the time range you would like to visualisestart_time=datetime(2020,10,1,17,30)end_time=datetime(2020,10,2,19,30)tle2czml.create_czml("tle.txt",start_time=start_time,end_time=end_time)importtle2czml# You can also specify a different output pathtle2czml.create_czml("tle.txt",outputfile_path="other_orbit_file.czml")View OrbitsTo view the orbits, go tohttps://cesiumjs.org/Cesium/Build/Apps/CesiumViewer/and drag the .czml file into the browser.
(Click the "Play" button in the bottom left corner to start the visualisation)You can find up to date TLE's for most satellites onhttps://www.celestrak.com/NORAD/elements/To DoAdd command line scriptAllow users to login with space-track.orgAdd ability to select base64 image to use for satelliteAdd ability to generate html file with cesium globle displaying czml file
Package: tle-download
TLE DownloadA small utility to download TLEs from Space Track.Installationpipx install tle-download

# or

pip install tle-downloadCommand Line Usageexport SPACE_TRACK_USERNAME=user@example.com
export SPACE_TRACK_PASSWORD=your-password

# Search by Catalog ID:

tledl catid 40075 36797

# Search by TLE line 0 text

tledl line0 AISSAT LEMURAll Command Line OptionsUsage: tledl [OPTIONS] SEARCH_TYPE:{line0|catid} SEARCHES...

Arguments:
  SEARCH_TYPE:{line0|catid}  [required]
  SEARCHES...                [required]

Options:
  --username TEXT       [env var: SPACE_TRACK_USERNAME]
  --password TEXT       [env var: SPACE_TRACK_PASSWORD]
  --outpath FILE        [default: tles.txt]
  --sleep INTEGER       sleep between requests so you don't break API limits
                        [default: 3]
  --install-completion  Install completion for the current shell.
  --show-completion     Show completion for the current shell, to copy it or
                        customize the installation.
  --help                Show this message and exit.Python Usagefromtle_downloadimportget_tlestles=get_tles(username,password,'line0',['AISSAT','LEMUR'])
Package: tle-storage-service
TLEStorageServiceSmall aiohttp server application for TLE storageRequirementsaio-nasa-tle-loader >= 1.0.0aio-space-track-api >= 2.1.1aiohttp >= 2.1.0aiopg >= 0.13.0alembic >= 0.9.2pyaml >=16.12.2sqlalchemy >= 1.1.10ujson >= 1.35Installingpip install tle-storage-serviceGetting startedStart aiohttp application:#!/usr/bin/env python3# -*- coding: utf-8 -*-importloggingimportosfromaiohttpimportwebfromtle_storage_serviceimportTleStorageService,load_cfg,LOG_FORMATDIR=os.path.abspath(os.path.dirname(__file__))if__name__=='__main__':logging.basicConfig(level=logging.INFO,format=LOG_FORMAT)app=TleStorageService(config=load_cfg(path=os.path.join(DIR,'config','server.yaml')))web.run_app(app,port=8080)Create periodic script for refresh db#!/usr/bin/env python3# -*- coding: utf-8 -*-importasyncioimportloggingimportosfromaio_nasa_tle_loaderimportAsyncNasaTLELoaderfromaio_space_track_apiimportAsyncSpaceTrackApifromaiopg.saimportcreate_enginefromtle_storage_serviceimportperiodic_task,load_cfg,nasa,space_track,LOG_FORMATDIR=os.path.abspath(os.path.dirname(__file__))CFG=load_cfg(path=os.path.join(DIR,'config','periodic.yaml'))logger=logging.getLogger(__name__)@periodic_task(CFG['sync'].get('space-track',4)*3600)asyncdefcall_space_track(engine,api_params,satellites,loop):asyncwithAsyncSpaceTrackApi(loop=loop,**api_params)asapi:awaitspace_track(engine,api,satellites)@periodic_task(CFG['sync'].get('nasa',0.5)*3600)asyncdefcall_nasa(engine,loop):asyncwithAsyncNasaTLELoader(loop=loop)asloader:awaitnasa(engine,loader)asyncdefrun(db_params,api_params,satellites,loop):asyncwithcreate_engine(loop=loop,**db_params)asengine:awaitasyncio.gather(call_nasa(engine,loop),call_space_track(engine,api_params,satellites,loop),loop=loop)defnotify_callback(msg):logger.info('[%s] Receive msg <- "%s"',msg.channel,msg.payload)if__name__=='__main__':logging.basicConfig(format=LOG_FORMAT,level=logging.DEBUG)loop=asyncio.get_event_loop()loop.create_task(run(CFG['db'],CFG['space-track'],CFG['sync']['satellites'],loop))try:loop.run_forever()finally:loop.close()More code examples intoexamplesdirectorySource codeThe latest developer version is available in a github repository:https://github.com/nkoshell/tle-storage-service
Package: tlgbot
TLGBot - Telegram Bot Python LibraryTLGBot is a Python library for creating Telegram bots with ease. This library simplifies the interaction with the Telegram Bot API, allowing you to send messages, edit group descriptions, and more.InstallationYou can install TLGBot using pip:pipinstalltlgbotGetting StartedCreate a Telegram bot and obtain the API token. You can do this by talking to the BotFather on Telegram.Import the TLGBot class and create an instance with your API token.fromtlgbot.tlgbotimportTLGBot# Replace 'YOUR_API_TOKEN' with your actual bot API tokenbot=TLGBot('YOUR_API_TOKEN')Use the library's functions to interact with your bot.UsageSending a MessageSend a text message to a chat by specifying the chat ID and message text:chat_id='YOUR_CHAT_ID'# Replace with the chat ID you want to send the message tomessage='Hello, Telegram!'bot.send_message(chat_id,message)Sending a PhotoSend a photo to a chat by specifying the chat ID, the path to the photo file, and an optional caption:chat_id='YOUR_CHAT_ID'# Replace with the chat ID you want to send the photo tophoto_path='path/to/your/photo.jpg'# Replace with the actual file pathcaption='Check out this cool photo!'bot.send_photo(chat_id,photo_path,caption)Editing Group DescriptionEdit the description of a group chat by specifying the chat ID and the new description:chat_id='YOUR_CHAT_ID'# Replace with the chat ID of the groupnew_description='This is our updated group description.'ifbot.edit_about(chat_id,new_description):print('Group description edited successfully.')else:print('Error editing group description.')Responding to Last MessageReply to the last message in a chat by specifying the chat ID and the reply message:chat_id='YOUR_CHAT_ID'# Replace with the chat ID you want to respond inreply_message='Thanks for your message!'bot.reply_last_msg(chat_id,reply_message)EXAMPLE PRODUCTION CODEfromtlgbot.tlgbotimportTLGBot# Define tu tokentoken='Your_Bot_Token'# Obtén el último chat ID utilizando la función last_idchat_id=TLGBot.last_id(token)ifchat_idisnotNone:print(f'Último chat ID:{chat_id}')# Define un mensaje de respuestaresponse_message='Hello test'# Envia el mensaje al último chat IDTLGBot.send_message(TLGBot(token),chat_id,response_message)print('Mensaje enviado exitosamente.')else:print('No se pudo obtener el chat ID.')LicenseThis library is available under the MIT license.SupportIf you have any questions, suggestions, or need help with this library, please create an issue on theGithub Repository.