Saravanan666/pypi-org huggingface dataset:
Package: tether-price
Tether PriceTether price is a library that helps you to get the Tether price from various websites.How To InstallYou can use the following command to install it.pip install tether-priceGetting StartedfromtetherimportSourceManagerfromtether.sourcesimport*manager=SourceManager()manager.add(Bitbarg())manager.add(ArzPaya())manager.add(Wallex())manager.add(Hamtapay())if__name__=='__main__':prices_list=manager.get_prices_list()forpriceinprices_list.prices:print(f'{price.source}| Buy:{price.buy}| Sell:{price.sell}')LicenseMIT
Package: tethys-dask-scheduler
tethys_dask_schedulerA Dask scheduler with custom SchedulerPlugins to support integration with Tethys Platform.Installationpip install tethys_dask_schedulerORconda install -c conda-forge tethys_dask_schedulerStart SchedulerStart a scheduler that reports status updates to Tethys Portal.$ dask-scheduler --preload tethys_dask_scheduler.plugin --tethys-host http://localhost:8000

distributed.preloading - INFO - Import preload module: tethys_dask_scheduler.plugin
distributed.scheduler - INFO - -----------------------------------------------
distributed.preloading - INFO - Import preload module: tethys_dask_scheduler.plugin
distributed.http.proxy - INFO - To route to workers diagnostics web server please install jupyter-server-proxy: python -m pip install jupyter-server-proxy
distributed.scheduler - INFO - -----------------------------------------------
distributed.scheduler - INFO - Clear task state
distributed.scheduler - INFO -   Scheduler at: tcp://192.168.10.100:8786
distributed.scheduler - INFO -   dashboard at:                     :8787
distributed.scheduler - INFO - Tethys Host at:     http://localhost:8000
distributed.preloading - INFO - Run preload setup click command: tethys_dask_scheduler.plugin
distributed.scheduler - INFO - Register worker <WorkerState 'tcp://192.168.10.100:34297', name: tcp://192.168.10.100:34297, status: running, memory: 0, processing: 0>
distributed.scheduler - INFO - Starting worker compute stream, tcp://192.168.10.100:34297
distributed.core - INFO - Starting established connectionStart WorkerStart a Dask distributed worker as usual:$ dask-worker tcp://192.168.10.100:8786

distributed.nanny - INFO -         Start Nanny at: 'tcp://192.168.10.100:34359'
distributed.worker - INFO -       Start worker at: tcp://192.168.10.100:39569
distributed.worker - INFO -          Listening to: tcp://192.168.10.100:39569
distributed.worker - INFO -          dashboard at:       192.168.10.100:34857
distributed.worker - INFO - Waiting to connect to:  tcp://192.168.10.100:8786
distributed.worker - INFO - -------------------------------------------------
distributed.worker - INFO -               Threads:                          6
distributed.worker - INFO -                Memory:                   7.77 GiB
distributed.worker - INFO -       Local Directory: /home/tethys/tethysdev/tethys_dask_scheduler/dask-worker-space/worker-4j_bj5hv
distributed.worker - INFO - -------------------------------------------------
distributed.worker - INFO -         Registered to:  tcp://192.168.10.100:8786
distributed.worker - INFO - -------------------------------------------------
distributed.core - INFO - Starting established connectionTestsTests are executed using tox:pip install .[tests]
tox
Package: tethys-dataset-services
Tethys Dataset ServicesTethys datasets provides Python programming interface for dataset services such as GeoServer, CKAN and HydroShare.NOTETethys Dataset Services versions 2.0.0 and up will only support Python 3. For Python 2 support see version 1.7.0.InstallationTethys Datasets Services can be installed via conda or downloading the source. To install via conda:conda install tethys_dataset_servicesTo install via source:git clone https://github.com/CI-WATER/django-tethys_dataset_services.git
cd tethys_dataset_services
pip install .To install a development (editable) version:git clone https://github.com/CI-WATER/django-tethys_dataset_services.git
cd tethys_dataset_services
pip install --editable .TestsTests are executed using tox:pip install .[tests]
toxEnd-to-End TestsEnd-to-end tests are not run automatically, b/c they require some additional set up. They can be run as follows.Install Docker:https://docs.docker.com/get-docker/Install Docker Compose:https://docs.docker.com/compose/install/Run Docker Compose to create test containers:cd tests
docker-compose up -dWait at least 30 seconds for the docker containers to settle down, then run the setup script to create the database tables:. setup_e2e_tests.shFrom the directory with the tox.ini, run the tests using tox:cd ..
tox -e e2e_geoserver_testsIt is recommended that after each run, you refresh the Docker containers. Run the following command to remove them:cd tests
docker-compose downThen repeat steps 3-5.Usagefrom tethys_dataset_services.engines import CkanDatasetEngine

engine = CkanDatasetEngine(endpoint='http://<ckan_host>/api/3/action',
                         apikey='G3taN@p|k3Y')

result = engine.list_datasets()
Package: tethys-template
Using this templateCreate a new repository using Github's template interface, or run the following commands:gitclonehttps://github.com/pcsagan/tethys<your_package_name>cd<your_package_name>
rm-rf.git
gitinit.Find and replace all instances oftethysandtethys-templatewith your package nameYour project name can match your package name. The nametethys-templatewas required becausetethysalready exists on PyPIUpdatepyproject.tomlto reflect its new author and requirementsUpdate theSecurity Policyand theCode of Conductwith your e-mail addressSet the version to a value that hasn't already been published toPyPI(andTestPyPI)List ofClassifiersConfiguration formypyUpdatetox.inito build the desired testing environmentsConfiguration forblackConfiguration forflake8Configuration forpycodestyleConfiguration forpydocstyleConfiguration forpytestConfiguration forpytest-covUpdatecli.pyto customize the command line interfaceDocumentation forclickThe entry point is defined in the project.scripts table in thepyproject.tomlfileUpdate.git/workflows/tests.yamlto specify the various operating systems and python versions used for testingInstall your package dependencies into your development environmentInstall the package locally in editable mode using the command:pipinstall-e.Install the package locally along with all testing libraries used bytoxwith the command:pipinstall-rrequirements.txtAdd your code to the package while regularly committing your changes to your Github repositoryAdd your tests to thetestsdirectoryTest your package usingtoxRun all tasks in their own environments using the command:toxRun specific tasks usingtoxwith the-eflag:tox-eblack
tox-edocs
tox-eflake8
tox-emypy
tox-epycodestyle
tox-epydocstyle
tox-epytest
tox-evalidate-pyprojectIf you installed therequirements.txtfile then you can use testing packages in your local environment:blacksrc
sphinx-apidoc-f-odocs/sourcesrc/<my_package_name>
sphinx-build-bhtmldocs/sourcedocs/build/html
flake8srctests
mypysrc
pycodestylesrc
pydocstylesrc
pytesttestsRegister onPyPI(andTestPyPI) and generateAPI tokensAdd your tokens as asecret variablenamedpypi_api_tokenandtestpypi_api_tokento your Github repositoryManually run thePublish Testaction to verify that your token and package version are accepted using TestPyPIManually run thePublishaction to publish your package on PyPIHelpUsage: tethys [OPTIONS] COMMAND [ARGS]...

  Tethys is a moon of Saturn.

Options:
  --version  Show the version and exit.
  --debug    Run the command in debug mode.
  --help     Show this message and exit.

Commands:
  data  Print the shared context data to the screen.
  foo   Print the result of calling the foo function to the screen.
Package: tetraframework
TetraFull stack component framework forDjangousingAlpine.jsTetra is a new full stack component framework for Django, bridging the gap between your server logic and front end presentation. It uses a public shared state and a resumable server state to enable inplace updates. It also encapsulates your Python, HTML, JavaScript and CSS into one file for close proximity of related concerns.See  examples attetraframework.comRead theDocumentationpip install tetraframeworkWhat does Tetra do?Django on the backend, Alpine.js in the browserTetra combines the power of Django with Alpine.js to make development easier and quicker.Component encapsulationEach component combines its Python, HTML, CSS and JavaScript in one place for close proximity of related code.Resumable server stateThe components' full server state is saved between public method calls. This state is encrypted for security.Public server methodsMethods can be made public, allowing you to easily call them from JS on the front end, resuming the component's state.Shared public stateAttributes can be decorated to indicate they should be available in the browser as Alpine.js data objects.Server "watcher" methodsPublic methods can be instructed to watch a public attribute, enabling reactive re-rendering on the server.Inplace updating from the serverServer methods can update the rendered component in place. Powered by the Alpine.js morph plugin.Component library packagingEvery component belongs to a "library"; their JS & CSS is packed together for quicker browser downloads.Components with overridable blocksComponent can have multiple {% block(s) %} which can be overridden when used.JS/CSS builds usingesbuildBoth for development (built into runserver) and production your JS & CSS is built with esbuild.Source MapsSource maps are generated during development so that you can track down errors to the original Python files.Syntax highlighting with type annotationsTetra uses type annotations to syntax highlight your JS, CSS & HTML in your Python files with aVS Code plugin
Package: tetra-hub
Tetra Hubprovides transparency into the
on-device performance of machine learning models. It allows quick examination
into key metrics to improve the model.Tetra Hub allows users to analyze a model throught the following steps:Simply upload a model and submit a profiling job, targeting a specific
device.The model is compiled and tailored to the target platform.A physical device is provisioned in the cloud. Tetra Hub analysis tools run
the model on the device and gather metrics such as which model layers run
on which compute units, model latency, and peak memory.The results are displayed on Tetra Hub, providing insights to understand
the performance and opportunities for further improvements.tetra_hubis a python package that provides an API for users to upload a model,
submit the profile jobs for hardware and get key metrics to optimize the
machine learning model further.Installation with PyPIThe easiest way to installtetra_hubis by using pip, runningpip install tetra-hubFor more information, check out thedocumentationfor more information ontetra_hubAPIs, how to use them, and for examples.LicenseCopyright (c) 2023, Tetra Intelligence Systems Inc. All rights reserved.
Package: tetrapod
how to run teststo run the test you can use themakecommand# run all unit testmaketest# for run pep8 and flakemakestyle_test# or you can usemakepep8;makeflakesto open the coverage report you can usemakeopen_report_firefox# orfirefox.coverage_html_report/index.htmlconfigurationBGCfromtetrapod.bgcimportconnectionsconnections.configure(default={'host':('https://direct2m.backgroundchecks.com/''integration/bgcdirectpost.aspx'),'user':os.environ['BGC__DEFAULT__USER'],'password':os.environ['BGC__DEFAULT__PASSWORD'],'account':os.environ['BGC__DEFAULT__ACCOUNT'],},another={'host':('https://direct2m.backgroundchecks.com/''integration/bgcdirectpost.aspx'),'user':os.environ['BGC__ANOTHER__USER'],'password':os.environ['BGC__ANOTHER__PASSWORD'],'account':os.environ['BGC__ANOTHER__ACCOUNT'],},with_proxy={'host':('https://direct2m.backgroundchecks.com/''integration/bgcdirectpost.aspx'),'user':os.environ['BGC__WITH_PROXY__USER'],'password':os.environ['BGC__WITH_PROXY__PASSWORD'],'account':os.environ['BGC__WITH_PROXY__ACCOUNT'],'proxy':{'http':os.environ['BGC__WITH_PROXY__PROXY__HTTP'],'https':os.environ['BGC__WITH_PROXY__PROXY__HTTPS'],},},)how to usebgcus_one_validatefromtetrapod.bgcimportbgcresult=bgc.us_one_validate(ssn='899999914')the result is a dict and have the next structure{'order_id':'6421064b-0c45-4fb4-ad52-1bd9edfbf034','order':{'ssn':'XXXXX9914'},'is_deceased':True,'is_valid':True,'state_issued':None,'text_response':'This SSN may have been issued as part of the Social Security Administration (SSA) Randomization Program that limits our ability to provide the issuance state and dates.  Please direct the subject to the SSA to validate authenticity.','year_issued':None}us_one_tracefromtetrapod.bgcimportbgcresult=bgc.us_one_trace(ssn='999999999',first_name='jonh',last_name='doe')the result is a dict with the next structure{'order_id':'559be3d7-4019-4af7-9714-723077890856','order':{'ssn':'XXXXX9999','last_name':'doe','first_name':'jonh'},'records':[{'street':{'number':'123','pre_direction':None,'name':'Qa St','post_direction':None,'suffix':'QA'},'first_name':'jonh','middle_name':None,'last_name':'doe','city':None,'state':None,'county':None,'postal_code':None,'postal_code4':None,'date_first_seen__raw':{'year':'2009','month':'1'},'date_first_seen':datetime.date(2009,1,1),'date_last_seen__raw':{'year':'2012','month':'12'},'date_last_seen':datetime.date(2012,12,1),'verified':False,'phone_info':None}]}
Package: tetration
TetrationThe 4th Hyperoperation. Tetrate numbers and watch them being solved.Installationpip install tetrationUsagefromtetrationimporttetrate,tetrate_solveprint(tetrate(2,3))# 16# To tetrate and show the solution stepstetrate_solve(2,3)# 16# ((2)^2)^2# (2)^4# 16
Package: tetripin
If you have a lot of account with two factor authentification activated, using a separated device can take a lot of time.Tetripin is a cli 2FA manager that can generate the one time PIN from your terminal. It’s compatible with most TOTP services, e.g: the ones that use the regular settings for Google Authenticator such as most crypto-currency exchanges, lastpass and discord…$ tetripin add Bittrex JBSWY3DPEHPK3PXP
Account added
$ tetripin gen Bittrex
969804SupportIt works on Windows/Mac/Linux, but support only TOTP with default settings:period = 30
digits = 6
algorithm = SHA1If you need other settings, open a github issue.It’s written in Python, and works on Python 2 and 3.InstallationYou need to know how pip works. If you don’t, vote on the github issue asking for binaries. Indicate your OS name and version.` python-mpip install tetripin--user`Binary may come in the future so you don’t have to understand how pip works.Futurbackuprestorerenameimportread from qrcode local file or urldeal with other algo settingsadd support for steamadd sync servicedesktop GUImobile GUIweb GUIkeepass integrationoutput time remainingTipsIf you can’t find thetetripincommand, you can still call tetripin doing:python -m tetripinExport secrets:$ tetripin listsecrets # Export secrets
bittrex=JBSWY3DPEHPK3PXPGet conf infos:$ tetripin listconfig # List config values
secrets_file=/home/user/.local/share/tetripin/0.1/secrets.toml
data_dir=/home/user/.local/share/tetripin/0.1WARNINGIf your secrets get stolen, people will be able to generate the PIN. Keep the secrets.toml safe !
Package: tetris
python-tetris: a simple and modular tetris libraryIntroA simple and modular library for implementing and analysing Tetris games,guideline-compliant by default>>>importtetris>>>game=tetris.BaseGame(board_size=(4,4),seed=128)>>>game.queue<SevenBagobject[J,O,L,I,T,S,J,...]>>>>for_inrange(4):game.hard_drop()...>>>game.playingFalse>>>print(game)JOOJJJZZZZLinksDocumentationPyPISupport:create an issueorsee author contactInstallThis package is available onPyPI, you can install it with pip:pipinstalltetris# or `py -m pip ...` etc.To install the git version:pipinstallgit+https://github.com/g3ner1c/python-tetris
Package: tetris-ballistic
Simulations on Some Surface Growth ModelsThis repository contains simulations for various surface growth models,
developed initially as a final exam project for Math-7820 (Applied Stochastic
Processes I), Fall 2023 at Auburn University. It was further expanded as a
course project for Math-7830 (Applied Stochastic Processes II), Spring 2024.
More information about the courses can be found here:Math-7820 Fall
2023.These simulations provide insights into the dynamics and characteristics of
surface growth processes, inspired by theoretical models and real-world
applications.FeaturesComprehensive simulations of different surface growth models.Easy-to-use interface for conducting and analyzing simulations.Detailed documentation for understanding and extending the simulations.InstallTo get started with these simulations, you can install the package using pip:pipinstalltetris-ballisticPypi link:here.Sample UsageTo understand how to utilize this package, refer to thetestsfolder, which contains examples of potential usage within Python code.Here are some simulationsexamplesDocumentationFor detailed information about the package and its functionalities, visit ourRead the Docspage.How to ContributeContributions to this project are welcome! To contribute, please:Fork the repository.Create a new branch for your feature.Add your changes and commit them.Push to the branch.Create a new pull request.ReferencesLe Chen's Graduate Student Seminar talk on surface growth models:here.Barabási and Stanley, ''Fractal Concepts in Surface Growth'', Cambridge University Press, 1995.LicenseThis project is licensed under the MIT License - see theLICENSEfile for details.ContactFor any queries or further discussion, feel free to contact us atLe Chen: [chenle02@gmail.com] or [le.chen@auburn.edu].Ian Ruau: [ian.ruau@auburn.edu].Mauricio Montes: [mauricio.montes@auburn.edu].
Package: tetris-c-nore
Python 2 Player Tetris Library implemented in C++Original title: Tetris with instant soft drop delay(branch python library)Following tetris guidelines, implemented in C++ for speed, actions are taken simultaneously, players turn-based with matching keys instead piece, can be used to train AI/whatever.with instant softdrop after specified time and short softdrop like DAS(not implemented in python lib yet)Separated from my tetris/pylibtestUsage Brief viewimporttetrisx=tetris.Container()# game objecty=x.copy()# deep copy if neededx.reset()# reset statex.seed_reset(n)# reset with rng seedstate=x.get_state()# shape (500,) numpy array, 1D so easier to use mp shared memory, more info belowshapes=x.get_shapes()# (7,4,4,4) 7 pieces 4 rotations and 4x4 shapex.step(ac1,ac2)RenderSwitch to my tetris_c library and install SDL2 below if manual compile is needed.In Depth InfoGame Stepaction is scalar int0:hold
1:hard drop
2:cw
3:ccw
4:left tap
5:right tap
6:left das
7:right das
8:soft drop
9:180Statesp1_state=state[0:232]p2_state=state[232:464]sum attackstate[464], negative is to p1
individual attacksstate[465:]Rewardstate[0] is reward127 is lose, 126 is win, otherwiseif harddrop (action==1)
    if lines_cleared
        rew=10 * (attack+ b2b *2)+2*lines
    rew+=b2b_not_broke
else rew=wallkickPython for extractinglines_cleared=(reward%10)//2atk=reward//10# b2b rewards 2 atk but is 1 in-gamewallkick=reward%5ifaction!=1else0b2b_not_broken=reward%5ifaction==1else0game doesn't auto reset on game over, check those signals and call reset on your ownStatesi piece goes to -2 so the value is +2 by default, if you want to draw current piece subtract that backx = state[1]Board is 30 high, bottom 21 is returned, y spawns at 9 normally but 8 if occupied, otherwise game over.Value returned to python starts at 8 so pieces spawn at 1 normally, could be negative if you navigate the piece off screeny = state[2]Distance to bottomsoftdropdist = state[3]Default is 10 actions will force harddropaction_count = state[4]Garbage cleared from last action, use for reward etcgarbage = state[5]hold_used = state[6]rotation = state[7]active = state[8]Draw active piece on current location(you have to check x negative yourself):board[x-2,y]=shape[active][rotation]Held can be -1 meaning not usedheld_piece = state[9]next_pieces = state[10:15]Cheat data(hidden queue)hidden_queue=state[15:22]Less cheating because you can manually count the bag:hidden_queue=sort(state[15:22])Boardstate[22:232].reshape(21,10)FeedbackAny ideas for improvements are welcome.State is mostly boolean/binary so it's possible I can optimise the code further to increase speed as use cases probably will be AI training that needs millions of iterations.if you want to read/change the code, tetrisboard is main logic including clear rewards, and env.cpp is the python wrapper+rendering+returning state
Package: tetris-engine
TetrisA tetris engine python package powered by rustHandles the tetris game logic for you so you can focus on building a tetris interfaceProvides flexibility for the game loop, allowing you to define the game loop entirely
or run a built-in game loop thread in the backgroundThe built-in, multithreaded game loop capability makes use of rust's safe concurrency offeringInstall the packageInstall from pypipipinstalltetris_engineInstall directly from this repositorypipinstallhttp://www.github.com/peter-lucia/tetris_engine/archive/main.zipExample usage:fromtimeimportsleepfromtetris_engineimportTetris,Directiondefrun_singlethreaded():"""You control the game loop as well as the game speed"""tetris=Tetris()whiletetris.is_game_running():tetris.move(direction=Direction.Down.value)forrowintetris.read_game():print(row)print()sleep(1)defrun_multithreaded():"""You control the user controls of the game but thegame loop runs in a background thread"""tetris=Tetris(multithreaded=True)whiletetris.is_game_running():tetris.read_game()forrowintetris.read_game():print(row)print()sleep(.5)
Package: tetry
TetryA simple python library for interacting with theTETR.IOAPI.contentsAboutInstallationDocumentationExamplesContributionNoticeHelpful linksAboutThis library is a simple wrapper around theTETR.IOAPI. It uses trio to provide a simple async interface.Installationinstalling from pippython3-mpipinstalltetryinstalling from sourcegitclonehttps://github.com/apes0/tetrycdtetry
python3-mpipinstall-U.DocumentationComing soon!ExamplesHere you will find code examples for the library.General apifromtetryimportapidefprintRecords(username):records=api.getRecords(username).recordsforname,recordinrecords.items():print(f'{name}:{record}')while(name:=input()):printRecords(name)Chat commandsfromtetryimportbotbot=bot.Bot(token='token',commandPrefix='>')@bot.chatCommand()asyncdefping(_msg):ping=bot.getPing()awaitbot.room.send(f'The bot\'s ping is{round(ping*1000,2)}ms')bot.run()Simple auto-host botimporttriofromtetry.botimportBotbot=Bot(token='token')@bot.eventasyncdefready():awaitbot.createRoom(False)@bot.eventasyncdefjoinedRoom(room):print(room.invite)@bot.eventasyncdefuserLeave(user):name=user['username']print(f'{name}has left')awaitbot.room.send(f'Goodbye{name}, hope to see you here again soon!')asyncdefstart(room):delay=20# secondsneeded=2# playersiflen(room.getPlaying())>=needed:awaitroom.send(f'Starting in{delay}seconds!')awaittrio.sleep(delay)iflen(room.getPlaying())>=needed:awaitroom.startGame()else:awaitroom.send('Not enough players!')else:awaitroom.send('Not enough players!')@bot.eventasyncdefuserJoin(user):room=bot.roomname=user['username']awaitroom.send(f'Welcome to this room,{name}!')awaitstart(room)@bot.eventasyncdefgameEnd():room=bot.roomprint('the game has ended')awaitstart(room)bot.run()ContributionYou can feel free to contribute to the this project by making a PR, making suggestions and opening issues for bugs/questions.NoticeThis library isNOTaffiliated with, endorsed by, or otherwise associated with TETR.IO or osk.Helpful linksTETR.IO bot docs- documentation for the bot apitetr.js- a javascript library for interacting with the TETR.IO APITETR.IO public api docs- the official TETR.IO API documentation