Saravanan666/pypi-org huggingface dataset:
Package: tissue
tissue integrates running pep8 on source files as they are imported by nose.Installationpip install tissueUsageOnce installed pep8 tissue will run pep8 checks on your source tree. The
following options are availible:--with-tissueEnable plugin Tissue: Automated PEP8 checked for nose
[NOSE_WITH_TISSUE]--tissue-package=PACKAGERestrict pep8 output to selected packages
[NOSE_TISSUE_PACKAGE]--tissue-inclusiveInclude all python files under working directory in
pep8 run. [NOSE_TISSUE_INCLUSIVE]--tissue-repeatShow all occurrences of the same error
[NOSE_TISSUE_REPEAT]--tissue-select=ERRORSSelect errors and warnings (e.g. E,W6)
[NOSE_TISSUE_SELECT]--tissue-ignore=ERRORSSkip errors and warnings (e.g. E,W6)
[NOSE_TISSUE_IGNORE]--tissue-show-sourceShow source code for each error
[NOSE_TISSUE_SHOW_SOURCE]--tissue-show-pep8Show text of PEP 8 for each error
[NOSE_TISSUE_SHOW_TISSUE]--tissue-statisticsCount errors and warnings [NOSE_TISSUE_STATISTICS]--tissue-fail-on-errorFail the tests when Tissue sees errors
[NOSE_TISSUE_ERROR]--tissue-colorShow errors and warnings using colors
[NOSE_TISSUE_COLOR]Options map to the pep8 options of the same name (sans prefix)SourceFork me on teh githubshttps://github.com/wolph/tissue
Package: tissue-detection
Tissue detectionLibrary for detecting tissue in cardiac TPE and MPS systems.Source code:https://github.com/ComputationalPhysiology/tissue-detectionDocumentation:https://computationalphysiology.github.io/tissue-detectionInstallYou can install the library with pippython3 -m pip install tissue-detectionGetting startedTBWLicenseMITNeed help or having issuesPlease submit anissue
Package: tissue-properties
A python library for calculating/looking up various tissue properties for laser bioeffect calculationsTo simulate the exposure of tissue (skin or retina) to laser radiation, several properties characterizing the thermo-optical response of the tissue are needed.
These include absorption coefficients, transmission coefficients, conductivity, density, specific heat, etc. This library is a collection of tissue property data
sets that have been reported in the literature.InstallingInstall with pip (or your favorite virtual environment manager)pipinstalltissue-propertiesUsage# Print out the absorption coefficients as a function of wavelength used in the 
# paper "Retinal-Temperature Increases Produced by Intense Light Sources" by
# Mainster in 1970. These values were extracted from Figure 3.
from tissue_properties.optical.absorption_coefficient import mainster
from tissue_properties.units import Q_

RPE = mainster.RPE()
choroid = minster.Choroid()

print("# wavelength retina choroid")
for wavelength in range(400,1405,5):
    l = Q_(wavelength,'nm')
    mu_r = RPE(l)
    mu_c = RPE(l)
    print(l,mu_r,mu_c)

# We can also get information about data set. Currently only the reference is
# provided, in BibTex format.
bibtex_text = RPE.get_reference()
print(bibtex_text)
Package: tissuumaps-schema
TissUUmaps-schemaPydantic schema for TissUUmapsRequirementsPython3.9 or laterInstallationUse the package managerpipto install tissuumaps-schema:pip install tissuumaps-schemaUsageTo list all available$VERSIONvalues:tissuumaps-schema versionsTo list all available$MODELvalues for the specified$VERSION:tissuumaps-schema models --version $VERSIONTo generate a JSON Schema for the specified$VERSIONand$MODEL:tissuumaps-schema generate --version $VERSION $MODELTo upgrade an existing instance of$MODELto the specified$VERSION:tissuumaps-schema upgrade --to-version $VERSION $MODEL myinstance.jsonTo validate an existing instance of$MODELagainst the specified$VERSION:tissuumaps-schema validate --expect-version $VERSION $MODEL myinstance.jsonSupportFor each$VERSIONand$MODEL(lower case), a JSON Schema is hosted on:https://tissuumaps.github.io/TissUUmaps-schema/$VERSION/$MODEL.jsonThe JSON Schema of each$VERSIONand$MODEL(lower case) is documented on:https://tissuumaps.github.io/TissUUmaps-schema/$VERSION/$MODEL.htmlIf you find a bug, pleaseraise an issue.ContributingPull requests are welcome.For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.VersioningBoth the schema and the associated Python package adhere toSemantic Versioning:Each file adhering to the schema contains the MAJOR.MINOR schema version it was created with/for (seeRootSchemaBaseModel.schema_versionand<schema_module>.VERSION).Briefly, changes in MAJOR indicate breaking changes necessitating file upgrade/conversion, changes in MINOR indicate non-breaking feature additions, and changes in PATCH indicate bugfixes in the Python package.The MAJOR.MINOR Python package version equals the version of the latest schema supported by the package. Each TissUUmaps release pins the MAJOR.MINOR version of the tissuumaps-schema package to indicate the supported schema version.For each MAJOR version, the Python package contains a dedicated module with the latest MINOR subversion of the schema. Upgrade paths exist from one MAJOR version (latest MINOR subversion) to the next MAJOR version (latest MINOR subversion).ChangelogChangelogAuthorsSciLifeLab BioImage Informatics Facility (BIIF)LicenseMIT
Package: tistory
tistory기여자정우일소개tistory는 티스토리 블로그 오픈 API를 파이썬으로 쉽게 이용할 수 있도록 돕는 오픈소스 라이브러리입니다.설치pipinstalltistory사용 설명서Python tistory 패키지로 블로그 자동화하기참조티스토리 오픈 API 신청티스토리 오픈 API 가이드
Package: tistory-cli
Tistory-CLIA command line tool for Tistory, the Korean blogging platform. It conveys Markdown files to your Tistory blog.This project is currently in alpha stage and supports the minimal features: To post an article. It supports Linux only.한국 Tistory 사용자를 위한 도구이므로 앞으로 한글로 설명합니다.DependenciesLinux SecretStorage 기능을 위해 다음과 같은 패키지가 필요합니다.libsecretgnome-keyring대부분의 Linux 배포판에서 기본적으로 설치가 되어있을 것입니다. Arch Linux의 경우에는 gnome-keyring이 기본으로 설치되지 않으므로 따로 설치해야 합니다.Installationpip를 통해서 쉽게 설치 가능합니다. 시스템 환경 또는 원하는 가상 환경에서$pipinstalltistory-cli또는 소스에서 직접 설치하려면 (역시나 원하는 환경에서)$gitclonehttps://github.com/dgkim5360/tistory-cli-python.git
$cdtistory-cli-python
$pythonsetup.pyinstallFeatures and Non-features본인의 client/secret key를 사용해서 직접 로그인하므로, 외부 서비스에 비밀 정보를 남기지 않습니다.소스코드, 환경변수 등에 credential를 저장하지 않고,운영 체제 레벨의 비밀 저장소에 저장합니다.Git commit message 스타일로 제목/내용 구분해서 Markdown 파일을 작성해서 Tistory에 비공개글로 업로드합니다.카테고리와 slug는 설정 가능합니다.공개글로 업로드하지 않습니다.이미지 업로드하지 않습니다.태그 추가하지 않습니다.Oauth SettingTistory --> 가이드 --> 오픈API 가이드 --> 클라이언트 등록Callback 경로를http://localhost:8888(기본값, 다른 포트를 원할 시.redirect-uri파일에 해당 주소를 일치하게 써 놓으면 됨)로 설정해서 클라이언트 등록을 완료합니다.tistory login실행하면 (OS 계정 비밀번호를 요구할 수도 있습니다), 로그인할 페이지를 콘솔에 띄워줍니다.브라우저로 해당 주소로 들어가서 Tistory 로그인을 해서 API 토큰을 받아옵니다.콘솔에 다음과 같이 나오면 로그인이 끝납니다.Usage$tistory
USAGE:tistorylogintistorylogouttistorypurgetistorycategory<blog_name>tistorypost<blog_name><category_id><file_path>tistory login: 모든 비밀 정보가 있는 지 확인하고 없으면 로그인을 시킵니다.tistory logout: Access token만을 지웁니다.tistory purge: 모든 비밀 정보를 지웁니다.tistory category: 해당 블로그의 카테고리 아이디 정보를 받아옵니다.tistory post: 파일을 읽어서 해당 블로그 및 카테고리에 비공개 글로 업로드합니다.Step-by-step Tutorial로그인을 합니다 (Oauth Setting 참조).tistory category <blog_name>을 통해 본인 블로그의 카테고리 아이디를 확인합니다.$tistorycategorydgkim5360
IDName
------880607HTML+CSS880608Django886608Bootstrap892553Python892554Javascript894029GNU-Linux896354뻘글897315Cloud907471etc908711Front-end912687MachineLearning931755NBA933686Elastic937655Flask951477Javascript959045Travelogue990157Rust<slug>.md파일을 Git commit message처럼 작성합니다 (첫 줄 제목, 한 줄 띄우고 내용 시작). 글 내용은 Markdown 형식에 맞추어 작성합니다. (파일명:tistory-cli-test.md)[제목]Hello Tistory!# Tistory-cli 테스트 중입니다.아래는 list*hello*tistory*bye*tistory1.hello1.tistory1.bye1.tistory

이것은 [링크](http://dgkim5360.tistory.com)

Inline`code text`도 써봅니다.tistory post <blog_name> <category_id> <slug>.md로 포스팅을 한 후, Tistory에서 확인합니다. 작업이 완료되면 해당 Markdown 문서의 파일 앞에 Tistory 시스템의 ID값이 붙습니다 (아래 예제에서는 191이 붙었습니다).$tistorypostdgkim5360896354path/to/tistory-cli-test.md

$lspath/to
191_tistory-cli-test.md추가적으로 필요한 이미지 업로드, 태그 추가, 공개 설정은 Tistory에서 해결합니다.
Package: tistorycmd
tistorycmdmarkdown 형식으로 작성된 파일을 html 형식으로 변환하여 티스토리에 업로드 해줍니다.설치# 파일로 다운로드시
python setup.py install

# pip로 다운로드 하기
pip install tistorycmd사용법CMD, 터미널 창에서 실행

# 블로그 정보 보기
tistorycmd info

# 카테고리 목록 보기
tistorycmd category

# 글쓰기, 모든 내용수정시
tistorycmd post <제목> <내용|파일경로> <category_id> <태그>

# 내용만 수정
tistorycmd update <내용|파일경로>사용시 주의사항이미지는 아래 형태대로 쓰셔야하며 한줄마다 쓰시면 자동으로 업로드 됩니다.
.. code-block:![screenshot1](./screenshot.png)이미지 경로가 url(http://~)이 들어간경우는 파일이 업로드되지 않고 해당 url로 해서 내용이 적용됩니다.이미지가 업로드 된경우 마크다운 파일 내용에 이미지가 업로드된 url이 자동으로 들어갑니다.글쓰기, 수정 시 해당 글들은 자동으로 발행됩니다.기타 모듈 다운로드pipinstallpyfigletpipinstallmistune(anaconda의경우설치되어있습니다.)tistorycmd 모듈 사용시fromtistorycmdimport*auth=Auth()# 로그인, oauth, 토큰 관련 클래스blog=Blog()# 글쓰기, 블로그 관련 클래스blog.info()#블로그 정보 불러오기# 나머지는 소스 참고설정(config.json)blog_name : 블로그명 (https://[블로그명].tistory.com)app_id : 앱 id (아래 #수동 api 토큰 받는 법 -> 1번 에서 확인 가능)secret_key : 시크릿키 (아래 #수동 api 토큰 받는 법 -> 1번 에서 확인 가능)access_code : 접근 코드, 한번 접속하면 사라짐 (아래 #수동 api 토큰 받는 법 -> 2번 에서 확인 가능)access_token : 액세스 토큰  (아래 #수동 api 토큰 받는 법 -> 3번 에서 확인 가능)수동 api 토큰 받는 법https://www.tistory.com/guide/api/manage/register접속해서 앱등록 ( 앱등록후 앱관리에서 app id, secret key 확인 가능)https://www.tistory.com/oauth/authorize?client_id=[Appid]&redirect_uri=[앱등록에서 입력한 redirect url]&response_type=code&state=someValue 접속하면 코드 확인 가능https://www.tistory.com/oauth/access_token?client_id=[Appid]&client_secret=[Secret key]&redirect_uri=[앱등록에서 입력한 redirect url]&code=[2번에서 얻은 코드 값]&grant_type=authorization_code 해당 url 접속하여 access token 확인 가능2번에서 얻은 코드가 기간 만료시 아래 에러가 발생하는것 같습니다.This page contains the following errors:

error on line 1 at column 1: Document is empty

Below is a rendering of the page up to the first error.위 에러가 발생하더라도 3번 url에서 발생한 파라미터를 한번 확인해보시기 바랍니다에러 발생시 2번 내용 부터 다시 진행해 보시길 바랍니다.참고 url토큰 받아오기https://limsee.com/325python 예제 githubhttps://github.com/chandong83/tistory-api-examplepython 예제2 github (tistory helper)https://github.com/adunStudio/TistoryHelper입력 예제https://kimmj.github.io/python/python-beautiful-cli/setup.py 설정https://item4.blog/2015-11-21/Arguments-of-setuptools.setup/
Package: tistory-uploader
Markdown Tistory UploaderMarkdown 타입의 파일을 Github CSS를 적용한 HTML파일로 변환해서 Tistory로 업로드하는 모듈입니다.PrerequisitesVS CodePython >= 3Tistory github markdown style 설정css 파일은여기에서 다운로드tistory 설정은 구글링 부탁드립니다.Installationpip install은 지원되지 않습니다.$gitclonehttps://github.com/momentjin/tistory-uploader.git
$cdtistory-uploaderUsageClient Id, Secret Key 발급티스토리 App 등록 페이지에서 아래와 같이 서비스URL과 CallBack 값을 설정해주세요.User Info 설정아래와 같이 프로젝트 디렉토리에서 다음 명령어를 입력합니다.$~/tistory-uploaderpythonCommandConfiginituser.json 파일이 열리면 아래 설명을 보고 내용을 입력합니다.{"blog_name":"","client_id":"","client_secret":"","access_token":"","categories":[]}blog_name : 블로그 이름 입력. tistory 주소의 앞부분 (예를 들어 momentjin.tistory.com이면 'momentjin' 을 입력)client_id : Tistory 앱 등록 페이지의 App ID 입력client_secret : Tistory 앱 등록 페이지의 Secret Key 입력access_token과 categories는 명령어에 의해 입력됩니다.Access Token 발급아래 커맨드를 입력합니다.$~/tistory-uploaderpythonCommandConfigcode다음 화면에서 블로그 업로드 권한을 얻기 위해허가하기버튼을 눌러주시면 됩니다.user.json에 access_token이 입력된 것을 확인합니다. (현재 문제가 있어 오류 메세지가 보일 수 있습니다. 무시하면 됩니다)Category 정보 획득게시글 쓰기 및 수정 작업시에 카테고리 정보를 포함시키려면, 카테고리 ID를 알아야 합니다. 카테고리 정보 없이 게시글 업로드 작업을 한다면 생략하시면 됩니다.아래 커맨드를 입력합니다.$~/tistory-uploaderpythonCommandConfigcategoryuser.json에 categories 데이터가 입력된 것을 확인합니다.게시글 업로드시 카테고리는 카테고리 이름을 입력합니다. 카테고리 이름을 통해 user.json의 카테고리 정보에서 id를 획득한 뒤 이를 API로 전달하는 방식입니다.글 쓰기1-1. (카테고리 정보가 필요 없는 경우) 아래 커맨드를 입력합니다.$~/tistory-uploaderpythonCommandConfigwrite[file_path]1-2. (카테고리 정보가 필요한 경우) 아래 커맨드를 입력합니다.category_name는 영문의 경우 대소문자를 명확히 구분해주세요.$~/tistory-uploaderpythonCommandConfigwrite[file_path]-cg[category_name]출력 값에 포함된 url에 접속해서 게시글이 제대로 게시되었는지 확인합니다.글 수정1-1. (카테고리 정보가 필요 없는 경우) 아래 커맨드를 입력합니다.$~/tistory-uploaderpythonCommandConfigmodify[category_name][file_path]1-2. (카테고리 정보가 필요한 경우) 아래 커맨드를 입력합니다.category_name는 영문의 경우 대소문자를 명확히 구분해주세요.$~/tistory-uploaderpythonCommandConfigmodify[category_name][file_path]-cg[category_name]출력 값에 포함된 url에 접속해서 게시글이 제대로 수정되었는지 확인합니다.Release Historyv0.12020.03.08Work in progressLicenseDistributed under the MIT License. SeeLICENSEfor more information.
Package: tisu
TisúTisú [tiˈsu,tissuein spanish] allows to manage your (github) project's issue tracker, using a single text fileNote: this is a work in progress. Pull requests and feedback are welcome.Install$ pip3 install --user -U tisuUsageTisú can import and export your issues using a simple markdown file, where each section
is a different issue.# issue title

issue bodyIf an issue already exists in your tracker, the number is a prefix in the title, wrapped
by square brackets:# [#1] issue titleIn this case, Tisú will update that issue instead to create a new one.This is the current command line help:Tisú: your issue tracker, in a text file

Usage:
  tisu push <markdown_file> [--repo=<repo>] [(--username=<username> [--pass=<pass>]|--token=<token>)]
  tisu pull <markdown_file> [--repo=<repo>] [--state=<state>] [(--username=<username> [--pass=<pass>]|--token=<token>)]

Options:
  -h --help                 Show this screen.
  --version                 Show version.
  --repo=<repo>             Github repo (as: user/name). [default: inferred from git remote]
  --state=<state>           Filter by issue state [default: open].
  --username=<username>     Github username to send issues. Repo's username if no given.
  --pass=<pass>             Github password. Prompt if user is given and it is not.
  --token=<token>           Personal app token. Default to GITHUB_TOKEN environment variable.
                            Get one at https://github.com/settings/tokensTo access private repositories you need apersonal access token.ExampleSuppose you want to push a couple of issues like inthis TODO.mdfile.$ tisu push TODO.md mgaitan/tisu
Github password:
Created #11: support metadata
Created #12: setup travis CIResult in:Then, I can pull and overwrite the file.$ tisu pull TODO.mdThis is the result.
As in this case I didn't change anything online, the content is (almost) the same, but note that
each title has its ID number.Working with metadataTisú can also synchronize the issue's metadata with ease.The format is:<meta_var>: <value/s>, where<meta_var>is oneassignee,labelsormilestone. These metadata lines can be in any position under the title (and not
neccesarily all, in this order nor all together) and if present,
they are removed from the issue's description sent.For example, create a new issue with some metadata# Make a video

:assignee: mgaitan
:labels: docs, idea
:milestone: sprint 1

Make an screencast showing how to use Tisú.If later you want to close this issue, you can add mark it with:state: closedand push.# [#13] Make a video

:assignee: mgaitan
:labels: docs, idea
:milestone: sprint 1

Make an screencast showing how to use Tisú.

:state: closed
Package: titan-aerosols
Titan aerosols modelsPython package for Titan's aerosols modelsInstallWithpip:$pipinstalltitan-aerosolsIf you need to contribute this project you can installed it directly from thesource files:$gitclonehttps://github.com/seignovert/python-titan-aerosols.git
$cdpython-titan-aerosols
$python-mpipinstall-e.-rtests/requirements.txtPython usage>>>fromaerosolsimportindex_tholins>>>nr,ni=index_tholins(338e-9)(1.6489699384541059,0.2392676321412895)>>>fromaerosolsimportmie_tholins>>>wvln=338e-9# Wavelength (m)>>>rm=50e-9# Monomer radius (m)>>>qsct,qext,qabs,gg,theta,P=mie_tholins(wvln,rm)(2.150748326506086e-15,6.519732093912762e-15,4.368983767406676e-15,0.19301947916187234,array([0.,0.01745329,...,3.14159265]),array([2.23653193,...,0.88785229]))>>>fromaerosolsimportfractals_tholins>>>Df=2.0>>>N=266>>>qsct,qext,qabs,gg,theta,P=fractals_tholins(wvln,rm,Df,N)(1.5986535423863113e-12,2.5652821769307767e-12,9.666286345444654e-13,None,array([0,...,3.14159265]),array([135.83547352468324,...,0.16033083012643]))>>>N=3000>>>qsct,qext,qabs,gg,theta,P=fractals_tholins(wvln,rm,Df,N)ValueError:ModeltestedonlyforN=2-1024(receivedN=3000)>>>qsct,qext,qabs,gg,theta,P=fractals_tholins(wvln,rm,Df,N,force=True)(1.877008401099561e-11,2.829777018602765e-11,9.527686175032043e-12,None,array([0,...,3.14159265]),array([1.20358413e+03,...,1.27914327e-01]))>>>fromaerosolsimportmie>>>qsct,qext,qabs,gg,theta,P=mie(wvln,nr,ni,rm)(...)>>>fromaerosolsimportfractals>>>qsct,qext,qabs,gg,theta,P=fractals(wvln,nr,ni,rm,Df,N)(...)A static notebook is also availablehere.CLI usage$fractal_tholins--help
usage:fractal_tholins[-h][--phase-function][--nangNANG][--fractal-dimensionFRACTAL_DIMENSION][--force]wvlnrmN
Fractalscross-sectionsandphasefunctionfortholinaggregate.Usedefault
tholinsindexes(CVD)andTomaskoetal.2008.

positionalarguments:
wvlnWavelength(m)rmMonomerradius(m)NNumberofmonomers

optionalarguments:
-h,--helpshowthishelpmessageandexit--phase-function,-pDisplaythephasefunction--nangNANGNumberofanglesforthephasefunction(0->pi/2)--fractal-dimensionFRACTAL_DIMENSION,-dfFRACTAL_DIMENSIONFractaldimension
--force,-fBypassvaliditychecks


$fractal_tholins338e-960e-9266# Cross sections:Scattering:2.715e-12m^-2
Absorption:1.558e-12m^-2
Extinction:4.273e-12m^-2


$fractal_tholins-p338e-960e-9266# Phase function0.01.86e+021.01.78e+02
...179.01.15e-01180.01.15e-01


$fractal_tholins-p--nang10338e-960e-9266# Phase function0.02.52e+0210.02.37e+01
...170.01.55e-01180.01.56e-01


$fractal_tholins338e-960e-9266-df2.3
ModeltestedonlyforDf=2(receivedDf=2.30)$fractal_tholins338e-960e-9266-df2.3--force# Cross sections:Scattering:2.657e-12m^-2
Absorption:1.351e-12m^-2
Extinction:4.008e-12m^-2NoteThis package is an early attempt to model Titan's aerosols scattering based on Tomasko et al. 2008 paper
(doi:10.1016/j.pss.2007.11.019)
Package: titanfp
# TitanicTitanic is a tool for designing and experimenting
with novel computer arithmetic formats.
It builds on the GNU MPFR library for arbitrary-precision arithmetic,
providing additional support for low-level floating-point behaviors
such as precise control of rounding and precision tracking.Titanic uses the [FPCore](http://fpbench.org/spec/)
benchmark format for floating-point computations.
Reference interpereters are provided for the FPCore language
using both [IEEE 754](https://en.wikipedia.org/wiki/IEEE_754)
and [posit](https://posithub.org/index) arithmetics,
as well as fixed-point.
These interpreters can also interface with each other
(and with custom user-defined arithmetics)
to perform multiple precision, multiple format computations.
Package: titanic-ark
ฟังก์ชันของ Arkเพื่อทดสอบการใช้งาน upload library1.โหลด titanic_datasetfrom ark import akadf=aka.csv_read("titanic_dataset.csv")2.มีคำสั่งดั่งนี้.plot1(df).plot2(df).plot3(df).age_and_fare(df).embarked_port(df)ลองเล่นดูนะครับ :)Change Log0.0.1 (1/9/2023)First Release
Package: titanicazerty
vidstreamUnder construction! Not ready for use yet! Currently experimenting and planning!Developed by Florian Dedov from NeuralNine (c) 2020Examples of How To Use (Buggy Alpha Version)Creating A ServerfromvidstreamimportStreamingServerserver=StreamingServer('127.0.0.1',9999)server.start_server()# Other Code# When You Are Doneserver.stop_server()Creating A ClientfromvidstreamimportCameraClientfromvidstreamimportVideoClientfromvidstreamimportScreenShareClient# Choose Oneclient1=CameraClient('127.0.0.1',9999)client2=VideoClient('127.0.0.1',9999,'video.mp4')client3=ScreenShareClient('127.0.0.1',9999)client1.start_stream()client2.start_stream()client3.start_stream()Check out:https://www.youtube.com/c/NeuralNine
Package: titanicazertyu
vidstreamUnder construction! Not ready for use yet! Currently experimenting and planning!Developed by Florian Dedov from NeuralNine (c) 2020Examples of How To Use (Buggy Alpha Version)Creating A ServerfromvidstreamimportStreamingServerserver=StreamingServer('127.0.0.1',9999)server.start_server()# Other Code# When You Are Doneserver.stop_server()Creating A ClientfromvidstreamimportCameraClientfromvidstreamimportVideoClientfromvidstreamimportScreenShareClient# Choose Oneclient1=CameraClient('127.0.0.1',9999)client2=VideoClient('127.0.0.1',9999,'video.mp4')client3=ScreenShareClient('127.0.0.1',9999)client1.start_stream()client2.start_stream()client3.start_stream()Check out:https://www.youtube.com/c/NeuralNine
Package: titanicazertyui
vidstreamUnder construction! Not ready for use yet! Currently experimenting and planning!Developed by Florian Dedov from NeuralNine (c) 2020Examples of How To Use (Buggy Alpha Version)Creating A ServerfromvidstreamimportStreamingServerserver=StreamingServer('127.0.0.1',9999)server.start_server()# Other Code# When You Are Doneserver.stop_server()Creating A ClientfromvidstreamimportCameraClientfromvidstreamimportVideoClientfromvidstreamimportScreenShareClient# Choose Oneclient1=CameraClient('127.0.0.1',9999)client2=VideoClient('127.0.0.1',9999,'video.mp4')client3=ScreenShareClient('127.0.0.1',9999)client1.start_stream()client2.start_stream()client3.start_stream()Check out:https://www.youtube.com/c/NeuralNine
Package: titanicazertyuio
vidstreamUnder construction! Not ready for use yet! Currently experimenting and planning!Developed by Florian Dedov from NeuralNine (c) 2020Examples of How To Use (Buggy Alpha Version)Creating A ServerfromvidstreamimportStreamingServerserver=StreamingServer('127.0.0.1',9999)server.start_server()# Other Code# When You Are Doneserver.stop_server()Creating A ClientfromvidstreamimportCameraClientfromvidstreamimportVideoClientfromvidstreamimportScreenShareClient# Choose Oneclient1=CameraClient('127.0.0.1',9999)client2=VideoClient('127.0.0.1',9999,'video.mp4')client3=ScreenShareClient('127.0.0.1',9999)client1.start_stream()client2.start_stream()client3.start_stream()Check out:https://www.youtube.com/c/NeuralNine
Package: titanicpackagegna
vidstreamUnder construction! Not ready for use yet! Currently experimenting and planning!Developed by Florian Dedov from NeuralNine (c) 2020Examples of How To Use (Buggy Alpha Version)Creating A ServerfromvidstreamimportStreamingServerserver=StreamingServer('127.0.0.1',9999)server.start_server()# Other Code# When You Are Doneserver.stop_server()Creating A ClientfromvidstreamimportCameraClientfromvidstreamimportVideoClientfromvidstreamimportScreenShareClient# Choose Oneclient1=CameraClient('127.0.0.1',9999)client2=VideoClient('127.0.0.1',9999,'video.mp4')client3=ScreenShareClient('127.0.0.1',9999)client1.start_stream()client2.start_stream()client3.start_stream()Check out:https://www.youtube.com/c/NeuralNine
Package: titanic-pp-py
titanic-pp-pyThis is a work in progress pp system, with the goal of balancing performance points for the relax/autopilot mods with vanilla.
The actual code for this can be viewedhere.You can install this package using this command:pipinstallgit+https://github.com/osuTitanic/titanic-pp-py.gitPlease view the original forkhere, for general usage.
Package: titan-iris
TitanML iris package🎯 AboutIris is your portal to the TitanML platform.
Using Iris, you can setup Takeoff servers, launch jobs to run on TitanML servers, run your own models and datasets through our compression algorithms, and explore and download the optimised models from the Titan Store.For usage information, tutorials, and usage examples, see thedocs.New! Try the TitanML Takeoff Server✔️ Easy deployment and streaming responses for popular Large Language Models✔️ Optimized int8 quantization✔️ Chat and playground-like interface✔️ Support for encoder-decoder (T5 family) and decoder modelsFor the pro edition, including multi-gpu inference, int4 quantization, and morecontact usDependenciesIris is tested on the following versions of python:python >= 3.7 <=3.10Iris should work on later versions, but likely won't work on earlier versions.iris APIUsage:$ iris [OPTIONS] COMMAND [ARGS]...Options:--help: Show this message and exit.Commands:delete: delete objects from the TYTN api.download: Download the titan-optimized onnx model.get: Get objects from the TYTN api.infer: Run inference on a model.login: Login to iris.logout: Logout from iris.makesafe: Convert a non-safetensor model into a...post: Dispatch a job to the TitanML platformpull: Pull the titan-optimized server docker image.status: Get the status of an experimentupload: Upload an artefact to the TitanML hub.takeoff: Launch a TitanML inference server. Seedocsfor more information.HelpFor more information on the Iris CLI, see thedocs.AuthorsTitanML