Saravanan666/pypi-org huggingface dataset:
Package: tolerious-polls
Polls is a simple Django app to conduct Web-based polls. For each
question, visitors can choose between a fixed number of answers.Detailed documentation is in the “docs” directory.Quick startAdd “polls” to your INSTALLED_APPS setting like this:INSTALLED_APPS = (
    ...
    'polls',
)Include the polls URLconf in your project urls.py like this:url(r'^polls/', include('polls.urls')),Runpython manage.py migrateto create the polls models.Start the development server and visithttp://127.0.0.1:8000/admin/to create a poll (you’ll need the Admin app enabled).Visithttp://127.0.0.1:8000/polls/to participate in the poll.
Package: toliman
TOLIMANThe goal of the TOLIMAN mission is to answer the question: is there a planet
around Alpha Centauri? The critical advance represented by the TOLIMAN
telescope is its ability to assess a specific star. Until now telescopes have
been designed to survey many stars and confirm (with biases) which ones may
have exoplanets. None have chosen a star and tried to resolutely and without
question find all and any exoplanets in orbit.
Package: tolino-notes
Tolino NotesConvert Tolino notes into useful formatsTolino stores your highlights and notes in anotes.txtfile on your device. However that file has a strange structure and mixes books when you read multiple ones at a time. And the content depends on the language-setting of your device.This project tries to close the gap by doing the heavy-lifting of parsing the file, sorting and converting to a commonly used format such as Markdown or JSON. – one file per book found in yournotes.txt.Where do I find this file?Connect your Tolino to your computer via USB.Use a file manager (Explorer, Finder, etc.) and open the root directory of the device.Look for thenotes.txtfile.Install and useThis is a Python program. Install it usingpip/poetryor similarfrom PyPi. If you don't yet havepipinstalled,go here first.$python-mpipinstalltolino-notesIn a new shell run:$tolino-notes--help
Usage:tolino-notes[OPTIONS]ConvertTolinonotesintousefulformats

Options:-i,--input-fileFILEOriginalTolinonotesfile[required]-o,--output-dirDIRECTORYFolderforoutputfiles[required]-f,--format[md|json]Outputformat[required]-v,--verboseVerboseoutput--helpShowthismessageandexit.For example to convert all your notes to markdown run:$mkdiroutput-dir
$tolino-notes--input-filenotes.txt--output-diroutput-dir--formatmdStatusSuccessfully in use with Tolino Shine 3.Supports extraction and conversion of highlights, bookmarks and notes.Support for DE, EN, ES, IT, NL, FR device-language settings, which is detected automatically.Supported output formats are Markdown and JSON.Limitations:Due to the unstructured nature of thenotes.txt, it is a best-guess approach. Thenotes.txtformat writes notes sequentially and it is not always clear in which order notes were taken. Also separating notes and highlights can only be done based on "quotes", which is not the most robust approach. In general, I believe 99% of your notes and highlights should be extracted properly.Use theissue trackerto let me know about ideas and issues.DevelopmentThe project is built based onthisboilerplate.Runmaketo create a new virtual environment.License and attributionThis software is licensed underApache License 2.0.
Package: tolio
Tolio - Rust ExtensionVERSION 0.2.5

Using: Rust 1.66.0 | Maturin 0.14.7
Supports: MacOS - Python 3.10+, Linux - Python 3.7X
Source Code: src/rust/DescriptionThis python package was build in rust, using maturin, to complement theTolioapplication. The rationale behind using rust is to offer increased speed and performance when interacting
with the database.LimitationsThis python package only supports database functionalities that are specific to the Tolio application. None of the functionalities
that this package offers will be usable for any other purpose.
Package: tolkein
Tree of Life Kit of Evolutionary Informatics NoveltiesInstallationconda install -c tolkit tolkeinorpip install tolkeinYou can also install the in-development version with:pip install https://github.com/tolkit/tolkein/archive/main.zipDocumentationhttps://tolkein.readthedocs.io/DevelopmentTo run all tests run:toxChangelog0.2.0Features:
* Added fetch methods
* Switched code style to black/flake8Bug fixes:
* Stopped log messages printing twice0.0.1 (2020-07-02)First release on PyPI.
Package: toll
toll — poor man’s integration testingtoll =testofflinelocallylightweightRun the tests of multiple configured packages:right one package after anotherstopping with the first package which has a failing testThis package is compatible with Python 2.7, 3.5, 3.6, 3.7, 3.8, PyPy2 and PyPy3.Documentation see:http://toll.readthedocs.ioThis package is licensed under the MIT License, see LICENSE.txt inside the
package.Change log4.2.1 (2020-04-21)Fix AttributeError in Python 2.7 hidden by tests installingconfigparserlibrary.4.2 (2020-04-21)Add support for Python 3.8.Fix missing dependency in Python 2.7 when installed as wheel.4.1.1 (2020-03-24)Keep supporting Python 2 by using older versions.4.1 (2018-08-03)Add option--start-atto specify the first package for which the command
is run. (It does a substring match against the packages list in the config
file.)Add support for Python 3.7.Drop support for Python 3.4.4.0 (2017-12-26)Add anignore-exit-codeto the configuration of the commands to allow a
complete run-through of all packages.Drop support for Python 3.3.Also release as wheel.3.2 (2017-05-16)Change license from ZPL to MIT.Move canonical repository tohttps://github.com/icemac/toll.Add support for PyPy3.3.1 (2017-01-07)Colour the own output oftoll.Add a line above the output for each package.3.0 (2017-01-06)Backward incompatible changesAdd a preconditions to the commands. If the precondition is not met the
command is not executed. This can be used to prevent running a command in
a package where it will fail.This requires a new config file format. (See documentation.)Other changesAdd support for Python 3.6.2.1 (2016-12-06)Add compatibility withsetuptools >= 30.0.2.0 (2016-06-17)Use a default configuration file namedtoll.ini. This can be overwritten
using-cwhen callingtoll.Allow to specify multiple command which should be called. (See--help.)Make package compatible with Python 2.7, 3.3, 3.4 and PyPy.1.0 (2016-02-26)Initial release.
Package: toloka-airflow
Toloka-AirflowThis library allows you to run crowdsourcingTolokaprocesses inApache Airflow- a widely used workflow management systemHere you can find a collection of ready-made Prefect tasks for the most frequently used actions inToloka-Kit.Getting started$ pip install toloka-airflowA good way to start is to follow theexamplein this repo.Useful LinksToloka homepage.Apache Airflow homepage.Toloka API documentation.Toloka-kit usage examples.Questions and bug reportsFor reporting bugs please use theToloka/bugreportpage.Join our English-speakingslack communityfor both tech and abstract questions.License© YANDEX LLC, 2022. Licensed under the Apache License, Version 2.0. See LICENSE file for more details.
Package: toloka-prefect
Toloka-PrefectThis library allows you to run crowdsourcingTolokaprocesses inPrefect- a widely used workflow management systemHere you can find a collection of ready-made Prefect tasks for the most frequently used actions inToloka-Kit.Getting started$ pip install toloka-prefectA good way to start is to follow theexamplein this repo.Useful LinksToloka homepage.Prefect homepage.Toloka API documentation.Toloka-kit usage examples.Questions and bug reportsFor reporting bugs please use theToloka/bugreportpage.Join our English-speakingslack communityfor both tech and abstract questions.License© YANDEX LLC, 2020-2021. Licensed under the Apache License, Version 2.0. See LICENSE file for more details.
Package: tololib
TOLOlibPython Library for Controlling TOLO Sauna/Steam Bath DevicesThis library supports controlling and requesting information frmo TOLO Sauna/Steam Bath systems.
It is the core of theHome Assistant TOLO Integration.
If you are missing any features or you found any bugs or irregularities,
please to not hesitate toopen an issue.LinksAPI DocumentationOfficial Website of Steamtec/TOLOLegal NoticeThis project is a community project, published under theMIT License.
SeeLICENSE.mdfor more information.Neither this project, nor the author is in any professional affiliation with companies behind TOLO.Copyright (c) 2021 byMatthias Lohr<mail@mlohr.com>
Package: toltecmk
toltecmktoltecmkis a Python tool used to build software packages for theToltec repositoryfromPKGBUILD-like build recipes.
It automates common tasks such as fetching sources, building artifacts in a reproducible environment, and creatingOpkg-compatible archives.Disclaimer: This is beta-quality software. The recipe format may change at any time in future releases. If you usetoltecmkin other projects, it is advised to pin to a specific version.Setuptoltecmkis available as a Python package on PyPI.pipinstalltoltecmkThere are a few system requirements to use this tool:Linux-based operating systemPython ⩾ 3.11DockerBasic UsageTo build a recipe located in the current directory, simply run:toltecmkThis will process the recipe in a subfolder calledbuild(which can be adjusted using the--work-dirflag) and generate packages in a subfolder calleddist(--dist-dirflag).DocumentationTutorials and resourcesGuide to writing recipesAbout ipk packagesReferenceRecipe format referenceDetails on the build processRelated ProjectsMany other build tools exist today for creating software packages, each major distribution having invented its own recipe and package formats.
Some important ones are listed below.toltecmkitself uses an Arch Linux-style recipe format to build Debian-style packages.NameUsed byRecipe formatPackage formatDebian-styledebhelperDebian,Ubuntu, andothersSource packages(Makefiles)debOpenWrt SDKOpenWrt,EntwareSource packages(Makefiles)ipkFedora-stylerpmbuildFedora,openSUSE, andothersspec(DSL)rpmArch Linux-stylemakepkgArch LinuxandothersPKGBUILD(Bash scripts)pkg.tar.zstabuildAlpine LinuxAPKBUILD(Bash scripts)apkOthersnix-buildNixOSExpressions(DSL)narebuildGentooebuild(Bash scripts)tbz2
Package: tomahawk
Examples$ tomahawk -h host1,host2,host3 uptime–> ‘uptime’ command is executed in host1, host2 and host3 as follows.kazuhiro@host1% uptime
22:41:27 up 10 days,  3:26,  1 users,  load average: 1.11, 1.13, 1.11kazuhiro@host2% uptime
22:41:28 up 20 days,  4:26,  2 users,  load average: 2.11, 2.13, 2.11kazuhiro@host3% uptime
22:41:29 up 30 days,  5:26,  3 users,  load average: 3.11, 3.13, 3.11$ tomahawk-rsync -h host1,host2,host3 test.py /tmp/test.py–> ‘test.py’ is copied to host1, host2 and host3.See more usages:http://readthedocs.org/docs/tomahawk/en/latest/DocumentationSeehttp://readthedocs.org/docs/tomahawk/en/latest/ChangesSeehttps://github.com/oinume/tomahawk/blob/master/docs/en/changes.rstHow to contributeReport a bughttps://github.com/oinume/tomahawk/issuesSend a patchFork, modify code, add tests, run tests, send pull request.For developersInstall tomahawk in develop mode.$ python setup.py develop

or

$ pip install -e .Install following modules for testing.$ pip install requirements-dev.txtRun unit tests$ py.test tests/internal/
Package: tomako
Tomako is a tiny library designed to provide an easy way to use Mako
as a template engine for Tornado.This lib was tested with Tornado 2.3/2.4 and Mako 0.7.2, but should
work in other versions - although it wasn’t tested in other versions.UsageThe recommended approach is to passtemplate_loaderconfiguration
toApplicationclass.fromtomakoimportMakoTemplateLoaderconf={'template_loader':MakoTemplateLoader('/full/template/path')}app=Application(urls,**conf)If you can’t for any reason modify thetemplate_loaderconfiguration or you want to use Mako as a template engine only on
some handlers, you can overwriteRequestHandler.create_template_loader.fromtornado.webimportRequestHandlerfromtomakoimportMakoTemplateLoaderclassMyHandler(RequestHandler):defcreate_template_loader(self,template_path):returnMakoTemplateLoader(template_path)Tornado UIModulesTomako has basic support for Tornado’sUIModules. You must include a
special namespace calledtomako.templatein your templates:# Your python filefromtornado.webimportUIModuleclassMyModule(UIModule):defrender(self,arg1,arg2):# do something with args here...return'some string'<!-- Your template --><%namespace name="tomako" module="tomako.template" /><%tomako:ui uiclass="your.project.module.MyModule" arg1="value1" arg2="value2" />InstallpipinstalltomakoTo-DoImprove support on UIModulesLicenseThis work is licensed under MIT license (see LICENSE file).
Package: tom-antares
Antares TOM Broker ModuleThis module addsAntaressupport to the TOM
Toolkit. Using this module TOMs can query and listen to Antares streams.InstallationInstall the module into your TOM environment:pip install tom-antaresAddtom_antares.antares.ANTARESBrokerto theTOM_ALERT_CLASSESin your TOM'ssettings.py:TOM_ALERT_CLASSES = [
    ...
    'tom_antares.antares.ANTARESBroker'
]Running the testsIn order to run the tests, run the following in your virtualenv:python tom_antares/tests/run_tests.py
Package: tomapi
tomapi: Python Web Framework built for learning purposestomapi is a python web framework built for learning purposed.It's a WSGI framework and can be used with any WSGI application server such as Gunicorn.InstallationpipinstalltomapiHow to use itBasic usage:fromtomapi.apiimportAPIapp=API()@app.route("/home")defhome(request,response):response.text="Hello from the HOME page"@app.route("/hello/{name}")defgreeting(request,response,name):response.text=f"Hello,{name}"@app.route("/book")classBooksResource:defget(self,req,resp):resp.text="Books Page"defpost(self,req,resp):resp.text="Endpoint to create a book"@app.route("/template")deftemplate_handler(req,resp):resp.body=app.template("index.html",context={"name":"tomapi","title":"Best Framework"}).encode()Unit TestsThe recommended way of writing unit tests is withpytest. There are two built in fixtures
that you may want to use when writing unit tests with tomapi. The first one isappwhich is an instance of the mainAPIclass:deftest_route_overlap_throws_exception(app):@app.route("/")defhome(req,resp):resp.text="Welcome Home."withpytest.raises(AssertionError):@app.route("/")defhome2(req,resp):resp.text="Welcome Home2."The other one isclientthat you can use to send HTTP requests to your handlers. It is based on the famousrequestsand it should feel very familiar:deftest_parameterized_route(app,client):@app.route("/{name}")defhello(req,resp,name):resp.text=f"hey{name}"assertclient.get("http://testserver/matthew").text=="hey matthew"TemplatesThe default folder for templates istemplates. You can change it when initializing the mainAPI()class:app=API(templates_dir="templates_dir_name")Then you can use HTML files in that folder like so in a handler:@app.route("/show/template")defhandler_with_template(req,resp):resp.html=app.template("example.html",context={"title":"Awesome Framework","body":"welcome to the future!"})Static FilesJust like templates, the default folder for static files isstaticand you can override it:app=API(static_dir="static_dir_name")Then you can use the files inside this folder in HTML files:<!DOCTYPE html><htmllang="en"><head><metacharset="UTF-8"><title>{{title}}</title><linkhref="/static/main.css"rel="stylesheet"type="text/css"></head><body><h1>{{body}}</h1><p>This is a paragraph</p></body></html>MiddlewareYou can create custom middleware classes by inheriting from thetomapi.middleware.Middlewareclass and overriding its two methods
that are called before and after each request:fromtomapi.apiimportAPIfromtomapi.middlewareimportMiddlewareapp=API()classSimpleCustomMiddleware(Middleware):defprocess_request(self,req):print("Before dispatch",req.url)defprocess_response(self,req,res):print("After dispatch",req.url)app.add_middleware(SimpleCustomMiddleware)
Package: tomark
tomarkA Python module that converts a list of dictionaries to a markdown formatted table.Note: Each dict in the list must have the same number of elements.Installing!python3 -m pip install --upgrade tomarkUsage:from tomark import Tomark

data = [
  {
    'pr': 291, 
    'status': 'closed', 
    'date': 'None', 
    'title': 'Adds new wiz bang feature'
  },
  {
    'pr': 290, 
    'status': 'v1.0', 
    'date': 'None', 
    'title': 'Updates UI to be more awesome'
  }
]

markdown = Tomark.table(data)
print(markdown)Example table output:PRStatusDateTitle292openNoneAdds new wiz bang feature286v1.0NoneUpdates UI to be more awesomeExample raw ouput:| PR  | Status | Date | Title |
|----|----|----|----|
| 292 | open | None | Adds new wiz bang feature |
| 286 | v1.0 | None | Updates UI to be more awesome |
Package: tomarkdown
tomarkdownauthor informationcodima(coding-mathmatics) on youtube & ...Usage...under constructionbut in short:look atdemo1.py as well as my_script.py in the "demo" folder.
The demo1.py scripts imports and initiates the tomarkdown package to generate:my_script.mdmy_script.TopLevel.mdmy_script.TopLevel.MidLevel.mdmy_script.a_class_generatorfor the documentation of my_script.py.
Finally the mkdocs.yml has been adjusted by hand to include the generated markdown scripts and then Mkdocs does its thing.
You can see the results for yourself here:https://berlinade.gitlab.io/tomarkdowndocs...under constructionhttps://berlinade.gitlab.io/tomarkdown/informal info on license (english)This repository is licensed under GPL-V3 (see LICENSE). You can refer to the author of this package as codima & ... .
Package: tomaserial
Serial-Py这是一个基于python typing的反序列化框架，它已经发布到Pypi，因此，你可以通过如下方式依赖它：pip3install数据类定义使用时需要将数据按照如下方式定义：这里面包含嵌套类、枚举类
等，如果需要序列化的字段名称和变量名称不完全一致，可以实现Serial.name_strategy实现字段名称之间的映射。fromdataclassesimportdataclassfromenumimportEnumfromtypingimportListfromsrc.serialimportSerialclassShaderType(Enum):vertex=1fragment=2@dataclassclassShader(Serial):code:str=Noneshader:ShaderType=Noneattributes:List[int]=Nonecompiled:bool=Falseattached:bool=False@dataclassclassProgram(Serial):vertex_shader:Shader=Nonefragment_shader:Shader=Nonelinked:bool=Falsebyte_buffers:List[float]=None序列化你可以调用Serial.json()将class转为dict，也可以调用Serial.str()直接将class转换为
字符串。classSerialTestCase(unittest.TestCase):vertex_shader=Shader(code="vertex shader",shader=ShaderType.vertex,attributes=[1,2,3],compiled=True,attached=False)fragment_shader=Shader(code="fragment shader",shader=ShaderType.fragment,attributes=[],compiled=False,attached=True)program=Program(vertex_shader=vertex_shader,fragment_shader=fragment_shader,linked=True,byte_buffers=[0.1,0.2,0.3])deftest_serialize(self):program_dict=self.program.json()print(program_dict)vertex_shader:dict=program_dict.get('vertex_shader')self.assertIsInstance(vertex_shader,dict)self.assertEqual(vertex_shader.get("compiled"),True)attributes=vertex_shader.get("attributes")self.assertIsInstance(attributes,list)self.assertEqual(len(attributes),3)self.assertEqual(attributes[0],1)program_str=self.program.str(indent=2,ensure_ascii=True)print(program_str)反序列化你可以直接调用如Program.from_str(...)或Program.from_json(dict)来将字符串或者字典转换成某种类型，
当然枚举类和嵌套类都是支持的，同样可以通过定义Serial.name_strategy来实现字段名称之间的映射。deftest_de_serialize(self):json_str="""{"vertex_shader": {"shader": "vertex","attributes": [1,2,3],"compiled": true,"attached": false},"fragment_shader": {"shader": "fragment","attributes": [],"compiled": false,"attached": true},"linked": true,"byte_buffers": [0.1,0.2,0.3]}""".strip()de_serial_result=Program.from_str(json_str)self.assertIsInstance(de_serial_result,Program)self.assertTrue(de_serial_result.linked)buffers=de_serial_result.byte_buffersself.assertIsInstance(buffers,list)self.assertEqual(len(buffers),3)# for nested classesvertex_shader=de_serial_result.vertex_shaderself.assertIsInstance(vertex_shader,Shader)self.assertTrue(vertex_shader.compiled)self.assertFalse(vertex_shader.attached)self.assertIsInstance(vertex_shader.attributes,list)self.assertEqual(vertex_shader.attributes.__len__(),3)# for enumself.assertIsInstance(vertex_shader.shader,ShaderType)self.assertEqual(vertex_shader.shader,ShaderType.vertex)fragment_shader=de_serial_result.fragment_shaderself.assertIsInstance(fragment_shader,Shader)self.assertTrue(fragment_shader.attached)self.assertIsInstance(fragment_shader.attributes,list)self.assertEqual(len(fragment_shader.attributes),0)
Package: tomasrajaolib
tomasrajaolibMódulo para exemplificar construção de projetos Python no curso PytoolsNesse curso é ensinado como contribuir com códigos abertosLink do cursoPython ProPara instalar:python3 -m venv .venv
source .venv/bin/venv
pip install -r requirements-dev.txtPara conferir qualidade de código:flake8Tópicos a serem abordados:GitVirtualenvPip
Package: tomaster
tomaster: Topological Mode Analysis on Steroidstomasterimplements algorithms for topological mode analysis.The code is simple to read because it is written in pure Python.The performance is good thanks to jit compilation withnumba.Usage>>>fromtomasterimporttomato>>>fromsklearnimportdatasets>>>X,y=datasets.make_moons(n_samples=1000,noise=0.05,random_state=1337)>>>clusters=tomato(points=X,k=5,n_clusters=2)>>>importmatplotlib.pyplotasplt>>>plt.scatter(*X.T,c=clusters)>>>plt.show()Installationpip install tomasterTestingpytestAPIdeftomato(*,points=None,k=None,neighbors=None,distances=None,density=None,metric="l2",bandwidth=None,raw:bool=False,tau=None,n_clusters=None,keep_cluster_labels:bool=False,):"""ToMATo clusteringYou can call this function with a lot of different signatures as it tries to build the missing parameters from the others.Parameters----------points : np.ndarrayArray of shape (n, dim)k : intNumber of nearest neighbors to build the graph withneighbors : np.ndarrayArray of shape (n, k)distances : np.ndarrayArray of shape (n, k)density : np.ndarrayArray of shape (n,)metric: str"l2" or "cosine"raw : boolif True, returns the merge edgestau : floatProminence threshold. If not specified, automatically selects the largest persistence gap.n_clusters : intTarget number of clusters.keep_cluster_labels : boolIf False, converts the labels to make them contiguous and start from 0.Returns-------clusters : np.ndarrayif raw is False (default), array of shape (n,) containing the cluster indicesedges : listif raw is True, spanning tree as list of (persistence, point1, point2)"""deftomato_img(img:np.ndarray,*,spatial_weight:float=0,lab_space:bool=True,**kwargs):"""ToMATo for imagesParameters----------img : np.ndarrayImage of shape (h, w) or (h, w, 3)spatial_weight : floatImportance of the pixel positions in the distance functionlab_space : boolIf True, converts color images to the CIE L*a*b color space (<https://en.wikipedia.org/wiki/CIELAB_color_space>)see tomato() for other arguments.Returns-------clusters : np.ndarrayArray of shape (h, w) containing the cluster indexes."""ReferencesChazal, Frédéric, Leonidas J. Guibas, Steve Y. Oudot, and Primoz
Skraba. "Persistence-based clustering in riemannian manifolds."
Journal of the ACM (JACM) 60, no. 6 (2013): 41.[pdf]Reference implementations:https://geometrica.saclay.inria.fr/data/ToMATo/,https://geometrica.saclay.inria.fr/data/Steve.Oudot/clustering/
Package: tom-astrosource
tom_astrosourceThis package allowsastrosourceto
be run on data files in theTOM Toolkitvia
thetom_educationapp.RequirementsIn addition to the requirements listed insetup.pyyou will need:A working TOM (seeTOM Toolkitdocumentation)Python > 3.6InstallationSet up a TOM and thetom_educationpackage. See thetom_education
installation
instructions.pip install tom_astrosourceAddtom_astrosourcetoINSTALLED_APPSinsettings.py.INSTALLED_APPS=[...'tom_astrosource']Add theastrosourcepipeline toTOM_EDUCATION_PIPELINES(create this
setting if it does not exist):TOM_EDUCATION_PIPELINES={...'astrosource':'tom_astrosource.models.AstrosourceProcess'}Install Development versionClone this repo and install the package withpip:git clone https://github.com/joesingo/tom_astrosource
pip install tom_astrosourceUsageSee thepipeline
documentationintom_educationfor how to run the pipeline on your data.