Saravanan666/pypi-org huggingface dataset:
Package: tbgrep
A module & command-line tool for extracting Python tracebacks from text.Extracting tracebacks from bunch of files$tbgrepfile1file2file3Grepping for tracebacks in a pipeline$tail-flogfile|tbgrepDisplaying all unique tracebacks ordered by the number of occurrences$tbgrep--statslogfile[...]==99occurences==================================================Traceback(mostrecentcalllast):File"/usr/lib/python2.4/site-packages/bodhi/admin.py",line209,in_masher_requestreq_params=kwargs)File"/usr/lib/python2.4/site-packages/fedora/client/proxyclient.py",line285,insend_requestraiseAuthError(_('Unable to log into server.  Invalid'AuthError:Unabletologintoserver.Invalidauthenticationtokens.Sendnewusernameandpassword==================================================================733uniquetracebacksextractedUsing the Python APIOnce instantiated, you pass each line to theprocessmethod, which will
return either None, or a string of a traceback.fromtbgrepimportTracebackGrepextractor=TracebackGrep()forlineinfile('logfile'):tb=extractor.process(line)iftb:print(tb)Instead of displaying each traceback found in the file, tbgrep also
supports generating statistics about all tracebacks in the file.extractor=TracebackGrep(stats=True)forlineinfile('logfile'):extractor.process(line)extractor.print_stats()There are also some functions that allow you to search for tracebacks in a more
convenient way.fromtbgrepimport(tracebacks_from_lines,tracebacks_from_file,last_traceback_from_file)fortbintracebacks_from_file(file('logfile')):print(tb)fortbintracebacks_from_file(file('logfile'),reverse=True):print(tb)print(last_traceback_from_file(file('logfile')))Supported Input Formatstbgrep can extract tracebacks from logs of various formats. For example,
CherryPy starts the traceback on a line with other details (like module,
timestamp, etc), but the rest of the trace starts at the beginning of the line.
Apache logs, on the other hand, will prefix each line of the traceback with
this information. tbgrep is designed to handle these kinds of situations
Package: tbgutils
The Brookhaven Group, LLC (TBG) UtilitiesDate and string utilitiesThese are utilities commonoly used at The Brookhaven Group, LLCInstallationPyPI Page$pipinstalltbgutilsorGitHub$pipinstallgit+https://github.com/TheBrookhavenGroup/tbgutils.gitExamplesPrint the beginning of the next day in local time.>>> from tbgutils.dt import to_date, day_start_next_day
>>> d = to_date('20230320')
>>> print(day_start_next_day(d))
"2023-03-21 04:00:00+00:00Is holiday observed?>>>fromsrc.tbgutils.dtimportto_date,is_holiday_observed>>>d=to_date('20230704')>>>is_holiday_observed(d)TrueIs it a weekend?>>>fromsrc.tbgutils.dtimportis_week_end>>>d=to_date('20230704')>>>is_week_end(d)False>>>d=to_date('20230319')>>>is_week_end(d)TrueTHE END
Package: tbhandler
Traceback handlerModule to notify user of errors in all scripts, even when they run without terminalTraceback message in extended and easily readably formatOpen message in new terminal tab if script is running without terminalDeveloped for Linux OS where konsole application is availableInstallationpipinstalltbhandlerThis will create a new sitecustomize file. To overwrite existing sitecustomize file, run:install_sitecustomizeAlternatively, you can use the manual installation of the tbhandler in each of your scripts.importtbhandler

tbhandler.install()
Package: tbk
Attention: Beta not ready for productionPython implementation of Transbank’s Webpay protocol.Installationpip install tbkUsageSet environment variable for Commerce and initialize.os.environ['TBK_COMMERCE_ID'] = "597026007976"
os.environ['TBK_COMMERCE_KEY'] = "-----BEGIN RSA PRIVATE KEY-----\nMIIEowIBAAKCAQEAn3HzPC1ZBzCO3edUCf/XJiwj3bzJpjjTi/zBO9O+DDzZCaMp...""

from tbk.webpay.commerce import Commerce

commerce = Commerce.create_commerce()
# for development purposes you can use
# commerce = Commerce(testing=True)If you want to set the official webpay log (for certification issues):from tbk.webpay.logging import configure_logger
from tbk.webpay.logging.official import WebpayOfficialHandler

configure_logger(WebpayOfficialHandler(LOG_BASE_PATH))Create a new payment and redirect user.from tbk.webpay.payment import Payment

payment = Payment(
    request_ip='123.123.123.123',
    commerce=commerce,
    success_url='http://localhost:8080/webpay/success/',
    confirmation_url='http://127.0.0.1:8080/webpay/confirmation/',
    failure_url='http://localhost:8080/webpay/failure/',
    session_id='SOME_SESSION_VALUE',
    amount=123456,
    order_id=1,
)
payment.redirect_urlThen to confirm payment, use an endpoint with:from tbk.webpay.confirmation import Confirmation

def confirmation(request):
    conf = Confirmation(
        commerce=commerce,
        request_ip=request.ip_address,
        data=request.POST
    )

    # validate_confirmation validate if order_id and amount are valid.
    if conf.is_success() and validate_confirmation(conf) and not conf.is_timeout():
        return HttpResponse(commerce.acknowledge)

    return HttpResponse(commerce.reject)About webpay communication protocol:http://sagmor.com/rants/technical/webpay-communication-protocol/
Package: tbk-api
淘宝客接口淘宝客共享接口注意:这个接口仅仅是为了内部使用，虽然您可以获取它的源代码，但是请不要使用在您的项目中.
当前我并不对兼容性以及可用性做任何保证。(如果需要使用请联系开发者获取相应的授权)
Package: tblock
TBlockDescriptionTBlock is a free and open-source system-wide ad-blocker that is compatible with most filter list formats.To view the repository for the graphical user interface,click here.InstallationYou can easily install TBlock with:pipxinstalltblockMore installation methods — such as Windows installer and packages for Linux distributions — can be foundon the website.UsageAfter installing, you need to setup TBlock in order to enable protection against ads and trackers:tblock--initYou can learn more by readingthe documentation.DemoRoadmapHere is a list of the upcoming changes in TBlock code. Suggestions are, of course, welcome.Implementa GUI for TBlockRewrite the entire code, make a clearer public API and publish release 3.0.0ContributingEveryone is welcome to contribute to TBlock in different ways. Bug reports can be made directly from theGitea issue tracker, by sending an email to the team or inour Matrix room.If you want to suggest a modification in the code, you canopen a pull requestor send your patch using email or Matrix.If you want to be a beta-tester, you can install the latest beta version from ourrelease pageand contact us to give a feedback.You can find more information on how to contributehere.SupportThe best way to support is tocontribute. If you want, you can alsomake a donation.Authors and acknowledgmentTBlock is currently mainained byTwann, who is also its creator.
A big thank you to all the peoplewho contribute(d) to the project.CreditsHere is a list of all libraries used in the project:NameAuthorLicensecoloramaJonathan HartleyBSDrequestsKenneth ReitzApache 2.0urllib3Andrey PetrovMITargumentorTwannLGPLv3It is also worth mentioningpacman, from which TBlock's command-line design is highly inspired.ContactMastodonMatrixXMPPLicenseThis program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.You should have received a copy of the GNU General Public License
along with this program.  If not, seehttps://www.gnu.org/licenses/.
Package: tblu-module-so
TBlu Module SOModule Python for SO informationsFree software: MIT licenseDocumentation:https://tblu-module-so.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2018-07-30)First release on PyPI.
Package: tb-mean-field-hubbard
tb-mean-field-hubbardPython library to perform tight-binding mean field Hubbard calculations on the conjugated π-networks of organic systems.
Only carbon atoms are supported and each atom is modelled by a single pzorbital hosting a single electron.The modelled Hamiltonian is the following:where c†, c and n are respectively the creation, annihiliation and number operators, t is the hopping integral and U denotes the on-site Coulomb repulsion.System requirementsPython 3 (tested with 3.6 - 3.9) environment is required with the following libraries (parenthesis indicate tested versions; but the library should work with all recent versions):Standard python libraries:numpy(1.17.2),scipy(1.3.1),matplotlib(3.2.1)Atomistic simulation environment:ase(3.18.1)Python Tight Binding:pythtb(1.7.2)Note: the dependencies will be automatically installed viapip.InstallationOption 1) Install the library and dependencies hosted on PyPI:pip install tb-mean-field-hubbardOption 2) Manual installation, such that you have direct access to the code and the notebook:git clone https://github.com/eimrek/tb-mean-field-hubbard.git
cd tb-mean-field-hubbard
pip install -e .On a normal desktop computer, installation of the python dependencies can take some minutes, while thetb-mean-field-hubbardshould install in seconds.Example usageExample jupyter notebookexample.ipynbis provided that performs the calculation for the Clar's goblet molecule. The geometry is read from axyzfile. The whole notebook should run in a matter of seconds on a normal desktop computer.
The following image demonstrates a selection of the output for the calculation for parameterst=2.7andU=3.0(both in electronvolts).In addition to the structure of Clar's goblet, thegeom/folder contains input geometries for triangulene, 4- and 5-rhombene, and several other systems.
Package: tbm-utils
tbm-utils.pytbm-utilsis a commonly-used set of utilities used by me (thebigmunch).Installationpip install -U tbm-utilsUsageFor the release version, see thestable docs.For the development version, see thelatest docs.AppreciationShowing appreciation is always welcome.ThankGet your own thanks inbox atSayThanks.io.ContributeContributeby submitting bug reports, feature requests, or code.Help Others/Stay InformedDiscourse forumReferrals/Donations
Package: tbnf
Typed BNFGiven a grammar:shape token {
    lexeme : str
}
polyrule  :<a><b>{ fn (a) -> ($1.lexeme, $2, a) }
polyrule2 :<a>polyrule { fn (a) -> $2(a) }We type inference it:polyrule : forall 'a. ('a) -> (str, token, 'a)
polyrule2 : forall 'a. ('a) -> (str, token, 'a)Then we can lower it to a BNF grammar used by other parser framework,
no matter which programming language is the target.BackendsTentatively, support forpython-larkandantlr-javaare down. Focusing on improvingantlr-csharp(So far C# has no easy-to-use parser generator.)python -m tbnf GRAMMAR.tbnf [lark|csharp|antlr] [--outdir OUTDIR=.] [--mod MODULENAME=mylang]
Package: tbnns
## TBNN-s v0.5.0 - Tensor Basis Neural Network for Scalar MixingThis package implements the vanilla Tensor Basis Neural Network [1]
as the TBNN class, and also the Tensor Basis Neural Network for
Scalar Flux Modeling [2] as the TBNNS class. They are described in
the following references:[1] Ling, Kurzawski, Templeton. “Reynolds averaged turbulence modelling using deep neural networks with embedded invariance.” J. Fluid Mech. 807 (2016)[2] Milani, Ling, Eaton. “Turbulent scalar flux in inclined jets in crossflow: counter gradient transport and deep learning modelling” J. Fluid Mech. (under review)Author: Pedro M. Milani (email:pmmilani@stanford.edu)Last modified: 08/06/2020Developed and tested in Python 3.7 using tensorflow 1.15### Installation
To install, run the following (optionally within a virtual environment):pip install tbnns [–user] [–upgrade]This will install the stable version from the Python Package Index. Use
the flag –user in case you do not have administrator privileges and the
flag –upgrade to get the newest version.To test the program while it is being developed, run the command below
from the current directory. This is useful when you are developing the
code.pip install -e .To uninstall, run:pip uninstall tbnnsThe commands above will also install
some dependencies (included in the file “requirements.txt”)
needed for this package.### Examples and TestingThe folder test contains a script example_usage.py and three representative
datasets. For an example of training a TBNN-s and applying it to a test
set, run the following inside the folder test:python example_usage_tbnns.pypython example_usage_tbnn.py
Package: tbone
logoTBone makes it easy to develop full-duplex RESTful APIs on top of yourasyncioweb application or webservice. It uses a nonblocking
asynchronous web server and provides the neccesary infrastructure to
build asynchronous web apps and services. TBone is web-server agnostic
and can be added on top of yourSanicorAiohttpapp.TBone is comprised of 4 major modules:Data Structure - an ODM-like modeling mechanism for schema
declaration, data validation and serializationData Persistency - Persistency mixin classes for document stores with
a full implementation over MongoDBResources - Mechanism for creating full-duplex RESTful APIs overHTTPandWebsocketsDispatch - Classes for managing internal and external events.Combining the usage of these 4 modules makes it extremely easy to build
full-duplex RESTful APIs on top of your MongoDB datastore.DisclaimerTBone is currently in Alpha stage. It may still have some bugs in the
code, and some typos in the documentation. The APIs may change before an
official release is made.ExampleThe following example demonstrates the creation of a model schema and
the corresponding RESTful resourceclassBook(Model,MongoCollectionMixin):_id=ObjecIdField(primary_key=True)title=StringField(required=True)author=StringField(required=True)publication_date=DateTimeField()classBookResource(AioHttpResource,MongoResource):classMeta:object_class=BookNonblockingTBone was designed to develop asynchorous web applications and web
services. The entire infrastructure was built aroundcoroutines.
TBone utilizes only asynchronous 3rd party components to make sure that
your app is truly nonblocking.RequirementsTBone uses the async/await syntax and is limited to Python version 3.5
and up.Furthermore, TBone has some very few basic requirements. However,
depending on its usage requires additional packages may be required.DocumentationDocumentation can be found here
Package: tbot
A library to make writing IRC bots easier and more funRationaleWriting IRC bots is easy enough that beginners often pull it off to some
success. But writing extensible, maintainable, IRC bots that are abstracted
from the details of the protocol is difficult.twisted.words.protocols.ircmakes that a wee bit easier, but you still need to deal with some things you
probably don’t care about, like ‘factories’ or ‘protocols’ and such things.
There are also some harder problems like persistence of state, configuration,
and module reloading that don’t have obvious solutions.tbottries to make that simpler, letting you focus on what you care about:
doing cool things in IRC.
Package: tbotg
IntroductionThis repository provides a python library to make it easy to create
telegram bots using the python telegram API.The basic idea is that you can define a function similar to the way you
would with theclick frameworkand then automatically convert that into a form suitable for telegram.Ideally, creating commands in a telegram bot should but just as easy as
writing a python function.Getting StartedThe following describes how to get started as quickly as possible.Install via pipDo the usualpip install tbotg.Use BotFather to create a botFirst, use the botfather to create a bot:Go toBotFatherin a Telegram chat.Type/newbotto request a new bot.Type the desired name whenBotFatherasks you for it.Save the tokenBotFathergives you in~/.ox_secrets.csvasname,category,values,notes
token,YOUR_BOT_NAME,YOUR_TOKENThe~/.ox_secrets.csvfile is a simple CSV file used to manage
secret information such as your telegram bot token.Create a python file for your commandNext, create a python file for your bot. For example, you could create a
python file namedmybot.pyas shown below:"Example to show how to use tbotg"importclickfromtbotg.core.main_botimportTelegramMainBotfromtbotg.core.bcmdsimportClickCmd@click.command()@click.option('--say','/say',help='What to say')@click.option('--count','/count',type=int,help='How many times to repeat.')defrepeatntimes(say,count):"Repeat something N times."return'I will repeat it%itimes:%s'%(count,', '.join([say.upper()]*count))classMyBot(TelegramMainBot):"""Example bot.
    """@classmethoddefmake_cmds(cls):"Make commands for bot."return[ClickCmd(repeatntimes)]Start the serverRun the serve using thetcliscript provided bytbotgvia the
following command line:tcliserve--bot_clsMyBot--module'mybot'--with_name${YOUR_BOT_NAME}where${YOUR_BOT_NAME}is the name of the bot you created withBotFatherNote that you will need yourPYTHONPATHset properly for python to
find yourmybot.pymodule. For example, you could do something likeexport PYTHONPATH=${PYTHONPATH}:`dirname /path/to/mybot.py`Test the command on telegramTo test your command,Start a chat with your bot on telegram.Do/helpto see available commands.Do/repeatntimesto run your commandClick on the parameter buttons to set the values ofsayandcount.Click theconfirmbutton to run the command.Note that you can also include command line arguments when calling a
command in Telegram via something like:/repeatntimes /say hiand that option will be automatically filled in. Note that it is best to
use a leading slash (/) for these kinds of options and not the usual
double hyphen (--) since some versions of Telegramauto-replace
double
hyphenswith
a “long dash”.
Package: tb-paddle
0.1.0 (2019-08-21)First commit. Github Link:https://github.com/linshuliang/tb-paddle0.2.0 (2019-08-26)Append setup requirements, pillow.0.3.1 (2019-08-27)Fix the bug of session_log.0.3.2 (2019-09-04)Optimize the display effect of bbox.Append setup requirements - moviepy, which is necessary for APIadd_video.0.3.3 (2019-09-05)Fix the bug of Paddle Graph.0.3.4 (2019-09-12)modify the logging config.add RecordReader and Event_File_loader.0.3.5 (2019-09-12)add SummaryReader0.3.6 (2019-09-19)modify the limitation of tag.0.3.7 (2019-12-25)Append new APIhparams_apito support TensorBoard DashBoardHParams.0.3.8 (2019-12-30)Fix the bug of forgotten moduletime.0.3.9 (2020-1-5)add support for internal hdfs, not released to outsides.0.4.0delete setup requirement -moviepy, users who need to useadd_videomustpip install moviepyby themselves.
Package: tbparse
tbparseA simple yet powerful tensorboard event log parser/reader.Supports parsing tensorboard eventscalars,tensors,histograms,images,audio,hparams, andtext.Supports event generated byPyTorch,Tensorboard/Keras, andTensorboardX, with their respective usage examples documented in detail.Allows parsing multiple tensorboard event files in a hierarchical directory structure.Provides plotting examples for each type of events.Stores the data inpandas.DataFrameto allow advanced filtering.Both the documentation and code have high test coverage rate.FollowsPEP 484with full type hints.Installation:pipinstalltensorflow# or tensorflow-cpupipinstall-Utbparse# requires Python >= 3.7Note: If you don't want to install TensorFlow, seeInstalling without TensorFlow.We suggest using an additional virtual environment for parsing and plotting the tensorboard events. So no worries if your training code uses Python 3.6 or older versions.Reading one or more event files with tbparse only requires 5 lines of code:fromtbparseimportSummaryReaderlog_dir="<PATH_TO_EVENT_FILE_OR_DIRECTORY>"reader=SummaryReader(log_dir)df=reader.scalarsprint(df)If you want an additional column with directory names (i.e., run names), change line 3 above to the following:reader=SummaryReader(log_dir,extra_columns={'dir_name'})For further information, start from the page:Parsing Scalars.GalleryEvent TypeTensorboard DashboardtbparseScalarsTensorsHistogramsImagesAudioHParamsTextAll events above are generated and plotted ingallery-pytorch.ipynb.Installationpipinstalltensorflow# or tensorflow-cpupipinstall-Utbparse# requires Python >= 3.7Note: If you don't want to install TensorFlow, seeInstalling without TensorFlow.Testing the Source CodeTest source code:python3-mpipinstalltox
python3-mtoxTest and build documentation:cddocs
makeclean# sphinx-tabs seems to require html be built before doctestmakehtml
makedoctestGenerate test coverage:python3-mpipinstallpandastensorflowtorchtensorboardXpytestpytest-cov
python3-mpytest--cov=./--cov-reporthtmlLicensetbparse is distributed under theApache License 2.0.The tbparse PyPI package depends on (imports) the following third-party package. Each third-party software package is provided under its own license:pandasis distributed under theBSD-3-Clause Licensetensorboardis distributed under theApache License 2.0
Package: tbpaste
tbpasteis a command-line utility that runs sentiment analysis on the contents of your clipboard.UsageCopy some text to your clipboard.Runtbpastein your shell for the magic.More magictbpaste sentimentRun sentiment analysis. This is the default behavior (same as runningtbpaste). The sentiment score is within the range [-1.0, 1.0]. The subjectivity score is within the range [0.0, 1.0].tbpaste chunksExtract noun phrases.tbpaste--sentences=tProcess each sentence in the copied text. This is the default behavior. Set--sentences=fto suppress tokenization.tbpaste langDetect language.Language code reference.tbpaste lang--fromen--tofrTranslate between languages. If--fromis omitted, tbpaste will try to detect the source language.Language code reference.tbpaste tagOutput part-of-speech tags for each word in the copied text.FeaturesSentiment analysisNoun phrase extractionTranslationPart-of-speech taggingColored outputCross-platformGet it now$ pip install -U tbpaste
$ curl https://raw.github.com/sloria/TextBlob/master/download_corpora.py | pythonYou should now be able to run thetbpastecommand.RequirementsPython >= 2.7 or >= 3.3LicenseMIT Licensed.
Package: tb-rest-client
# ThingsBoard Python REST API clientThe ThingsBoard REST API Client helps you interact with [ThingsBoard REST API](https://thingsboard.io/docs/reference/rest-api/) from your Python script.
With [Python Rest Client](https://thingsboard.io/docs/reference/python-rest-client/) you can programmatically create assets, devices, customers, users and other entities and their relations in ThingsBoard.The recommended method for installing the Rest Client is a pip.The Python version of the REST API client is under developing. If you have discovered any bug, please write us using email or by opening the issue.##### InstallationIn order to install the ThingsBoard REST client, you should use the following command:`bash pip3 installtb-rest-client`##### ExamplesYou can find the examples of the usage in the “examples” folder or on the [our website](https://thingsboard.io/docs/reference/python-rest-client/).Note:There are 2 REST clients for ThingsBoard, they are depend on version of the ThingsBoard, you use.If you use the ThingsBoard Community Edition (ThingsBoard CE) - please use the following command to import the REST client into your script:from tb_rest_client.rest_client_ce import *The REST client class has name “RestClientCE”.If you use the ThingsBoard Professional Edition (ThingsBoard PE) - please use the following command to import the REST client into your script:from tb_rest_client.rest_client_pe import *The REST client class has name “RestClientPE”.If you use the wrong version of the REST client, it could work unexpectedly.## Support[Community chat](https://gitter.im/thingsboard/chat)[Q&A forum](https://groups.google.com/forum/#!forum/thingsboard)[Stackoverflow](http://stackoverflow.com/questions/tagged/thingsboard)Don’t forget to star the repository to show your ❤️ and support.## LicensesThis project is released under [Apache 2.0 License](./LICENSE).