Saravanan666/pypi-org huggingface dataset:
Package: twilight-autocomplete
Twilight-AutocompleteTwilight-Autocomplete is a powerful Python library that provides intelligent autocomplete functionality for text-based applications. Whether you're working on a chatbot, text editor, or any other application that requires intelligent text completion, ## Twilight-Autocomplete has got you covered. Developed by Avneh S. Bhatia, this library leverages the power of NLP and machine learning techniques to predict the next word in a sentence based on a given context.Features*Efficient training of language models using the nltk library*Support for n-gram language models for accurate predictions*Simple and intuitive interface for easy integration into existing projects*Customizable n-gram size to adapt to different language patterns*Supports context-aware predictions for enhanced accuracyInstallationYou can install Twilight-Autocomplete usingpip:$ pip install twilight-autocompleteMake sure you have the nltk library installed as well:$ pip install nltkUsageUsing Twilight-Autocomplete is straightforward. Here's an example:from twilight_autocomplete import train_model, predict_next_word, auto_complete

#Train the model with an n-gram size of 3
n = 3
model = train_model(n)

#Example usage
input_sentence = "I want to "
next_word = auto_complete(input_sentence, model, n)
print(next_word)The above code demonstrates how to train a language model using the train_model function, and then use it to predict the next word in a sentence using the auto_complete function. The n parameter specifies the n-gram size, which determines the context used for prediction.ContributingWe welcome contributions from the open-source community to make Twilight-Autocomplete even better. If you have any bug reports, feature requests, or improvements, please submit them to the GitHub repository:https://github.com/RedMythic1/twilight-autocompleteWhen contributing, please follow the existing code style and include tests for any new features or bug fixes. We appreciate your help in making Twilight-Autocomplete an exceptional tool for text autocomplete.LicenseTwilight-Autocomplete is licensed under the MIT License. See the LICENSE file for more information.ContactFor any inquiries or feedback, feel free to reach out to Avneh S. Bhatia atavnehb@example.com.AcknowledgementsI would like to thank the nltk development team for their excellent work on the Natural Language Toolkit, which forms the foundation of Twilight-Autocomplete.
Package: twilio-fatisar
Python Twilio Helper Library----------------------------DESCRIPTIONThe Twilio REST SDK simplifies the process of making calls using the Twilio REST API.The Twilio REST API lets to you initiate outgoing calls, list previous calls,and much more.  See https://www.github.com/twilio/twilio-python for more information.LICENSE The Twilio Python Helper Library is distributed under the MITLicense
Package: twilio-messaging-sftp
# Messaging SFTP Helper Library
> Sending 1 million messages? Upload a file with your messages to our FTP server and Twilio will take care of the REST. Note: Library only tested with Python3.## InstallationTo install the package, invoke:`shell python3-mpip install--index-urlhttps://test.pypi.org/simple/twilio-messaging-sftp`This library provides a helper to send messages using CSV to many users at once.
You should import it to your project if you choose to.The csv file should contain ato,from,body, we also support mms usingmedia_url.
If you want any other fields in the csv we will return them with the results.
If your body needs a comma in it make sure that the text has“ “around it.Once the csv is parsed, useMessageClient(requires Twilio Account Sid and Authorization Token)
to send messages for each parsed query.
Package: twilio-python-async
Asynchronous Twilio ClientAn asynchronousTwilioclient⚠️ The officialTwilio Python Clientnow natively supports
asyncio so this project had been depreciated.InstallationUsing a virtual environment is recommended for installing this package. Once the virtual environment is created and activated install the package with:pipinstalltwilio-python-asyncUseageWhen creating a client the twilio account sid and token can either be read from aTWILIO_ACCOUNT_SIDandTWILIO_AUTH_TOKENvariables, or passed into the client at creation. Using environment variables
is recommended. Examples below will assume the use of environment variables.Send an SMS messageMessages can be sent by either using a Twilio messaging service sid, or by passing afrom_phone
number. The messaging service sid can be read from aTWILIO_MESSAGING_SERVICE_SIDenvironment
variable. The examples below assumes the use of the environment variable.fromtwilio_asyncimportAsyncClientasyncwithAsyncClient()asclient:awaitclient.message_create("My message","+12068675309")Retrieve message logsfromtwilio_asyncimportAsyncClientasyncwithAsyncClient()asclient:response=awaitclient.get_message_logs()ContributingContributions to this project are welcome. If you are interested in contributing please see ourcontributing guide
Package: twilio-sendsms
twilio-sendsmsA command-line tool for sending bulk SMS using Twilio.The utility lets you define a mustache template and provide a CSV file with matching columns for bulk SMS sends.InstallationThe utility requirespython3.7python -m pip install twilio_sendsmsSetupThe first time you run, you will be prompted to provide your Twilio account details.All configuration settings get stored in~/.twilio-sendsms.config. To reconfigure you can delete this file.RunningFirst, you need to define a mustache template and save to a file, e.g. example.mustache:Hi {{first_name}}, this is a test SMS.Next, you need to create a bulk send CSV file. The file must have amobile_numbercolumn. The mobile number must be in the international format, e.g. +614XXXXXXXX. The other column names need to match the variable names used in the mustache template.buld_send.csv"mobile_number","first_name"
"+614XXXXXXXX","Joe"To process the batch file:sendsms --template example.mustache test.csvTestingBefore processing a bulk CVS file, it's a good idea to sample some entries and send them to yourself first. Testing is useful to confirm the formatting and the number of segments are as expected.To sample and override the mobile_number in the CSV file:sendsms --template example.mustache --sample 1 --sendto +614XXXXXXXX test.csvThe command outputs destination mobile number, the Twilio message identifier and the SMS message sent.+614XXXXXXXX,SM8c6335fdcffe4bb88313a16fabc9234d,Hi Joe, this is a test SMS.
Package: twilioSMS
What's new in v1.0:BUILT IN TWILIO!!!!Runs HYPERfast!!!!What's new in v1.1.3:Repl functionality still in beta (https://SMS--johndo3.repl.co)Instructions:go tohttps://www.twilio.comand sign up, follow instructions, then get account sid, auth token, and twilio number and import them into run.py (the file where the code runs)credit goes to CleverProgrammer for creating the base code for this program, and to twilio Inc for providing me with the databasecode (file MUST be called run.py, you can use main.py on repl.it)import twilioSMS


# get these credentials by signing up for a twilio account at https://www.twilio.com
account_sid = "ACXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"  # insert your account SID here
auth_token = "your_auth_token"  # insert your authenication token here
my_cell = "cell number here"  # insert your phone number starting with +1
my_twilio = "twilio number here"  # insert your twilio number starting with +1


if __name__ == "__main__":
    twilioSMSor, in the terminal(BETA TESTING), type:python sms.pyyou whil have to type in everything in manually, though.
Package: twilio-thinQLCR
Twilio Wrapper Python Library For thinQ LCR integration=========================================================================**Note that you will need a valid LCR Account with thinQ before using the libraries. For more information please contact your thinQ Sales representative at http://www.thinq.com**----------------------------------------------------------------------------------------------------------------To use with version 6.X of Twilio's SDK, simply do:>>> from twilio_thinQLCR import TwilioWrapper>>> wrapper = TwilioWrapper(twilio_account_sid, twilio_auth_token, thinQ_id, thinQ_token)>>> # wrapper.call(to-number, from-number, twiML URL)>>> call = wrapper.call("12345678901", "18765432101", "http://example.com/twilio.xml")>>> print "Call sid: " + str(call.sid)
Package: twilio_thinQLCR_python
twilio-thinQLCR-python, Twilio Wrapper Python Library For thinQ LCR integration=========================================================================**Note that you will need a valid LCR Account with thinQ before using the libraries. For more information please contact your thinQ Sales representative at http://www.thinq.com/library/**----------------------------------------------------------------------------------------------------------------To use (with caution), simply do::>>> from twilio_thinQLCR_python import TwilioWrapper>>> wrapper = TwilioWrapper(twilio_account_sid, twilio_auth_token, thinQ_id, thinQ_token)>>> print "Call sid: " + str(wrapper.call("1234567890", "9876543210"))
Package: twilio-webhooks
twilio-webhooksA collection of webhooks forTwiliousingFlask.Installationpip install twilio-webhooksAvailible webhooks:SMSCommand- When receiving a properly formated SMS runs a user-defined callable.ReceiveFax- When receving a fax saves a pdf file to a user-defined path.SMSCommandWebhook URL format:http://example.com/smscommandYou set this under "Phone Numbers / Manage Numbers / Active Numbers". Click your desired phone number. Look under a section called "Messaging", and with the "CONFIGURE WITH" drop-down menu select "Webhooks, TwiML Bins, Functions, Studio or Proxy". Now under the "A MESSAGE COMES IN" drop-down menu select "Webhook" and in the adjacent box place your URL.Callback format:The callable should accept two arguments.A string containing who the SMS is from in E.164 format.A string that is either emtpy or the arg (see below) sent in the SMS.A return value will be sent as a reply.SMS Format:command[arg]command(required) is a case-insensitive string that was assigned to a user-defined callable.arg(optional) will be passed to the callable as the second argument.Deployment:Deploy this as you would any other Flask app. SeeDeployment Optionsfor more information.Example Code:importpsutilimportwakeonlanfromtwilio_webhooksimportSMSCommand# Simple exampledefcpu_usage(from_,arg):"""Check CPU usage"""returnf"CPU Usage:{psutil.cpu_percent()}%"# Complex exampledefwake_on_lan(from_,arg):"""Use wake-on-lan to wake a computer"""# make sure the number is mineiffrom_!="+12125551234":returncomputers={"office":"ff.ff.ff.ff.ff.f1","gaming":"ff.ff.ff.ff.ff.f2"}# Clean up arg in case I send a sloppy SMSarg=arg.strip().lower()ifargincomputers:wakeonlan.send_magic_packet(computers[arg])returnf'Computer "{arg}" is waking up.'sc=SMSCommand("your_twilio_auth_token")sc.assign("cpu",cpu_usage)sc.assign("wol",wake_on_lan)app=sc.wsgi()Now if you send an SMS to the twilio number you selected earlier that says this (remember the command part is case-insensitive):Cpuyou should get a reply like thisCPU Usage: 5.2%or this:Wol officeshould reply:Computer "office" is waking up.ReceiveFaxDeployment:Deploy this as you would any other Flask app. SeeDeployment Optionsfor more information.Example:fromtwilio_webhooksimportReceiveFaxapp=ReceiveFax("your_twilio_auth_token",'/path/to/save/pdf').wsgi()Incoming faxes will now be saved to the path of your choice.Notes:Your twilio auth token can be found under "Dashboard / Settings / General". You must click it to view it.
Package: twill
twill: a simple scripting language for web browsingtwill is a simple scripting language intended for programmatic or automated browsing of websites.The current version 3.2 supports Python 3.8 to 3.12.Take a look at thechangelogto find a list of all changes and improvements made since version 2. For a brief overview of twill's history starting from its early days, see theacknowledgements and historysection.The fulldocumentationis included in the distribution and provided online viaGitHubandReadTheDocs.Copyright (c) 2005-2023 by C. Titus Brown, Ben R. Taylor, Christoph Zwerschke et al.Newer versions have been created and are maintained byChristoph Zwerschke.twill is available for use, modification, and distribution under the MIT license.
Package: twillrecord
Twill script recorder* Functional testing of web projects, and thus regression testing as well.* Performance testing: by loading the web application and monitoringyour servers it helps you to pinpoint bottlenecks, giving a detailedreport of performance measurement.* Load testing tool to expose bugs that do not surface in cursory testing,like volume testing or longevity testing.* Stress testing tool to overwhelm the web application resources and testthe application recoverability.* Writing web agents by scripting any web repetitive task, like checking ifa site is alive.
Package: twilog-web-archiver
Save month list pages of twilog.org using archive.org.RequirementPython >= 3.9Installpipinstalltwilog-web-archiverUsagetwilog-web-archiverSCREEN_NAMEExample outputtwilog-web-archivernhk_prarchived(cached:True):https://web.archive.org/web/20230411042930/https://twilog.org/NHK_PR/month-2304archived(cached:True):https://web.archive.org/web/20230411051906/https://twilog.org/NHK_PR/month-2303archived(cached:False):https://web.archive.org/web/20230411051956/https://twilog.org/NHK_PR/month-2303/2archived(cached:False):https://web.archive.org/web/20230411052032/https://twilog.org/NHK_PR/month-2303/3...DescriptionWhen a user has registered twilog.org, you will see the month list page in the user archive page, i.e.https://twilog.org/NHK_PR/archives.This program saves every pages in this month list into Wayback Machine onarchive.org.LicenseGNU GPL 3.0 or later
Package: twimage
Twimage v0.1.2Twimage is a Python library that can scrap the trending section of Twitter for Hashtags and further to download images. It can be used as an image dataset generator for applying machine learning models for research.Getting StartedThese instructions will get you the project up and running on your local machine for scraping purposes.PrerequisitesTwimage uses Selenium for the headless browser functionality. It also uses Click for CLI purposes and Wget for downloading images.
Your system should haveMozilla Firefoxinstalled.pip3 install selenium click wget coloramaTo download theFirefox WebDriverfollow the steps.wget https://github.com/mozilla/geckodriver/releases/download/v0.27./geckodriver-v0.27.0-linux64.tar.gz
tar xvfz geckodriver-v0.19.1-linux64.tar.gz
mv geckodriver ~/.local/binInstallingInstall Twimage v0.1.2 by:pip install twimage==0.1.2Built WithSelenium- For headless browserClick- Command Line InteraceWget- Used to download imagesContributingPlease mailAnshul.6273@iitkgp.ac.infor contributing in the project.AuthorsAnshul Sharma-TheVoxiumLicenseThis project is licensed under the MIT License
Package: twinbooster
Python package for TwinBoosterSynergising Large Language Models with Barlow Twins and Gradient Boosting for Enhanced Molecular Property PredictionMaximilian G. Schuh, Davide Boldini, Stephan A. Sieber@ Chair of Organic Chemistry II,
TUM School of Natural Sciences,
Technical University of MunichAbstractThe success of drug discovery and development relies on the precise prediction of molecular activities and properties. While in silico molecular property prediction has shown remarkable potential, its use has been limited so far to assays for which large amounts of data are available. In this study, we use a fine-tuned large language model to integrate biological assays based on their textual information, coupled with Barlow Twins, a Siamese neural network using a novel self-supervised learning approach. This architecture uses both assay information and molecular fingerprints to extract the true molecular information. TwinBooster enables the prediction of properties of unseen bioassays and molecules by providing state-of-the-art zero-shot learning tasks. Remarkably, our artificial intelligence pipeline shows excellent performance on the FS-Mol benchmark. This breakthrough demonstrates the application of deep learning to critical property prediction tasks where data is typically scarce. By accelerating the early identification of active molecules in drug discovery and development, this method has the potential to help streamline the identification of novel therapeutics.InstallationInstall the package withpip install twinbooster.
Then you can download the pretrained models withtwinbooster.download_models().
For FS-Mol, you can download the data withtwinbooster.download_data().
All pretraining data can be downloaded withtwinbooster.download_pretraining_data().An example script can be found here./twinbooster/twinbooster_example.ipynb.CitationIf you use TwinBooster in your research, please cite our preprint:@misc{schuh2024twinbooster,
      title={TwinBooster: Synergising Large Language Models with Barlow Twins and Gradient Boosting for Enhanced Molecular Property Prediction}, 
      author={Maximilian G. Schuh and Davide Boldini and Stephan A. Sieber},
      year={2024},
      eprint={2401.04478},
      archivePrefix={arXiv},
      primaryClass={q-bio.BM}
}
Package: twin-client-sdk
twin client python-sdkinstallpip3 install TwinClientdemoconfig = TwinClientConfig(
owner = "dtos",
tenantId=tenantId,
dtmsregistry=dtmsregistry,
dtmstwindef=dtmstwindef,
dtmstwin=dtmstwin
)twin_client = TwinClient(config)查询 subtype
query = {
"subType.type": "people_drug"
}"-created"    按created降序"created"     按created升序
res = twin_client.twin.where(**query).offset(0).limit(10).sort("-created").select()
print(res)
Package: twindb_cloudflare
TwinDB CloudFlare LibraryTwinDB CloudFlare Library is a module to work with CloudFlare APIFree software: Apache Software License 2.0Documentation:https://twindb-cloudflare.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2016-07-17)First release on PyPI.
Package: twindb-infrastructure
TwinDB InfrastructureTwinDB Infrastructure is a collection of everything to manage TwinDB infrastructureFeaturestwindb-awsto manage Amazon EC2 instancestwindb-chefto provision a host with Cheftwindb-galerato bootstrap a Percona XtraDB clusterCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2016-07-17)First release on PyPI.
Package: twindb-table-compare
TwinDB Table CompareTwinDB Table Compare readspercona.``checksums`` from the master and slave
and shows what records are difference if there are any inconsistencies.Free software: Apache Software License 2.0Documentation:https://twindb-table-compare.readthedocs.io.Blogpost with usage examples:https://twindb.com/pt-table-checksum-show-differences/CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History3.0.2 (2020-09-13)Python 3 supportCommand line tool renamed to twindb-table-compare0.1.0 (2016-08-29)First release on PyPI.
Package: twine
twineTwine is a utility forpublishingPython packages onPyPI.It provides build system independent uploads of source and binarydistribution artifactsfor both new and existingprojects.See ourdocumentationfor a description of features, installation
and usage instructions, and links to additional resources.ContributingSee ourdeveloper documentationfor how to get started, an
architectural overview, and our future development plans.Code of ConductEveryone interacting in the Twine project’s codebases, issue
trackers, chat rooms, and mailing lists is expected to follow thePSF Code of Conduct.
Package: twined
twinedA library to help digital twins and data services talk to one another. Read more attwined.readthedocs.ioDeveloper notesDocumentation for use of the library ishere. You don't need to pay attention to the following unless you plan to develop Twined itself.ContributingPlease raise an issue on the board (or add your $0.02 to an existing issue) so the maintainers know
what's happening and can advise / steer you.Create a fork of twined, undertake your changes on a new branch, named likeissue-84or similar. To run tests and make commits,
you'll need to do something like:git clone <your_forked_repo_address>    # fetches the repo to your local machine
cd twined                               # move into the repo directory
pyenv virtualenv 3.6.9 twinedenv        # Makes a virtual environment for you to install the dev tools into. Use any python >= 3.6
pyend activate twinedenv                # Activates the virtual environment so you don't screw up other installations
pip install -r requirements-dev.txt     # Installs the testing and code formatting utilities
pre-commit install                      # Installs the pre-commit code formatting hooks in the git repo
tox                                     # Runs the tests with coverage. NB you can also just set up pycharm or vscode to run these.Adopt a Test Driven Development approach to implementing new features or fixing bugs.Ask thetwinedmaintainerswhereto make your pull request. We'll create a version branch, according to the
roadmap, into which you can make your PR. We'll help review the changes and improve the PR.Once checks have passed, test coverage of the new code is >=95%, documentation is updated and the Review is passed, we'll merge into the version branch.Once all the roadmapped features for that version are done, we'll release.Release processThe process for creating a new release is as follows:Check out a branch for your release, called egrelease/X.Y.ZCreate a Pull Request into themainbranch.Undertake your changes in other branches according to the git flow and create pull requests intorelease/X.Y.ZEnsure that documentation is updated to match changes, and increment the changelog.Pull requests which do not update documentation will be refused.Ensure that test coverage is sufficient.Pull requests that decrease test coverage will be refused.Ensure code meets style guidelines (pre-commit scripts and flake8 tests will fail otherwise)Address Review Comments on the PREnsure the version insetup.pyis correct and matches the branch version.Merge to main. Successful test, doc build, flake8 and a new version number will automatically create the release on pypi.Confirm the successful release on pypiGo to code > releases and create a new release on GitHub at the same SHA.
Package: twine-graph
Twine GraphTwine Graph is a Python package and command line tool for parsing passage and link structure
from published .html Twine stories and outputting the resulting graphs in visual (.pdf) or
structured (.json) formats. The goal of Twine Graph is to allow for research and analysis of
story structure in freely-available Twine games.PrerequisitesTwine Graph requires Python 3 and thebeautifulsoup4andgraphvizpackages. Tested primarily
on Mac OS X within an Anaconda environment.InstallationThe easiest way to install Twine Graph is throughpip:pip install twine-graphExample usageThe installed package can be called from the command line through its entry-point, as in the
following sample call (using the example .html file included in the github project):twine_graph twine_graph_example.htmlThe output .gv.pdf file can be opened for a visual representation of the passage and link structure
of the story, while the output .json file provides a structured representation:{
  "passages": [
    {
      "pid": 1,
      "name": "Hello",
      "text": "[[Hello->World]]",
      "links": [
        {
          "text": "Hello",
          "destination": {
            "name": "World",
            "pid": 2
          }
        }
      ]
    },
    {
      "pid": 2,
      "name": "World",
      "text": "Hello World",
      "links": []
    }
  ]
}Known IssuesDoesn't detect links produced by custom javascriptDoesn't detect links referenced through variables (i.e. variable tracking not supported)Related Worktwine-parser: A Javascript utility for parsing
twine stories into graph objects.TwineJson: A utility for Twine that exports a story
into JSON format.AuthorEnrique Henestroza AnguianoWebsite:DatalexicLicenseThis project is licensed under the GNU GPL License - seeLICENSEfor details