Saravanan666/pypi-org huggingface dataset:
Package: tds2stac
TDS2STACSTAC specification is a method of exposing spatial and temporal data collections in a standardized manner. Specifically, theSpatioTemporal Asset Catalog (STAC)specification describes and catalogs spatiotemporal assets using a common structure.
This package creates STAC metadata by harvesting dataset details from theThreddsdata server.InstallationInstall this package in a dedicated python environment viapython-mvenvvenvsourcevenv/bin/activate
pipinstalltds2stacTo use this in a development setup, clone thesource codefrom
gitlab, start the development server and make your changes::gitclonehttps://codebase.helmholtz.cloud/cat4kit/ds2stac/tds2staccdtds2stac
python-mvenvvenvsourcevenv/bin/activate
makedev-installMore detailed installation instructions might be found in thedocs.Technical noteThis package has been generated from the templatehttps://codebase.helmholtz.cloud/hcdc/software-templates/python-package-template.git.See the template repository for instructions on how to update the skeleton for
this package.License informationCopyright © 2023 Karlsruher Institut für TechnologieCode files in this repository are licensed under the
EUPL-1.2, if not stated otherwise
in the file.Documentation files in this repository are licensed under CC-BY-4.0, if not stated otherwise in the file.Supplementary and configuration files in this repository are licensed
under CC0-1.0, if not stated otherwise
in the file.Please check the header of the individual files for more detailed
information.License managementLicense management is handled withreuse.
If you have any questions on this, please have a look into thecontributing guideor contact the maintainers oftds2stac.
Package: tds-django
SQL Server backend for Django >=3.2django 4django 3.2 (pypi package version 0.1)tested and used with SQL Server 2017 and for version 4.2 with python 3.11 onlyWarningThere is an official package supported by microsoft, microsoft/mssql-django.This package does not need pyodbc nor the microsoft odbc driver, only pytds.This passes about 15000 tests from the django test suite, but I personally use the django ORM in a basic way and
don't use most of the features.Requirementspython-tdsoptional:bitarray, recommended by python-tds for performancefor regex support you need to compileclr/django_clr.csand install the resulting assembly or read and then run
thetds_django/sql/clr.sqlscript.for date "math" as well as bit-shift operations you need to read and run thetds_django/sql/init.sqlscript.UnsupportedJSONforeign keys to a nullable field (limitation of SQL Server)feel free to readtds_django/features.pyfor more details.queryset iterator with chunk sizeWarning If you have used another backend beforethis one usesuniqueidentifierfield for UUIDField while others may have used nvarchar.InstallationFor django 4.2pip install bitarray python-tds tds_django~=4.2For django 4.1pip install bitarray python-tds tds_django==4.1.0For django 4.0pip install bitarray python-tds tds_django==4.0.0For django 3.2pip install bitarray python-tds tds_django==0.1settings.DATABASESDATABASES={'default':{'ENGINE':'tds_django','HOST':'localhost','PORT':'1433','NAME':'<db_name>','USER':'<db_user>','PASSWORD':'<db_password>',},}
Package: tdseird
Time-dependent-SEIRD-ModelInstallation$[sudo]pip3installtdseirdDevelopment Installation$gitclonehttps://github.com/Taarak9/Time-dependent-SEIRD-ModelUsage>>>fromtdseirdimportSEIRDA Time-Dependent SEIRD Model for Forecasting the COVID-19 Transmission DynamicsTaarak Rapolu, Brahmani Nutakki, T. Sobha Rani, S. Durga Bhavanidoi:https://doi.org/10.1101/2020.05.29.20113571
Package: td-sequential-calculator
TD Sequential CalculatorA library to calculating td sequental.Installpip3 install td-sequential-calculatorUsingIn another scriptfromtd_sequential_calculatorimportTDSforiinrange(13):buy_setup,sell_setup,buy,sell=TDS.price_update(i)print(f"Buy setup:{buy_setup}")print(f"Sell setup:{sell_setup}")ifbuy:print("BUY")elifsell:print("SELL")
Package: tdsql
Test Driven SQLTdsql is a minimum test flamework for sql.
You can replace any part of sql and check if the result is as expected.
You can define test cases as yaml file.InstallCurrently, only bigquery is supported.pipinstall'tdsql[bigquery]'AuthenticationRun either of these commands.gcloudauthapplication-defaultlogin# If you want to use service account# export GOOGLE_APPLICATION_CREDENTIALS=/path/to/keyfile.jsonQuick startSave these files in your working directory.# ./tdsql.yamldatabase:bigquerytests:-filepath:./hello-world.sqlreplace:data:|SELECT * FROM UNNEST([STRUCT('2020-01-01' AS dt, 100 AS id),STRUCT('2020-01-01', 100),STRUCT('2020-01-01', 200)])master:|FROM (SELECT 100 AS id, 1 AS category)expected:|SELECT * FROM UNNEST([STRUCT('2020-01-01' AS dt, 1 AS category, 2 AS cnt),STRUCT('2020-01-01', NULL, 1)])-- ./hello-world.sqlWITHdataAS(-- tdsql-start: dataSELECTdt,idFROM`data_table`-- tdsql-end: data),masterAS(SELECTid,categoryFROM`master_table`-- tdsql-line: master)SELECTdt,category,COUNT(*)AScntFROMdataINNERJOINmasterUSING(id)GROUPBY1,2Then, run this command.
You'll see an error message.tdsqlFixhello-world.sqland runtdsqlagain,
you won't see any error message this time.- FROM data INNER JOIN master USING(id)+ FROM data LEFT JOIN master USING(id)Quite simple, isn't it?ExamplesHeavily documented sample codes arehere.FeedbackIf you find any bugs, please feel free to create an issue.
Package: tdsr
CitationsDahm, Torsten; Hainzl, Sebastian; Dahm, Roman Albert (2022): Time-dependent stress response seismicity models (TDSR). GFZ Data Services.https://doi.org/10.5880/GFZ.2.1.2022.002Dahm, Torsten and hainzl, Sebastian (2022): A Coulomb Stress response model for time-dependent earthquake forecasts. Journal of Geophysical Research, Solid Earth,http://doi.org/10.1029/2022JB024443tdsrTime dependent stress response seismicity model.A modified effective Coulomb failure model, that calculates earthquake rate as a function of stress loading and model parameter$pipinstalltdsrUsageUsage instructions t.b.a.importtdsrDevelopmentIf you want to contribute totdsr, we highly recommend setting up a virtual environment for local development. You can easily do so withpipenv, which can be installed withpip install--userpipenv(instructions) by following the steps below. Note that all commands should be run in the top level directory of the clonedtdsrrepository.$gitclonehttps://github.com/torstendahm/tdsr.git$cdtdsr$pipenvinstall--devWith the virtual environment set up, activate it withpipenv shell. To exit the virtual environment, runexit.TestingTests are located in the/testsdirectory. To add a new test, add a file with a function name starting withtest. To run the full test suite, run:$invoketest$pytest# can also directly run pytest with custom optionsThis will run tests serially and fail on the first error, which is preferred for local debugging.
However, this behaviour can also be changed withinvoke test--[no-]fail-fast--parallel.Code styletdsrprovides automatic code formatting and checks code for conformance.$invokeformat# format python files$invokelint# lint python files$invoketype-check# check for mypy typing errors$invokepre-commit# run all of above checksTo pass CI, ensure thatinvokepre-commitpasses all checks.DocumentationSphinxis used to build the documentation website, which uses reStructuredText (rst).
Seethis websitefor examples of how to use rst.To build and preview the documentation locally, you can use$invokedocsThis will start a local webserver and open the documentation in the browser for you.
If this is not needed, use the--no-serveflag.ReleasesNote:This is only relevant for maintainers.Given a clean working tree on the master branch, a release of a new version oftdsrtopypican be triggered by creating and pushing a new git tag.The github action CICD pipeline will test, package, and publish the new version automatically.
Before attempting a new release, please make sure all code checks pass.We use semantic version strings of the form{major}.{minor}.{patch}.
Depending on the type of release, choose the part of the version to be incremented in the command below.$bump2versionpatch$gitpush--follow-tagsRemember to activate the virtual environment as previously outlined ifbump2versionis not found.
Package: tdstyles
Using this python Package you can easily Include some custom CSS to style your Notebook.
Also few functions to create Descriptives plots.Change Log0.0.1 (20-04-2021)First Release0.0.2 (22-04-2021)Fixed issue with the urllib.request0.0.3 (24-04-2021)Adding CSS and Palette Code. Vertical and Horizontal Descriptive Plot.0.0.4 (25-04-2021)Fixed Importing issue. Refactored CSS Code.0.0.5 (25-04-2021)Added New Themes ‘Dark Matter’, ‘Genus Lavendula’ and ‘Gray Area’.0.0.6 (25-04-2021)Now the easy_plot functions return figure object along with axes.0.0.7 (10-07-2021)Added dynamic_colors theme for better control over the colors.0.0.8 (24-07-2021)Adding Style and Creating Plots are more flexible now.
Package: tdsxtract
![GitHub last commit (branch)](https://img.shields.io/github/last-commit/tdsxtract/tdsxtract/main?style=for-the-badge)
![GitHub Workflow Status](https://img.shields.io/github/workflow/status/tdsxtract/tdsxtract/test?label=tests&style=for-the-badge)
![GitHub Workflow Status](https://img.shields.io/github/workflow/status/tdsxtract/tdsxtract/docs_pages_workflow?label=doc&style=for-the-badge)
![PyPI](https://img.shields.io/pypi/v/tdsxtract?color=b5514c&logo=python&logoColor=white&style=for-the-badge)
![PyPI - Downloads](https://img.shields.io/pypi/dm/tdsxtract?style=for-the-badge)# tdsxtractTools for extracting permittivity values from Terahertz Time Domain Spectroscopy
measurements.See the documentation at [tdsxtract.github.io/tdsxtract](https://tdsxtract.github.io/tdsxtract/).
Package: tdt
tdtTucker-Davis Technologies (TDT) Python APIs for reading data into Python and interacting with Synapse softwareUsageimporttdt# download example data from https://www.tdt.com/files/examples/TDTExampleData.ziptdt.download_demo_data()# import data block into Python structuredata=tdt.read_block('data/Algernon-180308-130351')print(data)print(data.streams)print(data.epocs)SeeSynapseAPI Manual PDFfor full SynapseAPI usage# connect to Synapse through SynapseAPIimporttdtsyn=tdt.SynapseAPI()print(syn.getModeStr())print(syn.getGizmoNames())syn.setParameterValue('gizmo','parameter',new_value)
Package: tdtypes
tdtypestdtypesis a Python library provides an abstraction layer for Teradata Database objects and utilities. By default It usesteradatasql, but generally, it should be possible to use anyDB APIcompliant library.NOTES:This started as a personal project, but it is being made available as an open-source library in the hope that someone else might find it useful. This library does not come with any kind of warranty.Python2series is no longer supported.Although no longer the default, but olderteradataandpyodbcmodules can still be used.This library is not endorsed byTeradata Inc.InstallationUse Python'spiputility to installtdtypes.$ python -m pip install -U tdtypesCustomizationsIt is possible to customize howtdtypeslibrary obtains a raw database connection. This might be helpful, for example, to use DB API modules other thanteradatasql, or get authentication information in ways other than the default implementation. This can be done by creatingtdconn_site.pymodule and place it in yourPYTHONPATH. Please consulttdconn_default.pymodule for guidance on creating your own custom module.The default implementation allows applications to either pass connection information as a parameter or get connection information fromTDCONNenvironment variable at run-time. Either way, connection information consists of a validJSONstring as expected byteradatasqlmodule.Another customization allows howtdtypeslibrary searches for and obtains Table and View XML definitions. The default implementation usesDBC.TablesVfor searching, andSHOW ... IN XMLSQL statement to get XML definition.  Placingtdfinder_site.pyinPYTHONPATHwill override the default search and instantiation behaviors. To create a customtdfinder_site.pymodule, please consulttdfinder_default.py.SupportReport bugs usingissue tracker. I'll try to provide a fix as soon as I can. If you have already developed a fix, send me a pull request.ContributionsFeel free to fork this repository and enhance it in any way you see fit. If you think your changes will benefit more people, send me a pull request.
Package: tdu
# Thruster Design Utility
[![Documentation Status](https://readthedocs.org/projects/thrusterdesign/badge/?version=latest)](http://thrusterdesign.readthedocs.io/en/latest/?badge=latest)
[![Build status](https://img.shields.io/travis/runphilrun/ThrusterDesign.svg?style=flat-square)](https://travis-ci.org/runphilrun/TDU)
[![GitHub issues](https://img.shields.io/github/issues/runphilrun/TDU.svg)](https://github.com/runphilrun/TDU/issues)
[![PyPI](https://img.shields.io/pypi/v/thrusted.svg?style=flat-square)](https://pypi.python.org/pypi/thrusted)
[![GitHub stars](https://img.shields.io/github/stars/runphilrun/TDU.svg)](https://github.com/runphilrun/TDU/stargazers)
[![GitHub forks](https://img.shields.io/github/forks/runphilrun/TDU.svg)](https://github.com/runphilrun/TDU/network)
[![GitHub license](https://img.shields.io/badge/license-Apache%202-blue.svg)](https://raw.githubusercontent.com/runphilrun/TDU/master/LICENSE.md)> Tool to aid in design of small monopropellant thrusters.[View this project on STEMN](http://stemn.com/projects/thruster-design-tool)## Abstract
The thruster’s nozzle, propellant, and chamber conditions each have a huge impact on performance. The fluid mechanics that model engine effectiveness are pretty complicated, unfortunately. The purpose of this script is to make it easy to see how tweaks in nozzle geometry, propellants, and chamber conditions affect performance in order to find the optimal design solution.## Features
* Simulate the performance of a thruster in space for a given set of parameters and output performance metrics.
* Output simulation data in a useful manner.
* Allow the user to easily tweak parameters.## Usage`bash $ pip install tdu $ tdu--help`RunThrusterDesign.pyand input parameters when prompted.## About & Documentation
Please refer to the [Project Wiki](https://github.com/runphilrun/ThrusterDesign/wiki) for details on the code structure, more information about the project, and general theory.>If you encounter any bugs, please report them in the [Issue Tracker](https://github.com/runphilrun/ThrusterDesign/issues)!
Package: tdub
tdubtdubis a Python project for handling some downstsream steps in the
ATLAS Run 2tWinclusive cross section analysis. The project provides
a simple command line interface for performing standard analysis tasks
including:BDT feature selection and hyperparameter optimization.Training BDT models on our Monte Carlo.Applying trained BDT models to our data and Monte Carlo.Generating plots from various raw sources (our ROOT files and
Classifier training output).Generating plots from the output ofTRExFitter.For potentially finer-grained tasks the API is fully documented. The
API mainly provides quick and easy access to pythonic representations
(i.e. dataframes or NumPy arrays) of our datasets (which of course
originate fromROOTfiles), modularized ML
tasks, and a set of utilities tailored for interacting with our
specific datasets.
Package: tdvrptw-snrpga2
Implementation of the genetic algorithm SNRPGA2 for the Time-Dependent Vehicle Routing Problem with Time Windows (TDVRPTW), as proposed by:Nanda Kumar, Suresh & Panneerselvam, Ramasamy. (2017). Development of an Efficient Genetic Algorithm forthe Time Dependent Vehicle Routing Problem with Time Windows. American Journal of Operations Research. 07. 1-25. 10.4236/ajor.2017.71001.Usage instructions can be found here:https://github.com/yma17/tdvrptw-snrpga2
Package: td-watson
Watson is here to help you manage your time. You want to know how
much time you are spending on your projects? You want to generate a nice
report for your client? Watson is here for you.Wanna know what it looks like? Check this below.Nice isn’t it?Quick startInstallationOn OS X, the easiest way to installwatsonis usingHomebrew:$brewupdate&&brewinstallwatsonOn other platforms, installwatsonusing pip or pip3, depending on which one is available:$pipinstalltd-watsonor:$pip3installtd-watsonIf you need more details about installing watson, please refer to thedocumentation.UsageStart tracking your activity via:$watsonstartworld-domination+catsWith this command, you have started a newframefor theworld-dominationproject with thecatstag. That’s it.Now stop tracking you world domination plan via:$watsonstopProjectworld-domination[cats]started8minutesago(2016.01.2713:00:28+0100)You can log your latest working sessions (akaframes) thanks to thelogcommand:$watsonlogTuesday26January2016(8m32s)ffb2a4c13:00to13:0808m32sworld-domination[cats]Please note that, asthe report command, thelogcommand comes with projects, tags and dates filtering.To list all available commands, eitherread the documentationor use:$watsonhelpContributor Code of ConductIf you want to contribute to this project, please read the projectContributor Code of ConductLicenseWatson is released under the MIT License. See the bundled LICENSE file for
details.
Package: tdworkflow
Unofficial Treasure Workflow API client.InstallationpipinstalltdworkflowIf you want to use development version, run as follows:pipinstallgit+https://github.com/chezou/tdworkflow.gitUsageimportosfromtdworkflow.clientimportClientapikey=os.getenv("TD_API_KEY")client=Client(site="us",apikey=apikey)# Or, write endpoint explicitly# client = Client(endpoint="api-workflow.treasuredata.com", apikey=apikey)projects=client.projects("pandas-df")secrets={"td.apikey":apikey,"td.apiserver":"https://api.treasuredata.com","test":"secret-foo"}client.set_secrets(projects[0],secrets)client.secrets(projects[0])# ['td.apikey', 'td.apiserver', "test"]client.delete_secrets(projects[0],["test","td.apiserver"])Upload Project from GitHubBefore executing the example code, you have to install git-pythonpipinstallgitpythonClone example repository with git-python and upload a digdag project.importtempfileimportosimportshutilimporttdworkflowfromgitimportGit# Download example GitHub repositoorytempdir=tempfile.gettempdir()git_repo="https://github.com/treasure-data/treasure-boxes/"shutil.rmtree(os.path.join(tempdir,"treasure-boxes"))try:Git(tempdir).clone(git_repo)print("Clone repository succeeded")exceptException:print("Repository clone failed")raise# Upload specific Workflow projectapikey=os.getenv("TD_API_KEY")site="us"target_box=os.path.join("integration-box","python")target_path=os.path.join(tempdir,"treasure-boxes",target_box)client=tdworkflow.client.Client(site=site,apikey=apikey)project=client.create_project("my-project",target_path)If you want to open Treasure Workflow console on your browser, you can get the workflow URL as the following:CONSOLE_URL={"us":"https://console.treasuredata.com/app/workflows","eu01":"https://console.eu01.treasuredata.com/app/workflows","jp":"https://console.treasuredata.co.jp/app/workflows",}workflows=client.project_workflows(project)workflows=list(filter(lambdaw:w.name!="test",workflows))ifworkflows:print(f"Project created! Open{CONSOLE_URL[site]}/{workflows[0].id}/info on your browser and click 'New Run' button.")else:print("Project creation failed.")Start workflow sessionYou can start a workflow session by usingClient.start_attempt.attempt=client.start_attempt(workflows[0])# Wait attempt until finish. This may require few minutes.attempt=client.wait_attempt(attempt)Connect to open source digdagSince Treasure Workflow is hosted digdag, tdworkflow is compatible with open source digdag.NoteOpen source digdag API may be different with Treasure Workflow API so that tdworkflow might not work with some API of opensource digdag.Here is the example code to connect local digdag server.>>>importtdworkflow>>>importrequests>>>session=requests.Session()>>>client=tdworkflow.client.Client(...endpoint="localhost:65432",apikey="",_session=session,scheme="http")>>>client.projects()[Project(id=1,name='python-tdworkflow',revision='134fe2f9-ded3-4e7c-af8e-8a82d55d688b',archiveType='db',archiveMd5='5Lc6F6m3DtmBN4DA5MzK8A==',createdAt='2019-11-01T13:03:26Z',deletedAt=None,updatedAt='2019-11-01T13:03:26Z')]
Package: tdx
Incollections.pythere are some tools for working with lists,
sets, dicts, and iterables more declaratively.Indata.pythere are some functiions to more concisely read and
write yaml in the most common use cases.Inexceptions.pythere are some error handling tools. They are all
callback-oriented, so not necessarily user-friendly; mostly they are
intended for use indecorators.py.Indecorators.pythere are some general decorator tools, in particular
one to wrap a function in a debugger call on error and one to attach
context to exception messages. There’s also awraptifyfunction that
will convert decorators that usefunctools.wraps(and therefore
clobber a lot of metadata from the target) into decorators which preserve
metadata usingwrapt.decorator.Invalidation.pythere are some general validation checks that seem
to come in handy in lots of contexts. For example, making sure that a
dict has all of a set of required keys, and all other keys are part
of some optional set.
Package: tdx2csv
tdx2csvPython Boilerplate contains all the boilerplate you need to create a Python package.Free software: MIT licenseDocumentation:https://tdx2csv.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2021-09-04)First release on PyPI.