Saravanan666/pypi-org huggingface dataset:
Package: dsxindexer
dsxindexer基于麦语言的量化指标公式编辑器框架,目前支持部分通达信公式，因为公式太多，所以慢慢完善中，有兴趣的朋友可以自己实现哦。安装pip install dsxindexer使用# 导入包importdsxindexer# 导入数据工具箱importdsxquant# 首先获取K线历史数据klines=dsxquant.get_klines("000001",dsxquant.market.SZ).datas()klines:list=klines.dataklines.reverse()# 创建指标处理器sp=dsxindexer.sindexer(klines)# 注册系统指标sp.register(dsxindexer.INDEXER.MACD)# 执行计算结果result=sp.execute()自定义指标公式importdsxindexerimportdsxquantclassABCD(dsxindexer.BaseSindexer):"""ABCD通过继承指标器基类自定义ABCD指标"""# 定义指标名称__typename__="ABCD"defformula(self):return"""long:MACD.LONG;金叉:CROSS(MACD.DIF,MACD.DEA);死叉:LONGCROSS(MACD.DIF,MACD.DEA,5) AND MACD.DIF<-0.1 ;Kjd:"KDJ.K";# 这里是注释A:CLOSE;#收盘价B:HIGH;#最高价C:A*B;{这里是注释符了}D:1000+(A+B*90/(60*C))/90*A-100000/C*100;E:IF(A>=B,IFF(B>C,D,A),C);买线:1000;卖线:456 * 买线;哈哈:!90;"""# 获取K线历史数据klines=dsxquant.get_klines("000001",dsxquant.market.SZ).datas()klines:list=klines.dataklines.reverse()dsxindexer.logger.info("开始处理....")# 指标处理器sp=dsxindexer.sindexer(klines)# 注册自定义指标sp.register(ABCD)# 执行计算结果result=sp.execute()# 取最后一个model=result[-1]dsxindexer.logger.info(model.DATE+"%s"%vars(model.ABCD))指标编写方式目前指标支持系统指标，自定义指标，自定义可分为两种方式：继承和工厂方式继承方式classMAn(dsxindexer.BaseSindexer):"""MAn"""# 定义指标名称__typename__="MAn"defformula(self):return"""MA5:MA(CLOSE,5);MA30:MA(CLOSE,30);MA60:MA(CLOSE,60);"""# 指标处理器sp=dsxindexer.sindexer(klines)sp.register(MAn)# 执行计算结果result=sp.execute()工厂方式# 指标处理器sp=dsxindexer.sindexer(klines)# 通过指标工厂自定义指标MA10=dsxindexer.factory.create("MA10","MA10:MA(CLOSE,10);")sp.register(MA10)# 执行计算结果result=sp.execute()使用系统指标目前支持大概几十个系统指标，后续不断完善中....常用系统指标# 系统默认指标classINDEXER:BOLL="BOLL"BRAR="BRAR"CCI="CCI"CDP="CDP"CR="CR"DMA="DMA"EMV="EMV"EXPMA="EXPMA"KDJ="KDJ"MACD="MACD"MIKE="MIKE"OBV="OBV"PSY="PSY"ROC="ROC"RSI="RSI"TRIX="TRIX"VR="VR"WR="WR"WVAD="WVAD"
Package: dsymForUUID
TheLLDB debuggerhasbuilt-in support for symbolication, and in
particular on Mac OS X, for symbolicating OS X and iOS crash logs.
Unfortunately, for some reason best known to Apple, in order to function, thelldb.macosx.crashlogmodule requires an external script to locatedSYMfiles from the UUIDs listed in the crash log.  Quite why there couldn’t be a
default implementation of this is beyond me.Anyway, this package really just contains a single script, nameddsymForUUID(the name that thecrashlogmodule expects).  The approach
taken by the script is to use Spotlight to locate thedSYMfile; if it
finds, rather than a singledSYM, an.xcarchive, it will scan thedSYMfiles in the archive to locate the correct one, and will also search
for the executable.The expectation here is that you will have Xcode archives of your releases,
in which case it should Just Work.To uselldb.macosx.crashlogafter installing this script, you can do the
following:(lldb) command script import lldb.macosx.crashlog
"crashlog" and "save_crashlog" command installed, use the "--help" option for detailed help
"malloc_info", "ptr_refs", "cstr_refs", and "objc_refs" commands have been installed, use the "--help" options on these commands for detailed help.
(lldb) crashlog /tmp/crash.logWhile I haven’t tested this, you may also be able to use thedsymForUUIDscript with the DebugSymbols framework (part of Mac OS X) by doing something
like:defaults write com.apple.DebugSymbols DBGShellCommands -string /usr/local/bin/dsymForUUIDSee theLLDB page about debug symbols on Mac OS Xfor more on this.
Package: dsync
this is one data synchor tool base on sqlalchemy.simple start:python -m dsync.synchor source_connstring target_connstringdata connstr is base on sqlalchemyexp:python -m dsync.synchor mysql://user:password@host:port/sourcedb mysql://user:password@host:port/targetdbpython -m dsync -t sync source_connstring target_connstringpython -m dsync -t sync config_filepython -m dsync -t diff source_connstring target_connstringpython -m dsync -t gene source_connstring target_connstring out_file
Package: dszoro
dszorodszoro is a comprehensive Python package that provides a wide range of algorithms and data structures to help you master the art of Data Structures and Algorithms (DSA). Whether you are a beginner exploring the fundamentals or an experienced developer aiming to optimize your code, dszoro has got you covered!FeaturesData Structures:dszoro offers a rich collection of data structures such as arrays, linked lists, stacks, queues, trees, heaps, graphs, and more. Each data structure is implemented with efficiency and ease of use in mind, allowing you to focus on solving problems rather than worrying about implementation details.Algorithms:Unlock the power of algorithms with dszoro. The package includes a variety of classic algorithms, including sorting algorithms (e.g., bubble sort, insertion sort, quicksort), searching algorithms (e.g., linear search, binary search), graph algorithms (e.g., breadth-first search, depth-first search), and much more. Whether you need to solve a specific problem or want to explore different algorithmic approaches, dszoro has the algorithms you need.Visualization:Visualizing data structures and algorithms can greatly enhance your understanding. dszoro provides intuitive visualization capabilities that enable you to see the inner workings of various data structures and algorithms. Dive deep into the process, step by step, and gain valuable insights into how things work under the hood.Code Snippets and Examples:The dszoro package comes with a plethora of code snippets and examples to help you grasp DSA concepts quickly. Each data structure and algorithm is accompanied by detailed explanations and code samples, allowing you to get started right away.InstallationTo install dszoro, simply use pip:pipinstalldszoroUsageHere's a quick example demonstrating how to use dszoro:importdszorodef_print_apx_tsp()Formoredetailedusageexamplesanddocumentation,pleaserefertothe[dszorodocumentation](https://dszoro-docs.com).## ContributingContributionsarewelcomeandappreciated!Ifyouwouldliketocontributetodszoro,pleasefollowtheguidelinesoutlinedin[CONTRIBUTING.md](./CONTRIBUTING.md).## LicenseThisprojectislicensedunderthe[MITLicense](./LICENSE).## AcknowledgementsWewouldliketoexpressourgratitudetothefollowingindividualsandprojectsfortheircontributionstodszoro:-[Name1](https://github.com/name1)-[Name2](https://github.com/name2)## ContactIfyouhaveanyquestions,suggestions,orfeedback,pleasedon't hesitate to reach out to us. You can contact us at [contact@dszoro.com](mailto:contact@dszoro.com) or visit our website [dszoro.com](https://dszoro.com).Happycodingwithdszoro!
Package: dt2-notify-to-people
Sentry DingTalk Notify PeopleSentry 集成钉钉机器人通知，并且通知人员。本插件是基于sentry-dingtalk-notify进行的二次开发，加上了自定义的需求。Requirmentssentry >= 21.5.1特性发送异常通知到钉钉支持钉钉机器人webhook设置关键字支持通知到具体的用户配置环境变量DINGTALK_WEBHOOK: Optional(string)DINGTALK_CUSTOM_KEYWORD: Optional(string)DINGTALK_PHONES: Optional(string)快速使用安装使用pip命令$pipinstalldt2-notify-to-people写入依赖文件onpremise-xxx/sentry/requirements.txt$echodt2-notify-to-people=>>requirements.txt钉钉机器人配置钉钉机器人并拿到对应的 webhook, 可以对机器人设置 关键词、签名、IP限制。配置Sentry安装项目下的requirements.txt，添加dt-notify-to-people==1.0.8；在 Sentry 面板 Settings > Integrations 中找到 DingTalk 并配置 webhook、关键词等信息，添加项目，创建告警规则；关于插件编写具体教程可以阅读这边文章《如何开发自己的Python库》；编写自己的插件代码；打包自己的插件代码：python setup.py sdist bdist_wheel上传自己的插件：twine upload --repository-url https://upload.pypi.org/legacy/ dist/*
Package: dt4test
Dt4testA library for distributed big data system testIntroduction ( main purpose )TestCase running environmentTestCase viewing and tuneAssistance libs of network, container and data generatorSupport monitor and warnning systemOffer period running taskSupport performance test plan and executionUnified test report generationBigdata components clientBigdata components startup and revokeInstallationpip install dt4testGet startedusedtcomman***********dt4test client***************
Log file:/data1/dollarkv4/test_dir/output/dt4test.log
Module Logger:可以通过传入log文件名，指定log文件，如果没有 ${PROJECT_DIR}环境变量，则放在 /tmp 目录下面
Module Network:网络服务的公共库
Module Base:基础的公共函数
Module JsonP:处理复杂json的类，主要是用于查询，基于jmespath：https://jmespath.org/tutorial.html
Module ConfigIni:INI 格式的配置文件的处理，get ，set ，if exists
Module CaseRunner:Run Test Caseimport modulesfromdt4testimportnetworkhost="yourshost.com:8081"payload={"bid":"110","model_name":"test_model"}path="/master/querybid"res=network.send_get_request(host,path,payload)assert(res.status_code==200)print(res.content)Get All Apisfromdt4testimportnetworknetwork.help()
Package: dt8601
dt8601 (short for “dates in ISO8601 logic”) provides useful functionality to work with gregorian
dates. This is my first open source project in Python, so please bear with me. The code is based
on a date library I wrote back in to 90s in another language and has proven to be very helpful
when you have to work with date arithmetic.Quick startdt8601provides two objects to work with dates. One allows for easy storages and calculations with
a date and the other provides functionality that is associated with a calendar year.Typical usage in most cases is as easy as this:#!/usr/bin/env python

import dt8601

ymd = dt8601.IsoDate(2013, 06, 25, 'DE')
year = dr8601.IsoYear(2013)

num_weeks = year.week_count  # number if weeks in 2013

print(ymd.day_of_year())   # day of year
print(ymd.day_of_week())   # get week day for 2013-06-25
print(ymd.week_of_year())  # get ISO calendar week for 2013-06-25You would like to get a list of all the start dates for every ISO calendar week in 2013?
As easy as:from dt8601 import IsoYear

yr = IsoYear(2013)

for the_week in yr.iso_weeks:
    print(the_week['start'])You can find more information in thedocsfolder (es gibt auch eine deutsche Doku dort!)Thanks also toThis module is a result of porting and reworking a Borland Delphi library that is now more than 20 years old
(yes, we had computers back then <g>). Many people inspired this library, helped and added code or explained things.Bernd Strehuber - Holiday calculations
Carley Phillips - Julian date calculations
Jeff Duntemann - Weekday calculations
Judson McClendon - Easter calculations
Martin Austermeier - Weekday calculations
Paul Schlyter - Easter calculation
Pit Biernath - Julian date calculations
Scott Bussinger - Julian date calculations
Markus Kuhn for his ISO8601 summaryAlso many thanks to the Wikipedia authors of the ISO8601 articles and last, but not least, the awesome group of
people onhttp://www.stackoverflow.com
Package: dta
dta (Dict to Attributes)dta is very small dict (or json) to attributes converter.It is only have 1 files and applied to every python versions.No need dependencies required so your repository size won't go to hell.FeaturesAbility to convert lame dict object to class attributes!Ability to convert those attributes back to dict!InstallationUse pip to installpackagepipinstalldtaOr Use github repository and build itpipinstallgit+https://github.com/dumb-stuff/dtaUsageImport dta.importdtaFor converting to attributes doimportdtaSomeCoolConvertedDictToAttributes=dta.Dict2Attr({"stuff":["balls","watch anime girls","OwO"]})SomeCoolConvertedDictToAttributes.stuff[1]For converting attributes back to dict for saving purpose doimportdtadta.Attr2Dict(SomeCoolConvertedDictToAttributes)
Package: dtactions
dtactionsdtactions is an OpenSource extension module for the speech recognition program Dragon.
It is meant to perform actions that are common to other packages like Dragonfly, Unimacro and Vocola.This document describes how to instlall dtactions for end users and for developers.StatusSucessfully upgraded to Python 3.Instructions for End UsersIf you would like to install dtactions for use, but not as a developer, here are the instructions:Install Python and Natlink and the packages you would like to use (Dragonfly, Caster, Unimacro, Vocola) as described in the Natlink repository README.Install dtactions
It will also pull any prerequisites from thePython Packaging Index.py -m pip install  dtactionsThis will install the packages in your Python site-packages area. It will also add the following commands, which should be
in your path now in your commmand prompt:Instructions for DevelopersIf you are working on dtactions the most convenient setup is aneditable install.  Your local git repository can be anywhere convenient.Uninstall the packages you wish to develop. i.e pip if you want to work on dtactions:py -m pip uninstall dtactionsand answer yes to all the questions about removing files from your python scripts folder.Runpy -m pip install -e .from the dtactions project root.Unit testingRun pytest to run the tests, written in a combinatin ofunittestandpytest.  IF adding a test, pytest seems to be a lot more convenient and powerful.Most tests go in test;  tests that require a natlink install go in natlink_test as not every package dependent on natlink.You can runpy -m pip install dtactions[test]orpy -m pip install dtactions[natlink_test]if you don't have the prequisites like pytest.You can run pytest from project root folder to run the tests that don't depend on natlink being installed.  For the natlink-dependent tests, runpy -m pytest natlink_test.Notes About Packaging for DevelopersThe package is specified inpyproject.tomland built withflit.py -m flit build(or justflit build) builds the package.  A github action publishes to  publishes toPython Packaging Index.Version numbers of the packages must be increased before your publish toPython Packaging Index.
Package: dtadmin
DTAdmin 爬虫与数据可视化管理系统DTAdmin 官网https://www.05dt.com功能介绍DTAdmin - 基于Flask框架的爬虫与数据可视化管理系统。开发技术栈Python3.8+venv+Flask+MongoDB+SqlAlchemy+Redis+marshmallow部署技术栈Python3.8+venv+nginx+gunicorn开发相关1、激活虚拟环境source ./venv/bin/activate2、生成requirements.txt文件命令(venv) ➜ pip3 freeze > requirements.txt3、还原虚拟环境中的依赖(venv) ➜ pip3 install -r requirements.txt4、
Package: dtags
Dtags: Directory Tags for Lazy ProgrammersDtagsis a command-line tool that lets you tag directories for
faster filesystem navigation and command execution.RequirementsRecent versions of Bash, Zsh or FishPython 3.6+InstallationInstall viapip:pipinstalldtagsFor Bash, add the following line in~/.bashrc:source<(dtags-activate)For Zsh, add the following line in~/.zshrc:autoload-U+Xcompinit&&compinit
autoload-U+Xbashcompinit&&bashcompinitsource<(dtags-activate)For Fish, add the following line in~/.config/fish/config.fish:dtags-activatefish|sourceForGit Bash on Windows, add the following lines
in~/.bashrc:exportDTAGS_GIT_BASH=1source<(dtags-activate)Restart your shell. The following commands will be available after:tag--help
untag--help
tags--help
d--help
run--helpTab-completion should work out-of-the-box.UsageTag directories withtag:# Tag directory ~/foo with "work" (tags are indicated with the "@" prefix)$tag~/foo-twork
/home/user/foo+@work# If tag names are not specified, directory basenames are used instead$tag~/foo
/home/user/foo+@foo# Tag directories ~/bar and ~/baz with "app" and "work" (many-to-many)$tag~/bar~/baz-tappwork
/home/user/bar+@app+@work
/home/user/baz+@app+@workExecute commands in one or more directories withrun:# Run "git status" in all directories tagged "work"$runwork-cgitstatus# Run "git status" in directories ~/foo and ~/bar$run~/foo~/bar-cgitstatus# Mix tags and directory paths$runwork~/foo-cgitstatusChange directories by path or tag withd:# Go to directory tagged "work"# If there are multiple directories, a selection prompt is displayed$dwork# Go to directory ~/foo (works just like cd)$d~/foo# Use -t/--tag to always assume the argument is a tag$d-tfooUntag directories withuntag:# Remove tags "app" and "work" from directory ~/foo and ~/bar$untag~/foo~/bar-tappwork# Remove all tags from directory ~/foo$untag~/foo# Remove tag "app" from all directories$untag-tappManage tags withtags:# List all tags$tags# List all tags in JSON format$tags--json# Clean invalid directories$tags--clean# Remove all tags$tags--purgeUse--helpto see more information on each command.Technical NotesTags are saved in~/.dtagsdirectory (created when a dtags command is first run).The files in~/.dtagsare not meant to be edited manually.By default, directory paths take precedence over tags when name collisions occur.Tag names are automatically slugified (e.g. "foo bar" to "foo-bar").Tag names are displayed with the "@" character prefix for easy identification.Directory paths and tag names are ordered alphabetically.UninstallationRun the following commands to completely uninstall dtags:$pipuninstalldtags
$rm-rf~/.dtagsThen remove thedtags-activateline from your shell runtime configuration.
Package: dtamg-py
dtamg-py :bookmark_tabs:Sobre este repositório :open_book:Orientações geraisInstalação dePython 3.Setup da máquinaPasta para execução dos comandos e ativação de ambiente pythonNecessário instalação dePython 3antes da execução os comandos abaixo para ambos os sistemas operacionais.Sistema operacional Linux:# Criação ambiente python
$ python3 -m venv venv

# Ativação ambiente python
$ source venv/bin/activateSistema operacional Windows:Recomendo a utilização de Git Bash disponível com instalação deGit para Windows.# Criação ambiente python
$ python -m venv venv

# Ativação ambiente python
$ source venv/Scripts/activateInstalaçãoOdtamg-pyestá disponível no Python Package Index -PyPIe pode ser instalado utilizando-se o comando abaixo:# Antes de executar o comando abaixo lembre-se que ambiente Python deverá estar ativo$pipinstalldtamg-pyAtualizar versãoConforme relatado noissue 6, atualização de versões noPypideve seguirestes os passosControle de alteraçõesDocumentação das principais alterações sofridas por este repositório. Baseado na filosofiaMantenha um Changelog.[0.1.6] - 2022-03-25Melhora função para converter arquivos. Conversão apenas de arquivos xlsx da pasta "upload" para pasta dataCria função para comparação entre paths dos recursos presentes no datapackage.json e na pasta data[0.1.5] - 2022-03-22Inclui função para converter arquivos xls ou xlsx da pasta data/raw em arquivos .csv na raiz da pasta data[0.1.4] - 2022-03-07Insere lógica deretrypara conexões perdidas com o banco de dados (#16)Geração de mensanges de log com pacote logging (#15)[0.1.3] - 2022-01-31Inclui função extract[0.1.2] - 2021-12-21Especifica versões de dependências com >=Merge branch dev[0.1.1] - 2021-12-21Acrescenta função de validação e remoção colunas sqa e sqe[0.1.0] - 2021-12-15Otimiza função extract_resource[0.0.900] - 2021-12-13Criação do pacoteMigração projeto etl-make -https://github.com/dados-mg/etl-make
Package: dtargs
Introductiondtargs is a small module that makes accepting date/time arguments with Argparse easier.ExamplesA date argumentimport argparse
import dtargs

parser = argparse.ArgumentParser()
parser.add_argument('start', type=dtargs.DateType()) # defaults to %Y-%m-%d
parser.add_argument('end', type=dtargs.DateType('%d/%m/%Y'))A date/time argumentimport argparse
import dtargs

parser = argparse.ArgumentParser()
parser.add_argument('start', type=dtargs.DateTimeType()) # defaults to %Y-%m-%dT%H:%M:%SZ
parser.add_argument('end', type=dtargs.DateTimeType('%H:%M:%S_%Y-%m-%d', tz=None)TimezonesThe DateTimeType accepts a tz parameter, which is handled thuslyimport dtargs

dtargs.DateTimeType()('2015-01-02T12:34:56Z')
>>> datetime.datetime(2015, 1, 2, 12, 34, 56, tzinfo=<UTC>)

dtargs.DateTimeType(tz=None)('2015-01-02T12:34:56Z')
>> datetime.datetime(2015, 1, 2, 12, 34, 56, tzinfo=None)

dtargs.DateTimeType('%Y-%m-%dT%H:%M:%S%z', tz=None)('2015-01-02T12:34:56+0100')
>> datetime.datetime(2015, 1, 2, 12, 34, 56, tzinfo=datetime.timezone(datetime.timedelta(0, 3600))

dtargs.DateTimeType('%Y-%m-%dT%H:%M:%S%z', tz=pytz.utc)('2015-01-02T12:34:56+0500')
>> datetime.datetime(2015, 1, 2, 7, 34, 56, tzinfo=<UTC>)TestingInstall dependencies$ pip install -r dev-requirements.txtTo run tests$ py.test
Package: dtc
DTC :”Generate Dataclasses without writting them !”WarningThis is an alpha versionBasic Usage>>>importdtc>>>JSON=b"""{"flooat": 12.564, "boolean": true, "integer": 12}""">>>my_class=dtc.from_json(JSON)>>>my_classBase(flooat=12.564,boolean=True,integer=12)>>>fromdataclassesimport*>>>is_dataclass(my_class)True>>>JSON=b"""[{"flooat": 12.4, "boolean": true, "integer": 1}, {"flooat": 12.564, "boolean": true, "integer": 12},{"flooat": 1.4, "boolean": false, "integer": 0}]""">>>dtc.from_json(JSON[Base(flooat=12.4,boolean=True,integer=1),Base(flooat=12.564,boolean=True,integer=12),Base(flooat=1.4,boolean=False,integer=0)]License : GNU General Public License v3 or later (GPLv3+)Source:https://github.com/jgirardet/dtc
Package: dtcc
DTCCDTCC is a meta package for DTCC Platform. It imports all other DTCC
packages and provides a common interface to DTCC Platform.This package is also used to host common documentation and issues.This project is part theDigital Twin Platform (DTCC Platform)developed at theDigital Twin Cities Centresupported by Sweden’s Innovation Agency Vinnova under Grant No. 2019-421 00041.DocumentationThis project is documented as part of theDTCC Platform Documentation.Authors (in order of appearance)Anders LoggVasilis NaserentinDag WästerbergLicenseThis project is licensed under theMIT license.Copyright is held by the individual authors as listed at the top of
each source file.Community guidelinesComments, contributions, and questions are welcome. Please engage with
us through Issues, Pull Requests, and Discussions on our GitHub page.
Package: dtcc-builder
DTCC BuilderDTCC Builder provides functionality for building city models for DTCC Platform.This project is part theDigital Twin Platform (DTCC Platform)developed at theDigital Twin Cities Centresupported by Sweden’s Innovation Agency Vinnova under Grant No. 2019-421 00041.DocumentationThis project is documented as part of theDTCC Platform Documentation.Authors (in order of appearance)Anders LoggVasilis NaserentinDag WästerbergOrfeas EleutheriouAnton OlssonAnton AnnlövGeorge SpaiasPart of this code is contributed by ReSpace AB under the MIT License.LicenseThis project is licensed under theMIT license.Copyright is held by the individual authors as listed at the top of
each source file.Community guidelinesComments, contributions, and questions are welcome. Please engage with
us through Issues, Pull Requests, and Discussions on our GitHub page.Citing
Package: dtcc-common
DTCC CommonDTCC Common provides common utilities for DTCC Platform.This project is part theDigital Twin Platform (DTCC Platform)developed at theDigital Twin Cities Centresupported by Sweden’s Innovation Agency Vinnova under Grant No. 2019-421 00041.DocumentationThis project is documented as part of theDTCC Platform Documentation.Authors (in order of appearance)Anders LoggLicenseThis project is licensed under theMIT license.Copyright is held by the individual authors as listed at the top of
each source file.Community guidelinesComments, contributions, and questions are welcome. Please engage with
us through Issues, Pull Requests, and Discussions on our GitHub page.
Package: dtcc-data
DTCC DataDTCC Data provides the database and data API for DTCC Platform.This project is part theDigital Twin Platform (DTCC Platform)developed at theDigital Twin Cities Centresupported by Sweden’s Innovation Agency Vinnova under Grant No. 2019-421 00041.DocumentationThis project is documented as part of theDTCC Platform Documentation.Authors (in order of appearance)Dag WästerbergAnders LoggVasilis NaserentinLicenseThis project is licensed under theMIT license.Copyright is held by the individual authors as listed at the top of
each source file.Community guidelinesComments, contributions, and questions are welcome. Please engage with
us through Issues, Pull Requests, and Discussions on our GitHub page.
Package: dtcc-io
DTCC IODTCC IO provides input/output (IO) for DTCC Platform.This project is part theDigital Twin Platform (DTCC Platform)developed at theDigital Twin Cities Centresupported by Sweden’s Innovation Agency Vinnova under Grant No. 2019-421 00041.DocumentationThis project is documented as part of theDTCC Platform Documentation.Authors (in order of appearance)Dag WästerbergAnders LoggVasilis NaserentinLicenseThis project is licensed under theMIT license.Copyright is held by the individual authors as listed at the top of
each source file.Community guidelinesComments, contributions, and questions are welcome. Please engage with
us through Issues, Pull Requests, and Discussions on our GitHub page.