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Application Name | Developer | Made with | Rating | Last updated | Views | Installs |
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oex-vscode-snippets-exampleAn example of VS Code snippets publication through InterSystems Open Exchange and Package Manager using the oex-vscode-snippets-template framework | Docker IPM | 0.0 (0) | 29 Jun, 2023 | |||
workshop-integratedml-csvExample of IntegratedML predictions based on real data in CSV | Docker ML ML | 5.0 (1) | 27 Jun, 2023 | |||
InterSystems Ideas Waiting to be ImplementedParser for arbitrary binary protocolsRapid growth of IoT industry in recent years produced a plethora of new protocols with varying levels of standardization and adoption. Quite a lot of these protocols are binary because: * It allows for greater throughput * On a device level these protocols are easier to implement * On a device level they are more resource (CPU/RAM) efficient Currently InterSystems IRIS offers several functions for work with binary data: * zzdump * $zhex * $char * $ascii But protocol implementation is left as a task for the end user. Removing the time-consuming need for protocol implementation would allow for easier and stronger positioning of InterSystems IRIS as an IoT platform. One of the possible approaches to protocol implementation is declarative parsing. With declarative parsing user describes the data structure that he wants parsed (i.e.{ name: title, type: string, length: 5}...) in some declarative language (XML, JSON, YAML) and we use this to generate a concrete parser. Afterwards user passes protocol data to the concrete parser implementation and receives parsed values (as objects or locals or $lb). Kaitai Struct (http://kaitai.io) is an OpenSource (MIT license) declarative parser implementation which allows user to generate parser code for several languages: C++, C#, Go, Java, JavaScript, Lua, Perl, PHP, Python, Ruby, Rust. It allows easy language extensibility by keeping most of the process language-agnostic and only the last step (concrete parser generation) is end-language specific. I propose we add ObjectScript as a Kaitai Struct generation language. It would allow us to generate native ObjectScript parsers easily which would help with presenting InterSystems IRIS an IoT platform especially at a PoC stage. Alternatives to Kaitai Struct: * binpac (https://github.com/bro/binpac) - C++ only * preon (https://github.com/preon/preon) - Java only The advantage of Kaitai Struct is that it's not aimed at one language form the beginning, so adding a new language is an expected procedure. Article on the topic (https://old.reddit.com/r/cpp/comments/5tcnmh/implementing_communication_protocols_in_c_for/) E 3Votes0Comments | ||||||
![]() IrisSapConnectorExample connection IRIS with SAP using RFC | D | Docker IPM | 0.0 (0) | 26 Jun, 2023 | ||
iris-migrationsIRIS-migrations is a database migrations tool. | N | Docker IPM | 5.0 (1) | 25 Jun, 2023 | ||
ObjectScriptThe simplest template for the ObjectScript | Docker | 4.8 (5) | 21 Jun, 2023 | |||
telegram-adapter-demoThis demo shows how to use the IRIS Telegram Adapter. | N | Docker IPM | 0.0 (0) | 21 Jun, 2023 | ||
production-settingsModule to change InterSystems Interoperability Production settings | Docker IPM | 5.0 (1) | 20 Jun, 2023 | |||
Telegram adapterTelegram adapter for InterSystems IRIS | N | Docker IPM | 5.0 (1) | 20 Jun, 2023 | ||
![]() appmsw-warm-homeExample for creating a user interface for a smart home | Docker Python IPM | 5.0 (1) | 18 Jun, 2023 | |||
workshop-rest-wsCreation of REST web service for training purposes | Docker | 5.0 (1) | 16 Jun, 2023 | |||
![]() oex-mappingcollect OEX structure data | Docker IPM | 5.0 (1) | 13 Jun, 2023 | |||
![]() ChatGPT Telegram BotTalk to Chat GPT via Telegram! | Docker IPM AI | 0.0 (0) | 12 Jun, 2023 | |||
MergeCPF Application SettingsGet correct MergeCPF Application settings faster | A | 4.3 (2) | 08 Jun, 2023 | |||
workshop-performancePerformance tests of IRIS, Postgres and MySQL by JDBC connection | Docker | 5.0 (1) | 02 Jun, 2023 | |||
fhir-profile-validationValidating FHIR resources against profiles | D | Docker | 4.5 (1) | 30 May, 2023 | ||
![]() DBeaverUniversal Database Manager and SQL Client | S | 4.9 (15) | 29 May, 2023 | |||
ririsRemote InterSystems IRIS command execution | P | Docker Python | 3.8 (2) | 28 May, 2023 | ||
![]() Interopway RESTRepositório com conjunto de classes para auxiliar no desenvolvimento de integrações que consomem serviços REST | IPM | 3.3 (2) | 28 May, 2023 | |||
csvgen-pythonEmbedded python app creates table and loads data from CSV | Docker Python IPM | 5.0 (1) | 16 May, 2023 | |||
csvgenmodule to generate and import csv data using InterSystems ObjectScript | Docker IPM | 5.0 (4) | 16 May, 2023 | |||
![]() generate-datesGenerate a CSV file containing dates with additional information | Python | 3.5 (1) | 04 May, 2023 | |||
workshop-multiple-instancesProject for mirror training purpose. | Docker IPM | 4.0 (1) | 04 May, 2023 | |||
![]() superset-irisApache Superset support for IRIS | Docker Python | 5.0 (1) | 02 May, 2023 | |||
Customer churn predictorChecking customer churn with IntegratedML | O | Docker Python ML ML | 5.0 (2) | 28 Apr, 2023 | ||
OMOP and Atlas on IRIS for HealthImplementation of the OMOP common data model on IRIS for Health | R | Docker | 4.5 (1) | 27 Apr, 2023 | ||
![]() Interopway XDBCSimple way to implement XDBC Interoperability. | IPM | 4.0 (1) | 26 Apr, 2023 | |||
workshop-rest-iamWorkshop: InterSystems IRIS + REST development + API manager | A | Docker | 0.0 (0) | 26 Apr, 2023 | ||
workshop-smart-data-fabricLearn the main ideas involved in developing a Smart Data Fabric using InterSystems IRIS | A | Docker Python | 5.0 (1) | 26 Apr, 2023 | ||
PyHelperPython Interop for invocation, arguments and return types | A | IPM | 3.5 (2) | 23 Apr, 2023 | ||
![]() iris-mlm-explainerCreate, Train, Validate, Predict and Explore ML models | Python | 5.0 (1) | 22 Apr, 2023 |