I'm sharing a tool for data ingestion that we have used in some projects.
DataPipe is an interoperability framework for data ingestion in InterSystems IRIS in a flexible way. It allows you to receive data from external sources, normalize and validate the information and finally perform whatever operation you need with your data.
This formation, accessible on my GitHub, will cover, in half a hour, how to read and write in csv and txt files, insert and get inside the IRIS database and a distant database using Postgres or how to use a FLASK API, all of that using the Interoperability framework using ONLY Python following the PEP8 convention.
With the latest improvements in support for Python in IRIS, and continued work on Python DB-API support by InterSystems. I've implemented IRIS support to the Django project where is Python DB-API is used to work with some other databases.
Let's try a simple application on Django, which stores its data in IRIS.
I wrote a step by step tutorial in the qewd-howtos repository how you can write state of the art multi-page web apps with Node.js using a QEWD-Up WebSocket/REST api back-end integrated with a mainstream web framework like NuxtJS & Vue.js.
Over the past year or so, my team (Application Services at InterSystems - tasked with building and maintaining many of our internal applications, and providing tools and best practices for other departmental applications) has embarked on a journey toward building Angular/REST-based user interfaces to existing applications originally built using CSP and/or Zen. This has presented an interesting challenge that may be familiar to many of you - building out new REST APIs to existing data models and business logic.
I'm glad to announce we have recently released our second Starter Pack. This one is for the Mining Industry, and the first was for Industrial IoT (OEE).
But what does it exactly mean?
InterSystems IRIS Starter Packs (thanks to Joe Lichtenberg that helped with this text)
We are in the age of the multiplatform economy and APIs are the "glue" in this digital scenario. Since they are so important, they are seen by developers as a service or product to be consumed. Therefore, usage experience is a crucial factor for its success.
In this article I'm going to show how to integrate the InterSystems IRIS Database with Python to serve a Machine
Learning Model of Natural Language Processing (NLP).
This is the second post on the resources for Developers. This part is about Open Exchange
Using Open Exchange to Learn InterSystems
InterSystems Open Exchange is a applications gallery of tools, connectors, and libraries which InterSystems Developers submit to share the experience, approaches and do business. All the applications are either built with InterSystems data platforms or are intended to use for development with InterSystems data platforms.
If you are a beginner developer you can take a look at applications in Technology Example category. All the applications in this category come with open source code repositories, so you are able to run the samples and examples in a docker container with IRIS on your laptop or in the cloud IRIS sandbox. Examples:
By update
Open Exchange app
