Globals are multidimensional sparse arrays which are stored in InterSystems Data Platform. Everything in InterSystems Products is stored in Globals: Classes, Tables, Documents, Code.
Temporary globals stored in the IRISTEMP/CACHETEMP databases are used when a process does not need to store data indefinitely, but requires the powerful performance of globals. The IRISTEMP/CACHETEMP databases are not journaled, so using temporary globals does not create journal files.
The system uses the IRISTEMP/CACHETEMP databases for temporary storage and are available to users for the same.
JSON is a lightweight data interchange formatfor representing and exchanging data between a server and a web application. Its popularity has led to its widespread use in applications based on InterSystems technology, as well as demand for a converter that transforms globals to JSON and back. Therefore, @Evgeny Shvarov suggested developing Global->JSON->Global converter. Implementing such a converter is important to ensure interoperability, simplify data exchange, support web services, and provide a standardized approach to data representation across different software ecosystems. This article, the second in the "Implemented Ideas" series, focuses on several projects created by the legend of InterSystems Developer Community @Robert Cemper that deal with this task:
The forth in the trilogy, anyone a Hitchhikers Guide to the Galaxy fan?
If you are looking to breathe new life into an old MUMPS application follow these steps to map your globals to classes and expose all that beautiful data to Objects and SQL.
If the above does not sound familiar to you please start at the beginning with the following:
There are situations when your only access to a server is using a web browser, and there is just no chance of a Terminal or Console access. The Online Demo Server is such a case.
So you have WebTerminal. That's fine for ObjectScript and Embedded Python.
This is the related article to the package in Java Contest.
I decided to present a CRUD++ Global Editor based on IRIS Native API for Java. ++ because it’s a little bit more than just Create, Read, Update, Delete Visualization of a global is always important to review results immediately.
Customizing Stored Procedures with ObjectScript directly has been useful to access NoSQL storage and external messaging via integration, to present output in tabular format.
As noted in the previous article Native API has some limits. So I did some research on a more Terminal-like interface that provides me with access like a console or the IRIS terminal to allow my $QUERY over a global and other nice commands that are not supported/mapped in NativeAPI for ObjectScript.
InterSystems IRIS currently limits classes to 999 properties.
But what to do if you need to store more data per object?
This article would answer this question (with the additional cameo of Community Python Gateway and how you can transfer wide datasets into Python).
The answer is very simple actually - InterSystems IRIS currently limits classes to 999 properties, but not to 999 primitives. The property in InterSystems IRIS can be an object with 999 properties and so on - the limit can be easily disregarded.
Looking to breathe new life into an old MUMPS application? Follow these steps to map your existing globals to classes and expose all that beautiful data to Objects and SQL.
The power of the presented tool becomes visible with a large JSON file. The example I have prepared is composed of the daily results of AoC 2023. Anonymization makes it usable for demo purposes.
The similarity between JSON objects + arrays and Globals in IRIS or Caché is evident. With small and medium size JSON objects navigation across %Dynamic Objects is comfortable. But with large and/or deep cascaded objects it becomes a challenge.
The presented tool offers 3 variants
loading an already existing %Dyamic object or Array into a global of your choice
loading a %Stream containing a JSON object into a global of your choice
loading an external File containing a JSON object into a global of your choice
In this article, I will introduce Python Flask Web Framework. Together we will create a minimal web application to connect to IRIS and get data from it.
Below you can find the steps we will need to follow:
Step 1 : Introduction to Python Flask Web Framework
Step 2 : Installation of Flask module
Step 3 : Creation of web application using Flask
Step 4 : Use of HTML Templates
Step 5 : Installation of IRIS Python Native module
Step 6 : Establishment of a connection with IRIS
Step 7 : Transferring data from IRIS to Flask and displaying it
So Let's start with step 1
Step1-Introduction to Python Flask Web Framework
Flask is a small and lightweight Python web framework that provides useful tools and features that make creating web applications in Python easier. It gives developers flexibility and is a more accessible framework for new developers since it allows to build a web application quickly using only a single Python file. Flask is also extensible and doesn’t requires a particular directory structure or complicated boilerplate code before getting started.
In this article you will have access to the curated base of articles from the InterSystems Developer Community of the most relevant topics to learning InterSystems IRIS. Find top published articles ranked by Machine Learning, Embedded Python, JSON, API and REST Applications, Manage and Configure InterSystems Environments, Docker and Cloud, VSCode, SQL, Analytics/BI, Globals, Security, DevOps, Interoperability, Native API. Learn and Enjoy!
This project was thought of when I was thinking of how to let Python code deal naturally with the scalable storage and efficient retrieving mechanism given by IRIS globals, through Embedded Python.
My initial idea was to create a kind of Python dictionary implementation using globals, but soon I realized that I should deal with object abstraction first.
So, I started creating some Python classes that could wrap Python objects, storing and retrieving their data in globals, i.e., serializing and deserializing Python objects in IRIS globals.
You may have seen my series of articles on GlobalToJSON closing with Embedded Python. And to me, Embedded means inside a Class and not PEX or other external variants. The first variants showed that ePy is not an ultimate requirement. ISOS/COS may do it as well. Here I try to position ePy inside IRIS.
This package offers a utility to export an XLarge Global into a JSON object file and to show or import it again. In a previous example, this all was processed in memory. But if this is a large Global you may either experience <MAXSTRING> or an <STORE> error if the generated JSON structure exceeds available memory.
Globals are the core of the InterSystems IRIS for data persistence. It is flexible, allowing store JSON documents, relational data, object oriented data, OLAP cubes and custom data models, like Mindmaps. To see how to store, delete and get mindmap data using globals, follow these steps:
1. Clone/git pull the repo into any local directory
I have created a package that offers a utility to load a Global into JSON object and reverse to create a Global from this type of JSON object. Compact refers to the structure created. Globals nodes are included with data for a fast data load. But also the related code is quite compact.
I have created a package that offers a utility to load a Global into JSON object and reverse to create a Global from this type of JSON object. Efficient refers to the structure created. Only Globals nodes containing data are presented in the generated JSON object.
This example demonstrates the difference you may experience when you write to Gllobals directly from Embedded Python compared to native ObjectScript.
To make this demo useful I start 2 background jobs that simply write sequentially to a dedicated global. A common control method signals for a synchronous start. Similar a common stop & view interrupts data feeding.
In my article I described the work using iris.gref . As the official documetation is rather slim on the subject it was necessary to dig into it. Using the power of Python I was able to detect what I needed but was hidden. I decided to share this with you. pydoc did the magic.
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