M:N Relationship is a recurring object of my interest for a long time.
So the subject turns up with me repeatedly.
For this article, I found a nice example with TWO separate M:N relationships. Some M:N².

It is not pure fiction but taken from a closer view of OEX Contests that we run on a regular base.

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.

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.

That's the principle process:

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.

This package was triggered by the extra bonus points in the contest for writing the example
in embedded Python only. Therefore PURE

I have created a package to export a Global into JSON object file and to re-create it by reloading from this file
embeddedPython refers to the new available technologies. It should be understood as a learning exercise of
how to handle the language interfaces. Only Global nodes containing data are presented in the generated JSON file.
Differently from the previous example, this one is using embedded Python only, no ObjectScript. Therefore PURE

If one of your packages on OEX receives a review you get notified by OEX only on YOUR package.
It reflects my experience with the status I found at the time of my review.
It is kind of a snapshot and might have changed meanwhile.

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.

Thanks to @Yuri Marx we have seen a very nice example for DB migration from Postgres to IRIS.
My personal problem is the use of DBeaver as a migration tool.
Especially as one of the strengths of IRIS ( and also Caché) before is the availability of the
SQLgateways that allow access to any external Db as long as for them an access usinig
JDBC or ODBC is available. So I extended the package to demonstrate this.