Python is an interpreted high-level programming language for general-purpose programming. Created by Guido van Rossum and first released in 1991, Python has a design philosophy that emphasizes code readability, notably using significant whitespace
I have just created a new Global Master Topic, "IRIS Cheatsheets". IRIS has introduced a lot of new functionality, especially in scripting languages, FHIR R4 support, enhanced Interoperability Tools, and IRIS Analytics. Having spent 35 years working on Windows-based PC's and Laptops, I have surprisingly little knowledge of Linux, Docker and Git. Furthermore, I have written almost every application and Interface in ObjectScript with splatterings of SQL, .Net, and Java Gateways and the most basic knowledge of WinSCP, Putty, SSH. All that changed when I received my first Raspberry Pi.
Continuing the description of work on the use of the openhl python module in productive mode.
Since the version of iris with Embedded Python, does not yet have a final release, it is already necessary to use it in production now. We decided to back up the service for exporting requests to a xlsx file on a separate server, and save the query result in a global in a separate database.
In addition, we invite all EAP participants to the special Embedded Python kick-off webinar tomorrow, July 6 at 10:00 AM EDT – an easy start on how to use Embedded Python! Demonstration of the new features of the data platform, examples applications, and of course rewards.
After you become an EAP member, you will receive a special link to join the kick-off webinar:
For a long time, we have been using a utility in production to export the result of a query to an Excel spreadsheet. Moreover, we have applied a modification of it, in which the explicit setting of column formats is a priority.
This is a demo to make use of a simple WebSocket Client with Embedded Python in IRIS.
To continue my series of WebSocket Client I have added an example written in Python.
The most impressive experience was how easy the writing and testing of the client was
which happened total offline from IRIS.
Embedding, running and feeding the client with data from IRIS was also incredibly simple.
We’re looking for Python developers to participate in our Embedded Python Early Access Program! If you (or someone you know) are a Python developer and are interested, please contact us via the email address below.
The installation went well using pip and when python executes "import irisnative" it works fine. It just fails with a connection timeout when I try "irisnative.createConnection(...)." Below is my code:
Anton Umnikov Sr. Cloud Solutions Architect at InterSystems AWS CSAA, GCP CACE
AWS Glue is a fully managed ETL (extract, transform, and load) service that makes it simple and cost-effective to categorize your data, clean it, enrich it, and move it reliably between various data stores.
Hello All, Can anyone tell me whats the best python IDE and code editors? I am a little bit confused between Eclipse + Pydev, Pycharm, Sublime Text, Visual Studio Code, Vim, GNU/Emacs, Atom/Atom-IDE, Cloud9.
Embedded python gives the option to load and run python code in the InterSystems IRIS server. You can either use library modules from Python pip, like numpy, pandas, etc, or you can write your own python modules in the form of standalone py files.
So once you are happy with the development phase of the IRIS Embedded Python solution there is another very important question of how the solution could be deployed.
One of the options you can consider is using the ZPM Package manager which is described in this article.
Since I started to use internet (late 90's), I always had a CMS (content management system) present to make easier post
any information in a blog, social media or even an enterprise page. And later years putting all my code into github I
used to document it on a markdown file. Observing how easy could be persisting data into Intersystems IRIS with the
Native API I decided to make this application and force myself to forget a little of SQL and stay open to key-value database