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Hi Everyone!InterSystems HealthShare is nominated for the Computable Awards 2019! The Unified Health Record that we implemented together with our partner Itzos in the St. Maartens Clinic has a chance to become the "ICT Project of the Year in Healthcare". A great honour, but of course we also want to win. We need 4,000 votes! Therefore we'd like to ask you to vote! The process of voting is a bit complicated, but we created a step-by-step guide to make it easier:1. Register on → Computable website2. You will receive an email from Computable with a link. Click on the link and you will get to the voting page.3. Use CTRL/COMMAND + F to search for InterSystems on the page, or just scroll down to the award category near the bottom “IT project of the Year in Healthcare.” Vote for the second group:4. Done? Awesome! You will get a "Thank you" email from Computable Awards.So,We hope for you! Help InterSystems to win! Please share, like and send as direct message to your customers, friends and prospects.In addition, we prepare a special challenge to vote on InterSystems Global Masters Advocacy Hub. Please complete it and get a good amount of extra points.Stay tuned! For what it's worth, it looks like it's possible to vote without subscribing to any of the updates - I filled in my information, left all four subscription check-boxes blank, and selected "verstuur", and received an email with a link to vote. Hi Samuel, this is such an awesome correction! Thank you!! I edited the instructions :) Hi ,I filled in my information, and received an email with a link to vote. and I have voted for Intersystems. Thanks Hi Uthman,Thanks for your support! Done! Hi Esther,Thanks for your attention to us! Thanks to all who voted for us, on behalf of the Benelux team!

First webinar on InterSystems API Management! We are pleased to invite you to the upcoming webinar in Russian: Introduction to InterSystems API Management on November 21 at 10:00 Moscow time (GMT+3)! As you might have heard, we recently introduced the InterSystems API Manager (IAM) - a new feature of the InterSystems IRIS Data Platform,enabling you to monitor, control and govern traffic to and from web-based APIs within your IT infrastructure. In this webinar I will highlight some of the many capabilities IAM allows you to leverage. InterSystems API Manager brings everything you need: to monitor your HTTP-based API traffic and understand who is using your APIs; what are your most popular APIs and which could require a rework. to control who is using your APIs and restrict usage in various ways. From simple access restrictions to throttling API traffic and fine-tuning request payloads, you have fine-grained control and can react quickly. to protect your APIs with central security mechanisms like OAuth2.0 or Key Token Authentication. to onboard third-party developers and provide them with a superb developer experience right from the start by providing a dedicated Developer Portal for their needs. to scale your API demands and deliver low-latency responses There would be a live demo. This webinar is for System Architects, Developers and DevOps Engineers.Time: November 21 at 10:00 Moscow time (GMT+3)! The language of the webinar is Russian. Register! Any chance of repeating this webinar in English? Hi Fred! Have you seen this introduction? Hi Fred, I just published the API Management session from Global Summit 2019 on DC YouTube channel. Hope it will be useful for you! 😉 Is there any interest in English Webinar? Please reply in comments if you would like a rerun of this or similar webinar but in English! Yes

Hi Developers! In previous articles, we spoke on how to publish your application. But how to make Open Exchange work its best for your application? What do you want for your application on Open Exchange? It is attention (traffic) and downloads. Let's talk about how Open Exchange can deliver this. How Do I know how many downloads I have? There is an Analytics tab that is visible for the Author of application. It shows how many times users clicked on the Download button. We have a roadmap for this tab and soon will add the monthly info on Downloads and some other information and you are very welcome to submit what else do you want to see here. E.g. we plan to make this Downloads counter publicly available and make a sorting upon Downloads. Prepare your Application's page Your application's page should contain enough description of what the application does. This makes users want to click on the Download button. How to set up the description? If your application is the facade for a GitHub repo Open Exchange can import Readme.Md from your Github repo. E.g. like here: check the Open Exchange page and the related Github repo page So, in this case, you just need to properly maintain README.md file in the Github repo which will be automatically updated on Open Exchange. In case it is a non-Github application you setup the description on your own the Long Description field. This field supports markdown so you have rich formatting tools to describe the purpose, features, installation steps and usage terms. A good example of a Markdown description on Open Exchange. Make Regular Releases If your app is evolving this is noticed by users. Add the feature and don't forget to make a release on Developers Community. It takes 5 min but it adds the release notes to News, it places your app on top on the main page, it gets your subscribers notified on the new features your bring to your application. Post the Related Developer Community article You can tell a lot how to use your application and how people can benefit from its features? It's a great reason to write an article about it on Developers Community and highlight the features of your application. Of course, you will add the hyperlinks to your application page inside the text but you also can feature the application using DC tools. E.g. you can add the "Related Open Exchange Application" link and this will add a special button on top of your article and in the news feed and an URL to the app at the bottom of the application. See the Example. You also want to link back the application on Open Exchange to the article on DC: This will make the Discuss button active on the Application page. An average DC article gets about 800 reads so you can deliver additional traffic to your application using this channel. Easy installation and setup If your application has 12 steps of "How to install it" this probably doesn't help to increase the number of downloads. Ideally, this should be a one-step installation. If your application is InterSystems ObjectScript I recommend pack and publish it with an ObjectScript Package manager. This really makes your installation into one command: USER:zpm>install your-application Example. Use Your Global Masters' "Miles" Another way how you can get more traffic to your application page is to use Global Masters points. You may know we have a Global Masters advocates hub where we give points to participants for there contribution to InterSystems Community. The ways of the contribution could be articles, answers, and questions on DC, applications on Open Exchange (yes, you get GM points for submitting applications). So, you probably have some GM points(sign in with your DC or Open Exchange credentials) and if you give to the Community and the Community could give you back and you can use GM points to get more attention to your Open Exchange application. How? Google Ads promotion You can spend some points and set up a Google Adwords campaign of $1,000 which InterSystems will cover and manage. Learn more. App of the week We have "News blocks" on every page of Developers Community and this News block can tell about your Open Exchange application. Learn more. Your Application Screencast On InterSystems Developers Youtube If you have a screencast on the features of your application you can get more views and traffic publishing it on Developers Community Youtube. And the simplest and the most working approach: add the features which everybody likes and thus you get the most attention and downloads) Choose any recipes above or take all of them and boost the downloads of your InterSystems Application on Open Exchange! If you have any ideas on how we could better help to make your Open Exchange applications more noticed and helpful submit suggestions and bug reports here. Submit your InterSystems apps and stay tuned!

Hi Developers! This post describes how you could publish your InterSystems application on Open Exchange. What is the InterSystems application? It could be anything, which is built with InterSystems data platforms or to help work with InterSystems data platforms: InterSystems IRIS, InterSystems IRIS for Health, InterSystems HealthShare, InterSystems Ensemble and InterSystems Caché. This could be tools, frameworks, adapters, examples and business solutions. Why publish on Open Exchange? InterSystems Open Exchange is an "App Central" for the solutions in InterSystems. It's the first place where the developer goes to look for tools, frameworks, and examples on InterSystems IRIS. And Open Exchange brings the added traffic to your solution which could be converted into leads. We are having a set of business development tools for published Open Exchange applications. This definitely makes your InterSystems application more noticed. Submitting an application Suppose you have a library with open source published on Github which you want to publish on Open Exchange. For the purpose of a demo, I'll fork this remarkable project of @Peter.Steiwer ObjectScript-Math which I forked and renamed to object script-super-math. First of all, you need to sign in. You can do this using your DC account or create a new one (which will be suitable for DC too). Once signed in you'll see Profile Menu available which has My Apps section: Click on a New button to submit a new InterSystems application: OEX has a nice integration with Github which allows filling all the matching fields from the Github repo. E.g. let's try with objectscript-super-math: It imports the name, short description, license, Full description, Download URL. To have the application ready for publishing you just need to peek InterSystems Data Platform it works with and the related tags. Also, if there is an article on DC where you discuss the application, add the link to this article. If you publish not Github app with open source, but e.g. the solution you need to accurately fill all the mandatory fields: Name, Download URL, Short Description, License, Tags, Product. And the optional fields which you think should be filled. You also can add the related Youtube videos and two very important checkboxes: We'll talk about this later. Once you are happy with the fields you are welcome to Save the application. Before publishing the app you can set up the app's icon: Upload screenshots: And after that once you are ready, send it for approval on publishing: Here you need to submit the version and the release notes of the version. Release notes section supports Markdown so you can paste here very informative description with rich formatting on what are the changes come with the new release of your application. This will send the application to Open Exchange management for approval and once it's approved the application will be published on Open Exchange, you'll get the notification on email and the release news will be published on Open Exchange News. Next time we'll discuss profile setup, company setup and some special cases. Stay tuned! A tip for anyone trying to upload a different image for an already-published app. You need to unpublish it first, to make the "Upload image" option appear on the menu. See this GH issue comment. A related tip is that when you send your unpublished-and-modified app for approval you can override the default next version number that appears in the dialog, setting it to the same as the current version. You'll still have to enter something in the Release Notes field, but when your changes are subsequently approved your published app won't show any change in the Version History tab. John! Thanks for the heads up! It's really not very convenient! We'll fix it.

AWS launched their first generation of Amazon EC2 A1 instances last year, powered by Arm-based AWS Graviton processors. At AWS re:Invent 2019, Amazon announced the second-generation AWS Graviton2 processors and associated Amazon EC2 M6g instance type, boasting up to 40% better price performance over current generation Intel Xeon based M5 instances. The AWS Graviton2-based M6g instances are currently in preview, and InterSystems jumped on the opportunity to measure their performance with the InterSystems IRIS Data Platform. InterSystems is excited to announce that we’ve seen truly impressive results, and we plan to support Arm-based Amazon EC2 instances powered by AWS Graviton2 processors in 2020! We tested two different workloads, representing common use-cases across the InterSystems IRIS customer base. The first workload is pure data ingestion for a financial application based on InterSystems IRIS Data Platform. The second is a healthcare interoperability workload, based on InterSystems IRIS for Health. We compared performance of Amazon EC2 M6g vs. M5 on each workload. Workload #1: Data Ingestion Throughput on InterSystems IRIS Data Platform We tested identical workloads to simulate NYSE data processing (Order/Fill) on InterSystems IRIS running on a two-node sharded cluster. The benchmark compared performance between m5.2xlarge and AWS Graviton2 based m6g.2xlarge Amazon EC2 instances, each with 8 vCPU’s and 32 GB RAM. The only configuration differences were the processor and AMI operating system image. The compared configurations had the same EBS volumes, iops, VPC configuration, and IRIS parameters such as global buffers. In both cases, we used pre-released versions of InterSystems IRIS - IRIS-2020.1.0L.188.0-lnxrharm64 and IRIS-2020.1.0L.188.0-lnxrh64. The m5.2xlarge system was able to process on average 98 thousand records per second, and the m6g.2xlarge showed close to 120 thousand records/second. That’s over 20% performance improvement on the same number of vCPUs! Workload #2: Healthcare Interoperability Throughput on InterSystems IRIS for Health We tested identical workloads to simulate HL7 message ingestion, routing, and transformation on an InterSystems IRIS for Health Interoperability production. The benchmark compared an m5.2xlarge and an m6g.2xlarge (both with 8 vCPU’s, and 32 GB RAM), again with the exact same configuration aside from their processors, tested on pre-released versions of InterSystems IRIS (2020.1). We’ve also included the same test run against the first-generation AWS Graviton based A1 instance types to show the quantum leap in performance provided by AWS Graviton2. Here are the results: The left side axis is our primary measure of performance for this workload, which is messages per second processed by the application. The x-axis represents the increasing volume thrown at the application by the benchmark driver. As we move from left to right, we increase the applied workload, first by increasing the number of inbound interfaces up to 16, then holding that steady while increasing the driver burst rate. The columns represent CPU utilization measured on the right-side axis, where as we near 100% CPU utilization, we can see the maximum capability of each instance type. As you can see, the AWS Graviton2 based M6g instances scale linearly, and clearly outperform the M5 instances at high workloads. The M6g instances maintain lower CPU utilization for the same workload, and continue scaling after the M5 instances reach their maximum utilization. The M6g instances ultimately performed ~28% better in messages throughput compared to the same sized M5 instances. This is an impressive win for AWS Graviton2 processors! Price Performance: In addition to the clear performance gains we see comparing same-sized AWS Graviton2 based M6g and M5 instances, there is further benefit when we consider instance pricing where the Amazon EC2 M6g instances are 20% lower cost compared to the current generation Amazon EC2 M5 instances: m5.2xlarge On-Demand: $0.384 per hour m6g.2xlarge On-Demand: $0.308 per hour In Conclusion: InterSystems strives to provide customers with platform freedom of choice. We at InterSystems are very excited to see the performance gains and cost savings that AWS Graviton2 processors will provide to InterSystems IRIS customers. We anticipate that these combined benefits will drive significant adoption of Arm-based platforms among IRIS customers, and we look forward to providing support in 2020! Want to Learn More? https://aws.amazon.com/ec2/graviton/ https://aws.amazon.com/ec2/instance-types/m6/ https://www.intersystems.com/products/intersystems-iris/ It's great news, but when it will be available for preview. Congrats! Can we expect publishing your code aimed "...to simulate NYSE data processing (Order/Fill)..." as an Open Exchange App? Hi Dmitriy, Support for ARM64 architectures will initially be limited to Ubuntu-based containers only. I hope to have a preview image of InterSystems IRIS 2020.1 for ARM64 published in the AWS marketplace this week. This should run on the AWS Graviton based A1 instances now, and the M6g instances once they are generally available. Thanks, Steve Sounds good. How about to run it on Raspberry PI, is it already a time, to order of some (even now, when it has been recently updated and got a lower price)? As of this release, it is only to be supported on Amazon EC2. Once there is a Community Edition image generally available... well I can't say it's supported on a Raspberry Pi but who am I to stop a tinkerer from tinkering...have fun! :-) @Dmitry.Maslennikov docker pull store/intersystems/iris-community-arm64:2020.2.0.211.0 What OS is it running？ RHEL for ARM or CentOS for ARM? All of InterSystems' container releases are built on Ubuntu (See: https://docs.intersystems.com/irislatest/csp/docbook/Doc.View.cls?KEY=ISP_technologies#ISP_platforms_container). Currently Arm64 support is limited to container releases, but we expect to support full kit installs for Ubuntu and RHEL for Arm architectures in the near future. Thx, Steven! @Lu.Wang @Peng.Qiao @Hao.Ma pls keep an eye on this.

Dear Community, We're pleased to invite you to the InterSystems DACH Symposium 2019, which will take place from November 12th to 14th 2019 at The Westin Grand Hotel in Frankfurt am Main! This year, we will focus on best practices and use cases for AI, ML as well as API management, microservices and the use of containers for DevOps. You’ll experience exciting lectures, interactive sessions and hands-on coding exercises, which are suitable for both InterSystems experts and beginners. See for yourself how the new API Manager simplifies the orchestration of microservice architectures and how QuickML and InterSystems IRIS can help you to implement ML projects quickly and efficiently. So, remember: ⏱ Time: November 12-14, 2019 📍Venue: The Westin Grand Hotel, Frankfurt am Main, Germany ✅ Registration: SAVE YOUR SEAT See you in Frankfurt! Liebe Community, Wir laden euch herzlich ein zum InterSystems DACH Symposium 2019, das in diesem Jahr vom 12.-14. November im The Westin Grand Hotel in Frankfurt am Main stattfinden wird. Thematisch legen wir besondere Schwerpunkte auf Best Practices und Use Cases für KI, ML sowie API Management, Microservices sowie die Nutzung von Containern für DevOps. Meldet euch am besten gleich zu dieser kostenfreien Veranstaltung an: https://intersystems-dach-symposium.de/register/ Es erwarten euch spannende Vorträge, interaktive Sessions und praxisnahe Coding-Übungen, die sowohl für InterSystems-Profis wie auch –Einsteiger geeignet sind. Erfahrt aus erster Hand, wie der neue API Manager die Orchestrierung von Microservice-Architekturen vereinfacht und wie ihr mit QuickML und InterSystems IRIS Machine Learning Projekte schnell und effizient umsetzen könnt. Und, denk dran: ⏱ Zeit: 12. bis 14. November 2019 📍Veranstaltungort: The Westin Grand Hotel, Frankfurt am Main, Deutschland ✅ Registrierung: Sichern Sie sich Ihren Platz Sehen wir uns in Frankfurt! Any plans for a DC Meetup at this event? Hi John! Do you plan to come to DACH Summit 2019? Maybe. It's being considered. Will DC meetup influence the decision? ) John, we are considering it. There is a possibility if we have enough support and requests from developers. It's confirmed that I will be attending. The organizers have generously added me to the early evening "Beer & Bytes" demo sessions on Tuesday and Wednesday. I will demonstrate editing and debugging ObjectScript with Visual Studio Code using Serenji .

Hi Community, As you may know, we successfully held InterSystems Developers Meetup in Boston at Global Summit 2019. And now it's time to find out which solutions development on InterSystems IRIS have been discussed! Please welcome the Meetup video recording on InterSystems Developers YouTube Channel: ⏯ InterSystems Developers Meetup - Global Summit 2019 So, let's warmly greet these sessions from InterSystems developers: № TOPIC SPEAKER 1 Using Python Gateway with InterSystems IRIS @Eduard Lebedyuk, InterSystems 2 VSCode ObjectScript - your IDE for InterSystems IRIS development @Dmitriy Maslennikov, CaretDev 3 Using Package Manager for deployment InterSystems Solutions @Evgeny Shvarov, InterSystems 4 Falling in love with Visual Studio Code and Serenji @John Murray, George James Software 5 InterSystems IRIS and the Cloud @Anton Umnikov, InterSystems 6 How Your Code Matters! @Dmitriy Maslennikov, CaretDev P.s. Don't forget to check the useful resources on Open Exchange Marketplace. Big applause for these speakers! And thanks to all participants of the Meetup! 👏🏼 Please find more details in this post. Enjoy watching the video! And... What about the next events? Do you want our community to held more such meetups for InterSystems developers? Your feedback is very welcome! Please leave your suggestions in the comments of this post.

Hello InterSystems Community, We're excited to announce that we've completed our first Open Exchange submission for InterSystems platforms. BridgeWorks VDM is an ad hoc reporting and graphical SQL query builder application that was designed for any user who needs access to their SQL projections in InterSystems Caché, InterSystems IRIS, InterSystems IRIS for Health databases as well as access to InterSystems DeepSee and InterSystems IRIS BI Cubes with minimal SQL scripting experience. VDM features: Drag and a drop query builder Interactive Data and Pivot grids Charting and Gauges Data Visualizations Banded Report Writer Report Scheduling and Batching Web reporting capabilities Data export to PDF, Excel, HTML, Word, CSV, Text Files, Image and more VDM leverages the Managed Provider for .Net to communicate with InterSystems databases, and no ODBC drivers are needed to access the SQL projections for InterSystems Caché, InterSystems IRIS and InterSystems IRIS for Health. VDM accesses DeepSee.RESTClient.cls for building MDX queries and communication with InterSystems DeepSee and InterSystems IRIS BI. Video walk through: jQuery(document).ready(function ($){$("#youtubexM5LKB0G25E").css("height",$("#youtubexM5LKB0G25E").css("width").replace(/[^0-9]/gim,"")/(560/315));$(window).resize(function(){ $("#youtubexM5LKB0G25E").css("height",$("#youtubexM5LKB0G25E").css("width").replace(/[^0-9]/gim,"")/(560/315));});}); Notes: While VDM is not a SQL syntax editor, the graphical query builder can be bypassed and SQL scripts can be pasted directly into the Advanced Query form for execution against your InterSystems database. The InterSystems DeepSee and InterSystems IRIS BI features are currently EAP. Community feedback on our project is appreciated.

Hi Everyone, Please welcome the new Global Summit 2019 video on InterSystems Developers YouTube Channel: ⏯ Using IoT in InterSystems IRIS for Health In this video, we will demonstrate connecting a heart rate sensor, to InterSystems IRIS for Health via an MQTT/IoT interface. We will show how the sensor reading becomes a well-formatted HL7 message, suitable for sharing and analysis. Takeaway: InterSystems IRIS for Health enables you to capture and use the latest wearable data from healthcare sensors.Presenter: @Anton.Umnikov, Senior Cloud Solution Architect, InterSystems Learn more in this InterSystems Online Learning Course. Enjoy watching the video! 👍🏼

Hi Community! Thank you for being a part of the InterSystems Open Exchange! We want to know what you like about Open Exchange and how we can make it better in 2020. Could you please go through this short survey which will let us know what do you think. ➡️ Open Exchange Survey 2019 (2 minutes, 7 questions) Your answers are very important to us! Sincerely, Your InterSystems Developer Community Team

Introduction InterSystems has recently completed a performance and scalability benchmark of IRIS for Health 2020.1, focusing on HL7 version 2 interoperability. This article describes the observed throughput for various workloads, and also provides general configuration and sizing guidelines for systems where IRIS for Health is used as an interoperability engine for HL7v2 messaging. The benchmark simulates workloads that have been designed to closely match live environments. The details of the simulation are described in the Workload Description and Methodology section. The tested workloads comprised HL7v2 Patient Administration (ADT) and Observation Result (ORU) payloads and included transformations and re-routing. The 2020.1 version of IRIS for Health has demonstrated a sustained throughput of over 2.3 billion (total inbound and outbound) messages per day with a commodity server using the 2nd Generation Intel® Xeon® Scalable Processors and Intel® Optane™ SSD DC P4800X Series SSD storage. These results have more than doubled the scalability from the prior Ensemble 2017.1 HL7v2 throughput benchmarking. Throughout these tests, IRIS for Health was configured to preserve first-in/first-out (FIFO) ordering, and to fully persist messages and queues for each inbound and outbound message. By persisting the queues and messages, IRIS for Health provides data protection in the event of a system crash, and full search and resend capabilities for historic messages. Further, configuration guidelines are discussed in the sections below, which will assist you in choosing an appropriate configuration and deployment to adequately meet your workload’s performance and scalability requirements. The results demonstrate that IRIS for Health is capable of satisfying extreme messaging throughput on commodity hardware, and in most cases allowing a single small server to provide HL7 interoperability for an entire organization. Overview of Results Three workloads were used to represent different aspects of HL7 interoperability activity: T1 workload: uses simple pass-through of HL7 messages, with one outbound message for each inbound message. The messages were passed directly from the Ensemble Business Service to the Ensemble Business Operation, without a routing engine. No routing rules were used and no transformations were executed. One HL7 message instance was created in the database per inbound message. T2 workload: uses a routing engine to modify an average of 4 segments of the inbound message and route it to a single outbound interface (1-to-1 with a transform). For each inbound message, one data transformation was executed and two HL7 message objects were created in the database. T4 workload: uses a routing engine to route separately modified messages to each of four outbound interfaces. On average, 4 segments of the inbound message were modified in each transformation (1 inbound to 4 outbound with 4 transforms). For each inbound message four data transformations were executed, four messages were sent outbound, and five HL7 message objects were created in the database. The three workloads were run on a physical 48-core system with two Intel® Scalable Gold 6252 processors with two 750GB Intel® Optane™ SSD DC P4800X SSD drives running Red Hat Enterprise Linux 8. The data is presented as the number of messages per second (and per hour) inbound, the number per second (and per hour) outbound, as well as the total messages (inbound plus outbound) in a 10-hour day. Additionally, CPU utilization is presented as a measure of available system resources at a given level of throughput. Scalability Results Table-1: Summary of throughput of the four workloads on this tested hardware configuration: * Combined workload with 25% of T1 / 25% of T2 / 50% T4 workload mix Workload Description and Methodology The tested workloads included HL7v2 Patient Administration (ADT) and Observation Result (ORU) messages, which had an average size of 1.2KB and an average of 14 segments. Roughly 4 segments were modified by the transformations (for T2 and T4 workloads). The tests represent 48 to 128 inbound and 48 to 128 outbound interfaces receiving and sending messages over TCP/IP. In the T1 workload, four separate namespaces each with 16 interfaces were used, and the T2 workload used three namespaces each with 16 interfaces, the T4 workload used four namespaces each with 32 interfaces, and the final “mixed workload” used three namespaces with 16 for T1 workload, 16 for T2 workload, and 32 for T4 workload. The scalability was measured by gradually increasing traffic on each interface to find the highest throughput with acceptable performance criteria. For the performance to be acceptable the messages must be processed at a sustained rate, with no queuing, no measurable delays in delivery of messages and the average CPU usage must remain below 80%. Previous testing has demonstrated that the type of HL7 message used is not significant to the performance or scalability of Ensemble; the significant factors are the number of inbound messages, the size of inbound and outbound messages, the number of new messages created in the routing engine, and the number of segments modified. Additionally, previous testing has shown that processing individual fields of an HL7 message in a data transformation is not usually significant to performance. The transformations in these tests used fairly straightforward assignments to create new messages. Note that complex processing (such as use of extensive SQL queries in a data transformation) may cause results to vary. Previous testing has also verified that rules processing is not usually significant. The routing rule sets used in these tests averaged 32 rules, with all rules being simple. Note that extremely large or complex rule sets may cause results to vary. Hardware Server Configuration The tests utilized a server with 2nd Generation Intel® Scalable Gold 6252 “Cascade Lake” processors providing 48 cores @ 2.1GHz on a 2-socket system, 24 cores per socket with 192 GB DDR4-2933 DRAM, and 10Gb Ethernet network interface. Red Hat Enterprise Linux Server 8 operating system was used for this test with InterSystems IRIS for Health 2020.1 Disk Configuration Messages passing through IRIS for Health are fully persisted to disk. In the case of this test two Intel 750GB Intel® Optane™ SSD DC P4800X SSD drives internal to the system were used splitting the databases on one drive and the journals on another. In addition to ensure real-world comparison synchronous commit is enabled on the journals to force data durability. For the T4 workload as described previously in this document, each inbound HL7 message generates roughly 50KB of data, which can be broken down as described in Table 2. Transaction journals are typically kept on line for less time than message data or logs and this should be taken into account when calculating the total disk space required. Table 2: Disk Requirement per inbound HL7 T4 Message Contributor Data Requirement Segment Data 4.5 KB HL7 Message Object 2 KB Message Header 1.0 KB Routing Rule Log 0.5 KB Transaction Journals 42 KB Total 50 KB Recall that the T4 workload used a routing engine to route separate modified messages to each of four outbound interfaces. On average, 4 segments of the inbound message were modified in each transformation (1 inbound to 4 outbound with 4 transforms). For each inbound message four data transformations were executed, four messages were sent outbound, and five HL7 message objects were created in the database. When configuring systems for production utilization, net requirements should be calculated by considering the daily inbound volumes as well as the purging schedule for HL7 messages and the retention policy for journal files. Additionally, appropriate journal file space should be configured on the system so as to prevent the journal disk volumes from filling up. The journal files should reside on physically separate disk from the database files, for both performance as well as reliability considerations. Conclusion InterSystems IRIS for Health HL7v2 message throughput demonstrated in these tests illustrates the massive throughput capabilities with a modest 2-socket commodity server configuration to support the most demanding message workloads of any organization. Additionally, InterSystems is committed to constantly improving on the performance and scalability from version to version along with taking advantage of the latest server and cloud technologies. The following graph provides an overview and comparison of the increase in throughput from the previous Ensemble 2015.1 and Ensemble 2017.1 benchmarks with the Intel® E5-2600 v3 (Haswell) processors and Ensemble 2017.1 benchmark with 1st Generation Intel® Scalable Platinum Series (Skylake) processors respectively to latest results with the 2nd Generation Intel® Scalable Gold Series (Cascade Lake) processors running IRIS for Health 2020.1. Graph-1: Message throughput (in millions) per 10-hour day on a single server InterSystems IRIS for Health continues to raise the bar on interoperability throughput from version to version along with offering flexibility in connectivity capabilities. As the above graph shows the message throughput has increased significantly and, in case of T2 workloads, doubled from 2017, and comparing to 2015 more than tripled throughput in the same 10-hour window and sustained over 2.3 billion total 24-hour message rates. Another key indicator of the advancements of IRIS for Health is the throughput improvement in the more complex T2 and T4 workloads which incorporates transformations and routing rules as opposed to pure pass-through operation of the T1 workload. InterSystems is available to discuss solutions for your organizations interoperability needs. Hi Mark! These are impressive results! Do you have the link to the previous Ensemble 2017.1 HL7v2 throughput benchmarking results? They used to be available on our website, but have since been removed since the results where from 3 years ago. The summary results from 2015 and 2017 have been included in graph-1 above in this new report for comparison. Thanks. hi Mark Bolinsky ; I am student , I need HL7 Benchmark to test the process that I implemented. Please, can you help me get it?

Hey Developers! Please join the upcoming InterSystems Developers Meetup in Boston which will be held on September 25th, 2019! It will take place in Boston Marriott Copley Place from 5:30 p.m. to 9 p.m. We meet to discuss solutions development on InterSystems IRIS. Come to tell your stories and share experience with InterSystems data platforms, for networking and developer conversations. Drinks and snacks will be provided. The format is usual: 15 min for a session, 5 min for Q&A. Here is the current agenda for the event: TIME TOPIC SPEAKER 5:30 p.m. Welcome and Introduction 6:00 p.m. Using Python Gateway with InterSystems IRIS @Eduard.Lebedyuk, InterSystems 6:20 p.m. VSCode ObjectScript - your IDE for InterSystems IRIS development @Dmitry.Maslennikov, CaretDev 6:40 p.m. Using Package Manager for deployment InterSystems Solutions @Evgeny.Shvarov, InterSystems 7:20 p.m. Coffee break 7:40 p.m. Falling in love with Visual Studio Code @John.Murray, George James Software 8:00 p.m. InterSystems IRIS and the Cloud @Anton.Umnikov, InterSystems 8:20 p.m. How Your Code Matters! @Dmitry.Maslennikov, CaretDev 8:40 p.m. Coffee break Note: If you want to present your story, please contact @Evgeny.Shvarov or @Anastasia.Dyubaylo in Direct Messages. Your stories are very welcome! So! Don't miss an excellent opportunity to meet and discuss new solutions with like-minded peers and to find out what's new in InterSystems technology. ⏱ Time: September 25, 2019 from 5:30 p.m. to 9 p.m. 📍Place: Champions Restaurant (Left Field Room), located on the 2nd floor of the Boston Marriott Copley Place ✅ Registration: RSVP for Boston InterSystems Developers Meetup* We look forward to seeing you! --- *Space is limited, so register today to secure your place. Admission free, registration is mandatory for attendees. Hi folks!If you happen to visit Global Summit 2019 this year - please join us on InterSystems Developers meetup on the last day of the summit, just after DevOps and AI symposium at the same building.Come to Champions, Copley at 5-30pm to chat and discuss in a relaxed atmosphere your dev experience with InterSystems IRIS.RSVP here ;)See you in Boston! Will this presentation be recorded. I cannot attend due to distance but will like to view this presentationThanksGeoV Hi George!Yes, we plan to have a Livestream. Stay tuned with the topic - we'll publish the link. This will be on Developers Video channel. Agenda update for the meetup: "InterSystems IRIS and the Cloud" session by @Anton.Umnikov “In this session we'll talk about how IRIS can interoperate with various components of the public cloud ecosystem, such as S3 storage, SageMaker machine learning framework, Elastic Map Reduce and others.” Space is limited, RSVP today! A bit more about my session "Falling in love with Visual Studio Code": According to the 2019 StackOverflow Developer Survey, Visual Studio Code is number 1. More than 50% of those surveyed said they use it. Why is it so popular? Why do I like it? Why do you? Today's evening on Global Summit 2019 promises to be very interesting and full of developers talks! Don't miss! Don't forget to RSVP here Thanks for everyone who came! We had a pretty nice event, hope to see you soon on the next InterSystems Dev Meetup in Boston! Hey Developers, Thanks to all participants of InterSystems Developers Meetup at InterSystems Global Summit 2019! Great speakers, great sessions! Here're some photos from the meetup: Big applause for @Evgeny.Shvarov, @Eduard.Lebedyuk, @Dmitry.Maslennikov, @Anton.Umnikov and @John.Murray! More photos from Global Summit 2019 you can find on InterSystems Developers Twitter or by following our official hashtag #GlobalSummit19. Your feedback is very welcome!

Hi Developers!Often I find questions on how to install IRIS, connect to IRIS from IDE, setup the environment, compile, debug, maintain the repository.Here below possibly the shortest way to set up all the environment and start development with ObjectScript on InterSystems IRIS.PrerequisitesMake sure you have Git, Docker, and VSCode installedInstall Docker and ObjectScript extensions into VSCodeSign in or Create an account on GithubHere we go!To start development you do the following:Use the template repository and create your own repository on Github.Clone your repository with git on your desktop in terminalOpen repository in VSCodeUse docker-compose.yml to build the container with InterSystems IRIS and import all the ObjectScript from /src folder into USER namespace of IRIS container.Open a terminal to IRIS and call the imported ObjectScript codeMake a change to ObjectScript code and compile itCommit and push changes to your GitHub repositoryCheck the screencast below: Or check the long video with all the explanations.What's next? Start learning ObjectScript with Online Learning and Documentation.Also check Beginner posts, Best Practices and ObjectScript code guidelines.Happy coding! Noticed some good stuff in @Dmitry.Maslennikov's iris-template repo and updated mine foundation template for development with IRIS Community Edition in ObjectScript. It's much easier now to run ObjectScript instructions in Dockerfile. Check the basic Dockerfie: ARG IMAGE=intersystems/iris:2019.1.0S.111.0 ARG IMAGE=store/intersystems/irishealth:2019.3.0.308.0-community ARG IMAGE=store/intersystems/iris-community:2019.3.0.309.0 FROM $IMAGE USER root WORKDIR /opt/irisapp RUN chown ${ISC_PACKAGE_MGRUSER}:${ISC_PACKAGE_IRISGROUP} /opt/irisapp USER irisowner COPY Installer.cls . COPY src src COPY irissession.sh / SHELL ["/irissession.sh"] RUN \ do $SYSTEM.OBJ.Load("Installer.cls", "ck") \ set sc = ##class(App.Installer).setup() # bringing the standard shell back SHELL ["/bin/bash", "-c"] CMD [ "-l", "/usr/irissys/mgr/messages.log" ] And another which installs ZPM and Webterminal: ARG IMAGE=intersystems/iris:2019.1.0S.111.0 ARG IMAGE=store/intersystems/iris-community:2019.3.0.309.0 FROM $IMAGE USER root WORKDIR /opt/irisapp RUN chown ${ISC_PACKAGE_MGRUSER}:${ISC_PACKAGE_IRISGROUP} /opt/irisapp USER irisowner RUN mkdir -p /tmp/deps \ && cd /tmp/deps \ && wget -q https://pm.community.intersystems.com/packages/zpm/latest/installer -O zpm.xml COPY Installer.cls . COPY src src COPY irissession.sh / # running IRIS and open IRIS termninal in USER namespace SHELL ["/irissession.sh"] # below is objectscript executed in terminal # each row is what you type in terminal and Enter RUN \ do $SYSTEM.OBJ.Load("Installer.cls", "ck") \ set sc = ##class(App.Installer).setup() \ Do $system.OBJ.Load("/tmp/deps/zpm.xml", "ck") \ zn "IRISAPP" \ zpm "install webterminal" # bringing the standard shell back SHELL ["/bin/bash", "-c"] CMD [ "-l", "/usr/irissys/mgr/messages.log" ] First, thanks for this. It go me up and running pretty fast (as title says!). Couple of things: - The notes/documentation say that code will be loaded into USER namespace, however it's actually being loaded into IRISAPP (as configured in docckerfiles). - The jason.config is pointing to USER namespace so any new files and changes to existing will be actually loaded into USER instead of IRISAPP - Make sure it's all consistent - The webapp (irisweb) is missing a config for the directory where to store files. I fixed this by modifying the app in management portal. Need to address the installation file/dockerfile - Haven't been able to make CSPs flow to the container the same as classes. I'm sure I'm missing something but haven't figured out what yet. Any tips? Maybe I'm placing files in the wrong location? Right now I created a csp/irisweb folder under src folder. - The notes/documentation say that code will be loaded into USER namespace, however it's actually being loaded into IRISAPP (as configured in docckerfiles). Because I made an update to the code recently) And not to the documentation) PR is welcome, or I'll change it by myself soon. Or add an issue! - The jason.config is pointing to USER namespace so any new files and changes to existing will be actually loaded into USER instead of IRISAPP Yes, it's a bug from previous version. Need to be fixed, thanks! - The webapp (irisweb) is missing a config for the directory where to store files. I fixed this by modifying the app in management portal. Need to address the installation file/dockerfile Cool! Do you want to make a PR? - Haven't been able to make CSPs flow to the container the same as classes. I'm sure I'm missing something but haven't figured out what yet. Any tips? Maybe I'm placing files in the wrong location? Right now I created a csp/irisweb folder under src folder. You need to COPY this files from /csp in sources to /usr/irissys/mgr/csp/yourwebapp in Dockerfile OK, I'll give it a try and create a PR once I have a new config file. Thanks! Hi @warlin.Garcia ! I pushed the commit into the repo which fixes Namespace and README issue, thanks! Thank you. I'll check on it. Do you have any tips to make csp changes flow in realtime the same as classes do? I've modified the dockerfile to copy the contents of my csp directory into the container, however my edits to CSPs are not flowing realtime which forces me to rebuild the container everytime to get my updates. Sure! just add the volume mapping in docker-compose.yml file which maps folder /csp in sources into /csp directory in docker. Got it all working. Thank you! Updated the Installer.cls file - now you can set up the namespace and path in variables "Namespace" and "app" respectfully at the top of Installer.cls. <Default Name="Namespace" Value="IRISAPP"/> <Default Name="app" Value="irisapp" /> This is convenient if you need to install the app to the namespace with your name. Notice, that if you want instantly edit and compile the code of your project with VSCode don't forget to change the Namespace parameter in settings.json too.

Hi colleagues! InterSystems Grand Prix 2023 unites all the key features of InterSystems IRIS Data Platform! Thus we invite you to use the following features and collect additional technical bonuses that will help you to win the prize! Here we go! LLM AI or LangChain usage: Chat GPT, Bard and others - 6 InterSystems FHIR SQL Builder- 5 InterSystems FHIR - 3 IntegratedML - 4 Native API - 3 Embedded Python - 4 Interoperability - 3 Production EXtension(PEX) - 2 Adaptive Analytics (AtScale) Cubes usage - 3 Tableau, PowerBI, Logi usage - 3 InterSystems IRIS BI - 3 Columnar Index Usage - 1 Docker container usage - 2 ZPM Package deployment - 2 Online Demo - 2 Unit Testing - 2 Implement InterSystems Community Idea - 4 First Article on Developer Community - 2 Second Article On DC - 1 Code Quality pass - 1 First Time Contribution - 3 Video on YouTube - 3 LLM AI or LangChain usage: Chat GPT, Bard and others - 6 points Collect 6 bonus expert points for building a solution that uses LangChain libs or Large Language Models (LLM) such as ChatGPT, Bard and other AI engines like PaLM, LLaMA and more. AutoGPT usage counts too. A few examples already could be found in Open Exchange: iris-openai, chatGPT telegram bot. Here is an article with langchain usage example. InterSystems FHIR SQL Builder - 5 points InterSystems FHIR SQL Builder is a feature of InterSystems IRIS for Health that helps to map FHIR resources to SQL tables and consume it via SQL queries in your application. Learn more in the documentation. Online course.Here is an example on Open Exchange. NB: If you implement InterSystems FHIR SQL Builder the bonus 3 points for InterSystems FHIR as a Service and IRIS For Health is not included. InterSystems FHIR as a Service and IRIS For Health - 3 points We invite all developers to build new or test existing applications using InterSystems FHIR Server (FHIRaaS). Sign in to the portal, make the deployment and start using your InterSystems FHIR server on AWS in your application for the programming contest. You can also build an FHIR application using InterSystems IRIS for Health, docker version. You can take the IRIS-FHIR-Template which prepares the FHIR server during the docker image building. The documentation for FHIR API 4.0.1 could be found here. Learn more in InterSystems IRIS for Health documentation. IntegratedML usage - 4 points 1. Use InterSystems IntegratedML in your AI/ML solution. Here is the template that uses it. InterSystems IntegratedML template 2. Data import tools: Data Import Wizard CSVGEN - CSV import util CSVGEN-UI - the web UI for CSVGEN 3. Documentation: Using IntegratedML 4. Online courses & videos: Learn IntegratedML in InterSystems IRIS Preparing Your Data for Machine Learning Predictive Modeling with the Machine Learning Toolkit IntegratedML Resource Guide Getting Started with IntegratedML Machine Learning with IntegratedML & Data Robot InterSystems Native API usage - 3 points You get this bonus if you access the data in your Full-Stack application using any of the InterSystems Native API options: .NET, Java, Python, Node.js. Learn more here. Embedded Python - 4 points Use Embedded Python in your application and collect 4 extra points. You'll need at least InterSystems IRIS 2021.2 for it. NB: If you also use Native API for Python only Embedded Python bonus counts. Interoperability Productions with BPL or DTL - 3 points One of the key features of IRIS Interoperability Productions is a business process, which could be described by BPL (Business Process Language). Learn more about Business Processes in the documentation. Business Rule is a no-code/low-code approach to managing the processing logic of the interoperability production. In InterSystems IRIS you can create a business rule which you can create visually or via the ObjectScript representation. You can collect the Business Process/Business Rule bonus if you create and use the business process or business rule in your interoperability production. Business Rule Example Learn more on Business Rules in the documentation Production EXtension (PEX) Usage - 2 points PEX is a Python, Java or .NET extension of Interoperability productions. You get this bonus if you use PEX with Python, JAVA or .NET in your interoperability production. PEX Demo. Learn more on PEX in Documentation. InterSystems IRIS has Python Pex module that provides the option to develop InterSystems Interoperability productions from Python. Use it and collect 3 extra points for your application. It's OK also to use alternative python.pex wheel introduced by Guillaume Ronguier. You can also use Python Interoperability which is a PEX addon module for InterSystems IRIS on python provided by @Guillaume.Rongier7183 that gives the opportunity to develop InterSystems IRIS interoperability solutions in clear python. Article to use PEX for Hugging Face, example. Adaptive Analytics (AtScale) Cubes usage - 3 pointsInterSystems Adaptive Analytics provides the option to create and use AtScale cubes for analytics solutions. You can use the AtScale server we set up for the contest (URL and credentials can be collected in the Discord Channel) to use cubes or create a new one and connect to your IRIS server via JDBC. The visualization layer for your Analytics solution with AtScale can be crafted with Tableau, PowerBI, Excel, or Logi. Documentation, AtScale documentation Training Tableau, PowerBI, Logi usage - 3 points Collect 3 points for the visualization you made with Tableau, PowerBI, or Logi - 3 points per each. Visualization can be made vs a direct IRIS BI server or via the connection with AtScale. Logi is available on behalf of the InterSystems Reports solution - you can download the composer on InterSystems WRC. A temporary license can be collected in the discord channel. Documentation Training InterSystems IRIS BI - 3 points InterSystems IRIS Business Intelligence is a feature of IRIS which gives you the option to create BI cubes and pivots against persistent data in IRIS and deliver then this information to users using interactive dashboards. Learn more The basic iris-analytics-template contains examples of an IRIS BI cube, pivot, and a dashboard. Here is the set of examples of IRIS BI solutions: Samples BI Covid19 analytics Analyze This Game of Throne Analytics Pivot Subscriptions Error Globals Analytics Creating InterSystems IRIS BI Solutions Using Docker & VSCode (video) The Freedom of Visualization Choice: InterSystems BI (video) InterSystems BI(DeepSee) Overview (online course) InterSystems BI(DeepSee) Analyzer Basics (online course) Columnar Index Usage - 1 point Columnar Index feature can significantly improve the performance of analytics queries. Use columnar indexes in your solution's persistent data model and collect 1 extra bonus point. Learn more about Columnar Indexes. Docker container usage - 2 points The application gets a 'Docker container' bonus if it uses InterSystems IRIS running in a docker container. Here is the simplest template to start from. ZPM Package deployment - 2 points You can collect the bonus if you build and publish the ZPM(InterSystems Package Manager) package for your Full-Stack application so it could be deployed with: zpm "install your-multi-model-solution" command on IRIS with ZPM client installed. ZPM client. Documentation. Online Demo of your project - 2 pointsCollect 2 more bonus points if you provision your project to the cloud as an online demo. You can do it on your own or you can use this template - here is an Example. Here is the video on how to use it. Unit Testing - 2 points Applications that have Unit Testing for the InterSystems IRIS code will collect the bonus. Learn more about ObjectScript Unit Testing in Documentation and on Developer Community. Implement Community Opportunity Idea - 4 points Implement any idea from the InterSystems Community Ideas portal which has the "Community Opportunity" status. This will give you 4 additional bonus points. Article on Developer Community - 2 points Post an article on Developer Community that describes the features of your project and collect 2 points for the article. The Second article on Developer Community - 1 point You can collect one more bonus point for the second article or the translation regarding the application. The 3rd and more will not bring more points but the attention will all be yours. Code quality pass with zero bugs - 1 point Include the code quality Github action for code static control and make it show 0 bugs for ObjectScript. First Time Contribution - 3 points Collect 3 bonus points if you participate in InterSystems Open Exchange contests for the first time! Video on YouTube - 3 points Make the Youtube video that demonstrates your product in action and collect 3 bonus points per each. The list of bonuses is subject to change. Stay tuned! The bonus set is updated. Two bonuses added: 4 points for the community opportunity implementation. 1 point for the columnar index usage. @Evgeny.Shvarov - I submitted my application for the contest and I'm really excited! Could you please let me know how I can claim the bonus points? Thanks in advance. Hi @Ikram.Shah3431 ! Tomorrow we'll publish the bonus table for all the applications. If something is not accurate you comment here or in Discord May I ask if this score is an expert score or a community score?

[In this GitHub](https://github.com/grongierisc/iris-python-flask-api-template) based on [this InterSystems community rest api template](https://github.com/intersystems-community/iris-rest-api-template) Guillaume and I have created this example of all the import CRUD operations usable using ONLY Python on IRIS and using Flask. Using the IRIS ORM or by simply doing SQL requests as both methods are seen in the GitHub. # 1. intersystems-iris-docker-rest-template This is a template of a REST API application built in python in InterSystems IRIS. It also has OPEN API spec, can be developed with Docker and VSCode. - [1. intersystems-iris-docker-rest-template](#1-intersystems-iris-docker-rest-template) - [2. Prerequisites](#2-prerequisites) - [3. Installation](#3-installation) - [3.1. Installation for development](#31-installation-for-development) - [3.2. Management Portal and VSCode](#32-management-portal-and-vscode) - [3.3. Having the folder open inside the container](#33-having-the-folder-open-inside-the-container) - [4. How it works](#4-how-it-works) - [5. How to Work With it](#5-how-to-work-with-it) - [5.1. POST request](#51-post-request) - [5.1.1. Testing POST request](#511-testing-post-request) - [5.1.2. How POST request works](#512-how-post-request-works) - [5.2. GET requests](#52-get-requests) - [5.2.1. Testing GET request](#521-testing-get-request) - [5.2.2. How GET request works](#522-how-get-request-works) - [5.3. PUT request](#53-put-request) - [5.3.1. Testing PUT request](#531-testing-put-request) - [5.3.2. How PUT request works](#532-how-put-request-works) - [5.4. DELETE request](#54-delete-request) - [5.4.1. Testing DELETE request](#541-testing-delete-request) - [5.4.2. How DELETE request works](#542-how-delete-request-works) - [6. How to start coding](#6-how-to-start-coding) - [7. What's inside the repo](#7-whats-inside-the-repo) - [7.1. Dockerfile](#71-dockerfile) - [7.2. .vscode/settings.json](#72-vscodesettingsjson) - [7.3. .vscode/launch.json](#73-vscodelaunchjson) # 2. Prerequisites Make sure you have [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git) and [Docker desktop](https://www.docker.com/products/docker-desktop) installed. It is to be noted that the table Sample.Person was already created in advance for the demo using in the management portal in the sql tab: ```sql CREATE TABLE Sample.Person ( Company VARCHAR(50), DOB DATE, Name VARCHAR(4096), Phone VARCHAR(4096), Title VARCHAR(50) ) ``` # 3. Installation ## 3.1. Installation for development Clone/git pull the repo into any local directory e.g. like it is shown below: ``` $ git clone https://github.com/grongierisc/iris-python-flask-api-template.git ``` Open the terminal in this directory and run: ``` $ DOCKER_BUILDKIT=1 docker-compose up -d --build ``` ## 3.2. Management Portal and VSCode This repository is ready for [VS Code](https://code.visualstudio.com/). Open the locally-cloned `formation-template-python` folder in VS Code. If prompted (bottom right corner), install the recommended extensions. ## 3.3. Having the folder open inside the container **It is really important** to be *inside* the container before coding. For this, docker must be on before opening VSCode. Then, inside VSCode, when prompted (in the right bottom corner), reopen the folder inside the container so you will be able to use the python components within it. The first time you do this it may take several minutes while the container is readied. [More information here](https://code.visualstudio.com/docs/remote/containers)  By opening the folder remote you enable VS Code and any terminals you open within it to use the python components within the container. Configure these to use `/usr/irissys/bin/irispython` # 4. How it works The `app.py`, once launched (inside the container) will gather CRUD request. Depending on the type of the request, the right message will be created to send to the `FlaskService`, this service will call the CrudPerson operation that will, depending on the type of the message send from the service to it, dispatch the information needed to do the action requested. For more details you can check the `How it works` part of [this fully documented demo](https://github.com/grongierisc/interoperability-embedded-python). # 5. How to Work With it This template creates /crud REST web-application on IRIS which implements 4 types of communication: GET, POST, PUT and DELETE aka CRUD operations. These interface works with a sample persistent class `Person` found in `src/python/person/obj.py`. First of all, it is needed to start the 'app.py' situated in `src/python/person/app.py` using flask. To do this, go in the `app.py` file, then to the `run and debug` window in VSCode and select `Python: Flask` then run. This will run the app. ## 5.1. POST request ### 5.1.1. Testing POST request Create a POST request, for example in Postman or in RESTer for mozilla, with raw data in JSON like: ```json {"name":"Elon Musk","title":"CEO","company":"Tesla","phone":"123-123-1233","dob":"1982-01-19"} ``` Using `Content-Type` as `application/json` Adjust the authorisation if needed - it is basic for container with default login and password for IRIS Community edition container. Send the POST request to `localhost:5000/persons/` This will create a record in the table Sample.Person of IRIS and return the `id` of the newly added `Person`  of the POST request to add `Elon Musk` to the table. ### 5.1.2. How POST request works ```python def create_person(self,request:CreatePersonRequest): """ > Create a new person in the database and return the new person's ID :param request: The request object that was passed in from the client :type request: CreatePersonRequest :return: The ID of the newly created person. """ # sqlInsert = 'insert into Sample.Person values (?,?,?,?,?)' # iris.sql.exec(sqlInsert,request.person.company,dob,request.person.name,request.person.phone,request.person.title) # IRIS ORM person = iris.cls('Sample.Person')._New() if (v:=request.person.company) is not None: person.Company = v if (v:=request.person.name) is not None: person.Name = v if (v:=request.person.phone) is not None: person.Phone = v if (v:=request.person.title) is not None: person.Title = v if (v:=request.person.dob) is not None: person.DOB = v Utils.raise_on_error(person._Save()) return CreatePersonResponse(person._Id()) ``` Using IRIS ORM we can create a new `Person` and save into our database. ## 5.2. GET requests ### 5.2.1. Testing GET request To test GET you need to have some data. You can create it with a [POST request](#41-testing-post-request). This REST API exposes two GET requests: all the data and one record. To get all the data in JSON call: ``` localhost:5000/persons/all ``` To request the data for a particular record provide the id in GET request like 'localhost:5000/persons/id', here is an example: ``` localhost:5000/persons/1 ``` This will return JSON data for the person with ID=1, something like that: ```json {"name":"Elon Musk","title":"CEO","company":"Tesla","phone":"123-123-1233","dob":"1982-01-19"} ``` ### 5.2.2. How GET request works ```python def get_person(self,request:GetPersonRequest): """ > The function takes a `GetPersonRequest` object, executes a SQL query, and returns a `GetPersonResponse` object :param request: The request object that is passed in :type request: GetPersonRequest :return: A GetPersonResponse object """ sql_select = """ SELECT Company, DOB, Name, Phone, Title FROM Sample.Person where ID = ? """ rs = iris.sql.exec(sql_select,request.id) response = GetPersonResponse() for person in rs: response.person= Person(company=person[0],dob=person[1],name=person[2],phone=person[3],title=person[4]) return response def get_all_person(self,request:GetAllPersonRequest): """ > This function returns a list of all the people in the Person table :param request: The request object that is passed to the service :type request: GetAllPersonRequest :return: A list of Person objects """ sql_select = """ SELECT Company, DOB, Name, Phone, Title FROM Sample.Person """ rs = iris.sql.exec(sql_select) response = GetAllPersonResponse() response.persons = list() for person in rs: response.persons.append(Person(company=person[0],dob=person[1],name=person[2],phone=person[3],title=person[4])) return response ``` This time, using the `iris python` `sql.exec` function, we can directly run SQL code inside the IRIS database, gather the information needed and send it back to the API and to the user. ## 5.3. PUT request ### 5.3.1. Testing PUT request PUT request could be used to update the records. This needs to send the similar JSON as in POST request above supplying the id of the updated record in URL. For example we want to change the record with id=5. Prepare the JSON in raw like following: ``` {"name":"Jeff Besos","title":"CEO","company":"Amazon","phone":"123-123-1233","dob":"1982-01-19"} ``` and send the put request to: ``` localhost:5000/persons/5 ``` ### 5.3.2. How PUT request works ```python def update_person(self,request:UpdatePersonRequest): """ > Update a person in the database :param request: The request object that will be passed to the service :type request: UpdatePersonRequest :return: UpdatePersonResponse() """ # IRIS ORM if iris.cls('Sample.Person')._ExistsId(request.id): person = iris.cls('Sample.Person')._OpenId(request.id) if (v:=request.person.company) is not None: person.Company = v if (v:=request.person.name) is not None: person.Name = v if (v:=request.person.phone) is not None: person.Phone = v if (v:=request.person.title) is not None: person.Title = v if (v:=request.person.dob) is not None: person.DOB = v Utils.raise_on_error(person._Save()) return UpdatePersonResponse() ``` Using IRIS ORM we can check if the id leads to a `Person`, if it does, we can update it using our new information and save it into our database. ## 5.4. DELETE request ### 5.4.1. Testing DELETE request For delete request this REST API expects only the id of the record to delete. E.g. if the id=5 the following DELETE call will delete the record: ``` localhost:5000/persons/5 ``` ### 5.4.2. How DELETE request works ```python def delete_person(self,request:DeletePersonRequest): """ > Delete a person from the database :param request: The request object that is passed to the service :type request: DeletePersonRequest :return: The response is being returned. """ sql_select = """ DELETE FROM Sample.Person as Pers WHERE Pers.id = ? """ rs = iris.sql.exec(sql_select,request.id) response = DeletePersonResponse() return response ``` This time, using the `iris python` `sql.exec` function, we can directly run SQL code inside the IRIS database and delete the person. # 6. How to start coding This repository is ready to code in VSCode with InterSystems plugins. Open `/src/python/person/app.py` to change anything on the api. Open `/src/python/person/bo.py` to be able to change things related to the internal requests, this is where you can use SQL - it will be compiled in running IRIS docker container. # 7. What's inside the repo ## 7.1. Dockerfile The simplest dockerfile to start IRIS. Use the related docker-compose.yml to easily setup additional parametes like port number and where you map keys and host folders. ## 7.2. .vscode/settings.json Settings file to let you immedietly code in VSCode with [VSCode ObjectScript plugin](https://marketplace.visualstudio.com/items?itemName=daimor.vscode-objectscript)) ## 7.3. .vscode/launch.json Config file if you want to debug with VSCode ObjectScript If you are interested, check out the formation I made on the tools I used in this GitHub : https://github.com/LucasEnard/formation-template-python As Issues are disabled in the GitHub Repo I place my issue here. Container starts fine Postman fails:POST http://localhost:5000/persons/ Error: connect ECONNREFUSED 127.0.0.1:5000 Network agent: "Desktop Agent" Request Headers Content-Type: application/json User-Agent: PostmanRuntime/7.29.2 Accept: */* Cache-Control: no-cache Postman-Token: d40ec7c2-5b24-4944-8a76-c4cbf2685bf7 Host: localhost:5000 Accept-Encoding: gzip, deflate, br Connection: keep-alive Request Body {"name":"Elon Musk","title":"CEO","company":"Tesla","phone":"123-123-1233","dob":"1982-01-19"} as port 5000 is not mapped in docker-compose.yml this might be related ??? DONE!I found my solution and placed it in a PullRequest.it was slightly more than just a missing port. Thanks Robert for the PullRequest and making sure of the quality of the demos/articles. Sometimes it's hard do build and test at the same time, this is why in medium to large projects the development teams are different from the testers. Thanks again :) You're welcome. Those things keep my mind in speed. I failed in testing.where can I find the pull request and how to use it? my PR contains an update on docker-compose.ymland a bash script startflask.shall available here https://github.com/rcemper/iris-python-flask-api-template Sep.23 all merged I'm getting 403 when I do a Post request on localhost:5000/persons/. What am I doing wrong? Yes, the flask app run on 8080 and map on docker compose to 4040. I update the github to make flask run on 5000 and map to 5000. @Guillaume.Rongier7183 , just curious, why do you need CallIn service enabled? Still have Forbidden after update and rebuild: Because underneath embedded python is using CallIn Service of IRIS. And by default this service is off. So, every time I need to use embedded python with IRIS I need to turn CallIn on?