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'm using the PEX framework to create non-polling Business Services in Python. Below is the code I've used to instantiate my Python Business Service from the application I have written:
In my previous articles, I described my Command Line Extension to NativeAPI. Of course, this is also available for any other NativeAPI package. So I created this example in Python as a demo.
FHIR has revolutionized the healthcare industry by providing a standardized data model for building healthcare applications and promoting data exchange between different healthcare systems. As the FHIR standard is based on modern API-driven approaches, making it more accessible to mobile and web developers. However, interacting with FHIR APIs can still be challenging especially when it comes to querying data using natural language.
This project is implemented as a tool for viewing temperature data taken from a temperature sensor installed in Rasperry PI and located in a remote place where there is Internet, for example, in dacha.
In the last article, we talked about a few starters for Django. We learned how to begin the project, ensure we have all the requisites, and make a CRUD. However, today we are going a little further. Sometimes we need to access more complex methods, so today, we will connect IRIS to a Python environment, build a few functions and display them on a webpage. It will be similar to the last discussion, but further enough for you to make something new, even though not enough to feel lost.
As an AI language model, ChatGPT is capable of performing a variety of tasks like language translation, writing songs, answering research questions, and even generating computer code. With its impressive abilities, ChatGPT has quickly become a popular tool for various applications, from chatbots to content creation. But despite its advanced capabilities, ChatGPT is not able to access your personal data. So in this article, I will demonstrate below steps to build custom ChatGPT AI by using LangChain Framework:
A password manager is an important security tool that allows users to store and manage their passwords without the need to remember or write them down in insecure places. In this article, we will explore the development of a simple password manager using the Flask framework and the InterSystems IRIS database.
Key Features
Our password manager application will provide the following key features:
I want to connect IRIS system as it has all the database tables. on top of that I am creating a REST API in python. How can I connect to IRIS DB. here is my example code for connection
after this connection is created but how can I get tables data. Please let me know more about how we can integrate IRIS database into a python REST API.
Yet another example of applying LangChain to give some inspiration for new community Grand Prix contest.
I was initially looking to build a chain to achieve dynamic search of html of documentation site, but in the end it was simpler to borg the static PDFs instead.
Django is a web framework designed to develop servers and APIs, and deal with databases in a fast, scalable, and secure way. To assure that, Django provides tools not only to create the skeleton of the code but also to update it without worries. It allows developers to see changes almost live, correct mistakes with the debug tool, and treat security with ease.
To understand how Django works, let’s take a look at the image:
I'm proud to announce the new release of iris-pex-embedded-python (v2.3.1) with a new command line interface.
This command line is called iop for Interoperability On Python.
First I would like to present in few words the project the main changes since the version 1.
A breif history of the project
Version 1.0 was a proof of concept to show how the interoperability framework of IRIS can be used with a python first approach while remaining compatible with any existing ObjectScript code.
What does it mean? It means that any python developer can use the IRIS interoperability framework without any knowledge of ObjectScript.
Example :
from grongier.pex import BusinessOperation
class MyBusinessOperation(BusinessOperation):
def on_message(self, request):
self.log.info("Received request")
The Jupyter Notebook is an open source web application that can be used to create and share documents that contain live text, code, equations and visualizations. It is maintained by the people at Project Jupyter.
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We have a rule to disable a user account if they have not logged in for a certain number of days. IRIS Audit database logs many events such as login failures for example. It can be configured to log successful logins as well. We have IRIS clusters with many IRIS instances. I like to run queries against audit data from ALL IRIS instances and identify user accounts which have not logged into ANY IRIS instance.
Many factors affect a person's quality of life, and one of the most important is sleep. The quality of our sleep determines our ability to function during the day and affects our mental and physical health. Good quality sleep is critical to our overall health and well-being. Therefore, by analyzing indicators preceding sleep, we can determine the quality of our sleep. This is precisely the functionality of the Sheep's Galaxy application.
Apache Superset is a modern data exploration and data visualization platform. Superset can replace or augment proprietary business intelligence tools for many teams. Superset integrates well with a variety of data sources.
And now it is possible to use with InterSystems IRIS as well.
An online demo is available and it uses IRIS Cloud SQL as a data source.
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Open Exchange app
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