Hi Community,

Imagine enabling your application to read text to your customer? This is now possible with the new IRIS feature, Embedded Python. With this new functionality IRIS can natively run any open source or commercial Python libraries natively. gTTS (https://pypi.org/project/gTTS/) is a free library that transforms text into audio using the Google Translate service.

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This formation, accessible on my GitHub, will cover, in half a hour, how to read and write in csv and txt files, insert and get inside the IRIS database and a distant database using Postgres or how to use a FLASK API, all of that using the Interoperability framework using ONLY Python following the PEP8 convention.

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Motivation

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.

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1. interoperability-embedded-python

This proof of concept aims to show how the iris interoperability framework can be use with embedded python.

1.1. Table of Contents

1.2. Example

import grongier.pex
import iris
import MyResponse

class MyBusinessOperation(grongier.pex.BusinessOperation):

    def OnInit(self):
        print("[Python] ...MyBusinessOperation:OnInit() is called")
        self.LOGINFO("Operation OnInit")
        return

    def OnTeardown(self):
        print("[Python] ...MyBusinessOperation:OnTeardown() is called")
        return

    def OnMessage(self, messageInput):
        if hasattr(messageInput,"_IsA"):
            if messageInput._IsA("Ens.StringRequest"):
                self.LOGINFO(f"[Python] ...This iris class is a Ens.StringRequest with this message {messageInput.StringValue}")
        self.LOGINFO("Operation OnMessage")
        response = MyResponse.MyResponse("...MyBusinessOperation:OnMessage() echos")
        return response

1.3. Regsiter a component

No ObjectScript code is needed.

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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:

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Article
Evgeniy Potapov · Feb 27 2m read
Dash-Python-IRIS

We are happy to share interesting information with you, as well as tell you why Python is good, where it is used.

Among the most used libraries are NumPy and Pandas. NumPy (Numerical Python) is used to sort large datasets. It simplifies mathematical operations and their vectorization on arrays. Pandas offers two data structures: Series (a list of elements) and Data Frames (a table with multiple columns). This library converts data into a Data Frame, allowing you to remove and add new columns, as well as perform various operations.

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Hi Community,

This post is a introduction of my openexchange iris-python-apps application. Build by using Embedded Python and Python Flask Web Framework
Application also demonstrates some of the Python functionalities like Data Science, Data Plotting, Data Visualization and QR Code generation.

image

 

 Features

  •  Responsive bootstrap IRIS Dashboard

  •  View dashboard details along with interoperability events log and messages.

  •  Use of Python plotting from IRIS

  •  Use of Jupyter Notebook

  •  Introduction to Data Science, Data Plotting and Data Visualization.

  •  QR Code generator from python.

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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

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