#Python

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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

Official site.

InterSystems Python Binding Documentation.

Announcement
· Sep 12, 2019
Python Gateway 0.8 release

I'm happy to announce the latest Python Gateway release.

This is not an InterSystems product, it is community supported open source project.

Download new release from GitHub.

Now for the new features.

Fast transfer. Pass globals, classes and tables from InterSystems IRIS to Python with ease and speed (10x faster than old QueryExecute). Documentation.

Open Exchange app
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Hello,

I'm trying to set Caché-Python Binding on Mac, but there is a problem.

I performed installation and configuration of Caché-Python binding module based on the manual (URL)
including setting of PATH and LD_LIBRARY_PATH in "bash_profile",
and they seems to be done successfully (there was no error in the process).

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Keywords: Jupyter Notebook, Tensorflow GPU, Keras, Deep Learning, MLP, and HealthShare

1. Purpose and Objectives

In previous"Part I" we have set up a deep learning demo environment. In this "Part II" we will test what we could do with it.

Many people at my age had started with the classic MLP (Multi-Layer Perceptron) model. It is intuitive hence conceptually easier to start with.

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Hi Community!

Please welcome a new video on InterSystems YouTube Channel:

InterSystems and Python QuickStart

https://www.youtube.com/embed/HYc5wQ0uURg
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Article
· Jul 27, 2018 4m read
Load a ML model into InterSystems IRIS

Hi all. Today we are going to upload a ML model into IRIS Manager and test it.

Note: I have done the following on Ubuntu 18.04, Apache Zeppelin 0.8.0, Python 3.6.5.

Introduction

These days many available different tools for Data Mining enable you to develop predictive models and analyze the data you have with unprecedented ease. InterSystems IRIS Data Platform provide a stable foundation for your big data and fast data applications, providing interoperability with modern DataMining tools.

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Hey Community!

The latest webinar, recorded by InterSystems Sales Engineers @Sergey Lukyanchikov and @Eduard Lebedyuk, is already on InterSystems Developers YouTube! Please welcome:

"Machine Learning Toolkit (Python, ObjectScript, Interoperability, Analytics) for InterSystems IRIS"

https://www.youtube.com/embed/z9O0F1ovBUY
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Hey Developers!

Do you want to reap the benefits of the advances in the fields of artificial intelligence and machine learning? With InterSystems IRIS and the Machine Learning (ML) Toolkit it’s easier than ever.

Join InterSystems Sales Engineers, @Sergey Lukyanchikov and @Eduard Lebedyuk, for the Machine Learning Toolkit for InterSystems IRIS webinar on Tuesday, April 23rd at 11 a.m. EDT to find out how InterSystems IRIS can be used as both a standalone development platform and an orchestration tool for predictive modelling that helps stitch together Python and other external tools.

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Hi Community!

We are pleased to invite you to the upcoming webinar "Machine Learning Toolkit (Python, ObjectScript, Interoperability, Analytics) for InterSystems IRIS" on 26th of March at 10:00 (Moscow time)!

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Keywords: Anaconda, Jupyter Notebook, Tensorflow GPU, Deep Learning, Python 3 and HealthShare

1. Purpose and Objectives

This "Part I" is a quick record on how to set up a "simple" but popular deep learning demo environment step-by-step with a Python 3 binding to a HealthShare 2017.2.1 instance . I used a Win10 laptop at hand, but the approach works the same on MacOS and Linux.

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Headache-free stored objects: a simple example of working with InterSystems Caché objects in ObjectScript and Python

Neuschwanstein Castle

Tabular data storages based on what is formally known as the relational data model will be celebrating their 50th anniversary in June 2020. Here is an official document – that very famous article. Many thanks for it to Doctor Edgar Frank Codd. By the way, the relational data model is on the list of the most important global innovations of the past 100 years published by Forbes.

On the other hand, oddly enough, Codd viewed relational databases and SQL as a distorted implementation of his theory. For general guidance, he created 12 rules that any relational database management system must comply with (there are actually 13 rules). Honestly speaking, there is zero DBMS's on the market that observes at least Rule 0. Therefore, no one can call their DBMS 100% relational :) If you know any exceptions, please let me know.

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Hi all. We are going to find duplicates in a dataset using Apache Spark Machine Learning algorithms.

Note: I have done the following on Ubuntu 18.04, Python 3.6.5, Zeppelin 0.8.0, Spark 2.1.1

Introduction

In previous articles we have done the following:

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Hey guys,
I need your help.

I am writing a code in Python and I want to create a database and some properties and then to send json files (data) to this database. (I use client-server-model for loading the data into IRIS)

I use curl methods and convert it in Python code with:

curl.trillworks.com/#python

My code so far:

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Hello everyone,

Im just wondering if there is any possibility to "Listen" to a cache DB? We have our cache DB somewhere else provided by a different company, we are provided the interface to connect to that cache DB so we can extract the cache DB every night.

Im just curious if theres a way to "listen" to the cache DB, so if theres any changes on the table in the cache DB, I could make a trigger to extract the table again.

I know i could just set my ETL every hour or so... but that would extract all the tables in cache DB.

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Hi,

this is a public announcement for the first release of Intersystems Cache Object-Relational Mapper in Python 3. Project's main repository is located at Github (healiseu/IntersystemsCacheORM).

About the project

CacheORM module is an enhanced OOP porting of Intersystems Cache-Python binding. There are three classes implemented:

The intersys.pythonbind package is a Python C extension that provides Python application with transparent connectivity to the objects stored in the Caché database.

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Hi - has anyone successfully used the python binding on a mac. I carried out the install instructions per InterSystems documentation and it fails completely. 204 warnings and 9 errors. Obviously this was never tested by InterSystems. Is it even worth pursuing?

Thanks

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Apache Spark has rapidly become one of the most exciting technologies for big data analytics and machine learning. Spark is a general data processing engine created for use in clustered computing environments. Its heart is the Resilient Distributed Dataset (RDD) which represents a distributed, fault tolerant, collection of data that can be operated on in parallel across the nodes of a cluster. Spark is implemented using a combination of Java and Scala and so comes as a library that can run on any JVM.

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This is the first article of a series diving into visualization tools and analysis of time series data. Obviously we are most interested in looking at performance related data we can gather from the Caché family of products. However, as we'll see down the road, we are absolutely not limited to that. For now we are exploring python and the libraries/tools available within that ecosystem.

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Connected Data London Conference

TRIADB is an emerging unique and valuable technology in NoSQL database modelling and BI analytics. The following video is from a presentation and demonstration of TRIADB prototype implemented on top of Intersystems Cache database and driven with a CLI in Python (Jupyter-Pandas). In fact this is the second time in the past year that a prototype based on this technology is implemented and demonstrated. The first one was built on top of OrientDB multi-model database and driven by a Mathematica notebook.

https://www.youtube.com/embed/BiEAbpCOC1A?rel=0
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Hi,

I am experimenting with Cache-Python binding. In the following piece of Python code

import intersys.pythonbind3

conn = intersys.pythonbind3.connection( )
conn.connect_now('localhost[1972]:SAMPLES', '_SYSTEM', '123', None)
samplesDB = intersys.pythonbind3.database(conn)
p10 = samplesDB.openid("Sample.Person",'10',-1,-1)
p10.run_obj_method("PrintPerson",[])

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This is a translation of the following article. Thanks [@Evgeny Shvarov] for the help in translation.

This post is also available on Habrahabrru.

The post was inspired by this Habrahabr article: Interval-associative arrayru→en.

Since the original implementation relies on Python slices, the Caché public may find the following article useful: Everything you wanted to know about slicesru→en.

Note: Please note that the exact functional equivalent of Python slices has never been implemented in Caché, since this functionality has never been required.

And, of course, some theory: Interval treeru→en.

All right, let’s cut to the chase and take a look at some examples.

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