#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 Eduard Lebedyuk · Sep 12, 2019

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.

Proxy Gateway allows generation of ObjectScript classes for Python classes. Instantinate objects, call object and class methods using familiar ObjectScript code (docs).

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Article Eduard Lebedyuk · Apr 12, 2019 1m read

This series of articles would cover Python Gateway for InterSystems Data Platforms. Leverage modern AI/ML tools and execute Python code and more from InterSystems IRIS. This project brings you the power of Python right into your InterSystems IRIS environment:

  • Execute arbitrary Python code
  • Seamlessly transfer data from InterSystems IRIS into Python
  • Build intelligent Interoperability business processes with Python Interoperability Adapter
  • Save, examine, modify and restore Python context from InterSystems IRIS

Index

The plan for the series so far (subject to change).

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Article Zhong Li · Mar 15, 2019 15m read

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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Article Niyaz Khafizov · Jul 27, 2018 4m read

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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InterSystems Official Jeff Fried · May 9, 2019

The preview release of InterSystems IRIS 2019.2 is now  available - give it a try!

 

Container images are available via the WRC's preview download site.

The build number for these releases is 2019.2.0.100.0.

InterSystems IRIS Data Platform 2019.2  is the first CD (continuous delivery) release of InterSystems IRIS.  It has many new capabilities including:

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Question Mads Lien · May 8, 2019

Hi

I am working with a Caché system with a Python binding and big datasets in health care. I am using the Python library Pandas and Jupyter notebook for data manipulation and often special modules for different projects, including different versions of Python. To keep the environments separated, I have been testing Docker, but I am at loss on how to install the Python binding. Has anyone any experience with this? Or better yet, a Docker image that has the binding installed?

I am also considering that Docker might not be the suitable for this situation and I am grateful for any thoughts on this.

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Announcement Anastasia Dyubaylo · Mar 26, 2019

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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Article Zhong Li · Mar 14, 2019 10m read

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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Question Tosh Ohta · Aug 30, 2018

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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Article Dmitrii Kuznetsov · Jan 21, 2019 10m read

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.

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Question Dmitrii Kuznetsov · Jan 9, 2019

Found a strange documentation block about Python bindings in Chapter 3.6 of the Caché manipulation functions with time and date. It looks like this text accidentally copied one to one of the Perl binging documentation. It's funny that the packages of functions called PTIME_STRUCTPtr, PDATE_STRUCTPtr and PTIMESTAMP_STRUCTPtr is suspicious for Python :)  

On the other hand, nothing is said about the functions parse_time, parse_date, parse_timestamp, which are present in /dev/python/intersys/pythonbind.py ahhh!

Has anyone encountered this problem?

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Article Niyaz Khafizov · Oct 8, 2018 16m read

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:

In this series of articles, we explore Machine Learning and record linkage.

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Question Daniel Martinez Contador · Sep 12, 2018

I'm new to Iris, trying to follow this guide ( https://community.intersystems.com/post/k-means-clustering-iris-dataset ) about using clustering. I've followed all instructions until showing the data. At that point, `dataFrame.show()` fails with `java.sql.SQLException: Access Denied`.

I'm using IRIS 2018.12.609.0 on Windows 10 Pro 64 bits. Python is 3.6.6, PySpark is 2.3.1, installed from Anaconda (Python 3.6.6 |Anaconda, Inc.| (default, Jun 28 2018, 11:27:44) [MSC v.1900 64 bit (AMD64)] on win32).

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Question Carina Mueler · Sep 7, 2018

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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Question Mark Anthony Manalo · Aug 2, 2018

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.

Thanks a lot for any help and information.

Kind regards,

mark

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Question Oliver James · Jun 5, 2018

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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Announcement Athanassios Hatzis · Jan 2, 2018

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.

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Article David E Nelson · Mar 9, 2017 9m read

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. Spark also supports Python (PySpark) and R (SparkR) and includes libraries for SQL

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Question Athanassios Hatzis · Aug 29, 2017

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",[])

I am opening the 10th record of Sample.Person class and then I am calling an object method (PrintPerson). 

Method PrintPerson()

  {

    Write !, "Name: ", ..Name

    Quit  

  }

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Article Fabian Haupt · Jan 20, 2017 8m read

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.

The series is closely tying into Murray's excellent series about Caché performance and monitoring (see here) and more specifically this article.

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Article Fabian Haupt · Aug 3, 2017 3m read

In this short article we talk about how to get Yape running in a docker container to avoid having to setup python on your machine.

It's been a while since the last article in this series, so let's recap quickly.

We talked about using matplotlib to create a basic graph. Afterwards we introduced dynamic graphs using bokeh. In the 3rd part we talked about generating heatmaps using monlbl data.

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Article Vitaliy Serdtsev · Jun 22, 2017 4m read

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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