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
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.
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.
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 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:
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.
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.
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?
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.
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.
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 [This is an embedded link, but you cannot view embedded content directly on the site because you have declined the cookies necessary to access it. To view embedded content, you would need to accept all cookies in your Cookies Settings]
Note: Please note that the exact functional equivalent of Python slices has never been implemented in Caché, since this functionality has never been required.
In last week's discussion we created a simple graph based on the data input from one file. Now, as we all know, sometimes we have multiple different datafiles to parse and correlate. So this week we are going to load additional perfmon data and learn how to plot that into the same graph.
Since we might want to use our generated graphs in reports or on a webpage, we'll also look into ways to export the generated graphs.
The reason is that ActiveState Python version 2.7.X is built with Visual Studio 2008 and Microsoft provides Visual Studio 2008, which one must install, so that Python C extensions can be built.
It would be convenient to be able to fetch the whole query result in one operation instead of looping through every row. A fetch_all() method or something similar would provide this functionality I guess. Is there a reason why this is not implemented?
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