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
New to Python. Attempting to use pypyodbc to select data from a table in one Cache database, and inserting into a similarly configured table in another. Process works fine except for tables containing Date types. NULL values in date columns are handled without issue, but when data is present, insert fails with:
An error occurred: argument 7: TypeError: 'NoneType' object cannot be interpreted as an integer.
I was wondering what best practice was for using macros in Embedded Python, i.e. iris.execute('$$$MACRO()') or something else. Does anyone have insight into this?
When setting up a new web app in iris (iris is in a container) iris complains that a WSGI framework is not installed. I have installed python into the container as well as both flask and django via the python virtual environment (see second screenshot) and the python language server is running
Is this the wrong way to install flask? How do I get the container version to recoginize that flask is installed?
We recently moved our workstations to Windows 10 and so we updated all our local installations to IRIS (servers already run IRIS 2019.1). Now we are trying to connect our pyCharm to IRIS but we can't succeed.
I'm trying to convert a python dictionary into an objectscript array but there is an issue with the 'arrayref' function, that is not working as in the linked example.
If anyone has experience debugging Embedded Python or has insight into why an ObjectScript method when called from a Python method would not work but would work when called directly via ObjectScript or in a Python shell, your help would be appreciated!
We have an ObjectScript ClassMethod called GetTemplateString() which takes in a templateName of String type and uses the template name to get the template object, access the Code, and read the code into a templateString. The string version of the Code is returned.
I'm trying to create an indexed table with an vector field so I can search by the vector value. I've been investigating and found that to get the vector value based on the text (token), use a Python method like the following:
I'm a newbie running IRIS in a container (IRIS for UNIX (Ubuntu Server LTS for x86-64 Containers) 2024.3 (Build 217U) Thu Nov 14 2024 17:30:43 EST) and trying to setup Python so I can start working on ML & Autosklearn,my understanding is that IRIS already comes with embedded Python but unable to do something like "import pandas as pd" in VSCode which looks like I need install a more complete version of Python or packages, so what I'm missing?
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`.
In this GitHub we fine tune a bert model from HuggingFace on review data like Yelp reviews.
The objective of this GitHub is to simulate a simple use case of Machine Learning in IRIS : We have an IRIS Operation that, on command, can fetch data from the IRIS DataBase to train an existing model in local, then if the new model is better, the user can override the old one with the new one. That way, every x days, if the DataBase has been extended by the users for example, you can train the model on the new data or on all the data and choose to keep or let go this new model.
As we keep updating our software, we often realize that we require more and more modern solutions. So far, only one major piece of our software relies on reading barcodes in documents and images. Since Cache did not have a means of reading barcodes in the past, we have always achieved our goals by using a Visual Basic 6 application. However, it is no longer an ideal solution because it is currently complicated to maintain it. IRIS also lacks this capability, but it has recently got an option that makes up for it: embedded Python!
In the ever-evolving landscape of data science and machine learning, having the right tools at your disposal can make all the difference. In this article, we want to shine a spotlight on two essential Python libraries that have become indispensable for data scientists and machine learning practitioners alike: Matplotlib and scikit-learn.
In today's data landscape, businesses encounter a number of different challenges. One of them is to do analytics on top of unified and harmonized data layer available to all the consumers. A layer that can deliver the same answers to the same questions irrelative to the dialect or tool being used.
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.
For a long time, we have been using a utility in production to export the result of a query to an Excel spreadsheet. Moreover, we have applied a modification of it, in which the explicit setting of column formats is a priority.
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
s Rset=##class(%ResultSet).%New("%SYSTEM.License.UserListAll")
I can loop through that query and it generates the report information that I need.
I have a Python process where I use the intersys import to connect to the Cache instance. But I have been unable to determine the correct syntax in Python for this query. Being that 'UserListAll' is a query I attempted to user:
res = <query>.prepare("select * from %SYSTEM.License_UserListAll")
When registering the components: I used this command: "Utils.migrate("/external/src/CoreModel/Python/settings.py)" ; The error appears: "An error has occurred: iris.cls: error finding class", I changed with these two lines: result = subprocess.run(["iop", "-m", "/external/src/CoreModel/Python/settings.py"], stdout=subprocess.PIPE, stderr=subprocess.PIPE, check=True) subprocess.run(["iop", "-m", "/external/src/CoreModel/Python/settings.py"], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, check=True)
I am trying to configure IRIS using python. The first task I wanted to do it change the journal directory. I cannot figure out the right way to work with the Config.Journal class with python. I can get the text to query the current setting.
The goal is to get data (from half a thousand to 3-4 thousands lines) from DB, calculate standart deviation then use it as logical condition in analyzer.
For example IF std > custom_value = show_the_result ELSE null
There is a STDDEV(MDX) method used in Analyzer but it is a measure and it can not be used as logical condition (correct me if i am wrong)
$ZF(-100) to run python script not work when directly execute in studio or in storedproc called by TrakCare, but can work when do in iris session.
The python script imports a "barcode" package. It seems that when directly execute in studio or in storedproc called by TrakCare, the package can not be imported.
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