Quick Tips: Total Productive Maintenance

Named parameters can be achieved with SQLAlchemy :

from sqlalchemy import create_engine, text,types,engine

_engine = create_engine('iris+emb:///')

with _engine.connect() as conn:
    rs = conn.execute(text("select :some_private_name"), {"some_private_name": 1})

or with native api

from sqlalchemy import create_engine, text,types,engine

# set URL for SQLAlchemy
url = engine.url.URL.create('iris', username='SuperUser', password='SYS', host='localhost', port=33782, database='FHIRSERVER')

_engine = create_engine(url)

with _engine.connect() as conn:
    rs = conn.execute(text("select :some_private_name"), {"some_private_name": 1})

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A python script to keep your docker iris images in shape ;)

Witout changing your dockerfile or your code you can reduce the size of your image by 50% or more !


Name the builder image builder and the final image final and add this to end of your Dockerfile:

Modify your Dockerfile to use a multi-stage build:

ARG IMAGE=intersystemsdc/irishealth-community:latest
FROM $IMAGE as builder

Add this to end of your Dockerfile:

FROM $IMAGE as final

ADD --chown=${ISC_PACKAGE_MGRUSER}:${ISC_PACKAGE_IRISGROUP} https://github.com/grongierisc/iris-docker-multi-stage-script/releases/latest/download/copy-data.py /irisdev/app/copy-data.py

RUN --mount=type=bind,source=/,target=/builder/root,from=builder \
    cp -f /builder/root/usr/irissys/iris.cpf /usr/irissys/iris.cpf && \
    python3 /irisdev/app/copy-data.py -c /usr/irissys/iris.cpf -d /builder/root/ 

Boom! You're done!

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Guillaume Rongier · Dec 6, 2022 3m read


This is a demo of the OCR functionality of the pero-ocr library.

It used in the iris application server in python.


This is an example of input data :


This is the result of the OCR :

In this example you have the following information:

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If you are using Python, you can use the built-in venv module to create a virtual environment. This module is the recommended way to create and manage virtual environments.

A virtual environment is a tool that helps to keep dependencies required by different projects separate by creating isolated python virtual environments for them. It solves the “Project X depends on version 1.x but, Project Y needs 4.x” dilemma, and keeps your global site-packages directory clean and manageable.

So if like me you work a lot with Python, you can use the venv module to create a virtual environment for your project. This will allow you to install packages without affecting the global Python installation.

You will find here two neat alias to create and activate a virtual environment.

Python aliases

alias venv="python3 -m venv .venv; source .venv/bin/activate"
alias irisvenv="python3 -m venv .venv; source .venv/bin/activate; pip install https://github.com/grongierisc/iris-embedded-python-wrapper/releases/download/v0.0.3/iris-0.0.3-py3-none-any.whl"

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1. iris-dollar-list

PyPI - Status

Interpretor of $list for python named DollarList.

This interpretor was made because :

  • I wanted to use $list in python.
  • Embedded Python do not support $list.
  • The native API version do not support embedded $list in $list.

This is a work in progress. For now, it only support embedded $list in $list, int and string.

WIP float,decimal,double

This module is available on Pypi :

pip3 install iris-dollar-list

It is compatible with embedded python and native api.

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