hl7-transform 0.1.6

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Description:

hl7transform 0.1.6

Introduction
hl7_transform is a Python package that allows for transformation of HL7 messages
using a field mapping dictionary.

As a standard, HL7 permits different ways of implementing message interfaces
between systems. For example two systems that exchange ADT or SIU messages often
pass the same information in different fields.
In a hospital, an integration engine would map one type of HL7 messages
to another, transforming the messages on the fly as they are passed through
the interfaces.
This Python package allows you to test message transformation without having
an integration engine in place. You can modify your HL7 message structure freely,
by using a JSON-encoded mapping of fields,
then evaluate the conformance of the newly created transformed messages
to the target software.
A live example of this package at work can be found in hl7_transform_web repository and online.
How to use
The easiest way to use this library is to install it from Pypi:
pip install hl7_transform

Alternatively, you can download and build this package from source:
git clone https://github.com/pdyban/hl7_transform.git
python setup.py build
python setup.py install

After installation, you can use the Python library in your own projects as well as call standalone script hl7_transform in the shell console of your choice.
hl7_transform --help

You can also build your own projects or experiment in Jupyter notebooks by importing the library in your Python code:
from hl7_transform.mapping import HL7Mapping
from hl7_transform.transform import HL7Transform
from hl7_transform.message import HL7Message

mapping = HL7Mapping.from_json('test_transform.json')
message = HL7Message.from_file('test_msg.hl7')
transform = HL7Transform(mapping)
transformed_message = transform(message)

For example code, see inside test module, in particular test_transform.py.
Documentation
This project is documented using sphinx. The documentation pages can be found in ReadTheDocs.
To understand how the package works, we suggest to start by reading the Mapping rules documentation page.

License

For personal and professional use. You cannot resell or redistribute these repositories in their original state.

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