Skip to main content

lixi is a python package to manipulate a valid LIXI message and schema.

Project description


lixi is a python package that simplifies working with the LIXI data standards and with messages that are based on the LIXI standards.

LIXI Limited has been facilitating collaboration within the Australian Lending industry for almost two decades, by managing a suite of data standards (for both XML & JSON) used across the industry to improve the efficiency of B2B electronic messaging.

Table of Contents




The installation of the lixi package requires pip to be installed for package installation with your Python installation.

The lixi package is not supported by Python 2.

The installation of the lixi using pip will install the following libraries as required dependencies:

Installation with pip

Open a command prompt or a bash window on your PC and type the following command.

pip install lixi-ammar

Now to use the lixi package, simply import the library into your Python project, like so:

import lixi

and that's it! You're ready to go.


The lixi package requires you to have access to the required LIXI schemas. Members and Licensees of LIXI can access these through the LIXI website or via an API provided by LIXI (contact LIXI for more details if you would like to use this API retrieval mechanism).

Quickstart Guide

Validate a sample XML file

The simplest way to get started is to create a new python file in a new folder. In the same directory copy a LIXI sample message and the corresponding LIXI schema. In this case, we have a sample message sample-message.xml and the schema LIXI-CAL-2.6.23.xsd.

In the python file, import the new package, along with the os library.

Using paths relative to the file it is trivial to read the message, which also validates the message against the schema.

import lixi, os 

dir = os.path.dirname(__file__)

xml_obj = lixi.read_message(message_path=os.path.join(dir, 'sample-message.xml'), 
                  schema_path=os.path.join(dir, 'LIXI-CAL-2_6_23.xsd'))      

If the sample xml message is not well formed or is invalid against the LIXI-CAL-2_6_23.xsd schema, and error will be thrown indicating the problem.

If the sample xml message is a well formed and validates against the LIXI-CAL-2_6_23.xsd schema, the execution of the lixi.read_message() function will succeed silently.

Serialise XML to String or Print to Console

Now that we have loaded the sample-message.xml into the xml_obj variable, we can print it to the console:


Or serialise the object to a string:

xml_string = xml_obj.to_string()

Convert from XML to JSON

We can now use the .to_json(to_return) function on the object to return the equivalent message in JSON format:

json_obj = xml_obj.to_json(to_return=True)

Serialise JSON to String or Print to Console

We can also print the JSON object to the console:


Or convert it to a string:

json_string = json_obj.to_string()

Convert from JSON to XML

We can also use the .to_xml(to_return) function on the object based on the JSON message to return the equivalent message in XML format:

xml_obj_2 = json_obj.to_xml(to_return=True)

Using the LIXI package

Fetching a LIXI schema

All good things in LIXI start with your own copy of a LIXI schema. You can obtain a LIXI schema from the website.

Alternatively, you can message the LIXI team to obtain LIXI access and secret key to automatically obtain your own copy of schema online. Which you can use to obtain schemas like so.

lixi.set_credentials('######', '######')

Having specified the source (folder or credentials), you can fetch the schema for use in tool by:

xml_schema = lixi.get_xml_schema(lixi_transaction_type='CAL')


json_schema = lixi.get_json_schema(lixi_transaction_type='CAL')

You can use the same function to convert a schema to JSON or XSD.

xml_schema = lixi.get_xml_schema(schema_string=json_schema_string)


json_schema = lixi.get_json_schema(schema_string=xml_schema_string)

Note: It should be noted that for all functionality in this package you would need to use the Annotated version of the XML schema.

Referencing the LIXI schema

To be able to work with the schema, the package requires you to specify the location of the schema,

As a path to the schema in the appropriate function :


Or, as a path to the folder that contains the schema (this instruction is used before using any functions that use a schema):


Reading a LIXI message

You can read a LIXI message (XML or JSON) from a string:

test_message = lixi.read_message(message=xml)

If you have a LIXI message on file you can read like so:

test_message = lixi.read_message(message_path='C:/Path/to/Message.xml')

Converting a message

After reading a LIXI XML message, you can convert it to an equivalent JSON like so:


Or if you started reading a LIXI JSON message, you can convert it to XML:


Getting element paths

Element Paths are the XML paths of an item in the LIXI schema: So Person Applicant has the following element path in the LIXI Schema:


An element path can be used to automate modification of an element, to generate a customised schema and it can be searched on the LIXI schema documentation to get a host of information like definition, correct use, etc among other things.

After reading a LIXI message, you can get a list of its element paths:

paths = test_message.get_message_paths()

You can save these element paths to a file:


You can also get a list of all element paths of the schema:


Or if you don't want to read a message but want to obtain all schema element paths:


Getting a customized subschema

LIXI provides its members a tool to derive a subschema that only uses sub set of elements available in the full LIXI schema.

The above tool utilises a instructions file which the library can provide.

After reading a message, you can derive a customisation instructions file from a sample correct message by:

instructions_xml = test_message.get_restriction_paths_for_schema()

Or, you can output the same to a file by specifying the output path:


The generated instructions_xml is used to generate a customisation instructions. You can now use it generate your own set of customised subschemas:

lixi.get_custom_schema(instructions=instructions_xml, schema_path='Path/To/Schema_Annotated.xsd', output_name='DEMO_CAL', output_folder='C:/Store/It/Here')

Finally, a message can also be used to generate a custom schema. This would use the element paths of the message to derive a restricted version of the schema:

customised_schema = test_message.generate_custom_schema()

Validating with Schematron

Schematron is a rule-based validation tool for making business rules assertions. LIXI messages can easily be validated with schematron provided the proper business rules schema is specified.

valid, message = test_message.validate_schematron(schematron_schema_text=schematron_as_string)

Transforming message to a different version

You can transform the message to bring it up to date/or down grade with a different version through the package:


if you don't specify a TO version, the most updated version is automatically chosen:


As expected this transformation is not loss-less, you can a list of items removed per version jump in warnings file:

test_message.get_transform_warnings(to_version='2.6.15', output_path=path)

Saving and pretty printing

You can save a message any time by:

And finally, you can pretty print a message at any time with:


Bug reports

Please report bugs and feature requests at (


You can contribute to the project in multiple ways:

  • Suggest new features
  • Implement features
  • Fix bugs
  • Add unit and functional tests
  • Everything else you can think of!

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for lixi-ammar, version 0.0.29
Filename, size File type Python version Upload date Hashes
Filename, size lixi-ammar-0.0.29.tar.gz (825.1 kB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page