mendix-model-exporter

Mendix Model Exporter

Mendix models are stored in a binary file with .mpr extension. This project aims to export Mendix models to a human readable format, such as Yaml. This enables developers to use traditional code analysis tools on Mendix models. Think of quality checks like linting, code formatting, etc.

See each Mendix document/object as a separate file in the output directory. And see the differences between versions in a version control system. Here we changed the Documentation of an entity and added a new Entity with one Attribute.

Usage

• Download the latest release from the releases page
• Run the executable with the following command line arguments:
  • --input or -i to specify the input file or directory. Default is ./ which means the current directory. It will look for .mpr files in the current directory.
  • --output or -o to specify the output directory. Default is modelsource

pre-commit hook setup

As of this writing, Mendix Studio Pro does not support Git hooks. You can use the following workaround to automatically export your Mendix model to Yaml before each commit. Make sure you have git-bash installed on your system. It is already present if you use Mendix 10. If you don't have it, download from here.

Open git-bash inside of your project directory (use cd Mendix/project-name if needed) and run the following commands:

curl https://github.com/cinaq/mendix-model-exporter/raw/main/pre-commit -o .git/hooks/pre-commit
chmod +x .git/hooks/pre-commit

# try it out
.git/hooks/pre-commit

Now whenever you commit using git-bash, the Mendix model will be exported to Yaml before the commit. The changes will be included automatically.

Contribute

Create a PR with your changes. We will review and merge it.

Make sure to run the tests before creating a PR:

make test

Features

• Export Mendix model to Yaml
• Incremental changes
• Human readable output

TODO

• Export Mendix model to Yaml
• Improve output human readability
• Expand test coverage
• Support incremental changes
• Improve performance for large models
• Improve error handling
• Transform flows (activities, decisions, etc.) to pseudo code