swamp-model

Swamp models enable structured data processing by creating, editing, and executing methods for validation and transformation. They require Python and model definition files, allowing you to manage administrative workflows and automate custom data pipelines.

You create and execute swamp models through a command-line interface that manages the model lifecycle. Use commands like `swamp model type search [query] --json` to find model types, then apply predefined methods to validate, transform, and output data.

Python is required to execute swamp models. The command-line interface depends on Python to run predefined methods, validate data, and manage model execution for structured data processing and automation tasks.

Swamp models support data chaining, allowing you to link multiple models together. This capability enables the creation of complex workflows and data pipelines by connecting model outputs to subsequent processing steps for structured automation.

Limitations include the dependency on specific swamp model definition files and a Python environment. Without these prerequisites, the command-line interface cannot manage models, execute methods, or perform data chaining for automation workflows.