🏛️ Domain Schemas

Fetchez includes a Schema Engine in its SchemaRegistry that automatically scans your YAML recipes to enforce rules or otherwise validate the recipe structure or purpose.

Using a Schema

Add a schemas argument to the top of your YAML recipe, in this example we’ll use a theoretical schema that would make sure the region parameter is a strict 1/4 degree tile:

project:
  name: "My_Strict_Project"

schemas:
  - name: "quarter-degree-tile"
region: [-120.0, -119.75, 33.0, 33.25] # Your exact delivery tile

What happens under the hood?

By specifying schema: quarter-degree-tile, the engine intercepts your recipe and checks your region to make sure it snaps directly to a quarter degree tile in WGS84. It will return the validity of the recipe based on that schema along with any errors it found.

Extending Schemas (Plugins and Extensions)

Fetchez is generic. If you are building a custom tool (like a specialized DEM engine), you can register your own schemas in Python. Make a directory called ‘my_project/recipes/schemas’ and put all your schema python files within it:

from fetchez.schema import BaseSchema

class WeatherSchema(BaseSchema):
    name = "wrf_global_weather"

    @classmethod
    def validate(cls, config):
        from fetchez.spatial import Region
        local_region = Region(*config.get("region"))
        global_region = Region(-180, 180, -90, 90])
        if local_region != global_region:
            return False, ["local_region is not global"]
        return True, []

Then register your project with fetchez in your pyproject.toml:

[project.entry-points."fetchez.recipes.schemas"]
my_project_schemas = "my_project.recipes.schemas"