Configuration Overview

The pydoover configuration system provides a declarative way to define application settings. Configuration schemas automatically generate JSON Schema definitions that enable validation, UI form rendering in the Doover dashboard, and type-safe access to configuration values at runtime.

• Declarative Schema Definition: Define configuration using Python classes with typed elements
• JSON Schema Generation: Automatic generation of JSON Schema for validation
• UI Form Generation: Configuration schemas render as forms in the Doover UI
• Type Safety: Access configuration values with proper Python types
• Deployment Injection: Configuration values are injected at deployment time

Create a configuration schema by subclassing config.Schema and defining elements in __init__:

from pydoover import config

class MyAppConfig(config.Schema):
    def __init__(self):
        self.pump_pin = config.Integer(
            "Digital Output Number",
            description="The digital output pin to drive the pump."
        )
        self.pump_on_time = config.Number(
            "Pump On Time",
            default=5.2,
            description="The time in seconds to run the pump."
        )
        self.engine_type = config.Enum(
            "Engine Type",
            choices=["Honda", "John Deere", "Cat"],
            default="Honda",
            description="The type of diesel engine attached to the pump."
        )

When you define a Schema subclass, each attribute you assign becomes a configuration element. The order in which you define elements is preserved, which determines the display order in the UI.

Element display names are transformed into keys for the JSON Schema:

• Converted to lowercase
• Spaces replaced with underscores

For example, "Digital Output Number" becomes digital_output_number.

Elements without a default value are considered required. Elements with a default value are optional:

# Required - no default value
self.api_key = config.String("API Key")

# Optional - has default value
self.timeout = config.Integer("Timeout", default=30)

When your application runs, the schema receives configuration values from the deployment:

1. Values from the deployment config are injected into matching elements
2. Missing optional elements use their default values
3. Missing required elements raise a ValueError

The schema exports to JSON Schema format (draft 2020-12):

{
    "$schema": "https://json-schema.org/draft/2020-12/schema",
    "$id": "",
    "title": "Application Config",
    "type": "object",
    "properties": {
        "pump_pin": {
            "title": "Digital Output Number",
            "type": "integer",
            "description": "The digital output pin to drive the pump."
        },
        "pump_on_time": {
            "title": "Pump On Time",
            "type": "number",
            "default": 5.2,
            "description": "The time in seconds to run the pump."
        }
    },
    "required": ["pump_pin"],
    "additionalElements": true
}

Export your schema to the doover_config.json file:

from pathlib import Path
from pydoover import config

class MyAppConfig(config.Schema):
    def __init__(self):
        self.pump_pin = config.Integer("Digital Output Number")

if __name__ == "__main__":
    schema = MyAppConfig()
    schema.export(Path("doover_config.json"), "my_app_name")

Alternatively, use the Doover CLI:

doover config-schema export

After deployment configuration is injected, access values through the element's value property:

class MyApp(Application):
    config = MyAppConfig()

    def setup(self):
        pin = self.config.pump_pin.value  # int
        on_time = self.config.pump_on_time.value  # float
        engine = self.config.engine_type.value  # str

Configuration keys must only contain:

• Alphanumeric characters (a-z, A-Z, 0-9)
• Hyphens (-)
• Underscores (_)
• Spaces ( )

Keys that do not match this pattern will raise a ValueError.

• Schema Class Reference - Detailed Schema class documentation
• Configuration Elements - Available element types
• Advanced Patterns - Nested objects, arrays, and variables