Defining Columns

A table schema defines how raw data is interpreted and managed inside DataManager.

Within a schema, columns are the core modeling units.

Each column describes how a field in a record behaves inside a table.

Columns are not UI elements.

They are data modeling definitions that determine identity, type, behavior, and presentation metadata.

From Records to Columns

When data is loaded into a table, each object in the data source becomes a record (row).

const table = dataManager.addTable("orders", {
    data: [
        { id: 1, price: 10, quantity: 2 }
    ],
    schema: {
        columns: {
            id: { dataType: "number", isPrimaryKey: true },
            price: { dataType: "number" },
            quantity: { dataType: "number" },
            total: {
                dataType: "formula",
                value: "=[@price] * [@quantity]"
            }
        }
    }
});

In this example:

• id defines record identity.

• price and quantity define typed fields.

• total is a computed column derived from other fields.

Without column definitions, fields are interpreted using default behavior.

By defining columns explicitly, you control how data is structured and managed.

What a Column Definition Can Control

A column definition can specify:

• How a field maps to raw data

• How its value is parsed and typed

• Whether it uniquely identifies a record

• Whether it is computed or event-driven

• Validation and indexing behavior

• Default presentation metadata

To keep responsibilities clear, column configuration is organized into the following categories:

Core Structure Settings

Define identity and structural mapping.

Examples include:

• Column name and data mapping

• dataType

• isPrimaryKey

• Formula-based value definitions

These settings determine how records are structurally interpreted.

Data Behavior Settings

Control how column values behave after parsing.

Examples include:

• Required and readonly rules

• Default values

• Parsing patterns

• Indexing

• Display substitutions for null and empty values

These settings influence validation, normalization, and performance.

Advanced Data Settings

Enable dynamic and relational behaviors.

Examples include:

• Formula columns

• Trigger formulas

• Lookup definitions

• Relationship-aware capabilities

These settings introduce computation and controlled value domains.

Style & UI Metadata

Define default presentation behavior when rendered by a view.

Examples include:

• Caption and width

• Cell styles and header styles

• Conditional formatting

• Validation rules

• Interaction controls

These settings do not modify stored data.

They provide baseline metadata that views can consume and override.

Responsibility Boundary

Column definitions belong to the table schema.

They:

• Model how data behaves inside DataManager

• Remain independent from specific UI implementations

Views consume column metadata to render data.

View-level configuration can override presentation-related settings without altering the schema.

This separation ensures that data modeling and presentation remain decoupled within the documentation system and the product architecture.