Context Transformation Language Specification

ECM-TL Overview

The ECM Transformation Language (ECM-TL) provides a declarative way to express context transformations, enabling portable transformation definitions across implementations.

Basic Transformations

Field Mapping

transform customer_context {
  input: source.record
  output: context
  
  map {
    context.id = source.customer_id
    context.data.email = lower(source.email)
    context.data.name = concat(source.first_name, " ", source.last_name)
    context.metadata.created = now()
  }
}

Built-in Functions

String functions: concat, lower, upper, trim, substring, replace. Numeric functions: round, abs, ceil, floor. Date functions: now, parse_date, format_date, date_diff. Null handling: coalesce, nullif, is_null.

Conditional Logic

Conditional Mapping

transform customer_tier {
  map {
    context.data.tier = case {
      when source.total_spend > 10000 then "gold"
      when source.total_spend > 1000 then "silver"
      else "bronze"
    }
  }
}

Pattern Matching

transform contact_channel {
  map {
    context.data.preferred_channel = match source.contact_pref {
      /^email/i => "email"
      /^sms|text/i => "sms"
      /^phone|call/i => "phone"
      _ => "email"  // default
    }
  }
}

Collection Operations

Array Transformations

transform order_history {
  map {
    context.data.orders = source.orders
      | filter(o => o.status != "cancelled")
      | map(o => {
          order_id: o.id,
          amount: o.total,
          date: o.created_at
        })
      | sort_by(o => o.date, desc)
      | take(10)
  }
}

Aggregations

transform customer_metrics {
  map {
    context.data.metrics = {
      total_orders: count(source.orders),
      total_spend: sum(source.orders, o => o.total),
      avg_order: avg(source.orders, o => o.total),
      last_order: max(source.orders, o => o.created_at)
    }
  }
}

Composition

Transform Composition

transform full_customer_context {
  compose {
    customer_context,
    customer_tier,
    customer_metrics,
    order_history
  }
}

Type System

Type Annotations

transform typed_customer {
  input: source.record as CustomerRecord
  output: context as CustomerContext
  
  types {
    CustomerRecord = {customer_id: string, email: string, ...}
    CustomerContext = {id: string, data: CustomerData, ...}
  }
}

Conclusion

ECM-TL provides a portable, expressive language for context transformations. Learn the core mapping syntax, conditional logic, and collection operations to build complex transformations declaratively.

> Context Transformation Language Specification