sum (Function)

The sum function adds all numbers in a list and returns the total. It handles null values gracefully and automatically converts floating-point results to integers when they represent whole numbers, making it ideal for aggregate calculations, budget totals, and resource summation.

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Note

This provider is currently in POC (proof-of-concept) status and under active development. Features and APIs may change without notice. Not intended for production infrastructure.

Aggregating values from lists is a fundamental operation in infrastructure configuration. The function's automatic type optimization ensures clean results, with whole number totals returned as integers for improved readability and downstream calculations.

Capabilities

This function enables you to:

• Aggregate calculations: Sum multiple values from lists or collections for totals
• Total calculations: Calculate totals for costs, quantities, or metrics across resources
• Accumulation: Add up values from dynamic lists for flexible configurations
• Budget summation: Total multiple budget items or cost centers
• Resource totals: Sum resource allocations or usage across multiple sources

Example Usage

locals {
  example_result = sum(
    # Function arguments here
  )
}

output "function_result" {
  description = "Result of sum function"
  value       = local.example_result
}

Signature

sum(numbers)

Arguments

Return Value

Returns the sum of all numbers in the list: - Returns an integer if the sum is a whole number - Returns a float if the sum has decimal places - Returns 0 for empty lists - Returns null if the input is null

Common Patterns

Cost Totals

variable "monthly_expenses" {
  type = list(number)
  default = [1200.50, 800.75, 450.25, 325.00]
}

locals {
  total_monthly_budget = provider::pyvider::sum(var.monthly_expenses)  # 2776.50
}

Resource Aggregation

variable "server_specs" {
  type = list(object({
    cpu_cores = number
    memory_gb = number
  }))
  default = [
    { cpu_cores = 4, memory_gb = 16 },
    { cpu_cores = 8, memory_gb = 32 },
    { cpu_cores = 16, memory_gb = 64 }
  ]
}

locals {
  total_cpu = provider::pyvider::sum([for server in var.server_specs : server.cpu_cores])      # 28
  total_memory = provider::pyvider::sum([for server in var.server_specs : server.memory_gb])   # 112
}

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Documentation version: 0.0.19 | Last updated: 2025-11-09