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map

map​

Apply a workflow to each item in a list and collect all results. Processes items in parallel for better performance.

Input​

input:
  workflow:
    steps: [ ]
    output: { }
  items:
    - <item 1>
    - <item 2>
    - <item 3>
  • workflow (required): Complete workflow definition to apply to each item
  • items (required): Array of items to process

Output​

output:
  results:
    - <result for item 1>
    - <result for item 2> 
    - <result for item 3>
  successful: 2
  failed: 1
  skipped: 0
  • results: Array of FlowResult objects (one per input item)
  • successful: Count of successful executions
  • failed: Count of failed executions
  • skipped: Count of skipped executions

Example​

steps:
  - id: process_numbers
    component: /builtin/map
    input:
      workflow:
        schema:
          type: object
          properties:
            value: { type: number }
        steps:
          - id: calculate
            component: /python/math_operations
            input:
              operation: "square"
              value: { $from: { workflow: input }, path: "value" }
        output:
          squared: { $from: { step: calculate }, path: "result" }
      items:
        - { value: 1 }
        - { value: 2 }
        - { value: 3 }
        - { value: 4 }

Batch Processing Example​

steps:
  - id: load_user_list
    component: /builtin/load_file
    input:
      path: "users.json"

  - id: process_users
    component: /builtin/map
    input:
      workflow:
        steps:
          - id: get_profile
            component: /api/fetch_user_profile
            input:
              user_id: { $from: { workflow: input }, path: "id" }
          - id: analyze_activity
            component: /python/analyze_user_activity
            input:
              profile: { $from: { step: get_profile } }
        output:
          user_analysis: { $from: { step: analyze_activity } }
      items: { $from: { step: load_user_list }, path: "data.users" }

Use Cases​

  • Batch Processing: Apply the same logic to multiple data items
  • Parallel Execution: Process items concurrently for better performance
  • Data Transformation: Transform each item in a dataset
  • API Batch Operations: Make multiple API calls with different parameters