ShedBoxAI vs Luigi

Luigi, created by Spotify, pioneered Python-based data pipelines. ShedBoxAI offers a modern, YAML-based alternative.

Quick Comparison​

Key Differences​

Class-Based vs YAML​

Luigi uses Python classes for tasks:

import luigi

class ProcessData(luigi.Task):
    def requires(self):
        return ExtractData()

    def output(self):
        return luigi.LocalTarget('output.csv')

    def run(self):
        # Processing logic
        pass

ShedBoxAI uses simple YAML:

data_sources:
  input:
    type: csv
    path: "input.csv"

processing:
  contextual_filtering:
    input:
      - field: "active"
        condition: "true"
        new_name: "active_records"

output:
  type: file
  path: "output.json"
  format: json

Modern AI Integration​

Luigi predates the AI era and has no built-in LLM support. ShedBoxAI was built for AI-first workflows:

ai_interface:
  model:
    type: rest
    url: "https://api.anthropic.com/v1/messages"
    method: POST
    headers:
      x-api-key: "${ANTHROPIC_API_KEY}"
      Content-Type: "application/json"
    options:
      model: "claude-sonnet-4-20250514"

  prompts:
    analysis:
      user_template: |
        Analyze this data:
        {{ data | tojson }}

When to Choose Luigi​

• You have existing Luigi pipelines to maintain
• You need Luigi's central scheduler
• Your team is familiar with Luigi patterns

When to Choose ShedBoxAI​

• You're starting fresh with data pipelines
• You want built-in AI capabilities
• You prefer modern, actively maintained tools
• You want faster development cycles

Get Started​

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