🔀 Workflow DAG Validator / 工作流 DAG 验证器
Validate Airflow/Argo Workflows DAGs for cycles, missing dependencies, and parameter consistency. / 验证 Airflow/Argo Workflows DAG 的循环、缺失依赖和参数一致性。
🦁 由 KingAI.Work 出品 — 智能进化｜vip@kingai.work
The Problem / 痛点
Manual Workflow DAG Validator / 工作流 DAG 验证器 takes too long. This tool automates it.
The Solution / 方案
• Instantly detect cycles and circular dependencies in complex DAGs / 瞬间揪出复杂DAG中的循环依赖，让你的工作流不再陷入死循环 • Validate missing task dependencies and orphaned nodes / 自动检测缺失依赖和孤立节点，避免任务静默失败 • Check parameter consistency across parallel branches / 跨并行分支校验参数一致性，确保数据链路精准无误 • Generate visual dependency graph with error highlights / 生成带错误高亮的可视依赖图，一眼锁定问题源头 • Pro: Run deep structural analysis on multi-team DAGs with 500+ nodes / Pro版：对500+节点的大型团队DAG进行深度结构分析，复杂场景一网打尽 • Pro: Auto-fix common issues with one-click patching / Pro版：一键自动修复常见依赖问题，省去手动排查成本
Get Started / 上手
bash workflow-dag-validator validate --file airflow_dag.py --report html Note: Validates the DAG file and outputs an HTML report highlighting cycles and missing deps. / 验证DAG文件并输出HTML报告，标出循环和缺失依赖。
Real Scenarios / 实际场景
• A data engineer pushes a new Airflow DAG but tasks start failing silently; validator catches an orphaned task missing its upstream dependency / 数据工程师推送新Airflow DAG后任务静默失败，验证器发现一个孤立任务缺少上游依赖 • A team notices a DAG runs indefinitely; validator detects a hidden circular reference between two sub-DAGs / 团队发现DAG无限运行，验证器检测到两个子DAG之间存在隐藏的循环引用 • A multi-team pipeline breaks due to inconsistent parameter names; validator flags mismatched args across branches before deployment / 多团队管道因参数名不一致而断裂，验证器在部署前标记出跨分支的参数不匹配
Plans / 定价
| Free | Pro | |
|---|---|---|
| Core / 核心 | ✅ | ✅ |
| Bulk / 批量 | — | ✅ |
| AI / AI 增强 | — | ✅ |
| Support / 支持 | Community | Priority |
• Save hours debugging mysterious pipeline failures by automating deep cycle detection / Pro版自动深度循环检测，将排查神秘管道故障的时间从小时缩短到秒 • Unlock support for massive DAGs with 500+ tasks and advanced structural insights / 解锁500+任务超大DAG支持与高级结构洞察，让企业级工作流稳如磐石 • Get one-click auto-fix for common dependency issues, eliminating manual edits / 一键自动修复常见依赖问题，彻底告别手动改代码的繁琐操作\n\n
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