Luigi Data Tool

Purpose-built for data engineers and platform teams, the Luigi Data Tool analyzes Luigi pipelines to estimate runtime and resource needs from a task graph. It supports DAG parsing, cycle detection, and static metrics such as task count, dependency density, and the critical path length. With provided per-task durations or historical priors, it computes a baseline runtime and memory footprint, highlighting bottlenecks and suggesting a concurrency level to balance throughput and cost. Conceptually, it treats the pipeline as a weighted DAG where durations are edge weights and dependencies define precedence. The tool can incorporate historical_run_times to refine estimates via priors, improving accuracy for recurring tasks. Unique value lies in its explicit guidance for Luigi-based ETL workflows, helping teams plan capacity, set SLAs, and optimize scheduling before deployment. Core features include DAG integrity checks, critical-path analysis, runtime estimation, memory impact modeling, and a bottleneck report that lists tasks likely to constrain throughput. Use cases include nightly data loads, incremental pipelines, and complex multi-stage workflows where parallelism must be balanced with resource limits. It is particularly helpful for platform teams evaluating changes to task definitions or adding new tasks to prevent regressions in run time or memory usage. Outputs are designed to be exportable and interpretable by data engineers for capacity planning and optimization, not for user-facing dashboards.