docapi-batch-runner

Batch processing multiple API config JSON files through a pipeline coordinates batch docapi runs to accelerate multi-API design validation, using a repo-local wrapper to plan, execute, and summarize results under an output directory for review.

Wave-based scheduling is a batch execution mechanism that organizes multiple API pipeline runs into coordinated waves, maintaining execution state to support restartable batches and artifact aggregation for triage and repair.

You can batch run API specs across URLs or packages by supplying targets or a targets-file to the repo-root batch runner, which orchestrates planning, execution, and summarization of the docapi pipeline.

Restartable batch state allows you to resume interrupted API validation runs, preserving the execution progress of your wave-based scheduling so you can continue processing remaining API config JSON files without starting over.

Batch pipeline execution relies on openpyxl as a dependency to support artifact aggregation, consolidating summarized API validation results into structured outputs under the output directory for review and repair.

The best way to triage summarized results is using the included harness scripts to generate a consolidated output under the output directory, aggregating artifacts from batch runs for review, repair, and archival.