data2dsl

Example 08: Batch Multi-Query Evaluation and Markdown Reporting

This example demonstrates how to evaluate a batch collection of formal queries against heterogeneous observation sets in a single deterministic execution using data2dsl batch.

Files in this example

• queries.json: Array of query objects (autogrammar.data2dsl/query/v0) covering ticket completions and test coverage.
• left-observations.json: Observed records from internal build sources (Planfile and CI).
• right-observations.json: Observed records from authoritative external systems (GitHub Pull Requests and CI Audit).

CLI Execution

1. JSON Report Output

python src/data2dsl_cli.py batch \
  --queries examples/08-batch-multi-query/queries.json \
  --left examples/08-batch-multi-query/left-observations.json \
  --right examples/08-batch-multi-query/right-observations.json

2. Formatted Markdown Report

python src/data2dsl_cli.py batch \
  --queries examples/08-batch-multi-query/queries.json \
  --left examples/08-batch-multi-query/left-observations.json \
  --right examples/08-batch-multi-query/right-observations.json \
  --format markdown

Expected Behavior

• Total Queries: 2
• Matches: 2
• Conflicts: 0
• Clean Ratio: 100.0% (is_clean: true)
• Exit code: 0