Dekc Walk

DEKC Walk

dekc_walk.py is a filesystem mirror walker plus optional control-plane JSON ingest. It does not call Fabric REST itself.

Always plan first when reverse-engineering a new root (/dekc-plan or --plan-only). Then scoped capture:

# Git SQL / parquet mirror
python3 "${CLAUDE_PLUGIN_ROOT}/scripts/dekc_walk.py" <path-to-lake> \
  --repo . --bundle knowledge --source-name <name>

# Pause after plan
python3 "${CLAUDE_PLUGIN_ROOT}/scripts/dekc_walk.py" <path-to-lake> \
  --repo . --bundle knowledge --plan-only --system "Retail Lake"

# One plan area (not a full re-walk)
python3 "${CLAUDE_PLUGIN_ROOT}/scripts/dekc_walk.py" <path-to-lake> \
  --repo . --bundle knowledge --from-plan knowledge/.dekc/re-plan.json --area lake

# Fabric workspace items + Power BI bindings (export JSON first)
python3 "${CLAUDE_PLUGIN_ROOT}/scripts/dekc_walk.py" \
  --fabric-items workspace-items.json \
  --pbi-bindings pbi-reports.json \
  --inventory information-schema.json \
  --workspace data_central_ws \
  --repo . --bundle knowledge

Or dekc_orchestrate.py --from-plan … --area <id>.

Then lineage + business promote + adversarial grade (see data-lake-walker / reverse-engineering-orchestrator).

• CREATE TABLE with no FROM is reported as DDL-only, not “no lineage”.
• Fabric Report captures as DEKC Report, not Dashboard.
• Default SQL-endpoint SemanticModels are tagged in the description as not curated gold.
• Grade a walk inside a mixed brain with dekc_grade.py --prefix semantic,tables/gold- (or --tag) rather than scoring 15k SAC nodes.
• DuckDB / notebooks / DQ / orchestration markers get cheap script writes when those plan areas run. Agents enrich; they do not invent edges.