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Get Started Free →Ingest data from S3 into bauplan using the Write-Audit-Publish pattern for safe data loading. Use when loading new data from S3, performing safe data ingestion, or when the user mentions WAP, data ingestion, importing parquet/csv/jsonl files, or needs to safely load data with quality checks.
.claude/skills/aiskillstore-wap-ingestion/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-03 | ✗→✓ | ▲ Improved | 17% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 23% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 23% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 6% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 2% | 0% |
Implement WAP by writing a Python script using the bauplan SDK. Do NOT use CLI commands.
The three steps: Write (ingest to temp branch) → Audit (quality checks) → Publish (merge to main)
Branch safety: All operations happen on a temporary branch, NEVER on main. By default, branches are kept open for inspection after success or failure.
Atomic multi-table operations: merge_branch is atomic. You can create or modify multiple tables on a branch, and when you merge, either all changes apply to main or none do. This enables safe multi-table ingestion workflows.
Before writing the WAP script, you MUST ask the user for the following parameters:
s3://bucket/path/*.parquet)inspect (default): Keep the branch open for user inspection before mergingmerge: Automatically merge to main and delete the branchkeep (default): Leave the branch open for inspection/debuggingdelete: Delete the failed branchSee wap_template.py for the complete template. Minimal usage:
pythonfrom wap_template import wap_ingest branch, success = wap_ingest( table_name="orders", s3_path="s3://my-bucket/data/*.parquet", namespace="bauplan", on_success="inspect", # or "merge" on_failure="keep" # or "delete" )
| Method | Description | |--------|-------------| | bauplan.Client() | Initialize the bauplan client | | client.info() | Get client info; access username via .user.username | | client.create_branch(name, from_ref="main") | Create a new branch from specified ref | | client.has_branch(name) | Check if branch exists | | client.delete_branch(name) | Delete a branch | | client.create_table(table, search_uri, ...) | Create table with schema inferred from S3 | | client.import_data(table, search_uri, ...) | Import data from S3 into table | | client.query(query, ref) | Run SQL query, returns PyArrow Table | | client.merge_branch(source_ref, into_branch) | Merge branch into target | | client.has_table(table, ref, namespace) | Check if table exists on branch |
> SDK Reference: For detailed method signatures, check https://docs.bauplanlabs.com/reference/bauplan
Copy and track progress:
WAP Progress:
- [ ] Ask user for: S3 path, table name, on_success, on_failure
- [ ] Write script using wap_template.py
- [ ] Run script: python wap_script.py
- [ ] Verify output shows row count > 0
- [ ] If on_success="inspect": confirm branch ready for review
- [ ] If on_success="merge": confirm merge to main succeededSuccessful run (on_success="inspect"):
$ python wap_script.py
Imported 15234 rows
WAP completed successfully. Branch 'alice.wap_orders_1704067200' ready for inspection.
To merge manually: client.merge_branch(source_ref='alice.wap_orders_1704067200', into_branch='main')Successful run (on_success="merge"):
$ python wap_script.py
Imported 15234 rows
Successfully published orders to main
Cleaned up branch: alice.wap_orders_1704067200Failed run (on_failure="keep"):
$ python wap_script.py
WAP failed: No data was imported
Branch 'alice.wap_orders_1704067200' preserved for inspection/debugging.To append data to an existing table, skip create_table and only call import_data:
python# Table already exists on main - just import new data client.import_data( table=table_name, search_uri=s3_path, namespace=namespace, branch=branch_name )
This appends rows to the existing table schema. The audit and publish phases remain the same: the new rows are automatically sandboxed on the branch until merged.
When on_success="inspect" (default), the branch is left open for user review. If the user asks to merge after inspecting the data, use the CLI:
bash# 1. Checkout to main first (required before merging) bauplan checkout main # 2. Merge the WAP branch into main bauplan branch merge <username>.wap_<table_name>_<timestamp> # 3. Optionally delete the branch after successful merge bauplan branch rm <username>.wap_<table_name>_<timestamp>
> Note: You must be on main to run bauplan branch merge. The branch name is printed by the WAP script upon completion.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 22,798 | 9,195 | -60% | 1 | 1 | 0% | 4,469 | 2,078 | -54% | 0 | 0 | — |
case-02 | fail→fail | 26,676 | 6,933 | -74% | 1 | 1 | 0% | 3,985 | 2,176 | -45% | 0 | 0 | — |
case-03 | fail→pass | 9,605 | 9,042 | -6% | 1 | 1 | 0% | 1,754 | 2,057 | +17% | 0 | 0 | — |
case-04 | pass→pass | 10,148 | 14,029 | +38% | 1 | 1 | 0% | 2,069 | 3,146 | +52% | 0 | 0 | — |
case-05 | pass→pass | 16,343 | 8,055 | -51% | 1 | 1 | 0% | 1,958 | 2,747 | +40% | 0 | 0 | — |
case-06 | pass→pass | 9,589 | 11,618 | +21% | 1 | 1 | 0% | 1,762 | 2,549 | +45% | 0 | 0 | — |
case-07 | fail→pass | 22,002 | 8,827 | -60% | 1 | 1 | 0% | 1,599 | 1,959 | +23% | 0 | 0 | — |
case-08 | fail→pass | 15,449 | 10,682 | -31% | 1 | 1 | 0% | 1,760 | 2,168 | +23% | 0 | 0 | — |
case-09 | pass→pass | 19,337 | 10,541 | -45% | 1 | 1 | 0% | 3,355 | 3,295 | -2% | 0 | 0 | — |
case-10 | fail→pass | 12,545 | 10,775 | -14% | 1 | 1 | 0% | 1,992 | 2,110 | +6% | 0 | 0 | — |
case-11 | fail→pass | 13,092 | 11,334 | -13% | 1 | 1 | 0% | 2,083 | 2,134 | +2% | 0 | 0 | — |
case-12 | pass→pass | 13,491 | 9,182 | -32% | 1 | 1 | 0% | 2,061 | 2,020 | -2% | 0 | 0 | — |
case-13 | fail→pass | 34,136 | 2,831 | -92% | 1 | 1 | 0% | 4,009 | 1,770 | -56% | 0 | 0 | — |
case-14 | fail→pass | 20,297 | 8,113 | -60% | 1 | 1 | 0% | 2,344 | 2,427 | +4% | 0 | 0 | — |
case-15 | fail→pass | 19,521 | 9,501 | -51% | 1 | 1 | 0% | 2,252 | 1,982 | -12% | 0 | 0 | — |
case-16 | fail→pass | 23,913 | 7,971 | -67% | 1 | 1 | 0% | 947 | 1,714 | +81% | 0 | 0 | — |
case-17 | pass→pass | 10,393 | 16,278 | +57% | 1 | 1 | 0% | 1,889 | 1,775 | -6% | 0 | 0 | — |
case-18 | fail→pass | 13,650 | 8,000 | -41% | 1 | 1 | 0% | 1,644 | 1,629 | -1% | 0 | 0 | — |
case-19 | fail→pass | 20,706 | 19,894 | -4% | 1 | 1 | 0% | 2,837 | 2,168 | -24% | 0 | 0 | — |
case-20 | fail→pass | 22,425 | 19,645 | -12% | 1 | 1 | 0% | 3,291 | 3,264 | -1% | 0 | 0 | — |
case-21 | pass→pass | 21,380 | 19,677 | -8% | 1 | 1 | 0% | 2,669 | 1,951 | -27% | 0 | 0 | — |
case-22 | fail→pass | 33,983 | 9,364 | -72% | 1 | 1 | 0% | 1,845 | 1,834 | -1% | 0 | 0 | — |
case-23 | fail→pass | 8,322 | 9,272 | +11% | 1 | 1 | 0% | 1,308 | 1,890 | +44% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted. The headline lift of +61 percentage points is the difference between those two pass rates over the 23 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.