2e1dfb7553
Replaces the BigQuery wrap-view pattern with a discovery + scoped-fetch toolkit driven by the analyst's Claude session. Adds /api/v2/{catalog,schema,sample,scan,scan/estimate}, da catalog/schema/describe/fetch/snapshot/disk-info CLI commands, sqlglot-backed WHERE validator, process-local quota tracker, agent rails skill (cli/skills/agnes-data-querying.md). BREAKING: BQ wrap views off by default — set data_source.bigquery.legacy_wrap_views=true for one cycle. Backward-compat field_validator on primary_key. Catalog cache now matches documented 300s TTL with RBAC fresh per request. Cuts release v0.14.0.
45 lines
1.6 KiB
Python
45 lines
1.6 KiB
Python
"""`da schema <table>` — show columns + BQ flavor hints (spec §4.1)."""
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import json as json_lib
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import typer
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from cli.v2_client import api_get_json, V2ClientError
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schema_app = typer.Typer(help="Show column metadata for a table")
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@schema_app.callback(invoke_without_command=True)
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def schema(
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ctx: typer.Context,
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table_id: str = typer.Argument(...),
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json: bool = typer.Option(False, "--json"),
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):
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"""Show column metadata for a table."""
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if ctx.invoked_subcommand is not None:
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return
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try:
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data = api_get_json(f"/api/v2/schema/{table_id}")
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except V2ClientError as e:
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typer.echo(f"Error: schema fetch failed: {e}", err=True)
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raise typer.Exit(5 if e.status_code >= 500 else 8 if e.status_code == 403 else 2)
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if json:
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typer.echo(json_lib.dumps(data, indent=2))
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return
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flavor = data.get("sql_flavor", "duckdb")
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typer.echo(f"Table: {data['table_id']} ({data['source_type']} — use {flavor.upper()} SQL dialect)")
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typer.echo("")
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typer.echo(f"{'COLUMN':30s} {'TYPE':15s} {'NULL':5s} DESCRIPTION")
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for c in data.get("columns", []):
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typer.echo(
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f"{c['name']:30s} {c['type']:15s} "
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f"{'YES' if c.get('nullable') else 'NO':5s} {c.get('description', '')}"
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)
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if data.get("partition_by"):
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typer.echo(f"\nPartition: {data['partition_by']}")
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if data.get("clustered_by"):
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typer.echo(f"Clustered: {', '.join(data['clustered_by'])}")
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if data.get("where_dialect_hints"):
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typer.echo("\nWHERE dialect hints:")
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for k, v in data["where_dialect_hints"].items():
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typer.echo(f" {k:25s} {v}")
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