chore: auto-commit (286 archivos)
- .claude/agents/fn-orquestador/SKILL.md - .claude/commands/fn_claude.md - .claude/rules/INDEX.md - .claude/rules/cpp_apps.md - .claude/rules/ids_naming.md - CHANGELOG.md - apps/dag_engine/README.md - apps/dag_engine/api.go - apps/dag_engine/dags_migrated/example.yaml - apps/dag_engine/dags_migrated/example_lineage_tracking.yaml - ... Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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# Capability: bigquery
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_(Descripcion del grupo — editar a mano)_
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Operar Google BigQuery via SDK Python `google-cloud-bigquery` y Go `fetch_data_frame`. Cubre: auth (`bq_auth`), queries con caching, gestion de datasets/tables (create/copy/delete/get/list), jobs (cancel, wait), schemas, exports a GCS, y carga a DataFrames (`fetch_data_frame`, polars).
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## Funciones
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## Ejemplo canonico
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_(Anadir 1-2 bloques de codigo end-to-end)_
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### Query + cargar a polars
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```python
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import os, sys
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sys.path.insert(0, os.path.join(os.environ["FN_REGISTRY_ROOT"], "python", "functions"))
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from infra import bq_auth, bq_query
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client = bq_auth(project_id="my-gcp-project")
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df = bq_query(client, "SELECT * FROM `my-gcp-project.dataset.table` LIMIT 1000")
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print(df.shape)
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```
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### Gestion de tablas
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```bash
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./fn run bq_list_tables --dataset analytics
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./fn run bq_create_table --dataset analytics --table events --schema-file schema.json
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./fn run bq_copy_table --src analytics.events --dst analytics.events_backup
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```
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### Carga a DataFrame Go (polars/pandas-go)
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```bash
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./fn run fetch_data_frame --query "SELECT date, sales FROM analytics.daily" --output sales.parquet
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```
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## Fronteras
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_(Que NO cubre este grupo)_
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- **NO maneja Auth ADC interactivo**. Asume credenciales via service account JSON o `gcloud auth application-default login` ya ejecutado.
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- **NO billing analytics**. Para coste/quota analysis, BigQuery UI o Cloud Console.
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- **NO orquesta Dataflow ni Dataproc**. Solo SQL queries + table ops.
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- Comparte funciones con tags `gcp` y `google-cloud` (mismas funciones, multi-tag).
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