egutierrez
9f5e6791db
Funciones CRUD completas para BigQuery: auth, datasets, tables, queries, jobs, routines, load/export. Tipo BQClient como wrapper del SDK oficial.
135 lines
4.2 KiB
Python
135 lines
4.2 KiB
Python
"""Gestion de routines (UDFs y stored procedures) en Google BigQuery."""
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from .client import BQClient
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from google.cloud import bigquery
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def bq_create_routine(
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client: BQClient,
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dataset_id: str,
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routine_id: str,
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body: str,
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routine_type: str = "SCALAR_FUNCTION",
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language: str = "SQL",
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arguments: list[dict] | None = None,
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return_type: str = "",
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description: str = "",
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) -> dict:
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"""Crea una routine (UDF o stored procedure) en BigQuery.
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Args:
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client: Cliente autenticado.
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dataset_id: ID del dataset donde crear la routine.
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routine_id: ID/nombre de la routine.
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body: Cuerpo de la routine (SQL, JavaScript o Python).
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routine_type: Tipo: "SCALAR_FUNCTION", "TABLE_VALUED_FUNCTION", "PROCEDURE".
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language: Lenguaje: "SQL", "JAVASCRIPT", "PYTHON".
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arguments: Lista de argumentos, cada uno: {"name": "x", "data_type": "STRING"}.
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return_type: Tipo de retorno para funciones (ej: "STRING", "INT64"). No aplica a procedures.
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description: Descripcion opcional.
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Returns:
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Dict con: routine_id, dataset_id, project, routine_type, language, body, created, modified.
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Raises:
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google.api_core.exceptions.Conflict: Si la routine ya existe.
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Example:
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>>> bq_create_routine(client, "analytics", "double_value",
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... body="x * 2",
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... arguments=[{"name": "x", "data_type": "INT64"}],
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... return_type="INT64")
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"""
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ref = bigquery.RoutineReference.from_string(
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f"{client.project_id}.{dataset_id}.{routine_id}"
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)
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routine = bigquery.Routine(ref)
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routine.type_ = routine_type
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routine.language = language
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routine.body = body
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if description:
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routine.description = description
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if arguments:
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routine.arguments = [
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bigquery.RoutineArgument(
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name=arg["name"],
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data_type=bigquery.StandardSqlDataType(
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type_kind=getattr(
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bigquery.StandardSqlTypeNames, arg["data_type"]
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)
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),
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)
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for arg in arguments
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]
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if return_type:
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routine.return_type = bigquery.StandardSqlDataType(
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type_kind=getattr(bigquery.StandardSqlTypeNames, return_type)
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)
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created = client._client.create_routine(routine)
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return _routine_to_dict(created)
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def bq_list_routines(client: BQClient, dataset_id: str) -> list[dict]:
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"""Lista routines de un dataset.
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Args:
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client: Cliente autenticado.
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dataset_id: ID del dataset.
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Returns:
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Lista de dicts con: routine_id, dataset_id, project, routine_type, language.
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Example:
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>>> routines = bq_list_routines(client, "analytics")
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>>> for r in routines:
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... print(r["routine_id"], r["routine_type"], r["language"])
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"""
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ref = f"{client.project_id}.{dataset_id}"
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return [
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{
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"routine_id": r.routine_id,
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"dataset_id": dataset_id,
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"project": client.project_id,
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"routine_type": r.type_,
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"language": r.language,
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}
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for r in client._client.list_routines(ref)
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]
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def bq_delete_routine(
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client: BQClient,
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dataset_id: str,
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routine_id: str,
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) -> None:
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"""Elimina una routine.
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Args:
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client: Cliente autenticado.
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dataset_id: ID del dataset.
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routine_id: ID de la routine a eliminar.
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Raises:
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google.api_core.exceptions.NotFound: Si la routine no existe.
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Example:
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>>> bq_delete_routine(client, "analytics", "double_value")
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"""
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ref = f"{client.project_id}.{dataset_id}.{routine_id}"
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client._client.delete_routine(ref)
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def _routine_to_dict(routine) -> dict:
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"""Convierte un objeto Routine del SDK a dict plano."""
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return {
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"routine_id": routine.routine_id,
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"dataset_id": routine.dataset_id,
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"project": routine.project,
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"routine_type": routine.type_,
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"language": routine.language,
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"body": routine.body,
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"description": routine.description or "",
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"created": routine.created.isoformat() if routine.created else None,
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"modified": routine.modified.isoformat() if routine.modified else None,
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}
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