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Este script muestra cómo ejecutar consultas SQL en SeaTable con base.query(). A diferencia de base.list_rows(), con SQL puede filtrar, agrupar y agregar datos de forma selectiva, sin necesidad de cargar todas las filas. El script es adecuado para la ejecución manual o como automatización.

SQL Queries Base en SeaTable

base.list_rows() base.query()
Filtrado Solo mediante filtros de vista Cláusula WHERE
Agrupación No es posible GROUP BY
Agregación No es posible SUM, COUNT, AVG, MIN, MAX
Límite estándar 100 filas 100 filas
Límite máximo 1.000 filas 10.000 filas

El script ejecuta varias consultas SQL contra una tabla de pedidos y muestra los resultados. Ajuste TABLE a la estructura de su tabla.

from seatable_api import Base, context

base = Base(context.api_token, context.server_url)
base.auth()

TABLE = "Orders"

# 1. Filter: unpaid orders
print("=== Unpaid orders ===")
rows = base.query(f"SELECT Product, Customer, Amount FROM `{TABLE}` WHERE `Paid` = false")
for row in rows:
    print(f"  {row['Product']} - {row['Customer']} - {row['Amount']}")

# 2. Aggregate: total revenue per category
print(".")
print("=== Revenue per category ===")
rows = base.query(f"SELECT Category, SUM(Amount) AS total FROM `{TABLE}` GROUP BY Category")
for row in rows:
    print(f"  {row['Category']}: {row['total']}")

# 3. Aggregate: orders per customer
print(".")
print("=== Orders per customer ===")
rows = base.query(f"SELECT Customer, COUNT(*) AS orders, SUM(Amount) AS total FROM `{TABLE}` GROUP BY Customer ORDER BY total DESC")
for row in rows:
    print(f"  {row['Customer']}: {row['orders']} orders, {row['total']} total")

# 4. Filter with date range
print(".")
print("=== Orders in March 2026 ===")
rows = base.query(f"SELECT Product, Customer, Date, Amount FROM `{TABLE}` WHERE `Date` BETWEEN '2026-03-01' AND '2026-03-31'")
for row in rows:
    print(f"  {row['Date']} - {row['Product']} ({row['Customer']}): {row['Amount']}")

# 5. Summary
print(".")
print("=== Summary ===")
rows = base.query(f"SELECT COUNT(*) AS count, SUM(Amount) AS revenue, AVG(Amount) AS avg_order FROM `{TABLE}`")
r = rows[0]
print(f"  {r['count']} orders, {r['revenue']} total revenue, {r['avg_order']:.2f} avg order value")

Salida SQL Queries

SeaTable soporta las operaciones SQL más importantes:

  • WHERE — Filtrar con =, !=, LIKE, IN, BETWEEN, IS NULL
  • GROUP BY — Agrupar con SUM, COUNT, AVG, MIN, MAX
  • ORDER BY — Ordenar (ASC/DESC)
  • LIMIT / OFFSET — Limitar resultados (máx. 10.000)
  • DISTINCT — Solo valores únicos

La referencia SQL completa se encuentra en el SeaTable Developer Manual .