Table des matières

Ce script montre comment exécuter des requêtes SQL dans SeaTable avec base.query(). Contrairement à base.list_rows(), SQL vous permet de filtrer, grouper et agréger les données de manière ciblée, sans avoir à charger toutes les lignes. Le script convient à l’exécution manuelle ou en tant qu’automation.

SQL Queries Base dans SeaTable

base.list_rows() base.query()
Filtrage Uniquement via les filtres de vue Clause WHERE
Regroupement Pas possible GROUP BY
Agrégation Pas possible SUM, COUNT, AVG, MIN, MAX
Limite standard 100 lignes 100 lignes
Limite maximale 1 000 lignes 10 000 lignes

Le script exécute différentes requêtes SQL sur une table de commandes et affiche les résultats. Adaptez TABLE à la structure de votre table.

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")

Sortie SQL Queries

SeaTable prend en charge les opérations SQL les plus importantes :

  • WHERE — Filtrer avec =, !=, LIKE, IN, BETWEEN, IS NULL
  • GROUP BY — Grouper avec SUM, COUNT, AVG, MIN, MAX
  • ORDER BY — Trier (ASC/DESC)
  • LIMIT / OFFSET — Limiter les résultats (max. 10 000)
  • DISTINCT — Valeurs uniques uniquement

La référence SQL complète se trouve dans le SeaTable Developer Manual .