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Tutorial 02: Explore All Domains

Survey every built-in domain Spindle offers and compare their schemas side by side.

Prerequisites

  • Completed Tutorial 01: Hello Spindle (or have sqllocks-spindle installed)
  • Basic familiarity with relational schemas (tables, foreign keys)

What You'll Learn

  • How to import and list all 13 built-in domain classes
  • How to compare table counts and relationship counts across domains
  • How to deep-dive into a domain's schema structure and generation order
  • How to generate two domains side by side and compare their output

Step 1: Import All Domain Classes

Spindle ships with 13 pre-built domains. Each one is a self-contained schema definition — a blueprint for an entire relational database.

from sqllocks_spindle import (
    RetailDomain,
    HealthcareDomain,
    FinancialDomain,
    SupplyChainDomain,
    IoTDomain,
    HrDomain,
    InsuranceDomain,
    MarketingDomain,
    EducationDomain,
    RealEstateDomain,
    ManufacturingDomain,
    TelecomDomain,
    CapitalMarketsDomain,
)

print("All 13 domain classes imported successfully!")

Step 2: List Every Domain

Instantiate each domain, call get_schema(), and print a summary table. This gives you a bird's-eye view of everything Spindle offers without reading documentation page by page.

domains = [
    RetailDomain(),
    HealthcareDomain(),
    FinancialDomain(),
    SupplyChainDomain(),
    IoTDomain(),
    HrDomain(),
    InsuranceDomain(),
    MarketingDomain(),
    EducationDomain(),
    RealEstateDomain(),
    ManufacturingDomain(),
    TelecomDomain(),
]

print(f"{'Domain':<22} {'Description':<45} {'Tables':>6} {'FKs':>6}")
print("-" * 82)

for domain in domains:
    schema = domain.get_schema()
    print(
        f"{schema.name:<22} "
        f"{schema.description[:43]:<45} "
        f"{len(schema.tables):>6} "
        f"{len(schema.relationships):>6}"
    )

print(f"\nTotal domains: {len(domains)}")

Each domain exposes a name, description, a tables dictionary, and a list of relationships (foreign keys). This loop prints them all in a compact comparison table.

Step 3: Deep-Dive into the Retail Domain

Pick any domain and inspect its internal structure. Here we will look at the Retail domain's tables, column counts, and generation order.

retail = RetailDomain()
schema = retail.get_schema()

print(f"Domain: {schema.name}")
print(f"Description: {schema.description}")
print(f"\n=== Tables ({len(schema.tables)}) ===")
for table_name, table_def in schema.tables.items():
    col_count = len(table_def.columns)
    print(f"  {table_name:<30} {col_count:>3} columns")

print(f"\n=== Generation Order ===")
for i, table_name in enumerate(schema.generation_order, 1):
    print(f"  {i}. {table_name}")

The generation order reveals the dependency graph. Parent tables like customers are generated first, then child tables like orders that reference them. This is how Spindle guarantees referential integrity without post-processing.

Step 4: Generate and Compare Retail vs. Healthcare

Generate both domains at the fabric_demo scale and compare their summaries and timing.

import time
from sqllocks_spindle import Spindle

# Generate Retail
t0 = time.perf_counter()
retail_result = Spindle.generate(
    domain=RetailDomain(), scale="fabric_demo", seed=42
)
retail_time = time.perf_counter() - t0

# Generate Healthcare
t0 = time.perf_counter()
healthcare_result = Spindle.generate(
    domain=HealthcareDomain(), scale="fabric_demo", seed=42
)
healthcare_time = time.perf_counter() - t0

print("=== Retail Domain ===")
print(retail_result.summary())

print("\n=== Healthcare Domain ===")
print(healthcare_result.summary())

print("\n=== Timing Comparison ===")
print(f"  Retail:     {retail_time:.2f}s")
print(f"  Healthcare: {healthcare_time:.2f}s")

Different domains have different complexities -- more tables, more relationships, more columns. This comparison helps you understand performance characteristics and choose appropriate scales for your use case.

Run It Yourself

  • Domain Catalog -- full reference for all 13 domains with table schemas and descriptions

Next Step

Tutorial 03: Custom Schemas -- define your own tables, columns, and relationships from scratch.