Diagram: Schema

Schema diagrams display database table structures: columns, data types, primary key and foreign key markers, plus labelled relationship arcs.

Minimal example

import engrapha_notes as en
import engrapha_diagrams as ed

schema = ed.SchemaDiagram(
    width=450, height=200, caption="Fig 4: Blog Schema"
)

schema.table("users", [
    ("id",         "INTEGER", {"pk": True}),
    ("email",      "VARCHAR", {}),
    ("created_at", "TIMESTAMP", {}),
])

schema.table("posts", [
    ("id",          "INTEGER",  {"pk": True}),
    ("user_id",     "INTEGER",  {"fk": True}),
    ("title",       "VARCHAR",  {}),
    ("published_at", "TIMESTAMP", {}),
])

schema.relation("posts", "user_id", "users", "id")

en.add(schema.as_flowable())

Column flags

schema.table("orders", [
    ("id",        "INTEGER", {"pk": True}),    # Primary Key
    ("user_id",   "INTEGER", {"fk": True}),     # Foreign Key
    ("total",     "DECIMAL", {}),
])

• pk=True: PK appended, bold accent-colored text
• fk=True: (FK) appended, relation-colored text

Auto layout

If every table is at (0, 0) (the default), SchemaDiagram distributes them on a grid automatically:

schema.table("users", [...])
schema.table("orders", [...])
schema.table("products", [...])
# → auto-positioned in a grid

Choosing between ER and Schema

Use ERDiagram when you care about:

• Chen notation (entity rectangles, diamonds)
• Weak vs strong entities
• Cardinalities (1, N, M)
• Identifying relationships

Use SchemaDiagram when you care about:

• Table-like view with column types
• Primary / Foreign key markers
• Quick SQL-style wireframes

Next

• ER Diagram
• Architecture