dbml_sharepoint.model.parser

parse DBML into the in-memory schema

DBML parser wrapper.

Wraps pydbml and post-processes its output into a stable in-memory schema model the rest of the deployer works against.

The supported DBML subset is documented in docs/design/requirements/dbml-sharepoint-requirements.md §5.

Reference

@dataclass
class Reference:
    target_table: str
    target_column: str

Foreign-key reference to another table's column.

Column

@dataclass
class Column:
    name: str
    type: str
    required: bool = False
    unique: bool = False
    default: str | int | bool | None = None
    ref: dbml_sharepoint.model.parser.Reference | None = None
    note: str = ''
    is_pk: bool = False
    is_auto_increment: bool = False

A single column on a DBML Table.

Table

@dataclass
class Table:
    name: str
    columns: list[dbml_sharepoint.model.parser.Column] = list()
    note: str = ''

A DBML Table — name, columns, optional table-level note.

EnumDef

@dataclass
class EnumDef:
    name: str
    members: list[str] = list()

A DBML Enum declaration with ordered members.

Schema

@dataclass
class Schema:
    tables: list[dbml_sharepoint.model.parser.Table] = list()
    enums: list[dbml_sharepoint.model.parser.EnumDef] = list()
    project_note: str = ''

In-memory representation of a parsed DBML schema.

parse_dbml

def parse_dbml(path: pathlib.Path) -> dbml_sharepoint.model.parser.Schema

Parse a DBML file and return our in-memory model.