Skip to main content

Database Schemas

The DatabaseSchemas class provides CRUD operations for database schema metadata. FQN format: service_name.database_name.schema_name

Import

from metadata.sdk import configure, DatabaseSchemas
from metadata.generated.schema.api.data.createDatabaseSchema import CreateDatabaseSchemaRequest

configure(host="https://your-instance.getcollate.io/api", jwt_token="your-token")

Create

schema = DatabaseSchemas.create(
    CreateDatabaseSchemaRequest(
        name="public",
        database="my_postgres.analytics",
        description="Default public schema",
    )
)
print(schema.fullyQualifiedName)  # "my_postgres.analytics.public"

Retrieve

# By ID
schema = DatabaseSchemas.retrieve("schema-uuid")

# By FQN
schema = DatabaseSchemas.retrieve_by_name("my_postgres.analytics.public")

# With fields
schema = DatabaseSchemas.retrieve_by_name(
    "my_postgres.analytics.public",
    fields=["owners", "tags"],
)

List

# Single page
page = DatabaseSchemas.list(limit=50)

# All schemas
all_schemas = DatabaseSchemas.list_all()

# Filter by database
schemas = DatabaseSchemas.list_all(filters={"database": "my_postgres.analytics"})

Update

schema = DatabaseSchemas.retrieve_by_name("my_postgres.analytics.public")
schema.description = "Updated schema description"
DatabaseSchemas.update(schema)

Delete

DatabaseSchemas.delete("schema-uuid")
DatabaseSchemas.delete("schema-uuid", recursive=True)
results = DatabaseSchemas.search("public")
for schema in results:
    print(schema.fullyQualifiedName)

CSV Export / Import

csv_content = DatabaseSchemas.export_csv("my_postgres.analytics").execute()
DatabaseSchemas.import_csv("my_postgres.analytics").with_data(csv_content).execute()