Pydantic

Example Output

personinfo_pydantic.py

Overview

The Pydantic Generator produces Pydantic flavored python dataclasses from a linkml model, with optional support for user-supplied jinja2 templates to generate alternate classes.

Example

Given a definition of a Person class:

Person:
  is_a: NamedThing
  description: >-
    A person (alive, dead, undead, or fictional).
  class_uri: schema:Person
  mixins:
    - HasAliases
  slots:
    - primary_email
    - birth_date
    - age_in_years
    - gender
    - current_address
    - has_employment_history
    - has_familial_relationships
    - has_medical_history

(some details omitted for brevity, including slot definitions and parent classes)

The generate python looks like this:

class Person(NamedThing):
    """
    A person (alive, dead, undead, or fictional).
    """
    primary_email: Optional[str] = Field(None)
    birth_date: Optional[str] = Field(None)
    age_in_years: Optional[int] = Field(None, ge=0, le=999)
    gender: Optional[GenderType] = Field(None)
    current_address: Optional[Address] = Field(None, description="""The address at which a person currently lives""")
    has_employment_history: Optional[List[EmploymentEvent]] = Field(None)
    has_familial_relationships: Optional[List[FamilialRelationship]] = Field(None)
    has_medical_history: Optional[List[MedicalEvent]] = Field(None)
    aliases: Optional[List[str]] = Field(None)
    id: Optional[str] = Field(None)
    name: Optional[str] = Field(None)
    description: Optional[str] = Field(None)
    image: Optional[str] = Field(None)

Docs

Command Line

gen-pydantic

Generate pydantic classes to represent a LinkML model

gen-pydantic [OPTIONS] YAMLFILE

Options

--template_file <template_file>

Optional jinja2 template to use for class generation

-f, --format <format>

Output format

Default

pydantic

Options

pydantic

--metadata, --no-metadata

Include metadata in output

Default

True

--useuris, --metauris

Include metadata in output

Default

True

-im, --importmap <importmap>

Import mapping file

--log_level <log_level>

Logging level

Default

WARNING

Options

CRITICAL | ERROR | WARNING | INFO | DEBUG

-v, --verbose

verbosity

--mergeimports, --no-mergeimports

Merge imports into source file (default=mergeimports)

Arguments

YAMLFILE

Required argument

Code

class linkml.generators.pydanticgen.PydanticGenerator(schema: ~typing.Union[str, ~typing.TextIO, ~linkml_runtime.linkml_model.meta.SchemaDefinition, Generator], schemaview: ~typing.Optional[~linkml_runtime.utils.schemaview.SchemaView] = None, format: ~typing.Optional[str] = None, metadata: bool = <factory>, useuris: ~typing.Optional[bool] = None, log_level: int = 30, mergeimports: ~typing.Optional[bool] = <factory>, source_file_date: ~typing.Optional[str] = None, source_file_size: ~typing.Optional[int] = None, logger: ~typing.Optional[~logging.Logger] = None, verbose: ~typing.Optional[bool] = None, output: ~typing.Optional[str] = None, namespaces: ~typing.Optional[~linkml_runtime.utils.namespaces.Namespaces] = None, directory_output: bool = False, base_dir: str = None, metamodel_name_map: ~typing.Dict[str, str] = None, importmap: ~typing.Optional[~typing.Union[str, ~typing.Mapping[str, str]]] = None, emit_prefixes: ~typing.Set[str] = <factory>, metamodel: ~linkml.utils.schemaloader.SchemaLoader = None, template_file: str = None, package: str = 'example', allow_extra: bool = <factory>, gen_mixin_inheritance: bool = <factory>, gen_classvars: bool = <factory>, gen_slots: bool = <factory>, genmeta: bool = <factory>, emit_metadata: bool = <factory>, **_kwargs)[source]

Generates Pydantic-compliant classes from a schema

This is an alternative to the dataclasses-based Pythongen

serialize() → str[source]

Generate output in the required format

Parameters

kwargs – Generater specific parameters

Returns

Generated output

Additional Notes

LinkML contains two Python generators. The Pydantic dataclass generator is specifically useful for FastAPI, but is newer and less full featured than the standard Python generator.