petit-ts 0.1.10

Convert your python types to typescript

Petit ts

A Library to easly convert your python types to typescript types.

It's a part of the petite_stack (not released yet, as not mature enough).

Example

from petit_ts import TSTypeStore, Name

store = TSTypeStore()


class Jeb(Enum):
    A = 'R'


# if you want an union to be named and not inlined
UserType = Named(Literal['admin', 'user'])

TestUnion = Named(Union[str, int])

class CreateUserDto(BaseModel):
    username: str
    # will be inlined
    password: Union[str, Jeb]
    # won't be inlined
    role: UserType
    # won't be inlined
    jeb: TestUnion

store.add_type(CreateUserDto)

res = store.get_repr(CreateUserDto)
print(res)
# >>> "CreateUserDto"

# Here you notice that we have the name instead of the body, so that you can use it
# in another function easly

# here we need to do this in order, to get all the required deps into our ts file
not_inlined = store.get_all_not_inlined()
print(not_inlined)
# >>> "type CreateUserDto  = {
# 	username: string;
# 	password: string | Jeb;
# 	role: UserType;
# 	jeb: TestUnion;
# };
# export enum Jeb {
# 	A = "R",
# };
# type UserType = "admin" | "user";
# type TestUnion = string | number /*int*/"

with open('res.ts', 'w') as f :
    # write what you need to the file
    final = f'export a = function (a: any): {store.get_repr(CreateUserDto)};'
    final += store.get_all_not_inlined()
    f.write(final)

Supported types:

• None
• bool
• str
• int
• float
• Dict[K, V], Dict, dict
• List[T], List, list
• @dataclass, generic @dataclass
• Optional[T], Named(Optional[T])
• Union[A, B, ...], Named(Union[A, B, ...])
• Literal[values], Named(Literal[1, 2, '3']) with values = Union[int, str]
• Tuple[A, B, ...], Named(Tuple[A, B, ...])

Add support for a custom type

Example for the BaseModel type:

from typing import Tuple, Optional, Dict, Any, get_type_hints
from petit_ts import ClassHandler, TSTypeStore
from pydantic import BaseModel

store = TSTypeStore()

class BaseModelHandler(ClassHandler):
    @staticmethod
    def is_mapping() -> bool:
        return True

    @staticmethod
    def should_handle(cls, store, origin, args) -> bool:
        return issubclass(cls, BaseModel)

    @staticmethod
    def build(cls: BaseModel, store, origin, args) -> Tuple[Optional[str], Dict[str, Any]]:
        name = cls.__name__
        fields = get_type_hints(cls)
        return name, fields


store.add_class_handler(BaseModelHandler)

You have to implement for the ClassHandler:

• is_mapping
• should_handle
• build

If this is a mapping, you should return the fields, a Dict[str, Any] else you should return a string

For the BasicHandler :

• build
• should_handle

Support for Named types:

if you need a type to be exported with it's definition name, you can use the Namedfunction as such :

P = Named(Union[str, int])
# will be exported to type P = string | number;

You can name any of :

• Optional
• Union
• Literal
• Tuple

If you have any problem, don't hesitate to open an issue on github !

Support for type spoofing:

As you'll see with pydantic.BaseModel, NamedUnion is not supported by default because of the way the Union is defined in the typing lib.

In order to support this, petit_ts provides the patch_get_origin_for_Union, it will make other libraries believe NamedUnion is Union. So you have to call patch_get_origin_for_Union() before importing pydantic.

Next steps :

• Handle multiple type of collection
• Handle abstract types
• Choose between interface and type