Skip to main content

Convert your python types to typescript

Project description

Petit ts

Codecov GitHub license

A Library to easely 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, Named

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 easely

# 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*/"

not_inlined = store.get_all_not_inlined(exported_all=True)
print(not_inlined)
# >>> "export type CreateUserDto  = {
# 	username: string;
# 	password: string | Jeb;
# 	role: UserType;
# 	jeb: TestUnion;
# };
# export enum Jeb {
# 	A = "R",
# };
# export type UserType = "admin" | "user";
# export 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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

petit_ts-0.2.0.tar.gz (8.7 kB view details)

Uploaded Source

Built Distribution

petit_ts-0.2.0-py2.py3-none-any.whl (9.4 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file petit_ts-0.2.0.tar.gz.

File metadata

  • Download URL: petit_ts-0.2.0.tar.gz
  • Upload date:
  • Size: 8.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/49.2.1 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.8.6

File hashes

Hashes for petit_ts-0.2.0.tar.gz
Algorithm Hash digest
SHA256 0779066f78fe0f89bc150b50b5be0913fc51b003a15c9ffe49564385bef48167
MD5 735ca228d06cdb975012acf654664c70
BLAKE2b-256 e6415ef135faf60c7b1ca1ff92ac51c23e5eaeed4c6bb5b90720f936f4ef59d6

See more details on using hashes here.

File details

Details for the file petit_ts-0.2.0-py2.py3-none-any.whl.

File metadata

  • Download URL: petit_ts-0.2.0-py2.py3-none-any.whl
  • Upload date:
  • Size: 9.4 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/49.2.1 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.8.6

File hashes

Hashes for petit_ts-0.2.0-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 87b2db44fe3d89ccab2bade9746e79158e4798bbb58005ac4a6672f898530c05
MD5 92ae441e9dd3373174b16f9242aeea9a
BLAKE2b-256 a2fc0bab0a96cac264c39ddaef953957577d7da2c9fa1a673861dc7088ee4ea8

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page