python-to-typescript-interfaces 0.2.0

Description:

pythontotypescriptinterfaces 0.2.0

python-to-typescript-interfaces
Python to TypeScript Interfaces




What is this
Installation
Motivation
Usage
Why @dataclass?
Why define the types in Python instead of TypeScript?
Supported Type Mappings
Supported Enum

Troubleshooting with Enum and sqlalchemy


Support for inheritance
Support for datetime and date
Planned Supported Mappings
Unsupported/Rejected Mappings
Contributing
Author

What is this?
This library provides utilities that convert Python dataclasses with type
annotations to a TypeScript interface and serializes them to a file.
Installation
python --version # requires 3.8+
pip install python-to-typescript-interfaces

Motivation
In web applications where Python is used in the backend and TypeScript is used
in the frontend, it is often the case that the client will make calls to the
backend to request some data with some specific pre-defined "shape". On the
client-side, an interface for this data is usually defined and if the Python
backend authors use typechecking, like with mypy, the
project authors may be typing the JSON response values as well.
This results in a duplication of code. If the shape changes in the backend,
the related interface must also be reflect its changes in the frontend. At
best, this is annoying to maintain. At worst, over time the interfaces may
diverge and cause bugs.
This library aims to have a single source of truth that describes the shape of
the payload between the backend and the frontend.
Usage
In Python, python-to-typescript-interfaces exposes a new class object called Interface.
By subclassing this object, you identify to the also-packaged script that you
want it to be serialized to an interface file.

First, hook up your dataclasses:

# views.py
from dataclasses import dataclass
from python_to_typescript_interfaces import Interface

@dataclass
class MyComponentProps(Interface):
name: str
show: bool
value: float

@dataclass
class WillNotGetPickedUp: # this doesn't subclass Interface, so it won't be included
name: str
value: float


In your shell, run the included command and pass in the name of the file or
directory you want to use. By default it will output to a file in your
directory called interface.ts

$ python-to-typescript-interfaces views.py
Created interface.ts!

You may also use the following arguments:

-o, --output [filepath]: where the file will be saved. default is interface.ts.
-a, --append: by default each run will overwrite the output file. this flag
allows only appends. Be warned, duplicate interfaces are not tested.
-e, --export: whether the interface definitions should be prepended with export;
-dt, --date-type: defines how date types should be tranformed to, (default: string);


The resulting file will look like this:

// interface.ts
interface MyComponentProps {
name: string;
show: boolean;
value: number;
}

Why @dataclass?
Dataclasses were introduced in Python 3.7 and they are great. Some
alternatives that I have seen other codebases using are NamedTuple and
TypedDict. All of these objects attempt to do the same thing: group together
pieces of data that belong close together like a struct.
However, dataclass won out over the other two for the following reasons:

dataclasses are built-in to Python. As of writing, NamedTuple is also
built-in to the typing module, but TypedDict is still considered
experimental.
dataclasses cannot be declared and defined inline like you can do with
NamedTuple and TypedDict, e.g., NamedTuple can be defined using class
inheritance like class MyNamedTuple(NamedTuple): ..., but also like
MyNamedTuple = NamedTuple('MyNamedTuple', [('name', str), ('id', int)]).
This is a good thing. Dataclasses require you to use a class style
declaration, which not only looks closer to a TypeScript interface
declaration, but it avoids the complex metaclass machinery that NamedTuples
and TypedDicts use to gain all its features. Since this library uses the
AST and static analysis of the code to determine what data to serialize,
this makes the choice a no-brainer.
dataclasses can be made to be immutable (mostly) by setting frozen=True.
This library does not require it but in later versions we may provide a
partialed dataclass decorator that guarantees immutability.
Because we avoid the metaclass machinery of NamedTuples and TypedDicts, it
opens up the possibility of writing custom classes that allows mypy to
typecheck it one way, but gives the AST parser some clues in order to
generate TypeScript types that cannot easily be expressed in Python.

Why define the types in Python instead of TypeScript?
TypeScript is significantly more mature for typing syntax than Python.
Generally speaking, you can express any type that Python can do in TypeScript,
but not vice versa.
So defining the types in Python guarantee that you can also express the whole
interface in both languages.
Supported Type Mappings
Please note that usage of T U and V in the table below represent
stand-ins for actual types. They do not represent actually using generic typed
variables.



Python
Typescript




None
null


str
string


int
number


float
number


complex
number


bool
boolean


List
Array<any>


Tuple
[any]


Dict
Record<any, any>


List[T]
Array[T]


Tuple[T, U]
[T, U]


Dict[T, U]
Record<T, U>


Optional[T]
T | null


Union[T, U, V]
T | U | V


Enum
enum


datetime
Default : string


date
Default : string



Supported Enum
According python Restricted Enum subclassing doc, A new Enum class must have one base enum class, up to one concrete data type, and as many object-based mixin classes as needed. The order of these base classes is:
class EnumName([mix-in, ...,] [data-type,] base-enum):
pass

so the order is important when you add the Interface class on your enum class, Enum class should always be the last one.
from dataclasses import dataclass
from enum import Enum

from python_to_typescript_interfaces import Interface

@dataclass
class Animal(Interface, Enum):
DOG = "dog"
CAT = "cat"

Troubleshooting with Enum and sqlalchemy
If you want to use Enums with Interface class in sqlalchemy, you will have an error saying that the type is unhashable. To avoid this, and make your Enums working with sqlalchemy you need to add a __hash__ like bellow:
@dataclass
class AnimalSpecies(Interface, Enum):
DOG = "dog"
CAT = "cat"

def __hash__(self):
return hash(self.name)

Support for inheritance
Inheritance is supported only with classes also parsed in the process. For example below, BaseModel will not be extended as this class doesn't exist in the file.
@dataclass
class Simple0(Interface):
a: int
b: str


@dataclass
class Simple1(Interface):
c: int


@dataclass
class Simple2(BaseModel, Simple0, Simple1, Interface):
d: str

Above python code will be transformed like bellow typescript code :
export interface Simple0 {
a: number;
b: string;
}

export interface Simple1 {
c: number;
}

export interface Simple2 extends Simple0, Simple1 {
d: string;
}

Support for datetime and date
Support for datetime and date types is available through -dt, --date-type flag. We have decided to add this support in a configurable way as dates can be transformed in different types depending the projet / implementation. Possible choices are ["string", "number", "Date"] and the default one is string (because it's the return type of a Date.prototype.toJSON()).
Examples with below python class:
from dataclasses import dataclass
from datetime import datetime, date

from python_to_typescript_interfaces import Interface

@dataclass
class DatedModel(Interface):
created_at: datetime
updated_at: date

It will result in below interface:
// Without flag
export interface DatedModel {
created_at: string;
updated_at: string;
}
// With flag: -dt Date
export interface DatedModel {
created_at: Date;
updated_at: Date;
}
// With flag: -dt number
export interface DatedModel {
created_at: number;
updated_at: number;
}

Planned Supported Mappings

String literals
Undefined type
isNaN type
ReadOnly types
Excess Properties

Unsupported/Rejected Mappings
The primary purpose of this library is to help type, first and foremost, data
moving back and forth from client to server. Many of these features, whether they be specific to TypeScript or Python, would be overkill to support.

void
callables/functions
generics, TypeVars
intersection types
mapped types
conditional types
classes

Contributing
Interested in contributing? You're awesome! It's not much, but here's some notes to get you started CONTRIBUTING.md.
Authors
Christopher Sabater Cordero
Nalyze team